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Predicting the capacity of perfobond rib shear connector using an ANN model and GSA method

Frontiers of Structural and Civil Engineering 2022年第10期16卷 1233-1248页

作者： Guorui SUN Jun SHI Yuang DENG School of Civil Engineering Central South UniversityChangsha 410075China Key Laboratory of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of TechnologyHarbin 150090China National Engineering Laboratory for High-Speed Railway Construction Changsha 410075China

Due to recent advances in the field of artificial neural networks(ANN)and the global sensitivity analysis(GSA)method,the application of these techniques in structural analysis has become feasible.A connector is an important part of a composite beam,and its shear strength can have a significant impact on structural *** this paper,the shear performance of perfobond rib shear connectors(PRSCs)is predicted based on the back propagation(BP)ANN model,the Genetic Algorithm(GA)method and GSA method.A database was created using push-out test test and related references,where the input variables were based on different empirical formulas and the output variables were the corresponding shear *** results predicted by the ANN models and empirical equations were compared,and the factors affecting shear strength were examined by the GSA *** results show that the use of ANN model optimization by GA method has fewer errors compared to the empirical ***,penetrating reinforcement has the greatest sensitivity to shear performance,while the bonding force between steel plate and concrete has the least sensitivity to shear strength.

关键词： perfobond rib shear connector shear strength ANN model global sensitivity analysis

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