Reliability assessment of railway bridges subjected to high-speed trains considering the effects of seasonal temperature changes. (1st November 2016)

• Record Type: Journal Article
• Authors: Salcher, P.; Pradlwarter, H.; Adam, C.
• Is Part Of: Engineering structures. Volume 126(2016:Nov. 01)
• Page Start: 712
• Page End: 724
• Publication Date: 2016-11-01
• Subjects: Acceleration response -- Environmental influence -- High-speed train -- Monte Carlo simulation -- Ballasted steel bridge -- Track irregularities -- Uncertainties; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2016.08.017
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: Identification of the uncertainties of this bridge-train interaction system. Proposal of a stochastic model capturing the environmental impact on the bridge structure. Freezing temperatures show a positive effect on vibration amplitudes of the bridge. Irregular rails significantly influence deck accelerations amplitudes and scatter. Comparison of a stochastic and a code-based design for a case study bridge structure. Abstract: This paper addresses the reliability analysis of high-speed railway bridges with stochastic methods to account for uncertainties in the mechanical model. The emphasis is on ballasted steel bridges. The acceleration response of the bridge deck is assumed to be the governing response quantity for bridge serviceability, and thus, defines in the reliability assessment the limit state of the bridge. The uncertainties for this specific interaction problem are identified and modeled as random variables with appropriate distributions. The effect of uncertain track quality is considered via random rail profiles. A stochastic model is proposed to account for the environmental impact of seasonal temperature changes on the bridge structure. In a parametric study, the contribution of the random variables on the uncertain bridge response of a case study problem is quantified. The probability of exceeding the serviceability limit state is predicted using crude Monte Carlo simulations and Latin Hypercube samples. These predictions are set in contrast to outcomes of a traditional code-based deterministic design procedure.