Data-driven surrogate modeling for thermo-active road design
Author(s)
Ghalandari, Taher
Vuye, Cedric
Taborda, David
Type
Conference Paper
Abstract
The traditional iterative design process for engineering problems involves evaluating the performance of initial solutions based on prior experience and expertise, comparing them against specified project criteria, and refining design variables to achieve the desired system performance. This cycle continues until a satisfactory solution is reached. However, for more complex problems, the computational demands of simulation modelling can become prohibitively high, especially in design optimization tasks. Surrogate models are machine learning-based representations of complex physics-driven simulations, enabling significantly faster computations. They provide a rapid and accurate means to evaluate responses across multiple design scenarios, making them invaluable for efficient design exploration and optimization. This paper investigates the application of surrogate modelling for the design and thermal performance assessment of thermo-active roads, with a particular focus on systems that integrate a heat exchange layer with embedded pipes in the asphalt pavement, known as Pavement Solar Collectors (PSCs). The surrogate model developed in this study is based on an artificial neural network (ANN) trained on a comprehensive database generated from finite element simulations. These simulations account for variations in geometric configurations and thermophysical properties of materials. The ANN model is designed to predict the outlet water temperature of PSC systems, which is then used to calculate their heat harvesting capacity. Following hyperparameter optimization to enhance the performance of the surrogate model, the proposed framework demonstrated its effectiveness in optimizing the design of a PSC system in a case study. This highlights the model's potential to simplify and improve the efficiency of the design process for thermo-active road systems.
Date Issued
2026-06-14
Date Acceptance
2026-06-14
Citation
Proceedings of the 21st ICSMGE, 2026, pp.2077-2080
ISBN
978-3-9503898-4-5
Publisher
ÖGG, Austrian Society for Geomechanics
Start Page
2077
End Page
2080
Journal / Book Title
Proceedings of the 21st ICSMGE
Copyright Statement
© 2026 The Author(s).
Source
Proceedings of the 21st ICSMGE
Publication Status
Published
Start Date
2026-06-14
Finish Date
2026-06-19
Coverage Spatial
Vienna, Austria