Machine learning-based prediction of the thermal conductivity of filling material incorporating steelmaking slag in a ground heat exchanger system

Machine learning-based prediction of the thermal conductivity of filling material incorporating steelmaking slag in a ground heat exchanger system

Abstract This study used machine learning models to predict the thermal conductivity of heat-transfer materials based on steelmaking slag. A dataset containing various physical parameters of the heat-transfer materials was obtained from previous research results and Pearson correlation analysis was...

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Bibliographic Details
Main Authors: Gyeong-o Kang, Young-sang Kim, Jung-goo Kang, Seongkyu Chang
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Thermal conductivity
Machine learning
Steelmaking slag
Heat-transfer medium
Ground heat exchanger
Online Access:https://doi.org/10.1038/s41598-025-89713-7
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https://doi.org/10.1038/s41598-025-89713-7

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