Research On Interfacial Heat Transfer Coefficient And Thermophysical Properties Of Materials Based On Bionic Algorithm

At present,CAE software and numerical simulation technology have been widely used in forging,extrusion,hot stamping,rolling,quenching and other hot processing technology and get fruitful achievement.When the numerical simulation technology is used to study the hot processing technology,it is necessary to input thermo-physical parameters,mechanical properties parameters,contact boundary parameters and heat exchange boundary parameters of the blank and mold materials.In order to provide reliable material thermo-physical parameters and heat exchange boundary parameters for numerical simulation of thermal processing technology,and to ensure the accuracy and reliability of numerical simulation results,the development of database of material thermo-physical properties and interface heat transfer characteristics is gradually taken seriously by researchers and technicians.Interfacial heat transfer coefficient(IHTC)is a very important parameter in the numerical simulation of thermal processing.The interfacial heat transfer coefficient under various working conditions has been paid more and more attention,and has become a research hotspot in various countries.However,it is difficult to directly measure the interfacial heat transfer coefficient by experimental methods.So,inverse heat transfer method is used to solve the thermo-physical parameters and interface heat transfer characteristics.According to the number of target,the inverse heat conduction problem(IHCP)can be divided into single-parameter problem and multi-parameters problem.Single-parameter problem is to solve one variable,while multi-parameters problem is to solve two or more variables at same time.In order to solve the interfacial heat transfer coefficient in the cooling process,the artificial fish swarm algorithm is applied to the inverse heat conduction problem,and the inverse heat conduction program is written by Fortran in combination with the finite element algorithm.In order to improve the convergence speed,an improved artificial fish swarm algorithm(ZAFSA)based on the artificial fish swarm algorithm(AFSA)combined with the normal distribution algorithm(Z)was proposed.The interfacial heat transfer coefficient is solved by using the temperature curve in literature.By comparing the interfacial heat transfer coefficient between the literature and the artificial fish swarm algorithm and the improved artificial fish swarm algorithm,the results show that the artificial fish swarm algorithm and the improved artificial fish swarm algorithm can get the optimal solution.And the convergence speed of the improved artificial fish swarm algorithm is greatly improved.In order to solve the interfacial heat transfer coefficient in the gas cooling process,the firefly algorithm is applied to the inverse heat conduction problem,and the inverse heat conduction program is written by using the Fortran in combination with the finite element algorithm.In order to improve the convergence speed,this paper proposes an improved firefly algorithm(ZFA)by combining the firefly algorithm(FA)with the normal distribution algorithm(Z).In the improved firefly algorithm,in order to further accelerate the convergence speed,the social cognition(G)in the particle swarm optimization(PSO)and the firefly algorithm are combined to form ZGFA.The improved algorithm is verified by gas cooling experiment.The results show that ZFA and ZGFA greatly improve the convergence speed of the algorithm and improve the convergence performance of the algorithm.Since in the process of solving the interfacial heat transfer coefficient,there are also cases where other thermal property parameters are also unknown,that is,a multi-objective problem.The advantage of bionic algorithm in optimization problem is that multiple variables can be optimized at the same time.In order to solve the multi-objective problem,this paper uses particle swarm optimization algorithm combined with finite element algorithm to write multi-objective inverse heat conduction program(PSO-FEM)to solve thermal conductivity-interfacial heat transfer coefficient,interfacial heat transfer coefficient-specific heat capacity and thermal conductivity-specific heat capacity.In order to speed up the convergence of the algorithm,this paper combines the particle swarm optimization algorithm with the normal distribution algorithm and proposes an improved hybrid algorithm(ZPSO).The inverse heat conduction program prepared by the improved hybrid algorithm calculates the temperature curve obtained by the direct heat conduction problem.The results show that the interfacial heat transfer coefficient-thermal conductivity,interfacial heat transfer coefficient-specific heat capacity and thermal conductivity-specific heat capacity and application are solved by inverse heat conduction program.The values in the positive heat transfer agree well,and the improved ZPSO can quickly find the optimal value,and the convergence performance is greatly improved.