APPLICATION OF SOFT COMPUTING TECHNIQUES FOR PREDICTING COOLING TIME REQUIRED DROPPING INITIAL TEMPERATURE OF MASS CONCRETE.
Santosh Bhattarai, Yihong Zhou, Chunju Zhao, Huawei Zhou · Stavební obzor · 2017
Minimizing the thermal cracks in mass concrete at an early age can be achieved byremoving the hydration heat as quickly as possible within initial cooling period before the next lift isplaced. Recognizing the time needed to remove hydration heat within initial cooling period helps totake an effective and efficient decision on temperature control plan in advance. Thermal propertiesof concrete, water cooling parameters and construction parameter are the most influencing factorsinvolved in the process and the relationship between these parameters are non-linear in a pattern,complicated and not understood well. Some attempts had been made to understand and formulatethe relationship taking account of thermal properties of concrete and cooling water parameters.Thus, in this study, an effort have been made to formulate the relationship for the same takingaccount of thermal properties of concrete, water cooling parameters and construction parameter,with the help of two soft computing techniques namely: Genetic programming (GP) software“Eureqa” and Artificial Neural Network (ANN). Relationships were developed from the dataavailable from recently constructed high concrete double curvature arch dam. The value of R forthe relationship between the predicted and real cooling time from GP and ANN model is 0.8822and 0.9146 respectively. Relative impact on target parameter due to input parameters wasevaluated through sensitivity analysis and the results reveal that, construction parameter influencethe target parameter significantly. Furthermore, during the testing phase of proposed models withan independent set of data, the absolute and relative errors were significantly low, which indicatesthe prediction power of the employed soft computing techniques deemed satisfactory as comparedto the measured data.