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Deriving Optimum Mix Designs for High – Strength Concrete using Genetic Algorithms

 Deriving Optimum Mix Designs for High – Strength Concrete using Genetic Algorithms
Auteur(s): , , , ,
Présenté pendant 18th IABSE Congress: Innovative Infrastructures – Towards Human Urbanism, Seoul, Korea, 19-21 September 2012, publié dans , pp. 1935-1942
DOI: 10.2749/222137912805112716
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High-strength concrete (HSC) is a highly complex and evolving construction material. Careful selection of constituent materials must be employed to successfully proportion HSC mixtures. While there...
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Détails bibliographiques

Auteur(s):




Médium: papier de conférence
Langue(s): anglais
Conférence: 18th IABSE Congress: Innovative Infrastructures – Towards Human Urbanism, Seoul, Korea, 19-21 September 2012
Publié dans:
Page(s): 1935-1942 Nombre total de pages (du PDF): 8
Page(s): 1935-1942
Nombre total de pages (du PDF): 8
DOI: 10.2749/222137912805112716
Abstrait:

High-strength concrete (HSC) is a highly complex and evolving construction material. Careful selection of constituent materials must be employed to successfully proportion HSC mixtures. While there are codes like ACI and ASTM which guide concrete proportioning, batching companies perform trial and error to produce a number of trial mixes depending on a required strength and slump. This method, however, is costly, time consuming and sometimes uneconomical and wasteful. Hence, genetic algorithms (GA) was explored in deriving optimum HSC mix designs using data collected from a batching company. Verification was implemented through in-situ adjustments and compression tests resulted to be applicable in actual practice that suggested a reduction in the number of trial mixtures and lesser incurred overall material cost of HSC.