Abstract:In order to understand the corrosion influencing factors and the mechanism of each influencing factor of anchorage structures in underground engineering and improve the durability and long-term stability of permanent support structures in underground space, the research progress and achievements of the corrosion durability of anchorage structures in underground engineering are summarized and analyzed by combing literatures at home and abroad. Firstly, the necessity and urgency of research on corrosion durability of underground anchorage structures are pointed out. Secondly, the stress corrosion cracking mechanism of anchorage structures and the evaluation methods of stress corrosion are briefly described. Thirdly, the influencing factors of corrosion of underground anchorage structures are summarized, and the research status and mechanism of each influencing factor are discussed. Fourthly, the application of time-dependency analysis and reliability assessment in the study of durability of anchorage structures is introduced. Finally, based on the above analysis, the development trend of corrosion durability of underground anchorage structures is prospected in many aspects. It is pointed out that the transition from static analysis to dynamic analysis, the combination of qualitative and quantitative research, the development from single factor analysis to multi-factor analysis, the further development from macroscopic research to microcosmic research, and the evolution from deterministic analysis to probability and randomness analysis are the important directions to promote the research on corrosion durability of anchorage structures in underground engineering.

Abstract:To understand the temperature distributions of large scale cable-stayed bridges and provide loadings for thermal effect analysis, thermal field characteristics for the 3^rd Nanjing Yangtze River Bridge were investigated based on temperature monitoring data. Layout of the temperature sensors was firstly introduced. Then, the variation law of component temperatures over time was studied, and the correlation between component temperature and ambient temperature was discussed under the condition of solar radiation. Next, features of temperature gradients for the tower and steel box girder (vertical and transverse) were analyzed. Finally, extreme values of temperature actions corresponding to 100-year return period were estimated by using generalized Pareto distribution. Results show that the steel box girder temperature was linearly correlated with the ambient temperature, and the gradient parameter in the fitting equation increased with solar radiation intension. The maximum vertical temperature difference for the steel box girder occurred in summer, and its distribution form was much similar to the descriptions in BS 5400. The largest transverse temperature difference for the deck was in winter, and its distribution form was in line with multi-line model. The maximum temperature difference of the tower occurred in winter with the magnitude of 9.94 ℃. Except for the vertical temperature gradient of the steel box girder, the estimated values of the other thermal actions were all larger than those in the codes. The thermal field analysis results of the 3^rd Nanjing Yangtze River Bridge may assist thermal effect simulation of steel cable-stayed bridges as well as support bridge design specification revision and bridge maintenance.

Abstract:To improve the accuracy of urban traffic flow state identification under limited data condition, a model combining grey clustering and fisher transform (GC-fisher model) is proposed. First, the parameters of traffic volume (Q), speed (v), and occupation (O) were divided into four categories according to the grey clustering theory. Then training dataset was established by using the classified data, and the fisher transform and discriminant functions of each traffic flow state were obtained by using the GC-Fisher model. Afterwards, the combination of K-means and multi-class support vector machine (K-SVM) model was selected as the comparison model. Results of model discriminant rate and the case study show that the GC-fisher model outperformed K-SVM model under limited data condition: the discriminant rate was 92% by using GC-fisher, while the rate was 69% by using K-SVM. The GC-Fisher model can improve the discrimination accuracy of traffic flow state under limited data condition.

Abstract:A control strategy was proposed for air-to-air missile with blended lateral thrusters and aerodynamic control systems based on the fixed-time convergence sliding mode control and the dynamic control allocation. First, a fixed-time convergence sliding mode controller was designed by using the longitudinal dynamic model of the air-to-air missile to obtain the virtual control moments required by the overload of the missile, and the convergence of overload tracking error was realized in a given time. Then, with the dynamic control allocation, the required control moments were mapped into the control commands on the aerodynamic deflector and the lateral thrust engine array respectively. Third, on the basis of the Lyapunov theory, it was proved that the system which could quickly converge to the equilibrium point is fixed-time convergence. Finally, simulations were carried out to demonstrate the effectiveness of the control strategy.

Abstract:In order to accurately describe the Jones matrix of inhomogeneous field induced medium, elemental parameters in Jones matrix were studied. The physical parameters’ expression of Jones matrix based on the mathematical method of cascading micro-member Jones matrix was derived by means of unitary transformation. Theoretical research showed that the uneven distribution of the cross-section induction angle along the optical path was the reason for the multi-diagonal element of Jones matrix. The Jones matrix of the inhomogeneous field induced medium could be completely characterized by the physical parameters of medium phase delay, medium induction angle, and medium inhomogeneous angle. These physical parameters were the integrals of the corresponding section induced tensor components, among which the medium inhomogeneous angle could essentially characterize the sensing unevenness degree of the medium. The physical experiments of inhomogeneous magneto-optical mediums indicated that the off-diagonal elements of the Jones matrix on inhomogeneous field induced medium were complex numbers. The physical parameter simulation experiments of Jones matrix showed that the theoretical derivation of this paper had certain correctness. In general, the analytical expression of Jones matrix on inhomogeneous field induced medium is universal by considering not only all kinds of optical effects but also uniform and uneven conditions, where the Jones matrix on uniform medium is a special case.

Abstract:In order to investigate the attenuation effect of clear atmosphere on millimeter wave signals, the gases contributing the most to millimeter wave absorption in the atmosphere were analyzed based on HITRAN 2008 database of atmospheric molecular absorption spectroscopy parameters. A fine calculation model of the absorption of molecular spectral lines in the far wing was obtained by utilizing the Gross dynamic line. Based on this model, the physical property parameters and absorption spectrum of 6 primary absorbing gases including H₂O, O₂, and O₃ were calculated using the Line by Line method. Then, attenuation effects of atmosphere on millimeter wave were analyzed in both homogeneous and inhomogeneous path, respectively. Results calculated by the Line-by-Line method agreed well with the results calculated by the Liebe model method. In addition, compared with 94 GHz test system measurement data, the relative deviation was 3.7%. H₂O and O₂ strongly attenuated the millimeter wave signal in the 75-110 GHz millimeter wave band, accounting for more than 95% of the total gas attenuation. When the millimeter wave signal was transmitted horizontally at about 20 km, the attenuated effect of O₃ on the signal should be considered, and the attenuated effect of CH₄, CO, N₂O was negligible. The research results can provide reference for the engineering application of millimeter wave radar parameter design.

Abstract:In order to analyze the operational efficiency and the robustness of flight scheduling, computer simulation technology was applied to air transport system in this paper, and a flight operation system model which contains 118 major domestic airports was constructed based on Flexsim simulation software. The model implemented the flight scheduling operation of a large-scale airline by simulating the aircraft operation processes of take-off/landing, taxiing in/out, flight turnaround ground service, and segment flying. Parameters of several aircraft operation time were set by combining the classification method and different fitting distributions, such as fitting flight turnaround time with Logistic distribution. This system model could simulate flight operation under normal condition and abnormal condition (e.g., flow control), as well as export evaluation indexes, such as delay time, punctuality rate, aircraft utilization rate, and buffer time gap. Case analysis was validated to demonstrate the performance of the model and it showed that the model could accurately simulate the actual operation of airlines’ flight. Under normal condition, the key points of flight delays could be determined with the analysis of output indexes, whereas under flow control the transmission mode of delays were found to be passing down along the flight string as the delay time reduced gradually, and the turnaround time of directly affected flights was increased, while that of indirectly affected flights was reduced at the same time.

Abstract:In order to solve the problem of the effective aperture loss and resolution reduction of the direction of arrival (DOA) estimation algorithm under the coprime array due to the use of spatial smoothing preprocessing, a matrix with overlapped and augmented coarray preprocessing method is proposed. The principle of this method is to split the spatial smoothing covariance matrix and make use of the characteristic of its submatrices of having the same signal subspace. Overlap processing was applied to submatrices and the number of rows of the covariance matrix was expanded, thereby increasing the effective aperture. The simulation results validated that the proposed method can improve the resolution of the DOA estimation, and the accuracy of the estimation is also improved at low snapshots. At the same time, Unitary Estimation of Signal Parameter via Rotational Invariance Techniques (U-ESPRIT) algorithm was applied to the coprime array. By using matrix overlap preprocessing and combining U-ESPRIT algorithm, the DOA estimation result is more accurate than traditional methods.

Abstract:This research focused on the action depth of portable falling weight deflectometer (PFWD) impact load on road structure and proposed reasonable testing parameters for PFWD. Influence parameters of PFWD maximum load were analyzed and stress allowance θ was proposed as an index of stress attenuation. According to the stress solution of elastic half-space under rigid bearing plate, the relationship between θ and depth and radius of single-layer structure was established. Then the finite element model of double-layer structure under rigid bearing plate was built to analyze the effects of thickness, radius, modulus, and Poisson’s ratio on the vertical stress, and the relationship between θ and modulus ratio and thickness was established. The action depth was defined as the depth at which the stress decreases to a certain value. Results show that parameters such as the weight, height of the hammer, and the radius of the plate have effects on the maximum load. The degree of stress attenuation in a single layer structure depends only on the ratio of depth to plate radius. Stress attenuation becomes faster with the increase of the upper layer modulus, while it slows down with the increase of underlying layer modulus. Poisson’s ratio almost has no effect on the stress attenuation. The action depth of PFWD is different with different configurations (hammer weight, plate radius), which is recommended in accordance with analysis result and engineering practice, and reasonable parameters configuration was then proposed based on the stiffness ratio of the tested layer and the underlying layer.

Abstract:To ensure that the urban rail transit network timetables serve the passenger demand better, a flexible departing scheme was developed to improve the synchronization performance. Departure times with even headways were taken as the benchmark points, and the actual departure times were allowed to vary around the benchmark points within a certain range. Then, a synchronization optimization model with flexible departure headways was proposed to maximize the number of transfer-synchronized passengers in a network. Considering that the model includes an enormous amount of binary variables, an efficient genetic algorithm was designed to solve the model within limited time. The departure phase of each line with even headways and the flexibility of the departure time of each train were chosen as genes to form the chromosome. Finally, experiments were carried out and results showed that the genetic algorithm performed well and the method could improve the number of synchronized passengers significantly compared with the even-headway timetable that a flexibility of 10% in the even headway corresponded to an 11.85% increment in the number of synchronized passengers. The synchronized timetable with high transfer efficiency of a large-scale network could be quickly by the proposed method.

Abstract:In this paper, a driving controller for vehicles to avoid collision pedestrians in CVIS environment is designed. Based on the basic principle of the velocity obstacle method, a vehicle collision condition for pedestrian crossing was proposed, and an autonomous vehicle collision avoidance algorithm for pedestrians was established under the framework of model predictive control. Considering the operation constraints of driving, the vehicle driving strategy was optimized to minimize the change of vehicle speed and meet the driving comfort requirement under the premise of achieving pedestrian collision avoidance. Two control scenarios (i.e., vehicles going straight and changing lanes to avoid collision) were set up, and simulation experiments were carried out to verify the control effect in MATLAB environment. Results show that vehicles could avoid collisions by accelerating or decelerating when pedestrians cross the street under different conditions. By comparing with seven polynomials lane change trajectories, it showed that the safety of the autonomous collision avoidance driving was higher.

Abstract:To improve the accuracy of highway traffic flow prediction and provide effective support for the dynamic control induction of highway management departments, this paper takes the minimum prediction error of real-time traffic flow as the goal and divides the highway data into four different time intervals by cleaning and normalizing. The data set was divided into training data sets and test data sets. Genetic algorithm (GA) was used to optimize the parameters of data time window step as well as long-term and short-term memory (LSTM) neural network of hidden layer, training times, and dropout, and analyze the influence of four parameters on model optimization. In keras, GA-LSTM model utilized Tensorflow as a background for training and fitting. Experiments show that the GA-LSTM model had a fast search speed. Compared with the SVM, KNN, BP, and LSTM neural networks in the traditional prediction algorithm, the GA-LSTM had the minimum mean square error and root mean square error for data prediction, and the model exhibited better predictive performance.

Abstract:Aiming at the real-time, continuous, and quantitative evaluation of the homogeneity of asphalt concrete, taking the Jinan-Qimen Highway of Dangshan section in Anhui as an example, this study adopted the digital image processing technology, statistical method, and the principle of shape from shading to establish the homogeneity evaluation method and standard of asphalt concrete based on the quadrangular static moment variability and the structural depth variability in paving state and compaction state. Moment variation coefficient and structure depth variation coefficient were proposed as evaluation indexes to evaluate the homogeneity of asphalt concrete. To obtain accurate image information of asphalt concrete surface, the processes of digital image acquisition and pre-processing were standardized, and the illumination intensity and shooting height of image acquisition were recommended. The study showed that the proposed digital image evaluation method for the homogeneity of asphalt concrete was feasible and efficient, and the results were quantitative and objective, which could reflect homogeneity in the construction quality of asphalt concrete well. To achieve homogeneity of asphalt concrete paving, the moment variation coefficient should be controlled within (0,1.5%]. When AC-13 and AC-25 asphalt concretes were homogeneous in compaction state, the structure depth variation coefficient should be controlled within (0,4.0%] and (0,8.0%], respectively. Considering the method of subdividing asphalt concrete compaction image into 16 equal areas as the optimum, the correlation equation of the digital image structure depth variation coefficient in different equal subdivision ways was established by coefficient simulation, and the correlations were remarkable.

Abstract:To investigate different traffic modes for resident’s travel trajectories, a classification model was constructed based on Light Gradient Boosting Machine (LightGBM) to categorize transportation modes according to resident’s GPS trajectories. First, basic trajectory features were extracted, and then more features were obtained using geographic information of public transit network (i.e., Fréchet distance). Subsequently, the features were normalized and screened by the decision tree model. Finally, the screened features were trained and predicted by the model, and a stable prediction result was attained with a five-fold cross-validation method. Results show that geographic information of public transit network could optimize the model’s prediction accuracy. The proposed GPS trajectory recognition method achieved an accuracy of about 90%, which is superior to other machine learning classification models.

Abstract:To overcome the weakness of using the traditional model for static traffic assignment in analyzing traffic assignment problems in congested road networks, equilibrium models for static congested traffic flow assignment in road networks are presented in this paper. First, based on the characteristics of the traffic flow in congested link, properties of the impedance function of congested road links were analyzed, which satisified that the traffic flow rates would decrease with increasing vehicles in congested links. Then, the route choice behavior in congested road networks was investigated. The equilibrium principles and mathematical models of user equilibrium and system optimum were proposed in the static form. Additionally, it was proved that the proposed user equilibrium model was equivalent to the user equilibrium principle and had a unique solution. Finally, the iterative weighted algorithm was given to solve the proposed user equilibrium model. The comparison between the proposed model and the tranditional traffic assignment was made on the basis of a simple example. Results show that the proposed user equilibrium and the system optimum models could reasonably describe the congested user equilibrium and system optimum principles, and the user equilibrium model could reasonably describe the real passing flow rate in the congested state. The proposed models could be applied to partial congested areas and used as one of the core parts of the semi-congested traffic assignment model.

Abstract:The regularity of curved railway line conditions on the dynamic response of linear induction motor (LIM) wheel/rail train was investigated to provide theoretical basis for revising design specifications of railway line. Train-line dynamic model of LIM wheel/rail transit system was established, in which the vertical electromagnetic force of an LIM could change with vehicle speed and motor air gap. Effects of vertical electromagnetic force, vehicle speed, curve radius, superelevation, and track irregularity on train dynamic response were simulated and analyzed. Results show that track irregularity and high speed had significant effects on air gap. When the train passed through curved section of small radius, vertical electromagnetic force could remarkably reduce the values of derailment coefficient and wheel load reduction rate. The maximum values of derailment coefficient, wheel load reduction rate, wheel-rail lateral force, vehicle lateral acceleration, and vehicle lateral displacement were significantly affected by vehicle speed, curve radius, and superelevation. The fitting formulas of 5 kinds of maximum dynamic response were proposed, with which the reasonable matching of vehicle speed, curve radius, and superelevation range could be carried out, and the reasonable vehicle limit in curved section could be determined.

Abstract:To comprehensively and accurately evaluate the severity degree of asphalt pavement shoving, as well as realize the automatic calculation of the corresponding three-dimensional indicators, the indoor three-dimensional laser detection equipment was used to obtain high-precision and high-density surface laser point cloud data of shoving models, and the Lowess algorithm was adopted for data preprocessing. The RANSAC algorithm was then utilized to extract the contour data of the bottom of the shoving0, and the three-dimensional model of the shoving was established based on the HARR matrix. On this basis, the height-difference method and the micro-element approximation algorithm were used to calculate the three-dimensional indicators such as the maximum height, bottom area, uplift volume, and the maximum slope of the driving direction of the shoving. The calculation results of the three-dimensional indicators of two severity levels of light and heavy were compared, and the influence of laser line longitudinal spacing on calculation error was studied. Results show that when the longitudinal spacing of the laser line was 0.5 mm, the calculated relative errors of the maximum height, bottom area, uplift volume, and the maximum slope of the driving direction were less than 3.28%, 2.17%, 3.76%, and 1.97%, respectively. As the spacing increased to 10 mm, the relative error of the three-dimensional indicators of the shoving gradually increased due to the partial missing of the shoving model. When the spacing was 5 mm, the maximum relative error of the three-dimensional indicators was 3.49%, 4.65%, 7.11%, and 7.27%, respectively. When the spacing was 10 mm, the relative errors of the uplift volume and the maximum slope of the driving direction both exceeded 10%. It is recommended that when using three-dimensional laser technology to measure shoving, the longitudinal spacing should be not more than 5 mm to ensure the accuracy of the calculation results of the three-dimensional indicators. The three-dimensional indicators calculation method can evaluate the severity of the shoving and assess traffic safety risk.

Abstract:To enhance the reliability of the simulation model of reference speed for metro train, an improved simulation model of reference speed is proposed by analyzing factors affecting train speed. The general simulation model of train reference speed usually takes the command acceleration of train as the response acceleration of train traction/braking system, while the improved simulation model takes into consideration the jerk limitation of metro train traction/braking system for the command acceleration and the dynamic process of response acceleration. The improved model was adopted to simulate the reference speed of Harbin Metro Line train, and the calculation results of the general model and the improved model were compared with the actual speed data. Results show that the reference speed data obtained by the improved model were more consistent with the actual speed data than those by the general model. Train reference speed is the basic parameter of speed tracking control of automatic train operation system. Its calculation accuracy can be improved by considering jerk limitation of command acceleration and the dynamic response process.

Abstract:In order to provide reference for bicycle lane design, conflict between roadside bicycle and automobile was observed on urban road. The influences of the number of roadside bicycle per lane on conflict were analyzed. The models between them were established respectively for arterial road, sub arterial road, and branch road by regression method. One accident per week and month were selected as threshold values and conflict between automobile and bicycle was divided to slight conflict, general conflict, and serious conflict according to the relation between the number of conflict and accident. Based on established models, calculation method of bicycle lane width was given according to conflict grade division, and case study was conducted. It shows that the number of conflict between automobile and bicycle increased with the raise of the number of roadside bicycle and there were quadratic function relations between them for arterial road and branch road and power function relation between them for sub-arterial road. When conflict grade reached serious degree, it was necessary to widen bicycle lane and increase the number of bicycle lane so as to decrease the number of bicycle per lane and conflict between automobile and bicycle and improve safety level of bicycle.

Abstract:In order to explore the influence of external conditions on the glass transition temperature of asphalt mixture, such as environment and traffic, three factors including heating rate, load frequency, and strain level were considered in this research. Temperature sweep test was developed by DMA method at different test levels. The glass transition temperature of asphalt mixture was obtained by Boltzmann model. The main affecting factors of glass transition temperature were determined by statistical analysis of the experimental results, and then the prediction model of the glass transition temperature under multiple factors was established. Results show that the Boltzmann model could accurately and effectively determine the glass transition temperature of asphalt mixture. The heating rate and load frequency had a significant effect on the glass transition temperature, which increased as the hating rate and load frequency increased. In addition, there was a good linear relationship between the glass transition temperature and the logarithm of heating rate and the load frequency. The glass transition temperature of asphalt mixture had no obvious strain dependence in liner viscoelastic region under bending mechanics condition.

Abstract:The accurate and timely monitoring of asphalt mixture paving process is critical for reducing segregation and effective construction. In this study, 1085 construction site images were pre-processed by digital image processing techniques (i.e., grayscale, filtration, and binarization) to explore and build up a real-time evaluation method for paving asphalt mixture during construction process. The sum and standard deviation of the static moment of each particle larger than 9.5 mm was calculated and the min-max normalized standard deviation were utilized to evaluate the paving asphalt mixture distribution uniformity. Results show that the mix proportion value from the proposed image technique was close to the value from the reality. By comparing the value of min-max normalized static moment standard deviation with the corresponding image, a uniformity indicator was proposed for the evaluation of asphalt pavement uniformity during paving process. The paper provides a new method for paving asphalt mixture segregation detection.

Abstract:A multi-scale vehicle localization method was proposed to improve the localization accuracy of intelligent vehicles by constructing high definition maps from pavement landmarks. A high definition visual map was constructed based on pavement landmarks, where each landmark contains visual features, geometric structure information, and the positional coordinates in a reference coordinate system. Based on the constructed map, a coarse location of the vehicle was estimated through GPS matching, which was then improved by matching the visual features in the map to achieve landmark-level localization. Finally, the accurate and absolute position was achieved from the landmark geometry and its reference position, which thus could realize the multi-scale localization of the vehicle by high definition maps from pavement landmarks. A 3.4 km-long route of a university campus (including right-turn arrow, straight-way arrow, manhole, and so on) was taken as an example to construct a high definition visual map and then realize vehicle localization. Results showed that the mean and the max localization errors were 12.5 cm and 23.3 cm, respectively. The proposed mapping strategy based multi-scale localization method provides a new solution for intelligent vehicle localization.

Abstract:To fully describe the roughness of coarse aggregate, the height difference correlation function was introduced to characterize the surface texture of coarse aggregate with multi-parameters. First, the needle profiler was applied to obtain the texture profile curve of the aggregate surface and eliminate the error in data acquisition. Then, the height difference correlation function of the coarse aggregate was calculated, and the curve was fitted with piecewise fitting. The self-similar feature parameters (D, ξ_∥, ξSymbol^A@) of the surface texture curve were calculated as evaluation indexes to analyze the roughness of the surface texture of the coarse aggregate. Results show that the surface texture of the coarse aggregate had two sections of variable dimension within a certain range, and the scale boundary between the micro texture and the macro texture was 100-200 μm. The fractal dimension D₁ of the macro texture of different aggregates was about 1.3, and the fractal dimension D₂ of the micro texture was about 1.05, which revealed that the fractal dimension was insensitive to roughness. The horizontal cutoff wavelength ξ_∥ and the amplitude expectation value ξSymbol^A@ reflected the expected values of the horizontal wavelength and the vertical amplitude of the micro-convex surface of the coarse aggregate, respectively. The horizontal cutoff wavelength ξ_∥ reflected the size of the largest microbump. The dolomite and the diorite were smaller, while the granite with larger crystal structure had a maximum value. The amplitude expectation value ξSymbol^A@ was diorite, yellow sandstone, granite 1, diabase, granite 2, and dolomite in descending order, which was in line with the actual situation. The amplitude expectation value could quantitatively describe the overall roughness of the aggregate. The self-similar feature parameters could fully describe the roughness of the surface texture of the coarse aggregate.

Abstract:The identification and prediction of real-time traffic conditions rely on data processing. Abnormal data recognition in traffic big data uses machine learning methods with multi-source traffic to ensure the accuracy of traffic detection data. The recognition of anomaly detection data is based on AdaBoost method in machine learning. To eliminate the outlier phenomenon of the single detection source data, the training dataset of the training process selected datasets provided by multiple detection sources on the same road section. The cost-sensitive method optimizes the decision-making process of the improved algorithm. Experimental results show that the improved AdaBoost model forced the classifier to pay more attention to abnormal class samples, which enhanced the representation of training decision tree rules in the AdaBoost and improved the classification accuracy of abnormal samples. The highway test dataset verified the detection accuracy, false detection rate, false alarm rate, and other indicators of the improved algorithm and related classical algorithms. The accuracy rate of the improved algorithm was increased by 5.547%, and the false detection rate was reduced by 6.792%. The comparison of ROC curves shows that the improved AdaBoost method is more reliable in identifying abnormal samples of traffic detection and can effectively adjust the classification error caused by non-equilibrium data.

Abstract:To investigate the ignition delay characteristics of dimethyl ether (DME)/ethane (C₂H₆) mixtures at low temperatures, the ignition delays were measured at compressed temperatures of 627~912 K, compressed pressures of 16~30 bar,equivalence ratios of 0.5~1 and C₂H₆ blending ratios of 0~70 % based on a rapid compression machine (RCM). Meanwhile, the simulation was conducted at the same conditions as those in experiments using CHEMKIN-PRO software. Both experimental and simulation results show that the total ignition delay exhibits obvious negative temperature coefficient (NTC) behavior, especially at lower compressed pressures. Increasing compressed pressure and equivalence ratio lead to decrease the first-stage and total ignition delays, especially at NTC region. C₂H₆ addition inhibits the ignition process significantly, thus prolongs the first-stage and total ignition delays. Chemistry kinetics analysis indicates that C₂H₆ competes for OH radicals predominately produced by the DME’s low-temperature oxidation, thus the ignition process of DME is delayed while the ignition process of itself is promoted and even presents evident two-stage characteristic. With the increase of C₂H₆ blending ratio, the ignition process of whole mixtures is inhibited, the accumulation of heat release rate and active free radicals is decreased and the ignition delays are prolonged.

Abstract:To overcome the problem caused by the separation photocatalysts from system in the traditional photocatalytic technology, the photocatalytic membrane was prepared by filtrating suspended ZnIn₂S₄ on the surface of ultrafiltration membrane and was characterized by SEM, UV-Vis, XPS, XRD, and the ultrafiltration performance was also analyzed. The degradation rate of fluvastatin by photocatalytic membranes was investigated under a 500 W xenon lamp with intensity of 230 W/m². With the increase of the photocatalyst loading, the absorbance of photocatalytic membrane in ultraviolet and visible light region increased, the characteristic peak response of Zn, In and S elements increased, the diffraction peak of ZnIn₂S₄ with hexagonal phase increased and the hydrophilicity increased, which indicated that formation of photocatalytic coating layer on the surface. The degradation rate of fluvastatin was also enhanced by formation of photocatalytic coating layer. However, agglomeration of excess ZnIn₂S₄ on the surface of the membrane leaded to reducing the utilization rate of the photocatalyst and affeced the photocatalytic efficiency. The photocatalytic coating layer of photocatalytic membrane with 0.2 g ZnIn₂S₄ could be effectively excited by xenon lamp and the degradation rate of fluvastatin was 94.75%.

Abstract:Aiming at liquefaction of saturated fine sand in meizoseismal area and taking the Puqian Bridge project as the test site, this study simulated the vibration response of the free field under seismic action by the vibration table model test and the laminated shear model box. The variation law of pore pressure ratio of saturated fine sand at different depths under ground vibration intensity of 0.15g~0.80g (g represents gravity acceleration) was analyzed, and the liquefaction discrimination method of saturated fine sand was discussed. Results show that the growth of ultra-quiet pore water pressure and pore pressure ratio of saturated fine sand lagged behind ground motion stress, and the deeper the sand was, the longer the lag time. The saturated fine sand with a depth of 5 cm, 60 cm, and 110 cm was liquefied when the local vibration intensity was greater than or equal to 0.15g, 0.20g, and 0.25g respectively, and the pore pressure ratio stability value was greater than or equal to 0.8, which was proposed as a critical pore pressure ratio of saturated fine sand liquefaction. The liquefaction determination results of the existing common methods were discussed and a new method for discriminating the liquefaction of saturated fine sand by the criterion of saturated fine sand depth, ground motion intensity, and pore pressure ratio was proposed. It provides technical reference for similar projects and scientific basis for rational design and construction of bridge foundation before paving.

Abstract:This paper proposes a method based on Gaussian-Mixture-Model Hidden Markov Model (GMM-HMM) to recognize the activity-node type of trip chain for hazardous-materials (hazmat) transportation vehicle. The GPS data of vehicle were pre-processed to identify the activity nodes of the trip chains using a Decision-Tree based move-stop detection algorithm. Then the activity nodes were grouped into the activity hotspots by a dropout-based OPTICS (D-OPTICS) algorithm. A multi-scale feature system was constructed according to the individual features of the activity nodes, the relative features of the corresponding trip chains, and the group features of the related hotspots. These feature vectors were further transformed into low-dimensional vectors using Factor Analysis method. Finally, a GMM-HMM based activity type recognition model for hazmat transportation vehicles was built where Baum-Welch algorithm was used for parameter estimation, and Viterbi algorithm for decoding the hidden state to obtain the recognition results of the activity-node type of trip chains. Not only the accuracy of the proposed method was directly verified based on the small-scale real-activity dataset, but also the effectiveness of the proposed method on the activity type identification of large-scale GPS data was evaluated indirectly using the Point-of-Interest (POI) information. The results demonstrate that the identification rate of the GMM-HMM based activity type recognition method was more than 80% in the task of nine-type activity recognition. The recognition results can help analyzing the activity behavioral patterns, discovering the abnormal activities, and providing effective decision-making support for hazmat transportation supervision.