Optimization of time and temperature of dam construction for thermal analysis of roller compacted concrete dam

The growing number of roller compacted concrete dams built around the world demand good methods to reduce the risk of thermal cracks. In roller compacted concrete dams, usually, large amounts of concrete are poured in a short time and the heat generated by the hydration of the cement, leads to an in...

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Bibliographic Details
Main Authors: Ramtin Sobhkhiz Foumani, Alireza Mardookhpour, Forouzan Saberi
Format: Article
Language:English
Published: K. N. Toosi University of Technology 2023-06-01
Series:Numerical Methods in Civil Engineering
Subjects:
Online Access:https://nmce.kntu.ac.ir/article_169194_72705dd25bad158ce4a24f01c77912fd.pdf
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Summary:The growing number of roller compacted concrete dams built around the world demand good methods to reduce the risk of thermal cracks. In roller compacted concrete dams, usually, large amounts of concrete are poured in a short time and the heat generated by the hydration of the cement, leads to an increase in temperature in the body of the dam, which results in a significant heat slope. In this research, Abaqus software, a finite element software, was used for thermal analysis of the dam during construction and concreting. The method of applying thermal changes is as follows. For the structure, hypothetical 50 cm layers are considered, each layer takes up 72 hours of analysis time. In general, the problem under analysis is analyzed 12 times. Each analysis is based on the start of the project from different months of the year to achieve the optimal constructing time based on the maximum temperature in the concrete of the dam and the stresses created by it by collecting the information and using the perceptron network algorithm. Perceptron algorithm and machine learning were performed on the 12 mentioned analyzes and then the process output was generated for 365 days of the year as the start of the project. Finally the optimal time to start construction was achieved.
ISSN:2345-4296
2783-3941