{"title":"Track irregularity and mechanical characteristics analysis of CRTS I ballastless track under subgrade frost heaving","authors":"Ruiqi Cheng, B. Yan, Haoran Xie","doi":"10.2749/SEOUL.2020.123","DOIUrl":"https://doi.org/10.2749/SEOUL.2020.123","url":null,"abstract":"Harbin-Dalian high-speed railway is located in the northeast of China, part of which belongs to seasonal frozen area. In seasonal frozen area, the seasonal frost heaving and thaw settlement of subgrade will lead to local uneven subgrade frost heaving deformation, which will cause overarching deformation of track structure, even cause structural damage and track irregularity, and affect train safety directly. On the basis of full site investigation, taking CRTS I ballastless track in frost heaving area of Harbin-Dalian high-speed railway as research object, the spatial finite element model considering the interlayer contact characteristics was established using ANSYS finite element software. The transfer properties of track irregularity, interlayer separation characteristics and mechanical characteristics under frost heaving condition were analyzed. It provides an important reference for the design of ballastless track in cold and seasonal frozen area.","PeriodicalId":226026,"journal":{"name":"IABSE Conference, Seoul 2020: Risk Intelligence of Infrastructures","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128249898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A combined model-free Artificial Neural Network-based method with clustering for novelty detection: The case study of the KW51 railway bridge","authors":"A. Neves, K. Maes, I. González, R. Karoumi","doi":"10.2749/SEOUL.2020.181","DOIUrl":"https://doi.org/10.2749/SEOUL.2020.181","url":null,"abstract":"Clustering is one of the most commonly employed exploratory data analysis technique to get some valuable insight about the structure of data. It is considered to be an unsupervised learning method as there is no ground truth to compare the output of the algorithm with the true labels of the data. However, the intention in this work is not to evaluate the performance of the algorithm but to try to investigate the structure of the data and underlying patterns.This paper proposes an approach for condition assessment of bridges based on Artificial Neural Networks (ANNs) combined with data clustering. The approach is developed and validated through a monitoring campaign. The one span ballasted railway bridge was subjected to retrofitting and in the course of the several states - before, during and after retrofitting - data on relevant properties of the bridge has been collected. The data collected in the before retrofitting state was used to train ANNs. Over time, new measurements are collected from the bridge under the new states and presented to the trained ANNs. The predictions by the ANNs can be compared to real measurements and prediction errors can be obtained. Based on statistical data analysis of the prediction errors by means of clustering techniques, the ANN is able to identify the different states of the structure.","PeriodicalId":226026,"journal":{"name":"IABSE Conference, Seoul 2020: Risk Intelligence of Infrastructures","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128387150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Short-Term Forecasting of the Occurrence Time of Strong Wind Speed during a Typhoon based on LSTM for Sea-Crossing Bridge Operation","authors":"Jaehun Lim, Sejin Kim, Ho-Kyung Kim","doi":"10.2749/SEOUL.2020.230","DOIUrl":"https://doi.org/10.2749/SEOUL.2020.230","url":null,"abstract":"Vehicles running on sea-crossing bridges are vulnerable to strong winds with instantaneous speeds of over 20 m/s. Bridge operators should secure the safety of the bridge users by limiting vehicle speeds or restricting the traffic when wind speed measured on the bridges exceeds a certain threshold value. To guarantee the safety of the bridge users during typhoons, an accurate forecasting of the strong winds would be essential. In this study, an Artificial Neural Network (ANN) was considered to model the occurrence characteristics of the strong wind speed at the sea- crossing bridge during typhoons. The Long Short-Term Memory (LSTM), which is generally used in the time-series analysis, was applied. This research utilized 16 years of wind speed data acquired by sensors located on a suspension bridge in South Korea and Best Track data of typhoons from the Regional Specialized Meteorological Center (RSMC) in Tokyo.","PeriodicalId":226026,"journal":{"name":"IABSE Conference, Seoul 2020: Risk Intelligence of Infrastructures","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129353305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Young-Min Kim, Byoung-Gil Shin, Tae-Kang Yun, Seok-Jung Chang
{"title":"System Development for Performance Evaluation Suitable for Small and Medium Sized Aging Bridges","authors":"Young-Min Kim, Byoung-Gil Shin, Tae-Kang Yun, Seok-Jung Chang","doi":"10.2749/SEOUL.2020.167","DOIUrl":"https://doi.org/10.2749/SEOUL.2020.167","url":null,"abstract":"Although small and medium-sized bridges are closely related to people’s lives, safety and maintenance are often neglected compared to the large bridges. Moreover, the frequent occurrence of safety accidents due to aging, they are often placed in a blind spot for safety management. This study aims to develop a performance evaluation system suitable for small and medium-sized bridges based on the results of simulations on various performance evaluation methods using facility information.","PeriodicalId":226026,"journal":{"name":"IABSE Conference, Seoul 2020: Risk Intelligence of Infrastructures","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115525485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}