Heuristic Global Optimization for Thermal Model Reduction and Correlation in Aerospace Applications Article Swipe
João P. Castanheira
,
Beltran N. Arribas
,
Rui Melício
,
Paulo Gordo
,
André Silva
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/app15137002
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/app15137002
This study addresses the challenge of accurately correlating detailed and reduced thermal models in aerospace applications by using heuristic global optimization methods. In the context of increasingly complex thermal systems, traditional manual correlation methods are usually a time-consuming task. This research employs a series of numerical simulations using methods such as Genetic Algorithms, Cultural Algorithms, and Artificial Immune Systems, with an emphasis on parameter tuning to optimize the reduced thermal model correlation. Results indicate that these heuristic methods can achieve high-accuracy correlations, with transient simulations exhibiting temperature differences below 3 °C, thereby validating the hypothesis that heuristic methods can effectively navigate complex parameter optimizations. Moreover, a comparative analysis of fitness function performance across various optimization methods underscores both the potential and computational challenges inherent in these approaches. The findings suggest that while heuristic global optimization provides a robust framework for thermal model reduction and correlation, further refinement—particularly in scaling to larger, more complex models and adaptive parameter tuning—is necessary. Overall, this work contributes to the theoretical understanding and practical application of advanced optimization strategies in aerospace thermal analysis, paving the way for improved predictive reliability and more efficient engineering processes.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app15137002
- https://www.mdpi.com/2076-3417/15/13/7002/pdf?version=1750661013
- OA Status
- gold
- References
- 42
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411580229
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4411580229Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/app15137002Digital Object Identifier
- Title
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Heuristic Global Optimization for Thermal Model Reduction and Correlation in Aerospace ApplicationsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-06-21Full publication date if available
- Authors
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João P. Castanheira, Beltran N. Arribas, Rui Melício, Paulo Gordo, André SilvaList of authors in order
- Landing page
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https://doi.org/10.3390/app15137002Publisher landing page
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https://www.mdpi.com/2076-3417/15/13/7002/pdf?version=1750661013Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2076-3417/15/13/7002/pdf?version=1750661013Direct OA link when available
- Concepts
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Reduction (mathematics), Aerospace, Heuristic, Computer science, Aerospace engineering, Engineering, Mathematics, Artificial intelligence, GeometryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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