Interval Uncertainty Analysis for Wheel–Rail Contact Load Identification Based on First-Order Polynomial Chaos Expansion

Shengwen Yin (), Haotian Xiao and Lei Cao
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Shengwen Yin: School of Traffic & Transportation Engineering, Central South University, Changsha 410083, China
Haotian Xiao: School of Traffic & Transportation Engineering, Central South University, Changsha 410083, China
Lei Cao: School of Traffic & Transportation Engineering, Central South University, Changsha 410083, China

Mathematics, 2025, vol. 13, issue 4, 1-16

Abstract: Traditional methods for identifying wheel–rail contact loads are based on deterministic models, in which the uncertainties such as material inhomogeneity and geometric tolerance are not considered. For wheel–rail contact load analysis with uncertainties, a novel method named the Interval First-Order Polynomial Chaos Expansion method (IFOPCE) is proposed to propagate the uncertainty in wheel–rail contact systems. In IFOPCE, the polynomial chaos expansion (PCE) is first utilized to approximate the relationship between strain responses, wheel–rail loads, and uncertain variables. The expansion coefficients are calculated using Latin Hypercube Sampling (LHS). To efficiently decouple the wheel–rail loads, the relationship between load and strain is established based on the first-order PCE. By using IFOPCE, the variation range of wheel–rail contact loads can be effectively obtained. It is shown in numerical examples that the IFOPCE achieves high computational accuracy and the uncertainties have a great effect on the identification of wheel–rail loads.

Keywords: wheel–rail load; interval parameters; polynomial chaos expansion; Latin hypercube sampling; interval model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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