A genetic algorithm to identify the optimal concrete mix for the elements subject to risk of early age thermal cracking
- Publication Type:
- Conference Proceeding
- FIB 2018 - Proceedings for the 2018 fib Congress: Better, Smarter, Stronger, 2019, pp. 3351-3360
- Issue Date:
|Pages from fib Congress proceedings 2018 – final.pdf||Published version||1.32 MB|
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© 2019 by the fib. All rights reserved. The mismatch between the rate of heat generation due to cement hydration and the rate of heat dissipation through conduction and convection may result in considerable temperature gradient within mass concrete and concrete elements with high cement content. This temperature gradient may in turn lead to considerable thermal stresses in concrete at its early ages when it has not achieved its full capacity to resist tensile stress, leading to early age thermal cracking in concrete. Among various measures investigated to minimize the risk of early age thermal cracking, optimizing the concrete mixes and use of supplementary cementitious materials are usually favoured by the industry mainly because these methods do not require changes to the construction method and plan. However, regulating the internal heat generation to reduce the risk of thermal cracking is not considered as an objective in existing mix deign approaches which have been designed to achieve target mechanical properties. In this paper, a mathematical optimization model based on genetic algorithms is developed to identify the optimal mix for typical concrete elements subject to risk of early age thermal cracking. The optimization model is designed to reduce the temperature gradient within the concrete without comprising the development of mechanical properties of concrete. The proposed optimization method is applied to a case study involving identifying the optimal mix design for a large concrete raft. The reduction in the risk of thermal cracking due to use of optimal mix, rather than originally planned mix, is verified through numerical simulation.
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