Study on Bearing Capacity of Autoclaved Aerated Concrete Partition Board Based on Deep Learning

Abstract

For further research of steam pressure aerated concrete board carrying capacity, puts forward construction on the basis of deep learning autoclaved aerated concrete board pressure performance research methods. Through the autoclaved aerated concrete the bearing capacity of single correlation coefficient, the relationship between the nodal force and node displacement and the relationship between them, the calculation of the autoclaved aerated concrete stiffness, obtain the autoclaved aerated concrete board yield condition. The linear buckling and nonlinear buckling of the AUTOclaved aerated concrete sandwich panel are analyzed, and the bearing capacity of the autoclaved aerated concrete sandwich panel is calculated to realize the bearing capacity analysis. The test results show that this method can effectively improve the bearing stability of autoclaved aerated concrete sandwich.