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Journal ArticleDOI

Estimation of Spatially Distributed Thermal Properties of Heterogeneous Media with Non-Intrusive Measurement

02 Jan 2021-Heat Transfer Engineering (Taylor & Francis)-Vol. 42, Iss: 1, pp 61-87
TL;DR: In this article, the authors deal with estimation of spatially distributed thermal properties of two-dimensional heterogeneous media from the solution of inverse heat conduction problem, and the experimental procedur...
Abstract: This article deals with estimation of spatially distributed thermal properties of two-dimensional heterogeneous media from the solution of inverse heat conduction problem. The experimental procedur...
Citations
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Journal ArticleDOI
TL;DR: In this article , a divide and conquer approach was used to estimate the principal thermal conductivities of an orthotropic material, specifically engineered with a view to demonstrate the potency of the inverse heat transfer method with unsteady temperature data.
Abstract: Abstract This work reports a novel “divide and conquer” approach to estimate the principal thermal conductivities of an orthotropic material, specifically engineered with a view to demonstrate the potency of the inverse heat transfer method with unsteady temperature data. The sample is placed in a vacuum chamber maintained at a pressure of 8.6 mbar. The heat capacity of the engineered orthotropic material was determined via estimating the heat capacity of a solid SS304 in a sequential fashion. First steady-state experiments followed by a Bayesian estimation with the Metropolis Hastings-Markov Chain Monte Carlo method were done to obtain the thermal conductivity of a solid SS304 block. Using this as a prior, the heat capacity of solid SS304 was obtained through unsteady experiments followed by Bayesian estimation. The heat capacity of SS304 thus obtained is multiplied by the solidity of the engineered orthotropic material, and using this information, the three components of the orthotropic conductivity are estimated again using the Bayesian route. To expedite the estimation, a surrogate for the forward model was developed using artificial neural network. Finally, the retrieved parameters are used to determine the simulated temperatures through the forward model for the orthotropic material. These, when compared with the measured temperatures, gave excellent agreement.
Journal ArticleDOI
TL;DR: In this paper, an inverse estimation of heat flux for a two-dimensional heat conduction problem is carried out using Levenberg-Marquardt method as an inverse model to estimate the input parameter.
References
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Journal ArticleDOI
TL;DR: In this article, a two-dimensional inverse heat conduction problem is solved successfully by the conjugate gradient method (CGM) of minimization in imaging the unknown thermal conductivity of a non-homogeneous material.

80 citations

Journal ArticleDOI
TL;DR: In this paper, an inverse problem utilizing the Levenberg-Marquardt method (LMM) is applied to determine simultaneously the unknown spatial-dependent effective thermal conductivity and volumetric heat capacity for a biological tissue based on temperature measurements.

50 citations

Journal ArticleDOI
TL;DR: In this paper, the heat flux and temperature on the front (heated) surface of a 3D object is recovered using the conjugate gradient method (CGM) with temperature and heat flux measured on back surface (opposite to the heated surface).

49 citations

Journal ArticleDOI
TL;DR: Inverse heat transfer problems deal with the estimation of unknown quantities appearing in the mathematical formulation of physical processes in thermal sciences, by using measurements of temperatu... as mentioned in this paper, where the unknown quantities are assumed to be unknown.
Abstract: Inverse heat transfer problems deal with the estimation of unknown quantities appearing in the mathematical formulation of physical processes in thermal sciences, by using measurements of temperatu...

48 citations

Journal ArticleDOI
TL;DR: In this paper, the authors used the particle swarm optimization algorithm (PSO) coupled with the boundary elements method to identify the shape of an inclusion in a two-dimensional solid body.
Abstract: Temperature measurements from the exterior boundary of a two-dimensional solid body containing an inclusion, under steady state conditions, are used to estimate the thermal conductivity and the shape of the inclusion. The particle swarm optimization algorithm (PSO), coupled with the boundary elements method, is used in this identification problem. A fitness function which is the summation of the squared differences between the measured and calculated temperatures at the locations on the exterior boundary is minimized. To avoid trapping into the local optimum points, the PSO algorithm which is a global optimization method is used instead of local optimization methods. The credibility of the PSO algorithm and its effectiveness in solving inverse problems is investigated. The effect of measurement errors and the size of the inclusion on the estimation process will be addressed.

45 citations