The coupled heat and moisture transfer in a freezing process of wood particle material was mathematically modeled in the paper. The models were interactively solved by using the numerical method(the finite element met...The coupled heat and moisture transfer in a freezing process of wood particle material was mathematically modeled in the paper. The models were interactively solved by using the numerical method(the finite element method and the finite difference method). By matching the theoretical calculation to an experiment, the nonlinear problem was analyzed and the variable thermophysical parameters concerned was evaluated. The analysis procedure and the evaluation of the parameters were presented in detail. The result of the study showed that by using the method as described in the paper, it was possible to determine the variable (with respect to temperature, moisture content and freezing state) thermophysical parameters which were unknown or difficult to measure as long as the governing equations for a considered process were available. The method can significantly reduces the experiment efforts for determining thermophysical parameters which arc very complicated to measure. The determined variable of the effective heat conductivity of wood particle material was given in the paper. The error of the numerical calculation was also estimated by the comparison with a matched experiment.展开更多
The presence of non-gray radiative properties in a reheating furnace’s medium that absorbs,emits,and involves non-gray creates more complex radiative heat transfer problems.Furthermore,it adds difficulty to solving t...The presence of non-gray radiative properties in a reheating furnace’s medium that absorbs,emits,and involves non-gray creates more complex radiative heat transfer problems.Furthermore,it adds difficulty to solving the coupled conduction,convection,and radiation problem,leading to suboptimal efficiency that fails to meet real-time control demands.To overcome this difficulty,comparable gray radiative properties of non-gray media are proposed and estimated by solving an inverse problem.However,the required iteration numbers by using a least-squares method are too many and resulted in a very low inverse efficiency.It is necessary to present an efficient method for the equivalence.The Levenberg-Marquardt algorithm is utilized to solve the inverse problem of coupled heat transfer,and the gray-equivalent radiative characteristics are successfully recovered.It is our intention that the issue of low inverse efficiency,which has been observed when the least-squares method is employed,will be resolved.To enhance the performance of the Levenberg-Marquardt algorithm,a modification is implemented for determining the damping factor.Detailed investigations are also conducted to evaluate its accuracy,stability of convergence,efficiency,and robustness of the algorithm.Subsequently,a comparison is made between the results achieved using each method.展开更多
A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductiv...A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.展开更多
文摘The coupled heat and moisture transfer in a freezing process of wood particle material was mathematically modeled in the paper. The models were interactively solved by using the numerical method(the finite element method and the finite difference method). By matching the theoretical calculation to an experiment, the nonlinear problem was analyzed and the variable thermophysical parameters concerned was evaluated. The analysis procedure and the evaluation of the parameters were presented in detail. The result of the study showed that by using the method as described in the paper, it was possible to determine the variable (with respect to temperature, moisture content and freezing state) thermophysical parameters which were unknown or difficult to measure as long as the governing equations for a considered process were available. The method can significantly reduces the experiment efforts for determining thermophysical parameters which arc very complicated to measure. The determined variable of the effective heat conductivity of wood particle material was given in the paper. The error of the numerical calculation was also estimated by the comparison with a matched experiment.
基金supported by the Na⁃tional Natural Science Foundation of China(No.12172078)the Fundamental Research Funds for the Central Univer⁃sities(No.DUT24MS007).
文摘The presence of non-gray radiative properties in a reheating furnace’s medium that absorbs,emits,and involves non-gray creates more complex radiative heat transfer problems.Furthermore,it adds difficulty to solving the coupled conduction,convection,and radiation problem,leading to suboptimal efficiency that fails to meet real-time control demands.To overcome this difficulty,comparable gray radiative properties of non-gray media are proposed and estimated by solving an inverse problem.However,the required iteration numbers by using a least-squares method are too many and resulted in a very low inverse efficiency.It is necessary to present an efficient method for the equivalence.The Levenberg-Marquardt algorithm is utilized to solve the inverse problem of coupled heat transfer,and the gray-equivalent radiative characteristics are successfully recovered.It is our intention that the issue of low inverse efficiency,which has been observed when the least-squares method is employed,will be resolved.To enhance the performance of the Levenberg-Marquardt algorithm,a modification is implemented for determining the damping factor.Detailed investigations are also conducted to evaluate its accuracy,stability of convergence,efficiency,and robustness of the algorithm.Subsequently,a comparison is made between the results achieved using each method.
基金supported by the Fundamental Research Funds for the Central Universities (No.3122020072)the Multi-investment Project of Tianjin Applied Basic Research(No.23JCQNJC00250)。
文摘A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.
