Deriving Optimum Mix Designs for High – Strength Concrete using Genetic Algorithms
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Détails bibliographiques
Auteur(s): |
Andres Winston Oreta
Alden Paul Balili Bertrand Teodosio Iris Mae Malabatuan Analyn Yee Concepcion |
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Médium: | papier de conférence | ||||
Langue(s): | anglais | ||||
Conférence: | 18th IABSE Congress: Innovative Infrastructures – Towards Human Urbanism, Seoul, Korea, 19-21 September 2012 | ||||
Publié dans: | IABSE Congress Seoul 2012 | ||||
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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. |