A closed-box kernel function for numerical simulation of transient heat conduction

A new kernel function, termed the closed-box kernel function, has been developed to address numerical simulation of transient heat conduction in the same medium. Firstly, this method is versatile and not limited to specific industrial scenarios or designated materials. Secondly, the method solves th...

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Vydané v:Scientific reports Ročník 14; číslo 1; s. 31208 - 17
Hlavní autori: Zhang, Yalong, Yang, Jun, Zhang, Xinjiang, Yu, Wei, Li, Xuemei, Qin, Bentao
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Nature Publishing Group UK 28.12.2024
Nature Publishing Group
Nature Portfolio
Predmet:
639/166
639/301
639/705
Conduction
Heat
Heat conduction equation
Humanities and Social Sciences
Information processing
Kernel function
Mathematical models
multidisciplinary
Numerical simulation
Partial differential equation
Science
Science (multidisciplinary)
Simulation
Transient heat conduction
Visual stimuli
Kernel function
Numerical simulation
Heat conduction equation
Partial differential equation
Transient heat conduction
ISSN:2045-2322, 2045-2322
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Shrnutí:A new kernel function, termed the closed-box kernel function, has been developed to address numerical simulation of transient heat conduction in the same medium. Firstly, this method is versatile and not limited to specific industrial scenarios or designated materials. Secondly, the method solves the spatial temperature at each time point only once, eliminating the need for multiple iterations. Thirdly, the method allows for controlled and adjustable simulation speed of heat conduction while maintaining high accuracy. After 24,700 iterations in the transient process, the relative error in temperature values is merely 0.000072. Fourthly, this numerical technique can break data dependency between spatial nodes, making it suitable for parallel computing with Graphics Processing Units (GPUs). The average speedup achieved is 94.0712 times faster compared to Central Processing Unit (CPU) computations. Finally, we provide mathematical examples to verify the correctness and accuracy of this numerical approach and present a computational framework for parallel computing in the Visual Studio (VS) programming environment to demonstrate its practicality in engineering applications.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-82468-7