Study on Calculation Model of Normal Section Force Component of Recycled Concrete Based on BP Neural Network

Abstract

In view of the serious waste and pollution of ordinary concrete to the resources and the environment, it is necessary to use recycled concrete technology to solve the contradiction between the use of resources and environmental pollution, and there are still obvious deficiencies and shortcomings in the traditional recycled concrete technology research program. Therefore, the BP neural network algorithm of genetic optimization algorithm is creatively used to study the performance of four dimensions of the normal section of recycled concrete flexural members in this paper, including cracking moment, ultimate bearing capacity, crack width and cross center interference, and the allocation step structure of BP neural network and network weights is designed. Finally, the simulation test is carried out to verify the correctness of the test results, which provides a reference for the design of recycled concrete structure.