Optimal Shape Investigation of Masonry Arch Bridges under Dynamic Loads Using Support Vector Machine
Subject Areas : Machine learning
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Keywords: Masonry Arches, Dynamic Loads, Support Vector Machine (SVM), Structural Risk Minimization (SRM), Shape Optimization,
Abstract :
The objective of this study is to determine the optimal shape of masonry arches under dynamic loads using the Support Vector Machine (SVM) technique. This approach utilizes the principles of Structural Risk Minimization (SRM), which demonstrate superior performance compared to methods based on Empirical Risk Minimization (ERM). The research particularly focuses on the types of arches commonly used in traditional structures and their significance in ensuring structural stability and performance. The modeling, dynamic analysis, and shape optimization of a semi-circular arch are comprehensively explained using ANSYS 11 software and the SVM method. The necessity of this study lies in the critical role that the optimal shape of arches plays in enhancing the resilience and reducing the vulnerability of masonry structures against dynamic loads, especially given their widespread application in both historical and modern constructions. The main innovation of this research is the application of the Support Vector Machine as an advanced and less commonly employed method for arch shape optimization. For the first time, SRM principles are integrated with dynamic modeling and computational analysis, offering a novel framework for optimizing traditional structures.
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