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A stochastic dynamic model of train-track-bridge coupled system based on probability density evolution method
- Source :
- Applied Mathematical Modelling. 59:205-232
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- An innovative stochastic dynamic model of a 3D train-track-bridge coupled system (TTBS) with refined wheel/rail interaction is established for a high-speed railway based on the random theory of probability density evolution method (PDEM). The multi-coupling effect of excitations can be simultaneously input into the new model, e.g. random track irregularity, random vehicle loads, stochastic system parameters, et al. Moreover, a new approach, named “Number theoretic method of multi-target probability functions” (NTM-mp), is developed to obtain the discrete point sets of multidimensional random parameters in hypercube space, aims to solve the point design of system uncertainty. The stochastic harmonic function (SHF) is applied to generate representative random track irregularity samples. The results of TTBS got by PDEM are verified with several typical case studies for its efficiency and reliability, which are the deterministic results in the representative publication, the Monte Carlo method (MCM) results, and the field testing results on the high-speed railway. At last, a typical case study of TTBS on a high-speed railway is presented for numerical analysis. Discussions and significant conclusions on the random dynamic responses are presented.
- Subjects :
- Computer science
Applied Mathematics
Reliability (computer networking)
Numerical analysis
Monte Carlo method
020101 civil engineering
Probability density function
02 engineering and technology
Track (rail transport)
0201 civil engineering
020303 mechanical engineering & transports
0203 mechanical engineering
Harmonic function
Modeling and Simulation
Applied mathematics
Point (geometry)
Hypercube
Subjects
Details
- ISSN :
- 0307904X
- Volume :
- 59
- Database :
- OpenAIRE
- Journal :
- Applied Mathematical Modelling
- Accession number :
- edsair.doi...........eadb756341be7cee8c545dcda6145901