Research Data Leeds Repository

Data for - Conduction shape factors for thermal analysis of energy walls under varying boundary conditions

Citation

Gupta, Aakash, Loveridge, Fleur, Shafagh, Ida and Rees, Simon (2025) Data for - Conduction shape factors for thermal analysis of energy walls under varying boundary conditions. University of Leeds. [Dataset] https://doi.org/10.5518/1782

Dataset description

Energy walls are retaining walls embedded with heat exchanger pipes. Effective design requires fast, reliable thermal performance models. Analytical shape factors provide computationally efficient methods for predicting steady-state heat transfer rates; they relate temperature differences across surfaces to resulting heat flux. While shape factor equations have been successfully applied to energy piles and borehole heat exchangers, their systematic validation for energy walls under varying thermal boundary conditions remains unexplored. This study extends shape factor equations which were originally developed for pipeline applications and adapted via electrical analogies, to energy wall thermal analysis. The key innovation lies in systematic parametric validation across realistic geometric variations (pipe spacing, diameter, wall thickness, cover depth) and thermal conductivity ratios for practical design applications. Shape factor predictions are benchmarked against steady-state and transient numerical models. The findings demonstrate that existing shape factor equations can be successfully extended to model energy walls and similar planar energy geostructures, providing practitioners with a computationally efficient design tool validated across realistic parameter ranges. This data set presented here share the data sheets used to develop the connected paper.

Keywords:

Conduction Shape Factor, Thermal Resistance, Energy Walls, Thermal Analysis

Subjects:

H000 - Engineering > H200 - Civil engineering

Divisions:

Faculty of Engineering and Physical Sciences > School of Civil Engineering

License:

Creative Commons Attribution 4.0 International (CC BY 4.0)

Date deposited:

12 Dec 2025 16:23

URI:

https://archive.researchdata.leeds.ac.uk/id/eprint/1504

Additional details

Creators or authors:

Creators	ORCID	Primary affiliation	Primary affiliation ID	Primary affiliation ID type
Gupta, Aakash	https://orcid.org/0000-0003-1735-8706	University of Leeds	https://ror.org/024mrxd33	ror
Loveridge, Fleur	https://orcid.org/0000-0002-6688-6305	University of Leeds	https://ror.org/024mrxd33	ror
Shafagh, Ida	https://orcid.org/0000-0002-3171-4511	University of Leeds	https://ror.org/024mrxd33	ror
Rees, Simon	https://orcid.org/0000-0003-4869-1632	University of Leeds	https://ror.org/024mrxd33	ror