|
Title |
Concrete Optimum Mixture Proportioning Based on a Database Using Convex Hulls
|
|
Keywords |
최적 배합 ; 데이터베이스 ; 유전자 알고리즘 ; 인공신경회로망 ; 최소 볼록 집합 optimum mix-proportion ; database ; genetic algorithm ; artificial neural network ; convex hull |
|
Abstract |
This paper presents an optimum mixture design method for proportioning a concrete. In the proposed method, the search space is constrained as the domain defined by the minimal convex region of a database, instead of the available range of each component and the ratio composed of several components. The model for defining the search space which is expressed by the effective region is proposed. The effective region model evaluates whether a mix-proportion is effective on processing for optimization, yielding highly reliable results. Three concepts are adopted to realize the proposed methodology: A genetic algorithm for the optimization; an artificial neural network for predicting material properties; and a convex hull for evaluating the effective region. And then, it was applied to an optimization problem wherein the minimum cost should be obtained under a given strength requirement. Experimental test results show that the mix-proportion obtained from the proposed methodology using convex hulls is found to be more accurate and feasible than that obtained from a general optimum technique that does not consider this aspect.
|