A New Way of Solving Transient Radiative-Conductive Heat Transfer Problems

1998 ◽  
Vol 120 (4) ◽  
pp. 943-955 ◽  
Author(s):  
S. Andre ◽  
A. Degiovanni

One-dimensional transient energy transfer by conduction and radiation is solved for a finite medium. The semitransparent layer emits, absorbs, and scatters radiation (participating medium). The coupled transfer is solved analytically by considering the well-known two-flux approximation, assuming linear transfer and using the Laplace transform. The semitransparent layer can then be modeled by a matrix transfer function. The accuracy of the solution is verified in the case of sharp thermal excitation by a heat pulse on the front face. It is shown that this general model is very accurate for simulating both the limiting cases of purely scattering and purely absorbing media. In the latter case, the same modeling is derived using the kernel substitution technique, and very good agreement is achieved compared with numerical simulations. The resulting computation times are very small, and suggest that such a model can be used in the inverse approach of thermal problems involving semitransparent materials.

1998 ◽  
Vol 9 (4) ◽  
pp. 351-372 ◽  
Author(s):  
A. KLAR ◽  
N. SIEDOW

In this paper domain decomposition methods for radiative transfer problems including conductive heat transfer are treated. The paper focuses on semi-transparent materials, like glass, and the associated conditions at the interface between the materials. Using asymptotic analysis we derive conditions for the coupling of the radiative transfer equations and a diffusion approximation. Several test casts are treated and a problem appearing in glass manufacturing processes is computed. The results clearly show the advantages of a domain decomposition approach. Accuracy equivalent to the solution of the global radiative transfer solution is achieved, whereas computation time is strongly reduced.


2019 ◽  
Vol 16 (04) ◽  
pp. 1843001 ◽  
Author(s):  
Kuo-Chi Liu ◽  
Fong-Jou Tu

In the heat treatment process, blood perfusion starts up a negative feedback mechanism. The blood temperature undergoes a transient process before onset of equilibrium and then changes the situation of temperature distribution. In substance, the blood temperature undergoes a transient process for heat exchange between blood and tissue. For more fully exploring the heat transfer behavior of biological tissue, this paper analyzes the bioheat transfer problems with the nonconstant blood temperature based on the Pennes bioheat equation. A numerical scheme based on the Laplace transform is proposed for solving the present problems.


2020 ◽  
Vol 10 (7) ◽  
pp. 2351
Author(s):  
Marie-Marthe Groz ◽  
Mohamed Bensalem ◽  
Alain Sommier ◽  
Emmanuelle Abisset-Chavanne ◽  
Stéphane Chevalier ◽  
...  

In this paper, the problem of the quantitative characterization of thermal resistance fields in a multilayer sample is addressed by using the classical front face flash method as the thermal excitation and infrared thermography (IRT) as the monitoring sensor. In this challenging problem, the complete inverse processing of a multilayer analytical model is difficult due to the lack of sensitivity of some parameters (layer thickness, depth of thermal resistance, etc.) and the expansive computational iterative processing. For these reasons, the proposed strategy is to use a simple multilayer problem where only one resistive layer is estimated. Moreover, to simplify the inverse processing often based on iterative methods, an asymptotic development method is proposed here. Regarding the thermal signal reconstruction (TSR) methods, the drawback of these methods is the inability to be quantitative. To overcome this problem, the method incorporates a calibration process originating from the complete analytical quadrupole solution to the thermal problem. This analytical knowledge allows self-calibration of the asymptotic method. From this calibration, the quantitative thermal resistance field of a sample can be retrieved with a reasonable accuracy lower than 5%.


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