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Beck raised the concept of sensitivity coefficient and introduced it into the inverse problem, thereby successfully obtaining the steady-state and unsteady-state heat conduction application. The method mentioned above was applied to the identification of aerodynamic heating on an atmospheric reentry capsule. Duda identified the heat flux in two-dimensional transient heat conduction and reconstructed the transient temperature field by utilizing the finite element method (FEM) and Levenberg Marquardt method in ANSYS Multiphysics software. In view of the inverse problem of heat-transfer, experts and scholars have done quite a lot of research. It has been applied in almost all fields of scientific engineering, including power engineering, aerospace engineering, metallurgical engineering, biomedical engineering, mechanical manufacturing, chemical engineering, nuclear physics, material processing, geometry optimization of equipment, and nondestructive testing. The research of inverse heat conduction problem has a very wide application background. The Inverse Heat Conduction Problem is able to retrieve the unknown parameters such as boundary conditions, material thermophysical parameters, internal heat sources, and boundary geometry by measuring the temperature information at the boundary or at some point in the heat-transfer system. As demonstrated by empirical analysis, the proposed method remains highly precise despite the presence of measurement errors or the close distance of measurement point position from the boundary angular point angle.
HEAT TRANSFER 2D TRANSIENT MATLAB FDTD VERIFICATION
Finite difference method (FDM) is adopted for direct problem to calculate the temperature value in various time quanta of needed discrete point as well as the temperature field verification by time quantum, while inverse problem discusses the impact of different measurement errors and measurement point positions on the inverse result. The residual principle is introduced to estimate the optimized regularization parameter in the model prediction control method, thereby obtaining a more precise inversion result. The paper adopts Finite Difference Method (FDM) and Model Predictive Control Method (MPCM) to study the inverse problem in the third-type boundary heat-transfer coefficient involved in the two-dimensional unsteady heat conduction system. It has been extensively applied in the fields of engineering related to heat-transfer measurement, such as the aerospace, atomic energy technology, mechanical engineering, and metallurgy.
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The Inverse Heat Conduction Problem (IHCP) refers to the inversion of the internal characteristics or thermal boundary conditions of a heat transfer system by using other known conditions of the system and according to some information that the system can observe.