Ultimate Bending Strength Evaluation of MVFT Composite Girder by using Finite Element Method and Machine Learning Regressors

نویسندگان

چکیده

This paper has evaluated the bending performance of a novel prefabricated MVFT steel-concrete composite girder. 9 meters pilot girder was analyzed by validated finite element model. In test, height web, length grouted concrete in and net spacing between webs were parametrically modeled to discuss their effect strength. An ultimate strength formula been obtained, which based on regression parametric results. meantime, two Machine Learning (ML) models, BP neural network Least Squares Support Vector Machine, have also implemented train then predict Three factors selected as input ML models: distance steel girder’s Tensile Centroid(TC) slab’s Compressive Centroid(CC), TC its CC, compressive area After completion training, predictions 30 model compared, agrees well with each other validates accuracy.

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ژورنال

عنوان ژورنال: Latin American Journal of Solids and Structures

سال: 2022

ISSN: ['1679-7825', '1679-7817']

DOI: https://doi.org/10.1590/1679-78257006