Abstract:

Cavitation has been applied in medical treatments such as tissue ablation and lithotripsy. Considering that cavitation in medical applications always occurs within the fluid environment of the human body, which exhibits viscoelastic behavior, studying the dynamics of cavitation bubbles in viscoelastic media is essential for optimizing their medical use. This study used numerical simulations based on the open-source CFD platform OpenFOAM to develop a solver for compressible gas-liquid two-phase flows in viscoelastic fluid. Single cavitation bubble near a rigid boundary was simulated under various rheological parameters. Then the comparisons were made with corresponding cases in Newtonian fluid to analyze the effects of viscoelasticity on bubble dynamic characteristics. Results indicate that the viscoelastic effect inhibits the growth of cavitation bubbles and the intensity of the jet, and reduces the pressure load on the boundary caused by the cavitation process. Such influences are affected by the rheological properties of the fluid. As the relaxation time increases, the cavitation bubbles store more elastic potential energy in the early stage of growth and release it in the later stage, which prolongs the growth process of the cavitation bubbles and increases their maximum size. Conversely, when the migration coefficient increases, the energy dissipation during the growth of the cavitation bubbles increases, resulting in a decrease in their maximum size. Meanwhile, it is found that the velocity of the jet formed during the collapse of the cavitation bubble and the impact pressure on the boundary first increase and then decrease as the distance between the cavitation bubble and the boundary increases.This study can provide theoretical support for the application of cavitation bubbles in viscoelastic fluids and may inform both the beneficial use and mitigation of cavitation in fields such as chemical emulsification, seawater desalination, and petroleum transportation.

Abstract:

High-temperature environments and variations in hot water premise plumbing create unique microbial community characteristics that impact water safety. This study utilized a simulation platform for non-circulating hot water premise plumbing to investigate microbial growth under the effects of four specific hydraulic regimes: high variable flow (HIG), low variable flow (LOW), steady state (SS), and retention (R) conditions. After 91 days of operation, biofilm and water samples were collected from the simulation platform. The bacterial counts in the samples were measuerd, and the microbial community structure and the presence of potential pathogens genus were evaluated using 16S rRNA gene sequencing. The results showed that the R condition led to the highest microbial counts in both water and biofilm samples, while the continuously varying flow conditions, LOW and HIG, showed lower counts. Live bacteria demonstrated a propensity to colonize biofilms, exhibiting increased numbers and relative abundances of potentially pathogenic genera in the membrane samples. In addition, biofilms under varying flow conditions exhibited higher relative abundances of three typical potentially pathogenic genera, Pseudomonas spp., Legionella spp., and Mycobacterium spp., indicating a greater potential pathogenic risk.

Abstract:

Recently, there has been a significant focus on the issue of antibiotic pollution in water bodies. As a novel adsorbent material, magnetic biochar exhibits excellent potential for antibiotic removal due to its exceptional porosity, extensive surface area, abundant functional groups, and ease of recovery. This paper outlines the typical characteristics of magnetic biochar compared to conventional biochar. It summarizes the principles of various preparation methods, including pyrolysis, coprecipitation, hydrothermal synthesis, and ball milling, while comparing the crucial preparation conditions that must be considered for each method. In addition to controlling temperature, preparation time, and the ratio of magnetic material to biochar, further modifications with different reagents are discussed as potential means to enhance antibiotic adsorption capacity. The paper provides a detailed analysis of adsorption mechanisms such as pore filling, π—π conjugation, complexation, and electrostatic interactions, elucidating magnetic materials′ role during adsorption. Furthermore, the study reviews the recent progress in coupling magnetic biochar with other water treatment methods, such as photocatalysis and Fenton reactions. Finally, the paper outlines future research directions and application prospects for magnetic biochar, providing guidance for optimizing its design and enhancing the removal efficacy of antibiotic from water treatment.

Abstract:

To study the seismic performance of coal gangue concrete beam column joints, six full-scale specimens were prepared and subjected to low-cycle repeated loading tests. The analysis focused on various seismic indicators, including failure modes, hysteresis curves, skeleton curves, stiffness degradation, energy dissipation capacity. The effects of coal gangue aggregate replacement rates (0,0%, 50% and 100%) and beam longitudinal reinforcement ratios (0.67%, 1.34%, and 2.09%) on the seismic performance were studied. The results showed that the failure modes of joints are bending failure at the beam end and shear failure at the node area. The failure primarily manifests as extensive cracking in the joint area and significant spalling of concrete at the beam ends, with coal gangue concrete beam-column joints exhibiting more severe damage compared to ordinary concrete. Specimens with low coal gangue replacement rates displayed full hysteretic curves, slow stiffness degradation, good ductility, and good seismic performance. As the replacement rate of coal gangue increases, the specimens exhibits a pronounced pinching effect in the hysteretic curves, along with accelerated stiffness degradation and reduced ductility and energy dissipation. Increasing the longitudinal reinforcement ratio of the beam can improve the damage to the concrete at the end of the beam and enhance its bearing capacity. However, excessively high reinforcement ratio may induce shear failure of the nodes, reducing their energy dissipation capacity and ductility.

Abstract:

To investigate the influence of fiber incorporation on the mechanical properties of reinforced grouting sleeves, experimental studies were conducted on the material properties of polypropylene (PP) fiber-reinforced and polyvinyl alcohol (PVA) fiber-reinforced grouting materials. Mechanical property tests were performed on PP and PVA fiber-reinforced grouting materials with varying lengths and volume fractions. Uniaxial tensile tests were carried out on fiber-reinforced grouting sleeves with three different reinforcement anchorage lengths of 4d, 6d, and 8d (where d represents the diameter of the reinforcement bar). The results indicate that the addition of fibers leads to a certain degree of reduction in the fluidity and compressive strength of the grouting material, with insignificant impact on flexural strength. Moreover, as the fiber length and volume fraction increase, the compressive toughness of the grouting material improves significantly. For sleeve specimens with a 4d embedment depth, reinforcement pull-out failure occurred, while reinforcement rupture occurred in specimens with 6d and 8d embedment depths. Additionally, as the fiber length and volume fraction in the grouting material increase, the ultimate bearing capacity and ultimate displacement of the sleeves undergoing reinforcement pull-out failure also increase. There was a significant negative correlation between the compressive strength of the fiber-reinforced grouting material and the ultimate bearing capacity and ultimate displacement of the sleeves, whereas a positive correlation was observed with the compressive toughness of the material. Based on the traditional prediction formula for the ultimate bearing capacity of grouting sleeves, a new prediction formula that comprehensively considers both the compressive strength and compressive toughness of the grouting material is proposed by introducing the compressive toughness index as a parameter.

Abstract:

In order to analyze the impact of ambient temperature on the temperature field and long-term deformation of steel-tube-confined concrete-filled steel tube (TCFST), a temperature field analysis model of TCFST were established with ABAQUS finite element software. Taking the Shenzhen region as a case study, the temperature field of exposed TCFST columns under ambient temperature in the Shenzhen area were studied theoretically. Six TCFST short columns (with total steel content of the inner and outer steel tubes at 5.8%, 10.5%, and 15.0%, and a steel ratio of 0.75 between the inner and outer steel tubes) were designed and loaded under sustained axial compression for 850 days at room and changing ambient temperatures. The development law of long-term deformation of TCFST was clarified. Based on three commonly used long-term deformation prediction models for plain concrete, the long-term deformation of TCFST at room temperature was calculated. Real measurement data were used to modify the EC2 model for predicting long-term deformation of plain concrete, establishing a predictive model for long-term deformation of TCFST columns that accounts for temperature effects. The results indicate that when the average annual temperature of the section exceeds 20 ℃, it is advisable to consider the influence of temperature when calculating the long-term deformation of TCFST. The long-term deformation of TCFST columns decreases with an increasing total steel ratio of the inner and outer steel tubes, a higher ratio of steel content between the inner and outer layers, and lower temperatures. Additionally, the steel content of the outer steel tubes and season initial loading have no discernible impact on the long-term deformation of the TCFST.

Abstract:

To explore the load-bearing performance and the role of plate components in H-shaped section bending members, four-point pure bending tests were conducted on four welded H-shaped steel beams with different flange and web width-to-thickness ratios. The failure mode, force-displacement curve, ultimate bending capacity, and ductility of the test pieces were analyzed. By comparing the strain development and single plate bearing capacity of the web plates under different flange support conditions with the same dimensions, the mechanism of plate component interaction in this situation was revealed. Based on the experimental results, a calibrated finite element model was established using ABAQUS, and parameter analysis was conducted using this modeling method. By separating the flange and web plate bending load capacities of the parameterized components, the law of plate component interaction under bending conditions was further explored. The experimental and parametric analysis results both indicate that the occurrence of local buckling in the plate elements generally corresponds to the ultimate bending capacity of the H-shaped section members. The width-to-thickness ratio of the plates is a significant factor affecting local buckling. Furthermore, the interaction between the plates manifests as plates with different width-to-thickness ratios influencing the buckling timing of adjacent plates by altering the constraints on them, which affects the load-bearing capacity of individual plates and thus impacts the overall load-bearing performance of the member. Finally, based on the parameter analysis results, the ultimate load-bearing capacity of the members was normalized, and an S2-S4 grade section classification method considering the interaction of plate elements under bending conditions for H-shaped sections was proposed. The comparison results show that the section classification limits proposed in this paper match well with the experimental results and can reasonably reflect the impact of plate element interactions on the actual load-bearing capacity of the section.

Abstract:

Heliostats, as the core solar energy concentrating elements in tower solar thermal power plants, require accurate evaluation of the wind-resistance reliability to ensure safe and efficient operation of the power plants. To address this, a wind-resistance reliability evaluation method for heliostats considering the shielding effect of heliostat field is proposed. Firstly, wind tunnel pressure measurement tests were conducted on a heliostat field to obtain wind shape coefficients of the mirrors, and measure the shielding effects of the heliostat field based on its spatial variations. Subsequently, by combining random wind field simulation, finite element simulation, and probability density evolution theory, a wind-resistance reliability evaluation method for heliostats considering the shielding effects of heliostat field was established, with the mirror stress, deformation, and surface slope error as response indicators. Finally, taking a group of small heliostats in the heliostat field as an example, the influence of the shielding effects of the heliostat field, mirror pitch angle, wind direction angle and other parameters on its wind-resistance reliability was investigated. The results shows that the reliability of the helopstats on the outer side mirror of the heliostat field was significantly lower than that on the inner side. The reliability of the outer side was higher than when facing the wind compared to when facing away from it. In addition, for the heliostats on the outer side of the heliostat field, their reliability shows significant variations with changes in wind direction and pitch angle, whereas the reliability of the inner heliostats showed minimal variation with these parameters.

Abstract:

The drag force of buildings in urban environment represent a complex and critical issue. Currently, most research usually regards buildings with uniform heights, ignoring the effect of the non-uniformity of building heights on the drag force distribution. To address this, this study proposes a height stratification method to calculate the sectional drag coefficient of buildings with non-uniform heights, C_dz. This method employs a sectional correction factor β_z to adjust the drag coefficient of buildings with uniform heights to C_dz of buildings with non-uniform heights. Subquently, wind tunnel experiments are then conducted to investigate the effects of building height category N, layer type, and layout on the sectional drag coefficient of individual buildings and the total building array. The results show that the non-uniformity of building heights has a significant impact on the flow adjustment process. When the building height category, N, is 2 or 3, the layer layout has a minimal impact on β_z. However, when N increases to 4, β_z values of staggered layouts are higher than those of square layouts. When using the height stratification method to calculate C_dz of buildings with non-uniform heights, β_z requires further parameterization if N≥4. The outcome of this study provide theoretical support for estimating drag force in urban buildings, enhancing the accuracy of building effect parameterization, and improving the precision of urban weather forecasting and pollutant dispersion calculations.

Abstract:

Most of the existing constitutive models often relay on parameters that lack actual physical significance to account for the structure of soil, while neglecting the influence of structural yield stress. To address this gap, a structure parameter ξ incoporating the relationship between the shear strength of undistributed and remolded soils is proposed. Within the framework of critical state theory, a modified Cam-clay model is developed. This model employs Caputo-type fractional differential to describe the characteristics of soil plastic flow direction in the soil and the non-orthogonality of the yield surface. Consequently, a fractional constitutive model considering the structural effects in clay is established. The model is validated by Wenzhou clay and Osaka clay. When the stress of the soil is less than the structural yield stress, the structural parameter ξ>1, indicating that the mechanical properties of the soil are significantly affected by the structural properties. Conversely, when the stress of the clay is larger than the structure yield stress, the structural parameter ξ=1, and the structural influence disappears, allowing the model to reduce to a conventional fractional constitutive model. The prediction results of Wenzhou clay show that, when the confining pressure is 0,0, and 200 kPa, the fractional constitutive model considering the structural influence reduces the maximum prediction error by 27.6%, 13.05% and 1.8%, respectively, compared to the model ignoring the structural influence, with an average maximum prediction error of 4.92%. Further validation using prediction results of Osaka clay demonstrates that the model better predicts the mechanical and deformation characteristics of structural clay, exhibiting good applicability and reliability.

Abstract:

In view of the high spatial and temporal complexity of intrusion detection caused by high dimensionality of traffic data features in the modern network environment and low classification accuracy caused by the lack of sensitivity of traditional intrusion detection methods to the correlation between traffic data, an intrusion detection method based on feature reduction and improved self-attention mechanism is proposed to improve the efficiency and accuracy of intrusion detection. Firstly, aiming at the problem of high-dimensional data, an auto-encoder with nonlinear feature extraction capability is used to extract features, which reduces data redundancy and ensures classifier performance to be basically unchanged, so as to ensure that intrusion detection methods can effectively identify attacks. Secondly, aiming at the problem that traditional intrusion-detection methods ignore the correlation of traffic data, a self-attention mechanism is introduced in the intrusion detection classification process to learn the correlation of network data over a period of time. The causal convolution is introduced in original self-attention mechanism to calculate the correlation score between data, and integrate the local location information of current traffic data and the correlation between the traffic data in the concerned domain, which comprehensively analyzes current traffic behavior and complete accurate classification. Experimental results on UNSW-NB15 dataset show that the proposed intrusion detection method attains 98.32% accuracy on the binary classification tasks, and outperforms traditional methods on multi-classification tasks as well, indicating promising applicability in modern network environment.

Abstract:

In the field of radar communication integration, it is a crucial link to design a common waveform signal that can simultaneously support radar detection function and communication information transmission function. In response to the problem of low autocorrelation performance after modulating communication information within radar signal pulses, an integrated radar and communication signal format based on nonlinear frequency modulation (NLFM) signal with high frequency band utilization and low autocorrelation sidelobe is proposed. The core of establishing NLFM-16QAM integrated radar and communication signal model is to take NLFM signal as the carrier of 16 order quadrature amplitude modulation (QAM) signal. The ambiguity function of NLFM-16QAM signal and the related radar and communication performance are analyzed. Noting that the randomness of the communication baseband signal in the proposed NLFM-16QAM waveform can degrade radar functionality and thus reduce moving-target detection performance, we introduce improvements at the receiver of the integrated system. Specifically, a wavelet packet noise reduction is proposed to process NLFM-16QAM signal in combination with natural gradient separation algorithm. Simulation results show that the proposed signal has larger frequency band utilization in comparison with the integrated radar and communication signals of low-order modulation. Compared with the autocorrelation performance of 16QAM-LFM signal, integral sidelobe ratio and peak sidelobe ratio of proposed signal are reduced by 23.07 dB and 26.08 dB respectively. After NLFM-16QAM signal is processed by the joint algorithm of the receiving end, the detection results of the moving target are significantly improved.

Abstract:

The data distributions of cross-scenario images of strip steel defects vary considerably due to imaging factors such as camera type, parameters, and environmental illumination, resulting in poor generalization performance of defect recognition models based on deep learning. To address this issue, we propose a pseudo label correction and optimization domain adaptation (PLCODA) model for strip steel defect recognition. Firstly, a Retinex image enhancement module based on maximum entropy and brightness constraints was designed to generate an intermediate domain that is consistent with the label information in the source domain while different from the data distribution in the two domains. Second, we develop a dual-prediction adversarial coupling architecture that performs adversarial learning between the target domain and each of the source and intermediate domains to generate initial pseudo-labels for target-domain samples. Finally, we propose a pseudo-label correction and iterative purification strategy: we correct pseudo-labels via an improved noise matrix, then iteratively purify them by reinforcing high-confidence predictions, self-punishing low-confidence predictions, and reducing the discrepancy between pseudo-labels and ground-truth labels using a designed label-difference metric. The method was validated on steel-strip defect datasets from Handan Iron & Steel Group and the publicly Severstal Steel Defect Dataset. Experimental results show that the proposed method is superior to the existing domain adaptation methods for cross-scenario defect recognition.

Abstract:

To address the reliance of most deep learning methods for magnetic resonance (MR) imaging (MRI) reconstruction on extensive fully-sampled datasets for training, this study proposes an unsupervised dual-domain N2N network with attention mechanisms (DN2NA) for parallel MRI reconstruction. The proposed DN2NA network can directly reconstruct undersampled k-space data without requiring additional training data. Specifically, we integrate complex-valued convolution and channel attention mechanism into the N2N framework to construct a baseline unsupervised network N2NA. Two physical priors are incorporated to enhance the performance of the frequency-domain (k-space) N2NA network, which is then cascaded with an image-domain N2NA network to form the dual-domain DN2NA architecture. This combination effectively leverages the complementary advantages of frequency-domain and image-domain networks. Given the absence of ground-truth references in practical scenarios, an early-stopping strategy is adopted to prevent overfitting and improve stability. Experiments conducted on three knee and brain datasets demonstrate that DN2NA achieves higher PSNR and SSIM, along with lower HFEN and STD compared to existing unsupervised networks (IUNN and KUNN), indicating superior reconstruction quality and stability in repeated reconstructions. Furthermore, DN2NA exhibits comparable or better performance than the supervised network MICCAN.

Abstract:

In the decoder of live video streaming, compressed video often suffers from block loss during recovery. The spatial error concealment utilizes the correlation between blocks in the current frame for the recovery of error image, without requiring information from other frames. Among many spatial error concealment algorithms, sparse representation mechanism further utilizes the sparsity of an image and achieve better recovery quality than pixel-wise interpolation mechanism. The current sparse representation algorithms still face challenges such as inaccurate selection of candidate subregions and parameter sensitivity of correlation model. Therefore, this paper studies the dual space regularization framework according to sparse representation, and focuses on optimizing such two stages as local region matching and local linear correlation modeling in this framework. We proposes a double-sparse spatial error concealment algorithm with adaptive threshold and α-ML kernel function. During the stage of local region matching, the proposed algorithm designs a local region matching method with adaptive threshold, which can flexibly adapt to the missing subregions with different characteristics, and provide more accurate observation space and potential space for dictionary construction and local linear correlation modeling. During the stage of local linear correlation modeling, the proposed algorithm utilizes a kernel ridge regression method with α-ML kernel function as the local linear correlation model. Compared with the Gaussian kernel function, the α-ML kernel function has low parameter sensitivity and good flexibility. Experimental results show that in typical block loss modes, the proposed algorithm outperforms other existing spatial error concealment algorithms in terms of recovery quality.

Abstract:

Text in natural-scene images often present characteristics of complex backgrounds, varied shapes, multiple orientations and changing illumination. In order to improve detection performance for scene text, particularly irregular text, we propose the feature guided adaptive network (FGANet), an irregular-scene text detection network based on feature filtering and adaptive fusion mechanisms. In specific, FGANet designs a module that utilizes dilated convolution to enlarge the receptive and enhance the network′s feature representation capability. Its adaptive feature fusion module integrates deep semantic information with shallow detailed information, enabling stronger text-awareness. Experiments results show that for scene text detection, FGANet achieves notable improvements in F-score over comparative methods on four benchmark datasets: ICDAR2015, CTW1500, MSRA-TD500, and TotalText, with gains of 2.4%, 1.3%, 1.8%, and 1.4%, respectively.

Abstract:

A fault tolerant control scheme based on integral sliding mode surface is developed for spacecraft attitude stabilization in the presence of actuator faults, misalignments, magnitude saturation and external disturbances simultaneously. This approach is based on a novel integral-type sliding mode control strategy to compensate for these un-desired issues without controller reconfiguration. Especially, it guarantees the reachability of the system states by involving adaptive control technique to relax the boundary information in advance. A sufficient condition for the controller to accommodate magnitude saturation is also presented and then the fault tolerant attitude control system can be guaranteed theoretically to be asymptotically stable by using Lyapunov method. Numerical simulation results shows that the proposed control law can quarantee the stability of the spacecraft attitude control system in the presence of actuators' failures, and it has good robust performance.

Abstract:

It is well known that unmanned aerial vehicle (UAV) is more and more widely applied in military and civil areas. In order to play the better role of UAV, it is needed to utilize multi UAVs cooperative formation to accomplish cooperative reconnaissance, combat, defense and spraying pesticides and other tasks. The multi UAVs cooperative formation control technology mainly contains the following key techniques: data fusion technology, sensing technology, task allocation technology, path planning technology, formation control technology, communication network technology and virtual/physical verification platform technology. Firstly, summarize the research and development of key technologies worldwide. Then, the classification for multi UAVs formation control methods is mainly investigated, and the problems about formation design and adjustment, formation reconfiguration are summarized. Finally, the challenges and future development for multi UAV cooperative formation are prospected. Research shows: at present, the theory of multi UAV formation flight has acquired fruitful results, while the real cooperative formation flight test can only be implemented in the simple communication environment. The real time performance for task allocation and path planning is not high. The robustness of control methods to cope with the unexpected situation is low. The cooperative sensing ability for multi UAV with multi sensor is insufficient. The simulation of the entity is lacked. Breaking through the above key technologies, carrying out the cooperative formation flight of multi UAV in complex sensing constraints and complex communication environment, putting forward more effective control method and carrying out the UAV physical formation flying test so that the UAV can finish the task better may be the future research directions.

Abstract:

In the ultra-dense network environment, each access point is deployed in the hotspot area, which forms a complex heterogeneous network. Users need to choose the appropriate network to access, so as to achieve the best performance. Network selection problem is to choose the optimal network for the user, so that the user or network performance reaches the best. In order to solve the access selection problem of users in ultra-dense networks, we proposed an ultra-dense network access selection algorithm based on the improved deep Q network (DQN), considering network states, user preferences, and service types, and combining with load balancing strategies. First, by analyzing the influence of network attributes and user preferences on network selection, the appropriate network parameters were selected as the parameters of the access selection algorithm. Then, the problem of network access selection was modeled by Markov decision-making process, and the states, actions, and reward functions of the model were designed. Finally, the optimal network strategy was obtained by using DQN to solve the network selection model. In addition, the target function of traditional DQN was optimized to avoid overestimation of Q value by DQN, and a priority experience replay mechanism was introduced to improve learning efficiency. Simulation results show that the method could well solve the problem of overestimation of traditional DQN, accelerate the convergence of neural network, effectively reduce user congestion, and improve network throughput performance.

Abstract:

To investigate the ground motion intensity measures suitable for evaluating high-rise structures under near-fault ground motions with pulse-like effect, this paper proposes a new ground motion intensity measure considering period elongation effect and higher mode effect based on acceleration spectrum. Taking two high-rise reinforced chimney structures (120 m and 240 m) as research objects, the correlation between damage indices (ParkAng damage index, maximum inter-story drift ratio, maximum structural curvature, maximum floor acceleration, and maximum roof displacement) of high-rise structures and 37 ground motion intensity measures was studied under near-fault ground motions using OpenSEES. Results show that the proposed intensity measure was the optimal index in predicting the ParkAng damage of high-rise concrete structures under near-fault ground motions. High correlation between velocity-related intensity measures and structural damage index was observed. As the structural period increased, the correlation between damage indices and displacement-related intensity measures was improved. Besides, peak ground acceleration had limitations in characterizing the deformation and failure of high-rise structures, but it could be used to analyze the seismic performance of non-structural components. The research results can provide reference for selecting proper measures and structural damage indices to evaluate the seismic performance of high-rise structures under near-fault ground motions.

Abstract:

In view of the weaknesses of poor computing and storage capabilities of edge devices, lightweight processing was carried out on the backbone network CSPDarkNet53 for feature extraction in the traditional YOLOv5 model, and a lightweight gesture recognition algorithm MPE-YOLOv5 was proposed to realize the deployment of the model in low-power edge devices. Considering the problem that it is difficult to identify large-scale transformation targets and tiny targets due to less feature extraction in lightweight model, efficient channel attention (ECA) mechanism was added to alleviate the loss of information after high-level feature mapping due to the reduction of feature channel. A detection layer for tiny targets was added to improve the sensitivity to tiny target gestures. EIoU was selected as the loss function of the detection frame to improve the positioning accuracy. The effectiveness of the MPE-YOLOv5 algorithm was verified on the self-made dataset and NUS-Ⅱ public dataset, and the MPE-YOLOv5 algorithm was compared with lightweight M-YOLOv5 algorithm and original YOLOv5 algorithm on the self-made dataset. Experimental results show that the model parameters, model size, and computational complexity of the improved algorithm were 21.16%, 25.33%, and 27.33% of the original algorithm, and the average accuracy was 97.2%. Compared with the lightweight model M-YOLOv5, MPE-YOLOv5 improved the average accuracy by 8.72% while maintaining the original efficiency. The proposed MPE-YOLOv5 algorithm can better balance between the detection accuracy and real-time reasoning speed of the model, and can be deployed on edge terminals with limited hardware.

Abstract:

Considering the failure mechanism and weaknesses of traditional fabricated shear wall structures under strong earthquakes, a new type of fabricated shear wall with functions of energy dissipation and shock absorption was proposed. On the basis of model test and numerical simulation, seismic performance tests were carried out on four specimens with scale ratio of 1∶1.54 and shear span ratio of 1.52. Further analysis was conducted to investigate the effects of bolt number, axial compression ratio, and reinforcement ratio of edge members on the seismic performance of the new fabricated shear wall, including failure modes, hysteretic performance, bearing capacity, displacement ductility, stiffness degradation, and energy dissipation capacity. Test results show that the four specimens experienced shear compression failure, which was the same as the cast-in-place shear wall with the same shear span ratio. However, the proposed shear wall had better hysteretic performance and energy dissipation capacity, and the energy dissipation capacity was higher than that of the cast-in-place shear wall at the failure point. When the number of bolts decreased, the hysteretic performance of the new fabricated shear wall decreased, the wall deformation increased, while the bearing capacity remained almost unchanged. When the axial compression ratio or reinforcement ratio of edge members decreased, the bearing capacity decreased, and the ultimate displacement increased. Finally, the finite element model of the specimens was established by ABAQUS program. Comparisons of numerical results and test results showed a good agreement, verifying the correctness of the model, which can be applied to the analysis of the new fabricated shear wall.

Abstract:

Autonomous navigation based on sequential images (ANBSI) is the key technology of pinpoint landing missions for future deep space exploration and also is one of the major development directions for deep space exploration technology. The necessity of developing ANBSI for planetary pinpoint landing is elaborated in this paper. Firstly, state-of-art developments of ANBSI are reviewed in terms of active sensing and passive sensing. Then, the key techniques applied in ANBSI for planetary landing are summarized and analyzed. Finally, according to the analysis of the key techniques, the main issues of ANBSI are raised and their future developments are overviewed.

Abstract:

The advent of Industry 4.0 has spawned the widespread application of digital twin technology, providing digital solutions for intelligent manufacturing and product life-cycle management. In the field of civil engineering, the enhancement of digital disaster prevention and civil structure management is a critical component in the development of future smart cities. On one hand, the establishment of precise and reliable digital twins of real-life civil structures can facilitate disaster prevention from extreme hazards, as well as identify and warn against potential risks. On the other hand, digital twins lay the foundation for technological advancements in the digital construction and management of future cities. This study first categorizes the fundamental concepts and developmental stages of digital twin technology. Then, the acquisition of twining data and construction of digital twins for civil structures are systematically summarized. Building on this foundation, a comprehensive review and outlook is presented on the application of digital twin technology in civil engineering, encompassing the operation and maintenance of structures, disaster simulation and digital twin cities.

Abstract:

The development of advanced nano-integrated circuit processes has led to a decreasing threshold charge in microelectronic devices, resulting in an increased rate of soft errors caused by single-event effects in digital circuits. To enhance the radiation resistance of standard cells in integrated circuits, this paper proposes a NAND gate structure that is resistant to single-event transients (SETs). In the triple well process, by shorting the substrate and source of each NMOS transistor in the pull-down network, the radiation resistance of the NAND gate was effectively improved, and the hardening of the proposed NAND gate became more effective as the number of inputs increased. Particle incidence simulation experiments were performed by Sentaurus TCAD software in hybrid simulation mode. For the NMOS transistor connected to the output node, the three-dimensional physical model that has been calibrated by the process was used, and the Spice model provided by the manufacturer was adopted for other MOS transistors. Simulation results show that the proposed two-input NAND in 40 nm process could reduce the output voltage fluctuation amplitude in three-input cases at the linear energy transfer (LET) value of incidence particle of 10 MeV·cm²/mg. Besides, the effect of immunity to single particle incidence was achieved in the input mode with N₂ transistor closed. For the hardened three-input NAND gate, the output voltage disturbance could be reduced by up to 85.4% even in the “worst case”. Therefore, the proposed hardening method for NAND gate has a significant effect against SET.

Abstract:

This paper proposes a low-latency intelligent network data transmission scheduling algorithm for real-time network transmission demand scenarios of low latency, stable transmission, and high quality of experience (QoE). The algorithm consists of two parts: data block queuing control strategy and congestion control strategy. The data block queuing control strategy presents a cost-effective model that integrates the creation time and effective time of data blocks, effectively solving the problem of uneven information transmission under transmission time constraint. The congestion control strategy proposes a deep deterministic policy gradient (DDPG) method based on the Gumbel distribution sampling reparameterization with mixed experience prioritization model, which solves the problem that DDPG is not applicable to the congestion control of discrete network action space and significantly improves the quality of network congestion control by adaptively adjusting the sending parameters through learning. Results show that the proposed queuing algorithm could effectively improve QoE in real-time transmission scenarios, and the improved DDPG for congestion control could significantly reduce transmission delay. In the same scenario, compared with traditional network data transmission scheduling algorithms, by integrating the proposed queuing and congestion control strategies, the improved intelligent network data transmission scheduling algorithm could maintain a good balance between low latency and stable transmission and provide higher data transmission quality.

Abstract:

In view of the problems of low brightness and obvious color distortion of the sky in restored images in most existing algorithms for image dehazing, a haze removal method for UAV aerial images based on atmospheric light value and graph estimation was proposed. First, the depth-of-field image was obtained according to the color attenuation prior theory, and the mean value of the region with the minimum deviation in the depth-of-field image was taken as the atmospheric light value. Then, a random walk clustering method was designed to estimate the atmospheric light map. The random walk algorithm was used to cluster the image into N sub-regions, and the mean value of the first 0.1% pixels of the sub-regions was taken as the regional atmospheric light value, which was then combined and refined by guided filtering to obtain the atmospheric light map. Next, the two atmospheric light estimators were fused into a new atmospheric light map with atmospheric light valuegraph estimation, which is a more accurate atmospheric light estimator. The transmittance was obtained by haze-lines prior method, and a dark compensation method was proposed to improve the transmission accuracy. Finally, according to the atmospheric scattering model, a clear restored image was obtained based on the fused atmospheric light map and optimized transmittance. Experimental results show that compared with other algorithms, the proposed algorithm improved the information entropy, mean gradient, blur coefficient, and contrast by 1.1%, 6.3%, 8.5%, and 6.4%, respectively, with better subjective visual effect and more abundant information.

Abstract:

Image segmentation is to divide the region with special meanings into several disjoint sub-regions according to certain rules, which is the key link between image processing and image analysis. The traditional watershed image segmentation method is widely used, which has the advantages of fast and simple. However, it is easily interfered by noise, and the segmentation results are prone to lose important edge information, resulting in over-segmentation. In view of the problem of the traditional watershed image segmentation method, an improved watershed image segmentation method based on adaptive structural elements was proposed. First, the adaptive structural elements with variable shapes were constructed by using local density, symmetry, and boundary features of adjacent pixels of image targets, so as to ensure a good consistency between the proposed structural elements and the shape of image targets. Then, the adaptive structural elements were used to obtain the morphological gradient of the image, which could improve the positioning accuracy of the target edge. The L₀ norm gradient minimization and morphological open-close hybrid reconstruction were used to modify the gradient image, so as to reduce the local invalid minimum points in the gradient image and suppress the occurrence of over-segmentation. Finally, watershed segmentation was performed on the modified gradient image to realize accurate segmentation of the target region of the image. Experimental results show that the method could effectively restrain over-segmentation of traditional watershed algorithm and improve the accuracy of the target edge positioning, with high precision of image segmentation.

Abstract:

In view of the problem that general pre-trained models are not suitable for named entity recognition tasks in the medical domain, a neural network architecture that integrates knowledge graph in the medical domain was proposed. The elastic position and masking matrix were used to avoid semantic confusion and semantic interference in self-attention calculation of pre-trained model. The idea of multi-task learning in fine-tuning was adopted, and the optimization algorithm of recall learning was employed for pre-trained model to balance between general semantic expression and learning of the target task. Finally, a more efficient vector representation was obtained and label prediction was conducted. Experimental results showed that the proposed architecture achieved better results than the mainstream pre-trained models in the medical domain, and had relatively good results in the general domain. The architecture avoided retraining pre-trained models in particular domain and additional coding structures, which greatly reduced computational cost and model size. In addition, according to the ablation experiments, the medical domain was more dependent on the knowledge graph than the general domain, indicating the effectiveness of integrating the knowledge graph method in the medical domain. Parameter analysis proved that the optimization algorithm which used recall learning could effectively control the update of model parameters, so that the model retained more general semantic information and obtained more semantic vector representation. Besides, the experimental analysis showed that the proposed method had better performance in the category with a small number of entities.

Abstract:

Due to the complex background of ship targets and much irrelevant interference in visual images, it is difficult to conduct ship detection. In addition, there are few datasets for multi-category ship detection and the samples are often unbalanced, which makes the ship target detection performance degraded. Considering the ship detection background interference, an improved YOLOv3 model was proposed by introducing SimAM attention mechanism, which was used to enhance the weight of the ship target in the extracted features and suppress the weight of background interference, thus improving the model detection performance. Meanwhile, strong real-time data augmentation was applied to improve the unbalanced distribution of sample scales, and transfer learning was combined to improve the ship detection accuracy in the condition of a restricted number of samples. The visualization results of extracted features show that the improved model could suppress irrelevant background features, and the abilities of feature extraction and target localization were enhanced. Without introducing additional learnable parameters, the proposed model achieved 96.93% and 71.49% for mAP.5 and mAP.75 on the SeaShips dataset, and detection speed reached 66 frames per second, indicating a good balance between detection accuracy and efficiency. The improved model optimized the target features more effectively compared with the Saliency-aware CNN and eYOLOv3 models, resulting in an improvement of mAP.5 by 9.53% and 9.19%. The mAP.5 for ship type target detection on Singapore Maritime Dataset reached 81.81%, indicating that the proposed model has good generalization performance.

Abstract:

To study the mechanical performance of concrete-filled double-skin steel tubular long columns under compressive and torsional loads, two ordinary circular steel tube reinforced concrete columns and two double-layered steel tube reinforced concrete columns were subjected to low-cycle reciprocating tests under pure torsion and torsion-compression loading using a developed Stewart six-degree-of-freedom loading platform. Based on the tests, the bearing capacity, torsional deformation, energy dissipation, and hysteresis performance of each specimen were compared and analyzed, and finite element parameter analysis was conducted. The study shows that both ordinary circular steel tube reinforced concrete columns and double-layered circular steel tube reinforced concrete columns have good torsional resistance. Compared with ordinary circular steel tube reinforced concrete columns, the initial stiffness and bearing capacity of double-layered steel tube reinforced concrete columns are slightly improved, the hysteresis curve is more full, and the energy dissipation capacity and ductility are greatly improved. Parameter analysis shows that when the steel content is constant, the larger the thickness ratio of the inner steel tube, the more beneficial it is for torsional resistance; and within a certain range of axial loads, the torsional resistance of steel tube reinforced concrete columns can be improved.

Abstract:

To improve the ductility of steelultra-high performance concrete (UHPC) composite structures, we proposed a type of demountable steelUHPC composite slab based on demountable shear connectors. The flexural tests for demountable steelUHPC composite slabs with different shear connection degrees were designed and completed. The failure mode, ultimate capacity, stiffness, cracking behavior, and relative slip of demountable steelUHPC composite slabs were analyzed and compared with those of steelUHPC composite slabs with welded shear connectors. The demountability of demountable steelUHPC composite slabs was discussed. The ultimate flexural capacity and flexural stiffness of demountable steelUHPC composite slabs were theoretically analyzed, and related calculation formulas were deduced. Results showed that the failure mode of demountable steelUHPC composite slabs was longitudinal horizontal shear bonding failure. Reducing the stud spacing could enhance the cooperative deformation capacity of demountable steelUHPC composite slabs, resulting in the improvement of their ultimate flexural capacity, stiffness at the elastic-plastic stage, and crack control ability. Different from the steelUHPC composite slabs with welded shear connectors, the steel slab and UHPC slab of the demountable steelUHPC composite slabs could be easily disassembled even in the condition of large deformation. The formulas for the ultimate flexural capacity and flexural stiffness of demountable steelUHPC composite slabs were derived. It was proposed that the height of UHPC slab should be reduced when calculating the flexural stiffness, and the reduction coefficient (β_U) was suggested to be 0.85 in serviceability state. The theoretical calculation results were in good agreement with the test results. The research results can provide theoretical basis for the design and application of steelUHPC composite slabs with demountable shear connectors.

Abstract:

To improve the construction efficiency of building envelope and solve the long-term problems of falling off and ignition of traditional external insulation systems, a kind of rock wool composite insulation external formwork (RWCIEF) system integrating insulation and building formwork was proposed. The RWCIEF structure from inside to outside was designed as follows: inner reinforcing layer, rock wool insulation core material, adhesive layer, insulation transition layer, and outer reinforcing layer. Taking Harbin as an example, the optimal thickness of rock wool insulation core material was determined based on the life cycle cost (C_lc). The feasibility of RWCIEF in engineering was explored by combining finite element analysis with theoretical calculation. The bending properties, construction bearing capacity, and stress and deformation under temperature effect of RWCIEF were calculated and analyzed. The influences of groove form, groove width, groove depth, and groove spacing on the bending properties of RWCIEF were discussed. Results showed that the theoretical calculation results of bending properties of RWCIEF were in good agreement with the finite element analysis results. The grooving treatment effectively improved the bending properties of RWCIEF. Considering the bending properties, thermal characteristics, and processing angle, groove forms of symmetrical cross grooves or symmetrical longitudinal grooves were suggested, with the groove depth and width of 10 mm and the groove spacing of 150 mm. The designed RWCIEF met the construction bearing capacity and could fully guarantee the construction quality of the thermal insulation works of the outer enclosure structure. The maximum tensile stress and compressive stress caused by temperature effect did not exceed the bearing capacity of the outer reinforcing layer of RWCIEF, which indicates that RWCIEF is unlikely to hollow in summer or crack in winter. The proposed RWCIEF system can provide a new idea and method for the future research directions of exterior envelope insulation and building formwork engineering.

Abstract:

In order to investigate the flexural behavior of ultra-high performance concrete (UHPC) lightweight composite decks under local wheel load, four demountable steelUHPC composite slabs connected by high-strength bolts were designed and four-point bending test was conducted. The influence of steel plate type and spacing of shear connector on the flexural characteristics of demountable steelUHPC composite slabs was analyzed, including failure mode, load-deflection curve, interface relative slip, crack width, and sectional strain distribution. Results showed that under positive bending moment, the failure mode of composite slabs adopting Q355 steel plate was that the high-strength bolt was cut off. While the failure mode of composite slabs using steel plate with negative Poisson’s ratio (NPR) was as follows: part of high-strength bolts was cut off, part of pre-embedded elongated nuts with cushion was pulled out, and UHPC collapsed due to instantaneous instability. Besides, under the same spacing of high-strength bolts, the relative slip of plate end of composite slabs employing NPR steel plate was relatively small, indicating that NPR steel plate can effectively delay and restrain the relative slip between steel plate and UHPC plate, thus improving the synergistic deformation capacity, flexural stiffness, and flexural bearing capacity for composite slabs. According to the sectional strain distribution analysis, due to the negative Poisson’s ratio effect, high stiffness, and high yield strength of NPR steel plate, the tensile strain between NPR steel plate and the bottom UHPC layer maintained strain compatibility during the whole loading process, and the upward displacement for sectional plastic neutral axis could be ignored with increasing load. Therefore, under the premise that NPR steel plate is employed to improve the flexural performance of steelUHPC composite slab system, the thickness of UHPC should be reasonably matched with the performance of NPR steel plate, so as to give full play to their material properties, and avoid the buckling failure prior to the material strength failure of UHPC.

Abstract:

To reasonably select a suitable set of ground motion parameters and effectively reduce the uncertainty of structural damage prediction, various ground motion parameters were preferentially selected based on the elastic network regression technique. First, the elastic network regression model was established based on various ground motion parameters and the seismic capacity of a generic set of single-degree of freedom (SDOF) systems obtained from the results of incremental dynamical analysis. Second, the values of regression coefficients in the elastic network regression model and the number of times that the regression coefficients have non-zero values were used to define the sensitivity and frequency of ground motion parameters, respectively. Third, the ranking of ground motion parameters used for seismic capacity prediction was established in terms of sensitivity and frequency of ground motion parameters obtained from the results of elastic network regression on a generic set of SDOF systems. Results were statistically organized to evaluate the influence of various ground motions, structural types and structural limit-states. The analysis result obtained from an 8-story steel frame verified that the use of ground motion parameters selected based on elastic network regression can effectively reduce the uncertainty of structural damage prediction. In addition, results showed that the standard deviation of the residuals in the regression analysis for different structural limit-states was significantly reduced when the representative ground motion parameters were employed in the least squares regression model. Moreover, representative ground motion parameters that are less affected by various ground motions, structural types and structural limit-states were selected based on the ranking results obtained from a generic set of SDOF systems. Findings of this study can provide a theoretical basis for the comparison of ground motion parameters used for the prediction of structural seismic capacity.

Abstract:

With the increasing scale of network, the accurate and real-time prediction of network flow is essential for traffic scheduling and routing design. However, due to the nonlinearity and uncertainty of network flow data, some traditional methods fail to achieve good prediction accuracy. Considering the complex spatialtemporal features of network flow, a novel network flow prediction method based on spatialtemporal features fusion (ST-Fusion) was proposed, combined with encoderdecoder architecture. First, the encoder was designed with two parallel feature channels: temporal and spatial channels. The temporal features were extracted by integrating gated recurrent unit (GRU) and self-attention mechanism, and the graph convolutional network (GCN) was used to extract the spatial features. Then, the temporal and spatial features extracted by the encoder were fused by using the bilateral gated mechanism. Finally, the fused features were input into the GRU-based decoder to generate prediction results. Experiments were conducted on three public datasets (GEANT, ABILENE, and CERNET) using evaluation metrics including MAE, RMSE, ACCURACY, and VAR. Experimental results showed that the ST-Fusion method achieved better performance in network flow prediction.

Abstract:

In order to give full play to the advantages of the high degree of industrialization of assembly and the excellent mechanical properties of steel-concrete composite structures, a kind of assembled double-slotted channel steel-concrete composite floor slab was proposed. Three groups of simply supported composite floor slab specimens were tested under four-point loading, and the mechanical properties of the composite floor slab under vertical static load were studied. The development law of floor cracks, deflection and strain (steel bar, steel beam, concrete slab) with load was analyzed. Based on the limit equilibrium method, the bearing capacity calculation formula considering the tensile membrane effect and stiffness strengthening coefficient was proposed. The results showed that the deformation of the composite slab is characterized by two-way slab. When the specimens are destroyed, the corner cracks and arc cracks appear on the top of the slab, the central area of the concrete slab bottom shows mesh cracks and oblique cracks extending to the corner, and the plastic bending of the double main girder occurs. When the center deflection of the floor reaches l₀/40, the load of the specimens is 327.63 kN, 436.92 kN and 406.12 kN respectively, and the bearing capacity of the composite floor is higher. The strain development of the steel bar is larger in the direction perpendicular to the steel beam and yields along the plastic hinge line. The calculation formula considering the tensile membrane effect and the stiffness strengthening coefficient is in good agreement with the test results, and the load-deflection curve of the floor is accurately predicted.

Abstract:

To study the influence of the alkaline activator on the performance of steel slag cement, the effects of alkaline activators (water glass、Na₂CO₃/NaOH、NaOH) on the macroscopic mechanical properties of steel slag cement are studied in this article. Further, the microscopic characteristic is investigated by hydration heat release, X-ray diffraction (XRD), thermogravimetric analysis (DSC-TG), scanning electron microscope (SEM) and mercury intrusion porosimetry test (MIP). The results show that the alkaline activators increased the basicity in the early hydration liquid phase of steel slag cement, accelerating depolymerization of steel slag vitreous to produce H₃SiO-₄ and H₃AlO^2-₄, improving the reaction rate, facilitating the formation of C-S-H gel and zeolite products, which is manifested by the shortening of setting time and induction period, the increase of reaction heat, cumulative heat release and early mechanical strength; the influence of alkaline activators on the properties of steel slag cement is related to its molecular structure of activators, and the order of influence was water glass, Na₂CO₃/NaOH, NaOH in descending order; Water glass could increase the alkalinity of liquid phase in steel slag cement, and the SiO^2-₃ could react with Ca(OH)₂ to produce C-S-H gel. The addition of alkaline activators can promote the hydration reaction of steel slag cement, which is helpful to the improvement of the mechanical properties and the compactness of the microstructure of steel slag cement.

Abstract:

To investigate widely applicable shear capacity calculation methods of reinforced concrete column-steel beam (RCS) hybrid connection, this study analyzed the shear failure experimental data of RCS connections in recent years. The experimental results were compared with the calculation results of Chinese specification, Nishiyama method, Parra method, and ASCE guideline, and the parametric applicability of each method was discussed. The comparison results showed that all the four methods had engineering value. The minimum discreteness of the results of Parra method was obtained, and the calculation process of Chinese specification was the simplest. The results of parametric study showed that all the four methods were suitable for connections with different stirrup ratios and positions. However, conservative estimates were obtained for specimens with small axial load ratios (from 0 to 0.2) and column-through connections. For the Chinese specification, the predicted strength of connections with concrete strength higher than 60 MPa was unsafe, while the predicted strength of connections with transverse beams was conservative. Therefore, it is suggested to introduce concrete strength coefficient and confined coefficient of transverse beam into the equation considering the influence of these two factors.

Abstract:

To study the bending performance of prestressed steelbamboo composite I-shaped beams, 12 prestressed composite I-shaped beams were designed and manufactured for bending tests, considering prestress loads, prestressing schemes, and loading schemes as basic parameters. The experimental phenomenon was observed, and failure characteristics were analyzed during the test. The influences of different parameters on the load-bearing capacity, strain distribution, and deformation performance were explored, and an approximate formula for the bearing capacity of the prestress composite beam was proposed. The results indicated that the prestressed composite beams have relatively good performances from the perspectives of combination effect, deformation characteristic, and bearing capacity. Failure modes of tested specimens were mainly owing to the bamboo flanges damage and the local buckling of steel plates. With the technique of prestress and the increase of prestress level, the deformation performances can be improved effectively, as well as the load-bearing capacity considering the same deflection situation. Moreover, the improvements can be more significant with the two-point prestressing scheme. The mid-span strain distribution of prestressed composite beams conforms to the plane section assumption, and the neutral axis moves down with the increase of the prestressing level. Finally, the bearing capacities based on the theoretical calculation matched well with the experimental results, which showed the applicability of the proposed methods.

Abstract:

With the gradual deepening of the study of seepage erosion in soil, the research methods of soil particle loss and deformation and failure mechanism show the characteristics of multi-scale. The computational fluid dynamics-discrete element coupling method (CFD-DEM) provides an effective method to study the macroscopic mechanical characteristics of soil on the microscale, considering the influence of fluid-solid interaction. Regarding the current application status of CFD-DEM coupling method in geotechnical engineering, this paper systematically summarizes the advantages and disadvantages of existing fluid-solid coupling calculation methods, focusing on the modeling strategies of CFD-DEM coupling method. These strategies include solid particle shape modeling and inter-particle contact models, control equations and parameter calculation methods for the fluid phase, as well as CFD-DEM coupling calculation. Furthermore, the paper conducts an in-depth exploration of related issues and concludes by proposing future development directions for the CFD-DEM coupling method.

Abstract:

In order to compare the mechanical performance differences between grouted sleeve lapping connectors and butt connectors, uniaxial tensile and high stress repeated tension-compression tests were conducted on 41 lap connectors and 20 butt connectors. Results showed that under uniaxial tension and high stress repeated tension-compression loading, the total elongation ratio with maximum force of two kinds of connectors was greater than 6% and the ductility coefficient was greater than 4. The strength basically met the requirements of the codes. Under uniaxial tension after high stress repeated tension-compression, the bearing capacity of both connectors increased, while the initial stiffness and ductility of the specimens decreased. Moreover, the residual deformation of the lap connector was reduced by the anti-deflection measures, but the measured value of the residual deformation of the lap connector was slightly larger than that of the butt connector due to the limited constraint stiffness of the anti-deflection measures. However, the residual deformation of the lap connector and the butt connector of anti-deflection generally met the requirements of the specification. After high stress repeated tension-compression, during uniaxial tension testing, the middle section of the sleeve of the lap connector was longitudinally compressed and circumferentially stretched in the early stage of loading. In the later stage of loading, it experienced longitudinal stretch and circumferential compression, while the sleeve of the butt connector was longitudinally stretched and circumferentially stretched throughout the loading process. In the case of uniaxial tension after high stress repeated tension-compression, the maximum longitudinal tensile strain of the middle section of the sleeve near the bar side of the anti-deflection and non-deflection lap connector was 0.10 to 0.39 times and 0.13 to 0.18 times of the butt connector, respectively. Furthermore, the maximum circumferential compressive strain was 0.09 to 0.49 times and 0.02 to 0.32 times of the butt connector, respectively, which indicated that the lap connector had relatively low requirements on the material of the sleeve. When the diameter of rebar was the same, the material cost of the lap connector was about 35% lower than that of the butt connector.

Abstract:

To investigate the seismic behavior of reinforced concrete (RC) columns with stay-in-place ultra-high performance concrete (UHPC) formworks, named URC columns for short, we selected different assembly methods and surface treatment methods of UHPC formworks as design parameters and carried out pseudo-static tests on nine URC columns and one RC column. The assembly methods of UHPC formworks were boltangle steel connection, bolt connection, and epoxy resin mortar. The surface treatment methods of UHPC formworks were natural surface, bubble film printing, and adding ribs. The pseudo-static tests were conducted to study the influence of different assembly methods and surface treatment methods on the seismic behaviors of the URC columns. Additionally, on the basis of the assumption of plane section, a formula was proposed to predict the eccentric compressive bearing capacity of the URC columns. Results show that the bonding surface between UHPC formwork and concrete core had no apparent damage before the peak load, indicating that the URC columns have good integrity. In particular, the URC columns connected by boltangle steel had no interface bonding failure even under the failure load. Compared with the traditional RC column, the ultimate bearing capacity, ductility, and energy consumption of the URC columns were increased by 6.4%43.3%, 11.4%48.7%, and 27.7%85.3%, respectively. Among the three assembly methods, the URC columns connected by bolt and angle steel had the highest bearing capacity and the most reliable connection. Finally, the results calculated by the proposed formula were in good agreement with the test results, which can provide reference for practical application.

Abstract:

To study the impact of corrosion of both longitudinal bar and stirrup on the bonding performance of steel bar and concrete, we fabricated 25 corroded reinforced concrete (RC) specimens by the accelerated corrosion method of electroosmosis-constant current-dry wet cycles. Pullout tests were carried out on the specimens, and the influences of parameters such as longitudinal bar corrosion, stirrup corrosion, cover thickness, and stirrup spacing on bonding properties were studied. The effect of corrosion on the bonding force between concrete and steel bar was analyzed, and the degradation of the bonding performance was attributed to the reduction of the material behavior and the degradation of the constraint effect. On the basis of the test results, a modified bondslip constitutive model was established and verified considering design parameters and both corrosion of longitudinal bar and stirrup. A stressslip model of corroded longitudinal bar was obtained by combining the proposed constitutive model and infinitesimal algorithm. In the OpenSees platform, the stressslip model was applied to the zero-length section element, and the numerical model of corroded RC components considering bondslip behavior was established by adopting fiber-based beam-column element and zero-length section element. The accuracy of the model was verified according to the quasi-static test data of the corroded RC column, and the fiber model considering only corrosion damage was used for auxiliary verification. Results show that the bonding force between concrete and steel bar increased first and then decreased with the increase in the corrosion degree. Increasing the cover thickness could slightly improve the bonding force, while the increase in stirrup density could significantly improve the bonding force. Compared with the fiber model, the bearing capacity, cumulative energy dissipation, and ultimate displacement errors were reduced by 12.8%, 23.5%, and 14.2% in the constructed fiber model, indicating that the constructed model can reasonably calculate the contribution of steel bar slip and accurately predict the overall seismic response of the corroded RC columns.

Abstract:

In order to improve the separability of powdered activated carbon, a new type of magnetic activated carbon was prepared using chemical co-precipitation.Using methylene blue as target pollutants, performance of the powdered magnetic activated carbon was studied under varied conditions of pH, contact time and initial methylene blue concentrations, via the comparison with powdered activated carbon. The results showed that the adsorption capacity of synthetic magnetic powdered activated carbon was higher than that of the powdered activated carbon, and an alkaline pH value and adequate contact time were favorable for the pollutants removal. Under the condition of 100 mg/L methylene blue concentration, 0.4 g/L magnetic activated carbon dosage of, pH 9 and a reaction time of 300 minutes, the removal rate of methylene blue reached 98.9%. The adsorption behavior of methylene blue on magnetic activated carbon fitted the Langmuir isotherm and Elovich dynamics model. Thermodynamic analysis indicated that the adsorption was spontaneous endothermic reaction of single molecule layer, and the chemical adsorption played an important role during the adsorption process. The magnetic activated carbon had a good recyclable performance, it could complete precipitation in 10 minutes under natural condition, and could be quickly separated in 30 seconds under the action of outside magnetic field.

Abstract:

To accurately evaluate the safety and comfortability of structures after a long period of service under dynamic loads such as earthquakes and wind, it is critical to establish a structural dynamic model that can accurately reflect the dynamic responses of actual buildings under seismic, wind and other dynamic loads utilizing the monitoring/inspection data. In this paper, for popular frame building structures, an equivalent simplified dynamic modeling method is proposed by using a few numbers of wireless mobile sensors. First, the principle of equivalent interstory shear force for a simplified model of buildings is proposed, which proves that the simplified model constructed based on this principle has the ability to accurately simulate the dynamic response of actual buildings. Second, the form of simplified model of frame structure was derived, and the characteristics of the simplified model parameters were studied. Then, an iterative identification method for the parameters of the simplified model was proposed, which can identify all parameters of the simplified model by solely using a small number of wireless mobile sensors. Finally, a numerical simulation example of a 12-story 3-span steel frame structure was conducted, which investigates the predictive capability of the equivalent simplified model constructed by the method proposed herein to predict the dynamic responses of the actual frame structure subjected to different types of horizontal excitations, under the condition of without knowing the specific format of structural stiffness degradation and using only a small number of moving acceleration sensors. Simulation results show that the equivalent simplified model can very accurately predict the dynamic responses of the actual frame structure subjected to different types of horizontal excitations. Therefore, the model updating method for the equivalent simplified model of frame structures proposed herein will have important application potential in evaluating the structural safety and comfort of existing frame building structures under dynamic loads, such as wind and earthquake.

Abstract:

The existing graph-construction methods for graph optimization-based SLAM are summarized. The SLAM methods can be divided into three main classes, Kalman filter-based, partical filter-based and graph optimization-based, and the advantages and disadvantages of each class are overviewed. Moreover, there are mainly three graph modeling methods for the graph optimization-based SLAM problem, namely dynamic Bayesian network (DBN)-based model, factor graph-based model and Markov random field-based model. The key techniques of the front-end stage in graph optimization-based SLAM method, which mainly include data association between consecutive frame and loop closure detection, are discussed. Some newest research achievements on feature extraction, matching method, motion estimation, loop closure detection are introduced.

Abstract:

To explore the improvement mechanism of welding round steel at soffit on the flexural performance of eccentric concrete-filled steel tube (CFST) members, we established a numerical model of CFST beams reinforced with round steel by using ABAQUS software and verified the model by test results. By analyzing the bending momentdeflection curve, bending momentaxial strain curve, hoop strain curve, restraint index, and neutral axis offset of eccentric CFST members reinforced with round steel, the improvement mechanism of the flexural performance of the eccentric CFST members was revealed. Besides, the influence of the diameter of the round steel and the slenderness ratio of the beams on the flexural performance of eccentric CFST members reinforced with round steel was analyzed. Results show that welding round steel could lower the position of the neutral axis of the section and increase the hoop strain of the steel tube on the compression side. Therefore, the concrete area in compression was increased, and the restraint effect of the steel tube on the compression side on the concrete was enhanced. Furthermore, the flexural bearing capacity and flexural stiffness of the eccentric CFST members were improved, and the larger the diameter of the round steel, the greater the improvement. The ultimate bending moment of the eccentric CFST members decreased with the increase in the axial compression ratio, and the larger the diameter of round steel and the slenderness ratio of beams, the greater the reduction. Welding round steel had a better effect on improving the bending performance of the eccentric member with a large slenderness ratio, and the larger the axial compression ratio, the better the improvement effect.

Abstract:

Carbon dioxide (CO₂) capture, utilization and storage, as an emerging technology that can help reduce coal chemical plant greenhouse gas emission by large scale, have drawn significant attention. Pipeline transportation is an essential part of the technology, but high cost has greatly limited its application. Therefore the main objective is to develop an optimization model for supporting CO₂ pipeline transportation system planning to reduce the overall carbon capture utilization and storage (CCUS) system cost by optimizing key technology process of a CO₂ transportation system. The developed model was further applied to Shaanxi Yanchang's CCUS project for planning its CO₂ transportation system. The results indicated that in case of low demand of CO₂ storage, a gas-phase CO₂ pipeline transportation system coupled with in-situ compression and injection was recommended. In the case of high demand of CO₂ storage, this study would recommend a super-critical / density phase transportation system which could have lower system cost than gas phase pipeline system as the cost for compression at the site of storage can be saved

Abstract:

Starting from the tactile sensing performance of human skin, the progress and key technologies of tactile sensors for e-skin (electronic skin) akin to human skin by multidisciplinary fields are comprehensively reviewed. The sensing principle, new materials and structures, advanced design and making methods, sensing characteristics and performance of tactile sensors are analyzed. The recent domestic and foreign research advances of electronic skin tactile sensor array in flexibility, elasticity, spatial resolution, sensitivity, fast response, transparency, lightweight, multifunction and other aspects are summarized. It is difficult to achieve the tactile sensors for e-skin with high stretchable and flexible, less complex production process for high sensitivity e-skin, strong extensibility and low cost. The tactile sensors for e-skin can be widely used in robotics, medical health, aeronautics and space military, intelligent manufacturing, automotive security and other fields. The development of tactile sensors for e-skin toward the direction of high stretchable and flexible, high sensitivity in wide range, multifunction, self-healing and self-cleaning, self-powered and transparent, has been pointed out.

Abstract:

There are a large number of new and old concrete interfaces in prefabricated concrete structures. The template effect causes the enlargement of cement mortar porosity in the interfacial zones, which weakens their mechanical properties and durability. In order to quantitatively describe the porosity distribution characteristics of cement mortar in interfacial zones, new and old concrete specimens with smooth vertical interfaces and different water cement ratios were prefabricated. Scanning electron microscopy (SEM) was used to obtain the gray images of each specimen at different positions from the interface. Digital image processing (DIP) tools were used for image information enhancement and binarization. Thus, the ratio of pore pixels to total pixels was obtained, namely nominal porosity. With test results, the distribution characteristics of nominal porosity in the interfacial zones of new and old concrete with smooth vertical interfaces were analyzed. On the basis of the stable relationship between nominal porosity and real porosity, a porosity distribution model was established for the interfacial zones of new and old concrete with smooth vertical interfaces. Furthermore, considering the continuous variation of new and old concrete contents in the chiseled section, the porosity distribution model of chiseled interfacial zone was established. Results show that the nominal porosity reached the maximum at the interface, then decreased gradually towards the interior of concrete, and finally tended to be stable. The overall variation trend could be characterized by Gaussian function. With the increase in water cement ratio, the nominal porosity of each position from interface to interior concrete presented a relatively increasing trend, but the relative nominal porosity from the interfacial zone to the interior stable zone was nearly the same for the concrete with different water cement ratios.

Abstract:

To meet the requirements of large deployment ratio and high precision for deployable membrane mechanism in space missions, a deployable membrane mechanism based on Miura elastic creases was proposed and subjected to model, analyze and develop prototype. According to the crease distribution law and geometric relations, Miura-ori geometric model was established to investigate the influence law of the crease parameters on the deployment ratio and creases total length, and to calculate and optimize the crease parameters. In ABAQUS/Explicit, the numerical simulation models of the four-creases basic unit with θ= 90° and θ<90° were established respectively to analyze the mechanical behavior of the key membrane creases, and the feasibility of two-dimensional elastic crease was preliminarily proved. The elastoplasticity of the triangular membrane of Miura-ori was further studied, and the change curve of stress with folding process at the intersection of creases was plotted and the peak stress of which was within the range of material elasticity. And the space deployable membrane mechanism prototype was developed to conduct validation and analysis. The results show that the mechanism configuration design scheme is reasonable and a membrane folding scheme based on Miura-ori with large deployment ratio and small creases total length could be obtained by optimizing the crease parameters, and the high surface flatness of the deployed membrane proves the feasibility and superiority of Miura elastic creases.

Abstract:

To update the structural finite element model through stochastic static displacement measurement data and maintain the computational efficiency, we proposed a stochastic model updating method based on homotopy meta-model and Bayesian sampling method. First, the objective function was constructed by using the static displacement of the structure, and the delayed rejection adaptive sampling algorithm was used to estimate the posterior probability density of the updated parameters. In the process of sampling, the homotopy meta-model was adopted instead of the finite element model to calculate the static displacement of the structure. Numerical examples and test results show that when updating the finite element model of variable cross-section beam, as opposed to the quadratic response surface model, by incorporating the homotopy meta-model into the static Bayesian model method, the posterior probability density of the updated parameters could reproduce the stochastic response of the structure more accurately, making the probability density function of the stochastic response of the updated structure more consistent with that of the measured results. Even when the coefficient of variation of the stochastic measurement error was large and the difference between the prior information and the real updated parameters was large, the proposed method could quickly obtain the posterior probability density of the updated parameters, so that the probability density function of the structural stochastic displacement response calculated by the updated parameters was consistent with that of the measured results. The homotopy meta-model combined with Bayesian sampling algorithm can update the stochastic model of the structure quickly and accurately within the probability framework.

Abstract:

To describe the nonlinear magneto-mechanical coupling effect of materials more accurately, a coupled magneto-elastic model and a variable stiffness model were proposed based on nonlinear magneto-strictive strain equation, effective field theory, and energy balance equation. The magneto-mechanical effects and variable stiffness effects of ferromagnetic materials were studied, and the theoretical results of the nonlinear magnetization model were coupled with the simulation process using numerical analysis software. The results showed that the defect leakage field distribution obtained by the simulation was consistent with the existing research results, which verified the feasibility and accuracy of the proposed model and simulation method. The effects of stress, defect size, and defect location on the surface magnetic field were also analyzed. The results showed that under the action of tensile load, the normal magnetic field signal on the surface of the sample was like an S-shaped curve, and the tangential signal was like a conical curve, and its extreme values first decreased and then increased with the increase in the load. When there was a defect in the sample, the signals obtained on different acquisition paths were very different, and the peak value of the leakage magnetic field on the defect edge path was negatively correlated with the defect length, but the peak distance and span were opposite. On the collection route far from the defect, the peak value and span of the leakage magnetic field signal were positively correlated with the defect length.

Abstract:

In order to explore the erosion damage mechanism of polymer cement protective layer on concrete surface of water transfer project under the action of high-speed water flow, the erosion characteristics of protective layer were studied by using improved high-pressure water gun erosion test equipment. Four characteristic parameters including maximum length, maximum width, maximum depth, and volume of erosion area were extracted by 3D scanning. The erosion damage pattern, damage parameter evolution law, and damage mechanism of protective layer under different spray pressure, spray length, spray angle, and spray time were analyzed. Taking the maximum erosion depth of protective layer as the target value, a prediction model of protective layer erosion depth based on Logistic regression function was established. Results show that under the same working conditions, the four erosion damage characteristic parameters of protective layer all increased with the increase in spray pressure and erosion time. With the increase in spray length (from 0.5 cm to 6.6 cm), the erosion pattern of protective layer changed from "hourglass" to "strip". In this process, the damage effect of hydraulic fracturing on the interface between protective layer and concrete decreased. The proposed prediction model of erosion depth of protective layer achieved good accuracy, and the erosion damage degree of protective layer could be significantly reduced by increasing the spray length and spray angle, which provides a reference for the surface protection design of concrete engineering.

Abstract:

The wear of cutter is an important factor affecting the efficiency of shield tunneling, which is also a basis for determining the time and frequency of cutter replacement. As it is difficult to evaluate the overall wear state of the cutters in the process of shield tunneling, three wear degrees (light, moderate, and severe) were proposed based on the relationship between the wear amount of each cutter and the limited wear at the cutters change site. The theoretical relationship between three main tunneling parameters (thrust, torque, and tunneling speed) and the cutting force component of a single cutter was derived, and a method for recognizing the overall wear state of cutters was proposed by using the wavelet packet algorithm to decompose the tunneling parameter signals. In this method, the eigenvectors composed by the standard deviation of the wavelet packet coefficient of decomposed signal nodes were used as the wear recognition index. Sensitivity analysis was performed to find out the most sensitive node eigenvector of the cutter wear. Then the functional relationship between the wear state and the wear recognition index was determined by fitting. The analysis of the section from Dayun station to Baohe station of Shenzhen Metro Line 14 showed that the method could accurately recognize the overall wear state of the shield cutters. Among the three tunneling parameters, the recognition accuracy was the highest when using the tunneling speed signal, followed by the thrust signal, and the torque signal was the lowest. The proposed method is easy to use and cost-effective, since it only needs to analyze the automatically collected tunneling signals without installing any sensors, which provides reference for cutter replacement.

Abstract:

To investigate the dynamic performance and unloading failure characteristics of coal under non-hydrostatic conditions, based on 3D dynamic and static loading experiment, the effect of unloading method on the macroscopic failure characteristics of unloading coal samples after dynamic disturbance was studied. Firstly, Ф50 mm split Hopkinson pressure bar system was used to carry out the dynamic experiment of coal sample under 3D dynamic and static loading for the purpose of studying the influence of axial compression and strain rate on the dynamic response of coal samples. Secondly, based on the response surface theory, a regression model considering the interaction of factors was constructed by using the central composite test method and the significance of single factor and factor interaction were analyzed. Afterwards, combined with factor interaction, Weibull distribution and Drucker-Prager criterion, the strength statistical damage constitutive model of coal was modified. The reliability of the model was verified by comparing the theoretical and experimental results. Finally, with the help of loading and unloading electro-hydraulic servo device, the influence and mechanism of axial pressure, impact pressure and unloading mode on the failure characteristics of coal samples were explored. The results showed that the constructed strength statistical damage model has a correlation coefficient R²≥0.88, which can characterize the dynamic response behavior of coal samples. The coal samples with synchronous unloading after impact are mostly spalled, and the tensile interface moves backward and eventually disappears with the increase of axial pressure, unable to form spall failure. The failure modes of coal samples under non-synchronous unloading mainly include overall integrity, spalling and compression-shear failure. However, when the impact pressure is in the range of 0.4 to 0.6 MPa and the axial pressure is 14.5 MPa, a mixed failure mode of ‘spalling + compression-shear’ is observed.

Abstract:

To study the effect and mechanism of cohesive sediment gradation on cavitation and cavitation erosion in high velocity flow, we selected two cohesive sediment gradation curves and conducted research in a self-developed small looped water tunnel. Sediment-laden flows with different mass percentages of cohesive sediment smaller than a certain grain size were prepared, and the real-time pressure within cavitation and cavitation erosion zones in working section of water tunnel was measured by a dynamic pressure data acquisition system. Concrete specimens with different mix proportions were prepared. Tests of cavitation erosion on the concrete specimens under different mass percentages of cohesive sediment smaller than a certain grain size were carried out for 4 h. The mass loss of concrete specimen per hour was adopted to characterize the cavitation erosion amount . Results show that the time-averaged pressure and cavitation number at each measurement point in the cavitation erosion zone of the working section of water tunnel gradually increased with the decrease in the mass percentage of cohesive sediment smaller than a certain grain size. With the decrease in the mass percentage of cohesive sediment smaller than a certain grain size, the cavitation erosion amount of concrete specimens gradually increased. The anti-cavitation erosion capacity of concrete specimens with higher strength was significantly greater than that with lower strength at the same flow velocity. Cavitation zone was mainly located in the front of the specimen at lower velocity, while it was located in the rear at higher velocity. Under the same sediment concentration, the higher the percentage of cohesive fine grain used in the test, the greater the cavitation erosion amount was.

Abstract:

To further improve the cooling performance of the combustor flame tube, a binaural hole film cooling structure with higher cooling performance is proposed. The flow, heat transfer and cooling characteristics of traditional cylindrical hole, diffuser hole, convergent hole and binaural hole with blowing ratio from 0.67 to 2.01 were analyzed by numerical simulation. The results show that, compared with the other three film hole shapes, the aspect ratio of the cooling wall is in the range from 0 to 40, the kidney-shaped vortices formed by the cooling air flow at outlet of the binaural hole under the action of high temperature main flow are smaller in size, weaker in strength, larger in distance between the centers of the vortices, wider in transverse distribution of the cooling air flow, and lower in heat transfer coefficient on the wall, the film cooling performance is improved. When the blowing ratio is 2.01, compared with cylindrical hole, the flow coefficient of diffuser hole is increased by 13.7% , the wall heat transfer coefficient ratio is decreased by 1.5% , the flow coefficient of the convergent hole is unchanged, the heat transfer coefficient ratio is decreased by 2.7%. However, the flow coefficient of the binaural aperture decreased by 3.1% and that in the aspect of heat transfer coefficient ratio decreased by 11.25%. When the blowing ratio is 1.33, compared with diffusion hole and convergent hole, the flow coefficient of binaural hole is lower. When the slenderness ratio less than 40, the heat transfer coefficient ratio of binaural hole is the lowest and the cooling effect is the best.

Abstract:

The icing of transmission lines has seriously affected the safe operation of the power grid. Existing transmission line icing models mostly ignore the axial icing difference and consider the key icing parameters as time-invariant (single-step) conditions, while there are few reports on three-dimensional ice accretion model with time-varying (multi-step) parameters. Based on lubrication theory and line icing mechanism, this paper proposes a transmission line icing model considering the influence of time-varying icing parameters. By adopting the ANSYS-Fluent ICING module, the icing calculation for time-varying parameters was carried out on the three-dimensional line model. The validity of the calculation method was verified by using actual transmission line icing test data, and the calculation results were in good agreement with the test results. On this basis, the single-step and multi-step ice accretion calculation methods were compared. The influence of the transmission line inclination angle and line diameter on the shape and mass of ice accretion was analyzed. Results show that the accuracy of multi-step icing calculation method was about 8% higher than the single-step icing calculation method. Under the condition of dry ice coating, with the increase in the inclination angle of the transmission line, the shape and mass of ice accretion on the transmission line had no obvious change. Under wet icing conditions, the inclination angle of the transmission line had a significant effect on the ice accretion. As the inclination angle increased from 0° to 60°, the ice coverage area decreased and the shape of ice accretion gradually became smoother, but the ice accretion mass decreased by about 21%. The calculation results of ice accretion on transmission lines with large and small diameters were compared, and the amount of ice accretion on lines with large diameters was significantly higher than that on lines with small diameters.

Abstract:

The rolling bearing of gearbox of electric multiple-unit (EMU) is in a variable speed condition with high temperature and heavy load during operation, which is easy to induce faults such as cracks and pitting corrosion that are difficult to be detected. In order to diagnose the faults of rolling bearing in gearbox of EMU in time and ensure the safe operation of EMU, a rolling bearing fault diagnosis method under variable speed condition was proposed. First, a fusion time-frequency analysis algorithm was proposed, combining the characteristics of no interference term of short-time Fourier transform (STFT) and high time-frequency resolution of Wigner-Ville distribution (WVD), which can improve the time-frequency matrix accuracy of variable speed signal analysis. Then, the dynamic path planning method was improved considering the limitation that this method cannot deal with the normalized time-frequency matrix, and the speed curves in the fused time-frequency matrix were extracted. Furthermore, an order analysis method of interpolation resampling was proposed. The interpolation resampling of the original signal was performed according to the speed. The signal was reconstructed in the angular domain, and the corresponding order spectrum was obtained to realize the fault diagnosis of rolling bearing. Finally, the proposed fault rolling bearing diagnosis method was verified on test bench, and results showed that the proposed method could effectively extract the variable speed curves of the rolling bearing when the speed of the EMU changed, and accurately identify the fault types of the rolling bearing in the gearbox.

Abstract:

Considering that material parameters of U-shaped electrothermal actuators are affected by the temperature nonlinearity and the discontinuous boundary problem in the simplified model, the transient displacement characteristics were studied. By introducing temperature-related material renewal functions, based on thermodynamic theories such as energy conservation equations and material mechanics theories such as virtual work principles, the electro-thermal-mechanical coupling model of U-shaped electrothermal actuators was established. The improved Chebyshev spectrum method was used to solve the constructed coupling model, and the expression of temperature and transient displacement of U-shaped electrothermal actuator was obtained. The results of finite element simulation and theoretical analysis were basically the same, verifying the correctness of the model. An experimental platform for the transient displacement characteristics of the electrothermal driver was built, and the displacement response experimental results of the U-shaped electrothermal driver under constant voltage excitation were compared with the theoretical and simulation results. The transient displacement characteristics of the driver under the action of a periodic sinusoidal voltage were analyzed. The test and analysis results show that the displacement change trend of the U-shaped micro-electric thermal driver showed a sinusoidal change after a period of time, and the change period was equal to the voltage period; the displacement change range varied positively with the peak-to-peak voltage, and negatively with the change in voltage frequency.

Abstract:

To solve the problem that the single-vortex gripper is easy to cause the rotation of workpiece due to the internal rotating flow field, resulting in the failure of non-contact handling, a concentric double-vortex non-contact vacuum gripper scheme was proposed. The structures of the inner and outer vortex chambers are concentric and the flow directions are opposite. The inner vortex generates a vacuum to provide suction force, and the reverse airflow of the outer vortex is used to balance the friction torque of the inner vortex on the workpiece. The effects of the working parameters of the gripper on the friction torque and suction force on the workpiece were studied. Simulation results show that the friction torque generated by the outer vortex on the workpiece is slightly greater than that of the inner vortex under the same air supply pressure, suggesting that the rotation prevention can be achieved by appropriately reducing the air supply pressure of the outer vortex chamber. Under the same air supply flow, the suction force of double-vortex gripper is slightly less than that of single-vortex gripper. The influence of the structural parameters of the double vortex gripper on the suction force was analyzed, and the orthogonal experiment was carried out to obtain the optimal structural parameter. The prototype of double-vortex gripper was tested, the results show that under the same conditions, the suction force of concentric double-vortex non-contact vacuum gripper is basically equivalent to that of single-vortex gripper, and the torque of the workpiece is reduced by about 90%, that improves the stability of the workpiece and the reliability of handling.

Abstract:

Under the combined actions of wind, wave, and current, the floating wind turbine is prone to creep in mooring, which can accelerate corrosion, increase the failure probability, and affect the stability of the platform. In order to ensure the safe operation of floating wind turbine and achieve early warning in the early stage of mooring creep, this paper proposes a mooring fault diagnosis method for floating wind turbine based on multifractal analysis. First, the mooring fault nonlinear information was extracted by variational mode decomposition (VMD) method, and the impact of mooring creep and mooring failure at different locations on the stability of floating wind turbine was analyzed. Then, considering the multi-metric characteristics of the nonlinear signal, multiple fractal detrended fluctuation analysis was used to extract the fault signal characteristics, and it was estimated whether mooring creep occurred and the locations of mooring creep. Finally, the platform response data under mooring creep at different locations were analyzed. Results show that when the original signal was processed by VMD and the fractal box dimension was used to filter the feature signal, the noise was effectively filtered and more representative nonlinear features were extracted. The mooring fault signal had multiple fractal features, and the mooring creep and its location were effectively estimated by the singularity index α₀. The nonlinear features extracted by VMD could be estimated according to the data complexity by the multiple fractal detrended fluctuation analysis. The state of the mooring could be determined based on the complexity of the data. The research results can provide theoretical methods for information extraction and fault determination of offshore floating wind turbine moorings.

Abstract:

To investigate the effect of liquid phase convective on the mass burning rate of medium scale pool fires, the liquid phase of pool fires was studied. A 3-D numerical model based on gas-liquid two-way coupling was used to model the pool fire. The gas phase and liquid phase were solved by large eddy simulation and direct numerical simulation respectively, taking into account buoyancy and Marangoni effects in the liquid phase. The heat and mass transfer between the two phases were calculated using a conjugate heat transfer method and an evaporation model. The proposed model was then validated by three pool fire experiments with different fuel sizes, fuel thicknesses and fuel types. The research results showed that the proposed model could accurately predict the mass burning rate of medium scale pool fires with a prediction error of less than 3%; in the development stage of pool fires, ignoring the Marangoni effect and buoyancy effect led to the maximum liquid velocity increased by 34.3%, the liquid surface temperature difference increased by 70.1% and the mass burning rate prediction error increased by 11.2%. In the stable combustion stage of pool fires, the buoyancy effect and the Marangoni effect had little influence on the instantaneous mass burning rate. With the increase of the diameter and the decrease of the depth of pools, the effect of the buoyancy effect on the combustion rate gradually decreased; Considering the descending process of the liquid level of thin-layer pool could reduce the prediction error of the combustion rate by 19.2%. In the numerical simulation, considering the liquid phase convective motion and the liquid surface drop process contributed to improve the prediction accuracy of the mass burning rate of medium scale pool fires.

Abstract:

The large deviation of adjacent concave and convex angles in multi-pass roll forming of P-shaped special-shaped tubes for automobile columns cannot meet the high-precision requirements. On the basis of the large elastic-plastic deformation theory, a 15-pass roll forming finite element model of P-shaped special-shaped tube was established by using the professional design software COPRA. Combined with the actual production process, the finite element simulation of the complete forming process was carried out, and it was found that the insufficient supply of the perimeter of the welded pipe and the uneven metal flow of the corners of the P-shaped special-shaped tube in the roll pass caused the large deviation of the adjacent concave and convex angles. Thus, a precise control method of adjacent angles was proposed based on simulation and production practice, which combines selecting the appropriate compression coefficient, assigning the appropriate section deformation, and correcting the roll shape. The finite element simulation of roll forming of the P-shaped special-shaped tube was carried out by the proposed method. Results showed that the cross-section of the simulated final product was basically the same as the design cross-section, the concave and convex angles were 90.5° and 89.9°, and the angle deviation was within the error range of ±1°. The metal flow was in place, so that the corner metal filled the roll pass, which improved the forming quality of the adjacent concave and convex angles of the P-shaped special-shaped tube. The proposed method achieved an increase of 33.84% and 36.70% in the accuracy of the adjacent concave and convex angles of the P-shaped special-shaped tube through industrial application, which can effectively improve the forming quality of the P-shaped special-shaped tube and provide basis for production practice.

Abstract:

It is well known that unmanned aerial vehicle (UAV) is more and more widely applied in military and civil areas. In order to play the better role of UAV, it is needed to utilize multi UAVs cooperative formation to accomplish cooperative reconnaissance, combat, defense and spraying pesticides and other tasks. The multi UAVs cooperative formation control technology mainly contains the following key techniques: data fusion technology, sensing technology, task allocation technology, path planning technology, formation control technology, communication network technology and virtual/physical verification platform technology. Firstly, summarize the research and development of key technologies worldwide. Then, the classification for multi UAVs formation control methods is mainly investigated, and the problems about formation design and adjustment, formation reconfiguration are summarized. Finally, the challenges and future development for multi UAV cooperative formation are prospected. Research shows: at present, the theory of multi UAV formation flight has acquired fruitful results, while the real cooperative formation flight test can only be implemented in the simple communication environment. The real time performance for task allocation and path planning is not high. The robustness of control methods to cope with the unexpected situation is low. The cooperative sensing ability for multi UAV with multi sensor is insufficient. The simulation of the entity is lacked. Breaking through the above key technologies, carrying out the cooperative formation flight of multi UAV in complex sensing constraints and complex communication environment, putting forward more effective control method and carrying out the UAV physical formation flying test so that the UAV can finish the task better may be the future research directions.

Abstract:

A fault tolerant control scheme based on integral sliding mode surface is developed for spacecraft attitude stabilization in the presence of actuator faults, misalignments, magnitude saturation and external disturbances simultaneously. This approach is based on a novel integral-type sliding mode control strategy to compensate for these un-desired issues without controller reconfiguration. Especially, it guarantees the reachability of the system states by involving adaptive control technique to relax the boundary information in advance. A sufficient condition for the controller to accommodate magnitude saturation is also presented and then the fault tolerant attitude control system can be guaranteed theoretically to be asymptotically stable by using Lyapunov method. Numerical simulation results shows that the proposed control law can quarantee the stability of the spacecraft attitude control system in the presence of actuators' failures, and it has good robust performance.

Abstract:

To study the development status of wearable soft upper limb exoskeleton and its key technical challenges, the current literature in this field was analyzed and summarized. Exoskeletons can effectively provide functions such as protection and support to address limb fatigue and physical function decline resulting from high-intensity and repetitive work, as well as limb movement disorders caused by stroke or occupational diseases. Additionally, they have the capability to restore or enhance human movement ability through additional power and functionality. Wearable soft exoskeletons, as a new development direction of exoskeletons, have obvious advantages over traditional rigid exoskeletons, such as structural flexibility, human-machine interaction, and wearable comfort. Firstly, this paper provides a detailed analysis of three main driving methods of soft upper limb exoskeleton (rope drive, pneumatic, shape memory alloy). The relevant research results and corresponding structural characteristics of different driving methods are throughly examined. Then, the key technical challenges of soft upper limb exoskeleton are analyzed and expounded from four aspects: structure, material, control and auxiliary technology. Finally, considering the needs of exoskeleton applications in different fields, future trends in soft upper limb exoskeleton technology are speculated to focus on flexibility, comfort, compliance and intelligence. This study shows that the technology for wearable soft upper limb exoskeletons is still in its early stages, with many technical challenges to be solved. Futhurmore, breakthroughs in key technological challenges can be facilitated by novel soft actuators, soft sensors and other related advancements.

Abstract:

In the ultra-dense network environment, each access point is deployed in the hotspot area, which forms a complex heterogeneous network. Users need to choose the appropriate network to access, so as to achieve the best performance. Network selection problem is to choose the optimal network for the user, so that the user or network performance reaches the best. In order to solve the access selection problem of users in ultra-dense networks, we proposed an ultra-dense network access selection algorithm based on the improved deep Q network (DQN), considering network states, user preferences, and service types, and combining with load balancing strategies. First, by analyzing the influence of network attributes and user preferences on network selection, the appropriate network parameters were selected as the parameters of the access selection algorithm. Then, the problem of network access selection was modeled by Markov decision-making process, and the states, actions, and reward functions of the model were designed. Finally, the optimal network strategy was obtained by using DQN to solve the network selection model. In addition, the target function of traditional DQN was optimized to avoid overestimation of Q value by DQN, and a priority experience replay mechanism was introduced to improve learning efficiency. Simulation results show that the method could well solve the problem of overestimation of traditional DQN, accelerate the convergence of neural network, effectively reduce user congestion, and improve network throughput performance.

Abstract:

In view of the weaknesses of poor computing and storage capabilities of edge devices, lightweight processing was carried out on the backbone network CSPDarkNet53 for feature extraction in the traditional YOLOv5 model, and a lightweight gesture recognition algorithm MPE-YOLOv5 was proposed to realize the deployment of the model in low-power edge devices. Considering the problem that it is difficult to identify large-scale transformation targets and tiny targets due to less feature extraction in lightweight model, efficient channel attention (ECA) mechanism was added to alleviate the loss of information after high-level feature mapping due to the reduction of feature channel. A detection layer for tiny targets was added to improve the sensitivity to tiny target gestures. EIoU was selected as the loss function of the detection frame to improve the positioning accuracy. The effectiveness of the MPE-YOLOv5 algorithm was verified on the self-made dataset and NUS-Ⅱ public dataset, and the MPE-YOLOv5 algorithm was compared with lightweight M-YOLOv5 algorithm and original YOLOv5 algorithm on the self-made dataset. Experimental results show that the model parameters, model size, and computational complexity of the improved algorithm were 21.16%, 25.33%, and 27.33% of the original algorithm, and the average accuracy was 97.2%. Compared with the lightweight model M-YOLOv5, MPE-YOLOv5 improved the average accuracy by 8.72% while maintaining the original efficiency. The proposed MPE-YOLOv5 algorithm can better balance between the detection accuracy and real-time reasoning speed of the model, and can be deployed on edge terminals with limited hardware.

Abstract:

Autonomous navigation based on sequential images (ANBSI) is the key technology of pinpoint landing missions for future deep space exploration and also is one of the major development directions for deep space exploration technology. The necessity of developing ANBSI for planetary pinpoint landing is elaborated in this paper. Firstly, state-of-art developments of ANBSI are reviewed in terms of active sensing and passive sensing. Then, the key techniques applied in ANBSI for planetary landing are summarized and analyzed. Finally, according to the analysis of the key techniques, the main issues of ANBSI are raised and their future developments are overviewed.

Abstract:

The existing graph-construction methods for graph optimization-based SLAM are summarized. The SLAM methods can be divided into three main classes, Kalman filter-based, partical filter-based and graph optimization-based, and the advantages and disadvantages of each class are overviewed. Moreover, there are mainly three graph modeling methods for the graph optimization-based SLAM problem, namely dynamic Bayesian network (DBN)-based model, factor graph-based model and Markov random field-based model. The key techniques of the front-end stage in graph optimization-based SLAM method, which mainly include data association between consecutive frame and loop closure detection, are discussed. Some newest research achievements on feature extraction, matching method, motion estimation, loop closure detection are introduced.

Abstract:

In order to improve the separability of powdered activated carbon, a new type of magnetic activated carbon was prepared using chemical co-precipitation.Using methylene blue as target pollutants, performance of the powdered magnetic activated carbon was studied under varied conditions of pH, contact time and initial methylene blue concentrations, via the comparison with powdered activated carbon. The results showed that the adsorption capacity of synthetic magnetic powdered activated carbon was higher than that of the powdered activated carbon, and an alkaline pH value and adequate contact time were favorable for the pollutants removal. Under the condition of 100 mg/L methylene blue concentration, 0.4 g/L magnetic activated carbon dosage of, pH 9 and a reaction time of 300 minutes, the removal rate of methylene blue reached 98.9%. The adsorption behavior of methylene blue on magnetic activated carbon fitted the Langmuir isotherm and Elovich dynamics model. Thermodynamic analysis indicated that the adsorption was spontaneous endothermic reaction of single molecule layer, and the chemical adsorption played an important role during the adsorption process. The magnetic activated carbon had a good recyclable performance, it could complete precipitation in 10 minutes under natural condition, and could be quickly separated in 30 seconds under the action of outside magnetic field.

Abstract:

Starting from the tactile sensing performance of human skin, the progress and key technologies of tactile sensors for e-skin (electronic skin) akin to human skin by multidisciplinary fields are comprehensively reviewed. The sensing principle, new materials and structures, advanced design and making methods, sensing characteristics and performance of tactile sensors are analyzed. The recent domestic and foreign research advances of electronic skin tactile sensor array in flexibility, elasticity, spatial resolution, sensitivity, fast response, transparency, lightweight, multifunction and other aspects are summarized. It is difficult to achieve the tactile sensors for e-skin with high stretchable and flexible, less complex production process for high sensitivity e-skin, strong extensibility and low cost. The tactile sensors for e-skin can be widely used in robotics, medical health, aeronautics and space military, intelligent manufacturing, automotive security and other fields. The development of tactile sensors for e-skin toward the direction of high stretchable and flexible, high sensitivity in wide range, multifunction, self-healing and self-cleaning, self-powered and transparent, has been pointed out.

Abstract:

Considering the failure mechanism and weaknesses of traditional fabricated shear wall structures under strong earthquakes, a new type of fabricated shear wall with functions of energy dissipation and shock absorption was proposed. On the basis of model test and numerical simulation, seismic performance tests were carried out on four specimens with scale ratio of 1∶1.54 and shear span ratio of 1.52. Further analysis was conducted to investigate the effects of bolt number, axial compression ratio, and reinforcement ratio of edge members on the seismic performance of the new fabricated shear wall, including failure modes, hysteretic performance, bearing capacity, displacement ductility, stiffness degradation, and energy dissipation capacity. Test results show that the four specimens experienced shear compression failure, which was the same as the cast-in-place shear wall with the same shear span ratio. However, the proposed shear wall had better hysteretic performance and energy dissipation capacity, and the energy dissipation capacity was higher than that of the cast-in-place shear wall at the failure point. When the number of bolts decreased, the hysteretic performance of the new fabricated shear wall decreased, the wall deformation increased, while the bearing capacity remained almost unchanged. When the axial compression ratio or reinforcement ratio of edge members decreased, the bearing capacity decreased, and the ultimate displacement increased. Finally, the finite element model of the specimens was established by ABAQUS program. Comparisons of numerical results and test results showed a good agreement, verifying the correctness of the model, which can be applied to the analysis of the new fabricated shear wall.

Abstract:

To investigate the ground motion intensity measures suitable for evaluating high-rise structures under near-fault ground motions with pulse-like effect, this paper proposes a new ground motion intensity measure considering period elongation effect and higher mode effect based on acceleration spectrum. Taking two high-rise reinforced chimney structures (120 m and 240 m) as research objects, the correlation between damage indices (ParkAng damage index, maximum inter-story drift ratio, maximum structural curvature, maximum floor acceleration, and maximum roof displacement) of high-rise structures and 37 ground motion intensity measures was studied under near-fault ground motions using OpenSEES. Results show that the proposed intensity measure was the optimal index in predicting the ParkAng damage of high-rise concrete structures under near-fault ground motions. High correlation between velocity-related intensity measures and structural damage index was observed. As the structural period increased, the correlation between damage indices and displacement-related intensity measures was improved. Besides, peak ground acceleration had limitations in characterizing the deformation and failure of high-rise structures, but it could be used to analyze the seismic performance of non-structural components. The research results can provide reference for selecting proper measures and structural damage indices to evaluate the seismic performance of high-rise structures under near-fault ground motions.

Abstract:

In view of the problems of low brightness and obvious color distortion of the sky in restored images in most existing algorithms for image dehazing, a haze removal method for UAV aerial images based on atmospheric light value and graph estimation was proposed. First, the depth-of-field image was obtained according to the color attenuation prior theory, and the mean value of the region with the minimum deviation in the depth-of-field image was taken as the atmospheric light value. Then, a random walk clustering method was designed to estimate the atmospheric light map. The random walk algorithm was used to cluster the image into N sub-regions, and the mean value of the first 0.1% pixels of the sub-regions was taken as the regional atmospheric light value, which was then combined and refined by guided filtering to obtain the atmospheric light map. Next, the two atmospheric light estimators were fused into a new atmospheric light map with atmospheric light valuegraph estimation, which is a more accurate atmospheric light estimator. The transmittance was obtained by haze-lines prior method, and a dark compensation method was proposed to improve the transmission accuracy. Finally, according to the atmospheric scattering model, a clear restored image was obtained based on the fused atmospheric light map and optimized transmittance. Experimental results show that compared with other algorithms, the proposed algorithm improved the information entropy, mean gradient, blur coefficient, and contrast by 1.1%, 6.3%, 8.5%, and 6.4%, respectively, with better subjective visual effect and more abundant information.

Abstract:

The advent of Industry 4.0 has spawned the widespread application of digital twin technology, providing digital solutions for intelligent manufacturing and product life-cycle management. In the field of civil engineering, the enhancement of digital disaster prevention and civil structure management is a critical component in the development of future smart cities. On one hand, the establishment of precise and reliable digital twins of real-life civil structures can facilitate disaster prevention from extreme hazards, as well as identify and warn against potential risks. On the other hand, digital twins lay the foundation for technological advancements in the digital construction and management of future cities. This study first categorizes the fundamental concepts and developmental stages of digital twin technology. Then, the acquisition of twining data and construction of digital twins for civil structures are systematically summarized. Building on this foundation, a comprehensive review and outlook is presented on the application of digital twin technology in civil engineering, encompassing the operation and maintenance of structures, disaster simulation and digital twin cities.

Abstract:

In view of the problem that general pre-trained models are not suitable for named entity recognition tasks in the medical domain, a neural network architecture that integrates knowledge graph in the medical domain was proposed. The elastic position and masking matrix were used to avoid semantic confusion and semantic interference in self-attention calculation of pre-trained model. The idea of multi-task learning in fine-tuning was adopted, and the optimization algorithm of recall learning was employed for pre-trained model to balance between general semantic expression and learning of the target task. Finally, a more efficient vector representation was obtained and label prediction was conducted. Experimental results showed that the proposed architecture achieved better results than the mainstream pre-trained models in the medical domain, and had relatively good results in the general domain. The architecture avoided retraining pre-trained models in particular domain and additional coding structures, which greatly reduced computational cost and model size. In addition, according to the ablation experiments, the medical domain was more dependent on the knowledge graph than the general domain, indicating the effectiveness of integrating the knowledge graph method in the medical domain. Parameter analysis proved that the optimization algorithm which used recall learning could effectively control the update of model parameters, so that the model retained more general semantic information and obtained more semantic vector representation. Besides, the experimental analysis showed that the proposed method had better performance in the category with a small number of entities.

Abstract:

This paper proposes a low-latency intelligent network data transmission scheduling algorithm for real-time network transmission demand scenarios of low latency, stable transmission, and high quality of experience (QoE). The algorithm consists of two parts: data block queuing control strategy and congestion control strategy. The data block queuing control strategy presents a cost-effective model that integrates the creation time and effective time of data blocks, effectively solving the problem of uneven information transmission under transmission time constraint. The congestion control strategy proposes a deep deterministic policy gradient (DDPG) method based on the Gumbel distribution sampling reparameterization with mixed experience prioritization model, which solves the problem that DDPG is not applicable to the congestion control of discrete network action space and significantly improves the quality of network congestion control by adaptively adjusting the sending parameters through learning. Results show that the proposed queuing algorithm could effectively improve QoE in real-time transmission scenarios, and the improved DDPG for congestion control could significantly reduce transmission delay. In the same scenario, compared with traditional network data transmission scheduling algorithms, by integrating the proposed queuing and congestion control strategies, the improved intelligent network data transmission scheduling algorithm could maintain a good balance between low latency and stable transmission and provide higher data transmission quality.

Abstract:

Image segmentation is to divide the region with special meanings into several disjoint sub-regions according to certain rules, which is the key link between image processing and image analysis. The traditional watershed image segmentation method is widely used, which has the advantages of fast and simple. However, it is easily interfered by noise, and the segmentation results are prone to lose important edge information, resulting in over-segmentation. In view of the problem of the traditional watershed image segmentation method, an improved watershed image segmentation method based on adaptive structural elements was proposed. First, the adaptive structural elements with variable shapes were constructed by using local density, symmetry, and boundary features of adjacent pixels of image targets, so as to ensure a good consistency between the proposed structural elements and the shape of image targets. Then, the adaptive structural elements were used to obtain the morphological gradient of the image, which could improve the positioning accuracy of the target edge. The L₀ norm gradient minimization and morphological open-close hybrid reconstruction were used to modify the gradient image, so as to reduce the local invalid minimum points in the gradient image and suppress the occurrence of over-segmentation. Finally, watershed segmentation was performed on the modified gradient image to realize accurate segmentation of the target region of the image. Experimental results show that the method could effectively restrain over-segmentation of traditional watershed algorithm and improve the accuracy of the target edge positioning, with high precision of image segmentation.

Abstract:

The development of advanced nano-integrated circuit processes has led to a decreasing threshold charge in microelectronic devices, resulting in an increased rate of soft errors caused by single-event effects in digital circuits. To enhance the radiation resistance of standard cells in integrated circuits, this paper proposes a NAND gate structure that is resistant to single-event transients (SETs). In the triple well process, by shorting the substrate and source of each NMOS transistor in the pull-down network, the radiation resistance of the NAND gate was effectively improved, and the hardening of the proposed NAND gate became more effective as the number of inputs increased. Particle incidence simulation experiments were performed by Sentaurus TCAD software in hybrid simulation mode. For the NMOS transistor connected to the output node, the three-dimensional physical model that has been calibrated by the process was used, and the Spice model provided by the manufacturer was adopted for other MOS transistors. Simulation results show that the proposed two-input NAND in 40 nm process could reduce the output voltage fluctuation amplitude in three-input cases at the linear energy transfer (LET) value of incidence particle of 10 MeV·cm²/mg. Besides, the effect of immunity to single particle incidence was achieved in the input mode with N₂ transistor closed. For the hardened three-input NAND gate, the output voltage disturbance could be reduced by up to 85.4% even in the “worst case”. Therefore, the proposed hardening method for NAND gate has a significant effect against SET.

Abstract:

To study the connection method between reinforced bars of the precast concrete(PC) structure,81 plug-in filling hole for lap-joint of steel bar sample tests were made,and the main factors,such as reinforced bar diameter,concrete strength and anchorage length etc.were considered during the tests.The test results indicated that the ultimate failure state of all the anchoring specimens were the external reinforced bar yielding or broken up by pulling,and the abnormal anchorage was not destroyed.When the basic anchoring length was reduced by 10% or even 20%,specimens still showed enough safety.Based on this,the basic anchoring length of plug-in filling hole for lap-joint of steel bar can be given as 0.8 la.

Abstract:

Due to the complex background of ship targets and much irrelevant interference in visual images, it is difficult to conduct ship detection. In addition, there are few datasets for multi-category ship detection and the samples are often unbalanced, which makes the ship target detection performance degraded. Considering the ship detection background interference, an improved YOLOv3 model was proposed by introducing SimAM attention mechanism, which was used to enhance the weight of the ship target in the extracted features and suppress the weight of background interference, thus improving the model detection performance. Meanwhile, strong real-time data augmentation was applied to improve the unbalanced distribution of sample scales, and transfer learning was combined to improve the ship detection accuracy in the condition of a restricted number of samples. The visualization results of extracted features show that the improved model could suppress irrelevant background features, and the abilities of feature extraction and target localization were enhanced. Without introducing additional learnable parameters, the proposed model achieved 96.93% and 71.49% for mAP.5 and mAP.75 on the SeaShips dataset, and detection speed reached 66 frames per second, indicating a good balance between detection accuracy and efficiency. The improved model optimized the target features more effectively compared with the Saliency-aware CNN and eYOLOv3 models, resulting in an improvement of mAP.5 by 9.53% and 9.19%. The mAP.5 for ship type target detection on Singapore Maritime Dataset reached 81.81%, indicating that the proposed model has good generalization performance.

Abstract:

To clarify the wind-induced dynamic disaster mechanism of membrane structure, this paper analyzed the research progress of field test, aero-elastic model wind tunnel test and numerical simulation method of Fluid-Structure Interaction (FSI) problems, and discussed the latest research results on the additional aerodynamic force and aero-elastic instability mechanism of membrane structure. It was shown that by the limitation of field test equipment, similar theory of aero-elastic model and FSI simulation method, the research on the observation and simulation of practical membrane structure was still relatively few. As for the aero-elastic instability mechanism of membrane structure, it was believed that the aero-elastic instability of membrane structures was related to the vortices formed near the membrane surface, which was manifested as a significant attenuation of the total damping of the structure. However, the research results were based on the vibration phenomena observation of the simple membrane structure in the approximate uniform flow field, which was quite different from the actual project. The following aspects are suggested for researches: similarity analysis method and error correction technique of similarity theory of aero-elastic model wind tunnel test; key technology of numerical simulation of FSI problem of large-scale membrane structure; research on the aero-elastic instability mechanism of membrane structure that based on various research means including field test, aero-elastic model wind tunnel test, numerical simulation method, analytical theory, and so on; the wind-resistant design method of membrane structure, which is acceptable for designers to consider the FSI effect.