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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Chen Wang,Fayun Liang,Jingru Li.Probabilistic Quantile Regression-Based Scour Estimation Considering Foundation Widths and Flood Conditions[J].Journal of Harbin Institute Of Technology(New Series),2021,28(1):30-41.DOI:10.11916/j.issn.1005-9113.2019040.
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Probabilistic Quantile Regression-Based Scour Estimation Considering Foundation Widths and Flood Conditions
Author NameAffiliation
Chen Wang Department of Geotechnical Engineering, Tongji University, Shanghai 200092, China 
Fayun Liang Department of Geotechnical Engineering, Tongji University, Shanghai 200092, China 
Jingru Li Department of Mathematics, Tongji University, Shanghai 200092, China 
Abstract:
Scour has been widely accepted as a key reason for bridge failures. Bridges are susceptible and sensitive to the scour phenomenon, which describes the loss of riverbed sediments around the bridge supports because of flow. The carrying capacity of a deep-water foundation is influenced by the formation of a scour hole, which means that a severe scour can lead to a bridge failure without warning. Most of the current scour predictions are based on deterministic models, while other loads at bridges are usually provided as probabilistic values. To integrate scour factors with other loads in bridge design and research, a quantile regression model was utilized to estimate scour depth. Field data and experimental data from previous studies were collected to build the model. Moreover, scour estimations using the HEC-18 equation and the proposed method were compared. By using the “CCC (Calculate, Confirm, and Check)” procedure, the probabilistic concept could be used to calculate various scour depths with the targeted likelihood according to a specified chance of bridge failure. The study shows that with a sufficiently large and continuously updated database, the proposed model could present reasonable results and provide guidance for scour mitigation.
Key words:  bridge scour  scour estimation  quantile regression  probabilistic model  deterministic models
DOI:10.11916/j.issn.1005-9113.2019040
Clc Number:U442.59
Fund:
Descriptions in Chinese:
  

考虑基础宽度和洪水条件的桥梁冲刷分位数回归估计方法

王琛1,梁发云1,李静茹2

(1. 同济大学 地下建筑与工程系,上海 200092;2. 同济大学 数学系,上海 200092)

摘要:

冲刷是引起桥梁水毁破坏的最主要因素之一,是指桥梁基础周围的河床泥沙在水流作用下流失的现象,已建成的桥梁在其服役期间易受其影响。冲刷坑的形成降低了基础的承载能力,过大的冲刷会在没有预警的情况下引起桥梁破坏。目前,大多数冲刷预测方法都是基于确定性模型,但桥梁设计中的其他荷载通常是作为概率值提供的。为了在桥梁设计和研究中更好地综合考虑冲刷因素和其他荷载,本文通过收集前人研究的现场数据和实验数据,对其各影响参数进行深入分析,基于分位数回归方法的理念,提出一种预测冲刷深度的概率方法,并将其与HEC-18公式进行比较分析。通过“CCC(即计算、确认和检查)”计算步骤,基于分位数方法的概率理念,该计算模型可以根据给定的桥梁设计要求,计算出不同概率条件下相应的冲刷深度。结果表明,在具有足够大且可以不断更新的数据库时,该模型能够给出不同设计条件下的合理预测结果,可为冲刷减缓提供建议。

关键词:桥梁冲刷,冲刷预测,分位数回归,概率性模型,确定性模型

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