A Study on the GA-Based Design for Recycled Aggregate Concrete

Abstract:

Various desired performances of concrete, i.e. strength, slump, durability, etc., cannot be always obtained by current conventional mix proportion design methods for recycled aggregate concrete (RAC), because recycled aggregate (RA) generally has lower quality than natural aggregate due to the residual cement paste attached on RA and various impurities. On the other hand, design of concrete mix proportion using RA can be solved as the multi-criteria problem to meet the various required performances. This paper suggests a new method for the mix proportion of RAC to reduce the number of trial mixes using genetic algorithm (GA) which has been an optimization technique to solve the multi-object problem throughout the simulated biological evolutionary process. In mix design method by GA, several fitness functions for the required properties of concrete, i.e., slump, strength, carbonation speed coefficient, price, and emission of CO2 were considered based on conventional data or adapted from various early studies. As a result, various optimum mix proportions for RAC that meet required performances were obtained according to assumed case studies.

• Periodical: Applied Mechanics and Materials (Volumes 284-287)
• Pages: 1225-1229
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.284-287.1225
• Online since: January 2013
• Authors: Won Jun Park
• Keywords: Genetic Algorithm (GA), Mix Proportion, Optimal Design, Recycled Aggregate (RA)

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