Research On Solution To Inverse Surface Radiation Problem Based On Genetic Algorithm

Radiative heat transfer is an important branch of thermodynamics that can be divided into two types of positive and negative problems.Through the utilization of the measured values of temperature,heat flux density and radiation intensity of the system with radioactive media,the parameters of the reconstructed system or the boundary conditions can be inverted.Studying the inverse problem of radiation can effectively solve the problem that can not be solved in forward engineering.In engineering applications,it helps to solve various engineering optimization problems and thermodynamic estimation of unknown heat.The heat transfer mechanism of thermal radiation is directly related to either the emission and propagation of electromagnetic waves or the transport of photons.Depending on the participation of the medium in space,thermal radiation can be classified into two forms,which are surface radiation and gas radiation,respectively.In this study,two models were inversely modeled.Modeling the radiative convection heat transfer calculation process of the water wall tube in the pulverized coal furnace and inverting the solution of its parameters.The radiation of each surface inside the cylindrical axisymmetric cylindrical shell is analyzed and modeled.Through the inversion calculation estimate the temperature and material properties of each surface.Genetic algorithm is a kind of intelligent optimization algorithm.In this paper,we introduced the basic principle and formula of classical genetic algorithm in detail.Aiming at the defect that classic genetic algorithm does not have the memory function and thus loses the good solution that has been found.A new crossover operator is proposed and the genetic algorithm is improved.In this paper,eight well-known benchmark functions are used to test the performance of genetic algorithms with memory and classical genetic algorithms,as well as the existing improved genetic algorithms.The numerical results show that the genetic algorithm with memory function is superior to other improved genetic algorithms and classical genetic algorithms in search speed and accuracy.At present,the inverse problem of radiation has been widely used in engineering construction,so it is of great practical significance to study the solving algorithm of radiation inverse problem.In this paper,in order to study the method of solving the inverse problem of radiation,the genetic algorithm with memory function is applied to the calculation of the inverse problem of radiation.Various cases with different number of parameters are inversed and estimated.By analyzing the data,the feasibility and efficiency of the improved algorithm can be verified.