Details
| Original language | English |
|---|---|
| Number of pages | 20 |
| Journal | International Journal of Rail Transportation |
| Early online date | 20 Jan 2024 |
| Publication status | E-pub ahead of print - 20 Jan 2024 |
Abstract
Railway turnout (RT) is a crucial component of railway infrastructure that consists of several components. Assessing the derailment probability of freight wagons passing through the turnout is crucial for quantifying failure risks and optimizing the performance of the freight wagon-turnout system (FWTS). However, existing assessment methods often require extensive model evaluations and impose substantial computational costs. To address this issue, an efficient reliability analysis method is established for assessing the derailment risk at RTs. Firstly, a dynamic model is developed to capture the wheel-rail dynamic interaction and the numerical model is validated by field tests. Secondly, to reduce the computational cost in the reliability analysis, an efficient adaptive Kriging method based on an error stopping criteria and a learning function is adopted to estimate the failure probabilities under multiple failure modes of wheel derailments. Based on the efficient learning function and convergence criterion, accurate failure probability results can be obtained with a small number of multibody and finite element coupled dynamic simulations. Furthermore, the prediction accuracy of the proposed method in capturing random characteristics for FWTS is evaluated. Finally, the influence of the evolution of rail wear on the failure probability is further discussed.
Keywords
- Adaptive kriging model, derailment risk, multibody dynamics, Railway turnouts, reliability analysis
ASJC Scopus subject areas
- Engineering(all)
- Automotive Engineering
- Social Sciences(all)
- Transportation
- Engineering(all)
- Mechanics of Materials
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: International Journal of Rail Transportation, 20.01.2024.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Reliability assessment of freight wagon passing through railway turnouts using adaptive Kriging surrogate model
AU - Lai, Jun
AU - Wang, Kai
AU - Shi, Yan
AU - Xu, Jingmang
AU - Chen, Jiayin
AU - Wang, Ping
AU - Beer, Michael
N1 - Funding Information: The work was supported by National Natural Science Foundation of China (Grant No. 52122810 and 52108418), and Natural Science Foundation of Sichuan Province, China (Grant No. 2023NSFSC0398).
PY - 2024/1/20
Y1 - 2024/1/20
N2 - Railway turnout (RT) is a crucial component of railway infrastructure that consists of several components. Assessing the derailment probability of freight wagons passing through the turnout is crucial for quantifying failure risks and optimizing the performance of the freight wagon-turnout system (FWTS). However, existing assessment methods often require extensive model evaluations and impose substantial computational costs. To address this issue, an efficient reliability analysis method is established for assessing the derailment risk at RTs. Firstly, a dynamic model is developed to capture the wheel-rail dynamic interaction and the numerical model is validated by field tests. Secondly, to reduce the computational cost in the reliability analysis, an efficient adaptive Kriging method based on an error stopping criteria and a learning function is adopted to estimate the failure probabilities under multiple failure modes of wheel derailments. Based on the efficient learning function and convergence criterion, accurate failure probability results can be obtained with a small number of multibody and finite element coupled dynamic simulations. Furthermore, the prediction accuracy of the proposed method in capturing random characteristics for FWTS is evaluated. Finally, the influence of the evolution of rail wear on the failure probability is further discussed.
AB - Railway turnout (RT) is a crucial component of railway infrastructure that consists of several components. Assessing the derailment probability of freight wagons passing through the turnout is crucial for quantifying failure risks and optimizing the performance of the freight wagon-turnout system (FWTS). However, existing assessment methods often require extensive model evaluations and impose substantial computational costs. To address this issue, an efficient reliability analysis method is established for assessing the derailment risk at RTs. Firstly, a dynamic model is developed to capture the wheel-rail dynamic interaction and the numerical model is validated by field tests. Secondly, to reduce the computational cost in the reliability analysis, an efficient adaptive Kriging method based on an error stopping criteria and a learning function is adopted to estimate the failure probabilities under multiple failure modes of wheel derailments. Based on the efficient learning function and convergence criterion, accurate failure probability results can be obtained with a small number of multibody and finite element coupled dynamic simulations. Furthermore, the prediction accuracy of the proposed method in capturing random characteristics for FWTS is evaluated. Finally, the influence of the evolution of rail wear on the failure probability is further discussed.
KW - Adaptive kriging model
KW - derailment risk
KW - multibody dynamics
KW - Railway turnouts
KW - reliability analysis
UR - http://www.scopus.com/inward/record.url?scp=85182811963&partnerID=8YFLogxK
U2 - 10.1080/23248378.2024.2304000
DO - 10.1080/23248378.2024.2304000
M3 - Article
AN - SCOPUS:85182811963
JO - International Journal of Rail Transportation
JF - International Journal of Rail Transportation
SN - 2324-8378
ER -