Publication detail

Soft computing methods in the solution of an inverse heat transfer problem with phase change: A comparative study

MAUDER, T. KŮDELA, J. KLIMEŠ, L. ZÁLEŠÁK, M. CHARVÁT, P.

Original Title

Soft computing methods in the solution of an inverse heat transfer problem with phase change: A comparative study

Type

journal article in Web of Science

Language

English

Original Abstract

Inverse heat transfer problems are ill-posed problems and their solution is challenging. Conventional (hard computing) solution methods were developed for this purpose in the past, but they are not well applicable in cases including phase change, which contain strong non-linearity and bring additional computational difficulties. Soft computing methods, which currently experience very rapid development, are a promising tool for the solution of such problems. This paper addresses an inverse heat transfer problem with phase change, in which the boundary heat flux is estimated. Four methods based on distinct mathematical principles are applied to this problem and thoroughly compared. These methods include a conventional Levenberg-Marquardt method (LMM), a predictive fuzzy logic (PFL)-based method, a population-based meta-heuristic method called LSHADE (a state-of-the-art differential evolution variant), and a recently developed surrogate-assisted method coupled with differential evolution, referred to as LSADE method. Furthermore, a reformulation of the problem was developed, utilising a dimension reduction scheme and a decomposition scheme that led to sub-problems with different time frames. This reformulation brought extensive computational improvements. Results of the comparison of the methods then showed that the LMM and the PFL behave well in case without phase change but their performance deteriorates substantially in case with phase change. The LSHADE and the LSADE showed superior performance in the solution of the inverse problem with the phase change. Moreover, their performance was rather stable and insensitive to the location of the temperature sensor, which was the source of data for the estimation.

Keywords

Inverse heat transfer; Soft computing; Machine learning; Meta-heuristics; Surrogate model; Fuzzy logic

Authors

MAUDER, T.; KŮDELA, J.; KLIMEŠ, L.; ZÁLEŠÁK, M.; CHARVÁT, P.

Released

1. 7. 2024

Publisher

PERGAMON-ELSEVIER SCIENCE LTD

Location

OXFORD

ISBN

1873-6769

Periodical

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Year of study

133

Number

B

State

United Kingdom of Great Britain and Northern Ireland

Pages from

108229

Pages to

108245

Pages count

17

URL

https://www.sciencedirect.com/science/article/pii/S0952197624003877

BibTex

@article{BUT189235,
  author="Tomáš {Mauder} and Jakub {Kůdela} and Lubomír {Klimeš} and Martin {Zálešák} and Pavel {Charvát}",
  title="Soft computing methods in the solution of an inverse heat transfer problem with phase change: A comparative study",
  journal="ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE",
  year="2024",
  volume="133",
  number="B",
  pages="17",
  doi="10.1016/j.engappai.2024.108229",
  issn="1873-6769",
  url="https://www.sciencedirect.com/science/article/pii/S0952197624003877"
}