1. ABOUT THE DATASET -------------------- Title: Data on coupled hydrothermal flow in fine sands based on X-ray CT imaging and numerical simulation Creator(s): Kui Lui [1], Fleur Loveridge [2], Richard Boardman [3], William Powrie [3] Organisation(s): [1] Institut de Radioprotection et de Sûreté Nucléaire (IRSN), formerly University of Southampton; [2] University of Leeds; [3] University of Southampton Publication Year: 2022 Description: Coupled hydrothermal flow can occur in soils, for example in applications such as ground heat storage and nuclear waste disposal. Therefore, approaches to quantitative analysis of water transfer in response to imposed thermal gradients are required, especially in unsaturated conditions. Analysis methods also require validation by laboratory and field data, which can be hard to obtain. This dataset includes the processed results from X-ray µCT experiments where specimens of a fine sand and a fine silty sand were subjected to heating from their base. Repeated scans, set up to balance image quality and scan duration, were carried out during the heating process, on specimens between 20% and 50% saturation. Gaussian decomposition techniques were used to determine the changing soil phase proportions throughout the experiments, which are reported here. The CT data is accompanied by COMSOL files for simulation of the experiments on the fine sand. The dataset is to accompany the paper at https://doi.org/10.1016/j.gete.2022.100380 and provides the processed information used to construct the key results figures in that paper. Cite as: Kui Lui, Fleur Loveridge, Richard Boardman, William Powrie (2022): Data on coupled hydrothermal flow in fine sands based on X-ray CT imaging and numerical simulation. [Dataset]. https://doi.org/10.5518/1200 Related publication: Kui Lui, Fleur Loveridge, Richard Boardman, William Powrie (2022) Effect of soil saturation and grain size on coupled hydrothermal flow in fine sands based on X-ray CT imaging, Geomechanics for Energy and the Environment, 100380, https://doi.org/10.1016/j.gete.2022.100380 Contact: Kui Liu (kl5g14@southamptonalumni.ac.uk) ORCID ID: 0000-0002-7533-1272 2. TERMS OF USE --------------- This dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/. 3. PROJECT AND FUNDING INFORMATION ---------------------------------- The work reported in this dataset forms a part of a project funded by the Royal Academy of Engineering, the Doctoral Training Centre at University of Southampton and EPSRC (EP/G036896/1). 4. CONTENTS ----------- Saturation_and_Grey_value.xls: This file provides the processed grey value data with time for the specimens, the derived change in overall degree of saturation with time, the change in saturation with depth with time. Key: LBe - Leighton Buzzard Sand fraction E; HIQ5 - Silty Sand; S20 - initial saturation of 20%; S30 - initial saturation of 30%; S40 - initial saturation of 40%; S50 - initial saturation of 50% Corresponding figures: 8, 9 & 10 missing_moisture.xls: water balanace calculations and data to construct figure 12 outflow_BC.xls: the values used in the outflow boundary condition, U(t), of the COMSOL simulation Corresponding figure: 6 relative_permeabilty.xls: Output from the COMSOL simulation. Data for the evolution of estimated relative gas (Krg) and liquid (Krw) permeabilities over time for different initial degrees of saturation Corresponding figure: 14 TC_of_silt_and_clay.xls: Data for the relationship between thermal conductivity and degree of soil saturation in various soils (sand, silt sand clay), after Dong Y., McCartney J.S., Lu N. Critical review of thermal conductivity models for unsaturated soils Geotech Geol Eng, 33 (2) (2015), pp. 207-221 *.mph files are the COMSOL model files for the different degrees of initial saturation, for the simulation of the fine sand experiments S20: initial saturation of 20% S30: initial saturation of 30% S40: initial saturation of 40% S50: initial saturation of 50% 5. METHODS ---------- Full methods for generation of the data are given in the related publication: Lui et al (2020) https://doi.org/10.1016/j.gete.2022.100380