Inversion Analysis On Temperature Field Of RCC Dam Based On Genetic Algorithms

With the extensive application of RCC dam construction technology, the problem of concrete cracking has attracted more and more attention. Making a simulation calculation to get the temperature field and thermal stress field of dam is an effective approach to solve it, and the temperature field simulation should come first. However, the thermal parameters used in temperature field simulation are mostly obtained by empirical formula and test. The cost of test is so high and the results cann't completely reflect the true thermal properties of RCC, due to the differences between test conditions and actual construction environment, which lead to some deviations of calculation temperature from measured values. Therefore, doing the inversion analysis of RCC dam temperature field in order to obtain reliable thermal parameters, It is of great economic value and project construction significance to make inversion analysis on temperature field of RCC dam to obtain reliable thermal parameters.In the paper, some researches have been done on inversion analysis of RCC dam temperature field:according to its characteristics, the model of temperature field inversion is established, the inversion parameters are determined; based on optimization thought of genetic algorithm, combine optimization program and verify the reliability and superiority of genetic algorithm optimization program, based on an example of shape optimization design of a gravity dam; the optimization program and original RCTS are successfully combined to develop three-dimensional RCC dam temperature field inversion module; design the visual interface for the module pre-processing, to make thermal parameters inversion intuitive,simple and workable.In addition, according to measured temperature data of a RCC gravity dam, the thermal parameters inversion is done, whose result is used to calculate the temperature field again. From contrast curves of calculation temperature with measure values of measuring points, it is shown that reverse parameter can reflect true thermal properties of RCC, and verify the reliability of reverse results. By comparing this temperature field feedback calculation results with that used reverse parameters in flexible tolerance method, it can be seen that calculation temperature using the thermal parameters reversed in genetic algorithm is in line with measured values on the whole, which shows the superiority of genetic algorithm in global optimization. Therefore, the thermal stress field based on the dam temperature field feedback analysis is also able to reflect its real situation, which can instruct the implementation of temperature control work effectively.