Time Traveling Regularization for Inverse Heat Transfer Problems
This work presents a technique called Time Traveling Regularization (TTR) applied to an optimization technique in order to solve ill-posed problems. This new methodology does not interfere in the minimization technique process. The Golden Section method together with TTR are applied only to the obje...
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Online Access: | http://www.mdpi.com/1996-1073/11/3/507 |
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doaj-5a73577b1e484e7d9a97028d4096e6672020-11-24T23:16:31ZengMDPI AGEnergies1996-10732018-02-0111350710.3390/en11030507en11030507Time Traveling Regularization for Inverse Heat Transfer ProblemsElisan dos Santos Magalhães0Bruno de Campos Salles Anselmo1Ana Lúcia Fernandes de Lima e Silva2Sandro Metrevelle Marcondes Lima e Silva3Heat Transfer Laboratory—LabTC, Institute of Mechanical Engineering—IEM, Federal University of Itajubá—UNIFEI, Campus Prof. José Rodrigues Seabra, Av. BPS, 1303, 37500-903 Itajubá, MG, BrazilHeat Transfer Laboratory—LabTC, Institute of Mechanical Engineering—IEM, Federal University of Itajubá—UNIFEI, Campus Prof. José Rodrigues Seabra, Av. BPS, 1303, 37500-903 Itajubá, MG, BrazilHeat Transfer Laboratory—LabTC, Institute of Mechanical Engineering—IEM, Federal University of Itajubá—UNIFEI, Campus Prof. José Rodrigues Seabra, Av. BPS, 1303, 37500-903 Itajubá, MG, BrazilHeat Transfer Laboratory—LabTC, Institute of Mechanical Engineering—IEM, Federal University of Itajubá—UNIFEI, Campus Prof. José Rodrigues Seabra, Av. BPS, 1303, 37500-903 Itajubá, MG, BrazilThis work presents a technique called Time Traveling Regularization (TTR) applied to an optimization technique in order to solve ill-posed problems. This new methodology does not interfere in the minimization technique process. The Golden Section method together with TTR are applied only to the objective function which will be minimized. It consists of finding an ideal timeline that minimizes an objective function in a defined future time step. In order to apply the proposed methodology, inverse heat conduction problems were studied. Controlled experiments were performed on 5052 aluminum and AISI 304 stainless steel samples to validate the proposed technique. One-dimensional and three-dimensional heat input experiments were carried out for the 5052 aluminum and AISI 304 stainless steel samples, respectively. The Sequential Function Specification Method (SFSM) was also used to be compared with the results of heat flux obtained by TTR. The estimated heat flux presented a good agreement when compared with experimental values and those estimated by SFSM. Moreover, TTR presented lower residuals than the SFSM.http://www.mdpi.com/1996-1073/11/3/507inverse problemsheat fluxtemperature estimationtime-travelingsequential function specification methodGolden Section technique |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Elisan dos Santos Magalhães Bruno de Campos Salles Anselmo Ana Lúcia Fernandes de Lima e Silva Sandro Metrevelle Marcondes Lima e Silva |
spellingShingle |
Elisan dos Santos Magalhães Bruno de Campos Salles Anselmo Ana Lúcia Fernandes de Lima e Silva Sandro Metrevelle Marcondes Lima e Silva Time Traveling Regularization for Inverse Heat Transfer Problems Energies inverse problems heat flux temperature estimation time-traveling sequential function specification method Golden Section technique |
author_facet |
Elisan dos Santos Magalhães Bruno de Campos Salles Anselmo Ana Lúcia Fernandes de Lima e Silva Sandro Metrevelle Marcondes Lima e Silva |
author_sort |
Elisan dos Santos Magalhães |
title |
Time Traveling Regularization for Inverse Heat Transfer Problems |
title_short |
Time Traveling Regularization for Inverse Heat Transfer Problems |
title_full |
Time Traveling Regularization for Inverse Heat Transfer Problems |
title_fullStr |
Time Traveling Regularization for Inverse Heat Transfer Problems |
title_full_unstemmed |
Time Traveling Regularization for Inverse Heat Transfer Problems |
title_sort |
time traveling regularization for inverse heat transfer problems |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2018-02-01 |
description |
This work presents a technique called Time Traveling Regularization (TTR) applied to an optimization technique in order to solve ill-posed problems. This new methodology does not interfere in the minimization technique process. The Golden Section method together with TTR are applied only to the objective function which will be minimized. It consists of finding an ideal timeline that minimizes an objective function in a defined future time step. In order to apply the proposed methodology, inverse heat conduction problems were studied. Controlled experiments were performed on 5052 aluminum and AISI 304 stainless steel samples to validate the proposed technique. One-dimensional and three-dimensional heat input experiments were carried out for the 5052 aluminum and AISI 304 stainless steel samples, respectively. The Sequential Function Specification Method (SFSM) was also used to be compared with the results of heat flux obtained by TTR. The estimated heat flux presented a good agreement when compared with experimental values and those estimated by SFSM. Moreover, TTR presented lower residuals than the SFSM. |
topic |
inverse problems heat flux temperature estimation time-traveling sequential function specification method Golden Section technique |
url |
http://www.mdpi.com/1996-1073/11/3/507 |
work_keys_str_mv |
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