Estimation of the heat transfer coefficient for three ranges of reference values under fourth-kind boundary conditions using swarm algorithms

• Autorzy: Zych Maria , Dyja Robert , Gawrońska Elżbieta , Sczygiol Norbert , Domek Grzegorz

Identyfikatory

DOI

10.17512/jamcm.2025.4.08

• Języki publikacji: EN

Abstrakty

EN

The article discusses the problem of reconstructing the heat transfer coefficient under fourth-kind boundary conditions using swarm algorithms, considering the κ param eter’s variation in three value selection ranges. The analysis was conducted based on the time-varying nature of this coefficient, which represents the physics of the heat exchange pro cess at the interface between the casting and the mold. A three-tier division was adopted: low (0 W/m2K - 400W/m2K), medium (400W/m2K - 900W/m2K), and high (900W/m2K - 1500 W/m2 K) κ values, with appropriately selected reference values (250 W/m2 K, 500W/m2K, 1000W/m2K). The geometry of the problem allowed for a detailed analysis of heat behavior in the casting form and the casting itself. To solve the inverse problem, two metaheuristic optimization algorithms, Artificial Bee Colony (ABC) and Ant Colony Optimization (ACO), were applied and implemented in a dedicated computational environ ment. The verification of the correctness of the results involved comparing the determined coefficient values with their reference counterparts. A functional based on the L2 norm was adopted as the assessment criterion, measuring the difference between the computed and reference data. Numerical experiments were conducted for various configurations with different numbers of individuals, iterations, and levels of input data noise. For each case, three independent runs were performed to assess the reproducibility and stability of the results. Particular attention was given to how both algorithms behave depending on the range of κ values and the presence of noise. The analysis of the results indicates significant differences in the selection of the heat transfer coefficient for individual methods, noise, and how the parameter is mapped depending on the range of its values. It was observed that the characteristics of the κ interval and the type of algorithm used directly impact the dispersion of results and the quality of the fit.

Słowa kluczowe

EN

swarm algorithms; artificial intelligence; time-varying heat transfer coefficient; thermal conductivity modeling; optimization of computational parameters

PL

algorytm roju; sztuczna inteligencja; zmienny w czasie współczynnik przenikania ciepła; modelowanie przewodnictwa cieplnego; optymalizacja parametrów obliczeniowych

• Wydawca: Wydawnictwo Politechniki Częstochowskiej
• Czasopismo: Journal of Applied Mathematics and Computational Mechanics
• Rocznik: 2025
• Tom: Vol. 24, nr 4
• Strony: 119--131
• Opis fizyczny: Bibliogr. 22 poz., tab.

Twórcy

autor

Zych Maria

• Faculty of Computer Science and Artificial Intelligence, Czestochowa University of Technology Czestochowa, Poland

autor

Dyja Robert

• Faculty of Computer Science and Artificial Intelligence, Czestochowa University of Technology Czestochowa, Poland

autor

Gawrońska Elżbieta

• Faculty of Computer Science and Artificial Intelligence, Czestochowa University of Technology Czestochowa, Poland

autor

Sczygiol Norbert

• Faculty of Computer Science and Artificial Intelligence, Czestochowa University of Technology Czestochowa, Poland

autor

Domek Grzegorz

• Faculty of Mechatronics, Kazimierz Wielki University Bydgoszcz, Poland

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2026).