Prediction Of Strength For Basalt Fiber And Rubber Lightweight Aggregate Concrete With BP Neural Network Optimized By Genetic Algorithm And Microscopic Experimental Study

Concrete is widely used in different fields due to its high compressive strength and good durability.At present,China vigorously advocates the concept of energy conservation,emission reduction and green development.Higher requirements are put forward for concrete industry.In recent years,with the continuous increase of total mileage of roads and railways,Buildings are getting more taller,the development of green,lightweight and high-strength concrete has gradually become a research topic.Because the Inner Mongolia autonomous region is rich in pumice stone resources.The paper will be based on this,by adding basalt fiber and waste tires made of rubber particles are made of concrete to carry out experimental research.This paper is divided into macro level and micro level,in macro level through mechanical test to explain the basalt fiber rubber lightweight aggregate concrete mechanical rules,and at the same time using genetic optimization BP neural network for strength prediction.The pore structure and SEM scanning electron microscopy are used to characterize the macroscopic phenomena.The results are as follows:1.The influence of basalt fiber and rubber particles on the mechanical properties of concrete are as follows:the compressive and tensile strength of concrete increases with the increase of fiber content;The more the rubber content,the lower the compressive and tensile strength of concrete.With a certain amount of mbber,the compressive and tensile strength of concrete soil increase with the increase of fiber content.In the case of a certain fiber content,the compressive and tensile strength of concrete decreases with the increase of rubber content.When fiber content is 0.2%,the concrete strength is the highest.2.By comparing the result of BP neural network operation with the result after genetic optimization of BP neural network operation,it is concluded that the latter has higher prediction accuracy for concrete compressive strength model,with the minimum error between the actual value and the smaller variation range between sampics.The result is better for the actLal project.3.With the increase of fiber content the gas content and the pore diameter 200-300?m are the most important factors affecting the strength of concrete.With the increase of rubber content,the void spacing coefficient and 100-200 ?m diameter are the main factors affecting the compressive strength of concrete.When the aibber content is 10%,fiber content is 0.05%?0.1%?0.15%and 0.2%,the specific surface area and less than 100 ?m aperture are the most important factors affec the strength of concrete;when the fiber content is 0.2%,mbber content is 10%?20%?30%,the specific surface area and less than 100 ?m aperture are the most important factors affec the strength of concrete.