Research And Optimization On The Inversion Of The Thermal Conductivity Of Solid Materials Based On The Principle Of The Hot Plate Method

The determination of material thermophysical parameters has always been the research focus in the thermophysics field.Only by obtaining the material’s thermophysical parameters,can different materials be applied to different fields and engineering projects according to the thermophysical parameters values.Commonly used thermophysical parameters include thermal conductivity,specific heat,thermal diffusivity,etc.Among them,the measurement of thermal conductivity is the most important.At present,the thermal conductivity measurement methods mainly include theoretical derivation and experimental measurement.Due to the complexity of the theoretical derivation process,scholars mostly use experimental methods to determine the thermal conductivity.According to the different experimental measurement principles,experimental methods are divided into two types:steady-state method and transient method.Although the steady-state method is relatively stable,the measurement time is too long and the heat loss in the process is large,which affects the accuracy of the measurement results.The transient method has certain advantages over the steady-state method in measurement accuracy and measurement time,but the measurement device is complex and costly,and the transient method is more used to measure the thermal conductivity of fluid materials.Aiming at the problems of existing measurement methods,this paper uses inversion methods to obtain the thermal conductivity of solid materials:based on the principle of the hot plate method experimental measurement system under the steady-state category,use genetic algorithm,genetic-simulated annealing algorithm and particle swarm algorithm to invert the thermal conductivity of solid materials.The inversion method can shorten the measurement time,and considers the heat loss during the measurement process,which can improve the accuracy of the measurement results.The main research contents and conclusions are as follows:(1)Establish the physical and mathematical model of the hot plate method measurement system to simulate the temperature field distribution.With the help of simulation software,the physical model of the hot-plate method measurement system is established,which can be constructed as a two-dimensional heat transfer model under the condition of considering the heat loss.Simulate the model to obtain the temperature field distribution of the measured material and the temperature data at the measuring point on the boundary of the measured material;(2)Refer to the hot-plate model to derive the heat transfer equation and calculate the temperature field distribution.With reference to the physical model of the hot plate method,heat transfer equation under different boundary conditions is derived by the finite difference method,and the temperature field distribution of the measured material and the temperature data at the measuring point are obtained by equation calculation(3)Invert the thermal conductivity of solid materials.Using genetic algorithm,genetic-simulated annealing algorithm and particle swarm algorithm,the input is the difference between the simulation result and the calculation result of the temperature measurement point.Under the second type of boundary conditions and the third type of boundary conditions,the thermal conductivity of the four measured materials(Aluminum,Iron,Alumina,and Granite)are reversed;(4)To further improve the accuracy of inversion results,analyze the influence of inversion ranges,algorithm types,material types,and contact thermal resistance on the inversion results.The research results show that the accuracy of the inversion results depends not only on the algorithm used and its characteristics,but also on the characteristics of the material itself.From the point of view of algorithm,the inversion effect of genetic algorithm is the best;from the point of view of the initial inversion range,the inversion accuracy is closely related to the initial inversion range.When the initial inversion range is accurate,the accuracy of the inversion results obtained is very high,and when the inversion range is rough,the inversion accuracy decreases significantly;From the perspective of the properties of the material itself,the value of the thermal conductivity of the material itself is an important factor affecting the inversion results.The inversion accuracy increases with the increase of the thermal conductivity of the material itself,and when the thermal conductivity of the material is smaller,The inversion accuracy is significantly reduced.In addition,the influence of the contact thermal resistance at the material junction on the inversion result is also explored,which has theoretical guiding significance for the control of the contact thermal resistance disturbance.(5)An optimized genetic algorithm with variable inversion range is proposed.The genetic algorithm has a strong dependence on the initial population,and the initial inversion range of the algorithm has a great influence on the inversion result.Therefore,based on the original genetic algorithm,the initial inversion range of the algorithm is optimized and improved,obtaining an optimization algorithm with a variable inversion range.The thermal conductivity of the solid material is inverted using the algorithm before and after optimization.Comparing the inversion results obtained in the two cases,it can be seen that the optimized algorithm has a better inversion effect and the accuracy of the inversion results is better.In summary,a simulation study and a calculation study are carried out on the model of the hot plate method for measuring the thermal conductivity in this paper.The difference between the temperature data obtained by the simulation and calculation is used as the input,and introduced into the inversion process.Then use genetic algorithm,genetic-simulated annealing algorithm and particle swarm algorithm to invert the thermal conductivity of the Aluminum,Iron,Alumina,Granite.The influence of algorithm factors and material factors on the inversion results is analyzed,and based on the original algorithm,obtaining an algorithm with variable inversion range,which improves the accuracy of the inversion results.