Non-linear optimization method for mix proportion of concrete

Abstract

The invention discloses a non-linear optimization method for mix proportion of concrete. The non-linear optimization method is carried out according to the following steps: firstly, establishing a neural network model for predicting the performance of concrete; secondly, determining the target and constraint conditions of an optimization model for mix proportion; thirdly, establishing the optimization model for mix proportion by virtue of a particle swarm optimization algorithm; and fourthly, carrying out particle reduction, namely, respectively reducing optimal fitness values obtained by calculation and positions of the optimal fitness values into the lowest cost value and the corresponding mix proportion of concrete and completing the method. The non-linear optimization method has the beneficial effects that (1) the non-linear prediction model of the performance of concrete and the non-linear optimization model of the mix proportion are established; (2) the problem of over-fitting control in the non-linear prediction of the performance of concrete is solved; and (3) the global optimization of the mix proportion of concrete is achieved and the optimization efficiency is relatively high.

Description

technical field [0001] The invention belongs to the technical field of concrete production, and is mainly applied to the design and optimization of mix ratios in large-scale concrete production (such as commercial concrete companies and ready-mixed concrete plants), especially the mix ratio optimization of multi-component cementitious material concrete. Background technique [0002] Concrete is an inorganic non-metallic composite material composed of cement, water, sand, gravel, admixtures, and admixtures. It is one of the most widely used building materials in modern capital construction projects. In the production of concrete materials, the mix ratio design is used as a "recipe", which directly affects or even determines the performance of concrete. From the moment the concrete material is produced, the problem of mix ratio design becomes a key technical problem. The traditional four-component concrete (mixed only by cement, water, sand and gravel) conforms to the Paul Mi...

AI Technical Summary

Problems solved by technology

[0011] The aforementioned prior art, using the linear programming method, fails to consider the nonlinear relationship between the raw material and concrete properties; using the Monte-Carlo method for optimization, the efficiency is low and takes a long time; using the genetic algorithm, there

Images