Academic Journal

Applications of Methods of Solving Inverse Heat Conduction Problems for Energy-Intensive Industrial Processes and Energy Conversion—Current State of the Art and Recent Challenges.

Bibliographic Details
Title: Applications of Methods of Solving Inverse Heat Conduction Problems for Energy-Intensive Industrial Processes and Energy Conversion—Current State of the Art and Recent Challenges.
Authors: Joachimiak, Magda, Joachimiak, Damian
Source: Energies (19961073); Mar2026, Vol. 19 Issue 5, p1291, 19p
Subject Terms: Boundary value problems, Machine learning, Mathematical regularization, Heat treatment, Artificial neural networks
Abstract: This paper presents methods and applications of inverse heat conduction problems (IHCPs) that are ill-posed in the Hadamard sense. The IHCP solution allows for the determination of boundary conditions in the form of heat flux or temperature in places where measurement is impossible or difficult to perform. The applications of IHCP solutions to energy-intensive industrial processes, such as heat treatment and thermochemical treatment, are described. Examples are given of determining boundary conditions on the inner surface of the wall of a power boiler and piston machine, as well as on the surface of a gas turbine blade. It is noted that the application of IHCP solutions to the above-mentioned issues often requires simplification of the computational model, in particular, the method of stabilising the inverse problem (IP). For this purpose, quasi-regularisation of IP and machine learning are currently used. Methods with stabilising properties and neural networks were identified as a challenging and interesting direction for the development of IHCP solutions. [ABSTRACT FROM AUTHOR]
Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Applications of Methods of Solving Inverse Heat Conduction Problems for Energy-Intensive Industrial Processes and Energy Conversion—Current State of the Art and Recent Challenges.
– Name: Author
  Label: Authors
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  Data: <searchLink fieldCode="AR" term="%22Joachimiak%2C+Magda%22">Joachimiak, Magda</searchLink><br /><searchLink fieldCode="AR" term="%22Joachimiak%2C+Damian%22">Joachimiak, Damian</searchLink>
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  Data: Energies (19961073); Mar2026, Vol. 19 Issue 5, p1291, 19p
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Boundary+value+problems%22">Boundary value problems</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+regularization%22">Mathematical regularization</searchLink><br /><searchLink fieldCode="DE" term="%22Heat+treatment%22">Heat treatment</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper presents methods and applications of inverse heat conduction problems (IHCPs) that are ill-posed in the Hadamard sense. The IHCP solution allows for the determination of boundary conditions in the form of heat flux or temperature in places where measurement is impossible or difficult to perform. The applications of IHCP solutions to energy-intensive industrial processes, such as heat treatment and thermochemical treatment, are described. Examples are given of determining boundary conditions on the inner surface of the wall of a power boiler and piston machine, as well as on the surface of a gas turbine blade. It is noted that the application of IHCP solutions to the above-mentioned issues often requires simplification of the computational model, in particular, the method of stabilising the inverse problem (IP). For this purpose, quasi-regularisation of IP and machine learning are currently used. Methods with stabilising properties and neural networks were identified as a challenging and interesting direction for the development of IHCP solutions. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.3390/en19051291
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 19
        StartPage: 1291
    Subjects:
      – SubjectFull: Boundary value problems
        Type: general
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Mathematical regularization
        Type: general
      – SubjectFull: Heat treatment
        Type: general
      – SubjectFull: Artificial neural networks
        Type: general
    Titles:
      – TitleFull: Applications of Methods of Solving Inverse Heat Conduction Problems for Energy-Intensive Industrial Processes and Energy Conversion—Current State of the Art and Recent Challenges.
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            NameFull: Joachimiak, Magda
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              M: 03
              Text: Mar2026
              Type: published
              Y: 2026
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              Value: 19
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            – TitleFull: Energies (19961073)
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