Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Safety assessment using computer experiments and surrogate modeling: Railway vehicle safety and track quality indices

Safety assessment using computer experiments and surrogate modeling: Railway vehicle safety and track quality indices

Thumbnail Image
Download
Name

1-s2.0-S0951832022004732-main.pdf

Description
Published version
Size

1.44 MB

Format

Adobe PDF

Checksum (MD5)

95a20ffd8d389fb3c18557a7380b66a8

sword-2024-06-20T21:33:08.original.xml (130 B)
Original SWORD entry document
Author(s)
Neves Costa, João
•
Ambrósio, Jorge
•
Andrade, António R.
•
Frey, Daniel
Date Issued
January 2023
Journal
Reliability Engineering & System Safety
Publisher
Elsevier BV
Citation
Neves Costa, João, Ambrósio, Jorge, Andrade, António R. and Frey, Daniel. 2023. "Safety assessment using computer experiments and surrogate modeling: Railway vehicle safety and track quality indices." Reliability Engineering & System Safety, 229.
Version
Final published version
Abstract
Mathematical modeling and advances in computation allow exploring multiple scenarios and studying the reliability and safety of transportation systems. Although track geometry directly impacts vehicle safety, the track quality indices used by infrastructure managers to assess tracks seldom consider vehicle dynamics. This work provides a design and analysis of computer experiments framework to model the relationships between track quality and vehicle safety. The framework considers input selection and pre-processing, vehicle responses and post-processing, input screening, surrogate modeling, sensitivity analysis, and safety assessment. This approach allows studying how track geometry parameters and other variables influence safety quantities. The framework is demonstrated with a case study that combines two European standards: the standard for track geometry quality, EN 13848, and the standard for vehicle acceptance, EN 14363. The case study considers different vehicle types, vehicle speed, track curvature, track flexibility, and track irregularities. The results show, for each safety quantity, which inputs are relevant. In particular, the sensitivity analysis indicates two influential inputs not considered in EN 13848 that could help assess track condition. Finally, an example illustrates how these surrogates can be used to find which safety quantities govern safety and define track geometry limits directly linked to vehicle safety.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution
https://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/155291
DOI of Published Version
https://doi.org/10.1016/j.ress.2022.108856
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.