Inversion Method Of High Arch Dam Concrete Thermal Parameters Considering Measuring Point Sensitivity

The accuracy of the thermal parameters of concrete directly affects the reliability of the simulation results of dam concrete temperature field.Due to the influence of raw material batch and site construction environment,the thermal parameters of concrete obtained through laboratory test or empirical formula can not accurately reflect the thermal properties of concrete under the actual pouring condition.Practice shows that the inversion calculation based on the measured temperature data is an effective way to obtain the real thermal parameters of concrete.Therefore,it is of great significance to study the accurate retrieval method of real thermal parameters of concrete.Aiming at the problem that the inversion precision of mass concrete thermal parameters is influenced by the selection of the measuring points and the stability of the optimization algorithm,the following research is carried out in this paper:To solve the problem that the inversion accuracy is greatly influenced by the choice of temperature measurement point position,starting from the analytical relationship between monitoring error and inversion error,a square method is proposed to optimize the temperature measurement point of the thermal parameters by the principle of the highest sensitivity.On this basis,combined with the highly non-linear characteristics of the concrete heat transfer problem,the improved Morris method was introduced and the calculation process of the measurement point sensitivity was proposed.In order to solve the problem that the stability of the inverse precision of concrete thermal parameters is greatly influenced by the optimization algorithm,two inversion methods are compared,which are uniform design-numerical simulation-BP neural network-genetic algorithm and genetic algorithmnumerical simulation.The causes of similarities and inversion results are unstable;then,starting from the optimization strategy of genetic algorithms,a broad initial search space is an important factor influencing the stability of the inversion results,which is combined with the random test method and genetic algorithm.A thermal parameter inversion method for gradually narrowing the search space is proposed,that is,the initial search space of the genetic algorithm is gradually reduced according to the results of multiple inversion,thereby improving the stability of the inversion result.The results show that the accuracy of the parameter inversion through the optimized measurement point temperature value is higher;The use of an inversion method that gradually narrows the search space can effectively enhance the stability of the inversion results.The results show that when selecting the thermal parameters to invert the measurement points,the relationship between the location of the measurement points and the inversion parameters should be taken into account.The method for inverting the temperature measurement points proposed by the thermal parameters in this paper can improve the accuracy of the inversion parameters.Compared with the conventional intelligent inversion method,the "thermal parameter inversion method of gradually narrowing the search space" is used to control the stability of the inversion results,and the accuracy and efficiency of the inversion have also been improved to a certain extent,which has the characteristics of simple and effective.