Simplified vehicle–bridge interaction for medium to long-span bridges subject to random traffic load
Autor: | Shamim N. Pakzad, Soheil Sadeghi Eshkevari, Thomas J. Matarazzo |
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Rok vydání: | 2020 |
Předmět: |
Signal Processing (eess.SP)
Long span Computer science 010401 analytical chemistry 020101 civil engineering 02 engineering and technology White noise Surface finish Time step 01 natural sciences 0201 civil engineering 0104 chemical sciences Superposition principle Control theory 11. Sustainability Compatibility (mechanics) FOS: Electrical engineering electronic engineering information engineering Traffic load Electrical Engineering and Systems Science - Signal Processing Traffic network Safety Risk Reliability and Quality Civil and Structural Engineering |
Zdroj: | Journal of Civil Structural Health Monitoring. 10:693-707 |
ISSN: | 2190-5479 2190-5452 |
DOI: | 10.1007/s13349-020-00413-4 |
Popis: | This study introduces a simplified model for bridge-vehicle interaction for medium- to long-span bridges subject to random traffic loads. Previous studies have focused on calculating the exact response of the vehicle or the bridge based on an interaction force derived from the compatibility between two systems. This process requires multiple iterations per time step per vehicle until the compatibility is reached. When a network of vehicles is considered, the compatibility equation turns to a system of coupled equations which dramatically increases the complexity of the convergence process. In this study, we simplify the problem into two sub-problems that are decoupled: (a) a bridge subject to random Gaussian excitation, and (b) individual sensing agents that are subject to a linear superposition of the bridge response and the road profile roughness. The study provides sufficient evidence to confirm the simulation approach is valid with a minimal error when the bridge span is medium to long, and the spatio-temporal load pattern can be modeled as random Gaussian. Quantitatively, the proposed approach is over 1,000 times more computationally efficient when compared to the conventional approach for a 500 m long bridge, with response prediction errors below $0.1\%$. submitted to the Journal of Civil Structural Health Monitoring |
Databáze: | OpenAIRE |
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