Multi-Criteria Optimization of Durability Properties of Self-Compacting Concrete Using Artificial Intelligence
Publish place: Advance Researches in Civil Engineering، Vol: 5، Issue: 4
Publish Year: 1402
Type: Journal paper
Language: English
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Document National Code:
JR_ARCE-5-4_002
Index date: 17 October 2024
Multi-Criteria Optimization of Durability Properties of Self-Compacting Concrete Using Artificial Intelligence abstract
Permeability properties, mainly including migration, absorption, and diffusion, have been widely used to measure the durability of concrete. In this article, using the particle swarm optimization algorithm and based on the concept of Pareto optimization, the relations extracted from the results of the previous tests, and the optimal values of the constituents of self-compacting concrete to achieve the best durability are presented. Due to the lower amount of oxygen permeability in self-compacting concrete compared to SCC concrete with the same strength, Chlorine migration strongly depends on the type of filler. In this regard, durable concrete should have more filler. Pulverized fly ash (PFA) is a better filler to increase durability.
Multi-Criteria Optimization of Durability Properties of Self-Compacting Concrete Using Artificial Intelligence Keywords:
Pareto optimization , chloride migration , Durability , water absorption , Particle Swarm Optimization (PSO)
Multi-Criteria Optimization of Durability Properties of Self-Compacting Concrete Using Artificial Intelligence authors
sasan motaghed
Assistant Prof., Faculty of Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran
nasrolla eftekhari
Assistant Prof., Faculty of Technology and Mining, Yasouj University, Choram, Iran
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