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Digital twinning of thermal systems: A comparison between supervised and reinforcement learning

Armando Di Meglio, Nicola Massarotti, Perumal Nithiarasu Orcid Logo

Computational Thermal Sciences: An International Journal, Volume: 17, Issue: 3, Pages: 39 - 46

Swansea University Author: Perumal Nithiarasu Orcid Logo

  • Accepted Manuscript under embargo until: 18th February 2026

Abstract

This article explores two novel approaches for controlling heat transfer systems through the development of “digital twins”, focusing on transient thermal systems. The study involves creating a digital representation of a physical system, specifically a 2D square subjected to an inward and transient...

Full description

Published in: Computational Thermal Sciences: An International Journal
ISSN: 1940-2503
Published: Begell House 2025
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa68929
Abstract: This article explores two novel approaches for controlling heat transfer systems through the development of “digital twins”, focusing on transient thermal systems. The study involves creating a digital representation of a physical system, specifically a 2D square subjected to an inward and transient heat flux, with the goal of keeping the maximum temperature within a predefined limit by changing the convective cooling. The first method utilizes a neural network trained on steady-state data, whereas the second employs an interactive learning algorithm. Results show that both strategies prove to be effective in managing the system's thermal performance. However, the RL-based approach demonstrates greater flexibility in adapting to new scenarios, albeit at the cost of increased computational demands due to the necessity of integrating interactive learning with unsteady Finite Element Method (FEM) simulations for training, validation, and testing phases.
Keywords: digital twin, heat transfer, interactive AI, deep learning, machine learning, FEM simulation
College: Faculty of Science and Engineering
Issue: 3
Start Page: 39
End Page: 46