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Identification of High-Speed Moving Loads using Weakened Modal Shape Functions Conceptualised by Dynamic Influence Line

Tabar, A. M., Tsavdaridis, K. ORCID: 0000-0001-8349-3979 & Bravo-Haro, M. A. ORCID: 0000-0003-0757-777X (2025). Identification of High-Speed Moving Loads using Weakened Modal Shape Functions Conceptualised by Dynamic Influence Line. Structures, 74, article number 108549. doi: 10.1016/j.istruc.2025.108549

Abstract

Identification of moving loads is an inverse problem which is important for the lifespan evaluation of bridges. One of the challenging features is to overcome the ill-conditions commonly involved in the inverse problems. In this paper, the ill-conditions are significantly degraded using weakened modal shape functions conceptualised by the dynamic influence line. Employing the main concept of Muller-Breslau’s principle, a surrogate beam is developed by eliminating the required reaction. It is replaced by a dynamic load proportional to the modal shape functions of the surrogate beam; not those of the original beam. In this condition, the main source of singularities is eliminated. Consequently, the results obtained by the proposed method provide smooth curves that fit well to the exact solutions without any extra fluctuations which harden the load identification. The results obtained from the case studies show that the loads identified by the proposed method agree well with the exact solutions, although only the first shape function of the surrogate beam was involved.

Publication Type: Article
Additional Information: © 2025 The Author(s). Published by Elsevier Ltd on behalf of Institution of Structural Engineers. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Publisher Keywords: Moving load identification, High speed loads, Weakened shape functions, Dynamic influence line, DIL
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TH Building construction
Departments: School of Science & Technology
School of Science & Technology > Engineering
SWORD Depositor:
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