Effective Thermal Conductivity Of Soil Research Articles

Effective thermal conductivity of granular soils: a review of influencing factors and prediction models towards an investigation framework through multiscale characters

The effective thermal conductivity of soil is important to geo-engineering applications, and it is controlled by factors across different length scales. Through a comprehensive review of these factors, we found that while other more traditional factors have been well studied, there is still a lack of characterisation of soil microscale and mesoscale structures and their influence on effective thermal conductivity. In addition, after reviewing the models available in the literature for soil effective thermal conductivity prediction, it was found that compared with empirical and theoretical models, machine learning models can account for the influence of multi-scale factors, however, research into them is scarce. To overcome the limitations of previous research, we proposed a framework that can investigate the factors influencing soil effective thermal conductivity at multiple scale. It includes the impact of soil structural factors at micro to mesoscale, and this impact is integrated with the influence from other factors for accurate thermal conductivity prediction.

Influence of moisture on heat transfer of ground heat exchangers in unsaturated soils

The applications of ground heat exchangers (GHEs) in arid and semi-arid zones require knowledge about the effects of moisture on heat transfer in the ground. To evaluate the influence of moisture, this study integrates a finite line-source model, a normalized thermal conductivity model, and a saturation degree model. A normalized temperature difference, defined as a temperature-difference ratio (TDR) of unsaturated to saturated soils, is proposed to characterize the reduction in heat transfer of GHEs in unsaturated soils. The modeling results show that the effective thermal conductivity of soils increases with saturation degree in a nonlinear way, thus leading to the nonlinear effect of moisture on heat conduction of GHEs: the influence of moisture on heat transfer is more significant in low-moisture soils (Sl < 0.5) than that in high-moisture soils (Sl > 0.5). This result implies that the design length of borehole GHEs is highly sensitive to the degree of saturation in low-moisture soils.

Estimation of thermal conductivity of cemented sands using thermal network models

Effective thermal conductivity of soils can be enhanced to achieve higher efficiencies in the operation of shallow geothermal systems. Soil cementation is a ground improvement technique that can increase the interparticle contact area, leading to a high effective thermal conductivity. However, cementation may occur at different locations in the soil matrix, i.e. interparticle contacts, evenly or unevenly around particles, in the pore space or a combination of these. The topology of cementation at the particle scale and its influence on soil response have not been studied in detail to date. Additionally, soils are made of particles with different shapes, but the impact of particle shape on the cementation and the resulting change of effective thermal conductivity require further research. In this work, three kinds of sands with different particle shapes were selected and cementation was formed either evenly around the particles, or along the direction parallel or perpendicular to that of heat transfer. The effective thermal conductivity of each sample was computed using a thermal conductance network model. Results show that dry sand with more irregular particle shape and cemented along the heat transfer direction will lead to a more efficient thermal enhancement of the soil, i.e. a comparatively higher soil effective thermal conductivity.

Predicting the effective thermal conductivity of unfrozen soils with various water contents based on artificial neural network

The effective thermal conductivity of soils is a crucial parameter for many applications such as geothermal engineering, environmental science, and agriculture and engineering. However, it is pretty challenging to accurately determine it due to soils’ complex structure and components. In the present study, the influences of different parameters, including silt content (m si), sand content (m sa), clay content (m cl), quartz content (m qu), porosity, and water content on the effective thermal conductivity of soils, were firstly analyzed by the Pearson correlation coefficient. Then different artificial neural network (ANN) models were developed based on the 465 groups of thermal conductivity of unfrozen soils collected from the literature to predict the effective thermal conductivity of soils. Results reveal that the parameters of m si, m sa, m cl, and m qu have a relatively slight influence on the effective thermal conductivity of soils compared to the water content and porosity. Although the ANN model with six parameters has the highest accuracy, the ANN model with two input parameters (porosity and water content) could predict the effective thermal conductivity well with acceptable accuracy and R 2 = 0.940. Finally, a correlation of the effective thermal conductivity for different soils was proposed based on the large number of results predicted by the two input parameters ANN-based model. This correlation has proved to have a higher accuracy without assumptions and uncertain parameters when compared to several commonly used existing models.

A generalized model for effective thermal conductivity of soils considering porosity and mineral composition

A generalized model for effective thermal conductivity of soils considering porosity and mineral composition

Unsaturated cell model of effective thermal conductivity of soils

In this study, a cell model based on new physical conceptualizations is developed to calculate the effective thermal conductivity of unsaturated soils. The evolution of water phase saturation is treated using a cell model consisting of solid particle being enveloped by a mixture of water and air phases. The thermal conductivity of the mixed fluid phase is determined by the volume-weighted average of water and air thermal conductivities. The temperature distribution in the cell of soil and fluid mixture is solved along with boundary condition of linearly varying temperature field. The heat transfer through the cell is calculated by integration of the temperature gradient along with thermal conductivities of soil and fluid. The effective thermal conductivity of the unsaturated soils is determined by conceptualizing the soils as having the same heat transfer as the cell of solid particle and fluid mixture. The new model is compared with 268 data entries of unsaturated soil effective thermal conductivity measurements from the literature. The developed effective thermal conductivity model compares favorably with the experimental data. When the porosity is small, the increase in the effective thermal conductivity with water phase saturation is more significant and non-linear. When the porosity increases, the increases of effective thermal conductivity with water phase saturation approaches a linear relationship.

Serial Laboratory Effective Thermal Conductivity Measurements of Cohesive and Non-cohesive Soils for the Purpose of Shallow Geothermal Potential Mapping and Databases—Methodology and Testing Procedure Recommendations

The article presents the methodology of conducting serial laboratory measurements of thermal conductivity of recompacted samples of cohesive and non-cohesive soils. The presented research procedure has been developed for the purpose of supplementing the Engineering–Geology Database and its part–Physical and Mechanical Properties of Soils and Rocks (abbr. BDGI-WFM) with a new component regarding thermal properties of soils. The data contained in BDGI-WFM are the basis for the development of maps and plans for the assessment of geothermal potential and support for the sustainable development of low enthalpy geothermal energy. Effective thermal conductivity of soils was studied at various levels of water saturation and various degrees of compaction. Cohesive soils were tested in initial moisture content and after drying to a constant mass. Non-cohesive soils were tested in initial moisture, fully saturated with water and after drying to a constant mass. Effective thermal conductivity of non-cohesive soils was determined on samples mechanically compacted to the literature values of bulk density. Basic physical parameters were determined for each of the samples. In total, 120 measurements of thermal conductivity were carried out, for the purposes of developing the guidelines which allowed statistical analysis of the results. The results were cross-checked with different measuring equipment and with the literature data.

Meso-scale investigations on the effective thermal conductivity of multi-phase materials using the finite element method

Many materials (e.g. soil) are multi-phase composites in engineering, and the thermal conductivity of mixtures is a critical parameter for analyzing the temperature field. Owing to its heterogeneity, the effective thermal conductivity of multi-phase materials is also not deterministic. The prediction of the thermal properties of a multi-phase material remains a challenging task. In this study, soil is considered to be a typical multi-phase material. A numerical simulation model is established by the finite element method to predict the meso-scale effective thermal conductivity of soil. Monte Carlo simulation is employed to account for the random distribution of voids. Comparisons among numerical, experimental and empirical results suggest that the proposed model can predict reasonably accurate results. In addition, the effective thermal conductivity of unfrozen soil, partially frozen soil and fully frozen soil is calculated. The effects of soil type, porosity and saturation degree on effective thermal conductivity are considered via parametric studies. The proposed numerical method can be used as an effective supplement to empirical model and experimental tests for evaluating the thermal conductivity of multi-phase materials.

Estimation of fast groundwater flow velocity from thermal response test results

This study proposes a practical approach for the simultaneous determination of both the groundwater velocity and the effective thermal conductivity of the soil by using the moving line source theory. It is especially the process for verifying that the theory can be applied to the area where the groundwater velocity exceeds 100 m/y. Thermal response test (TRT) is carried out in Kazuno City, Japan having alluvial gravel deposits of 100 m in its depth. A borehole thermal resistance is calculated by a numerical simulation considering the effect of the groundwater velocity under the condition in which an inside borehole was filled with the porous material having a high permeability. A radius of an equivalent single pipe instead of the borehole radius is applied to the calculation model to calculate the circulating fluid temperature. The method can calculate the temperature variations of the equivalent pipe wall, reflecting a grout thermal resistance affected by the groundwater velocity. The groundwater velocity and the effective thermal conductivity of the soil are determined by using root mean square error between the calculated results and the TRT data. As a result, the groundwater velocity and the effective thermal conductivity of soil calculated by the moving line source theory were 120 m/y and 4.7 W/(m K), respectively.

Experimental and Modeling Study of Forest Fire Effect on Soil Thermal Conductivity

An understanding of soil thermal conductivity after a wildfire or controlled burn is important to land management and post-fire recovery efforts. Although soil thermal conductivity has been well studied for non-fire heated soils, comprehensive data that evaluate the long-term effect of extreme heating from a fire on the soil thermal conductivity are limited. The purpose of this study was to evaluate the long-term impact of fire on the effective thermal conductivity of soils by directly comparing fire-heated and no-fire control soils through a series of laboratory studies. The thermal conductivity was measured for ten soil samples from two sites within the Manitou Experimental Forest, Colorado, USA, for a range of water contents from saturation to the residual degree of saturation. The thermal conductivity measured was compared with independent estimates made using three empirical models from literature, including the Campbell et al. (1994), Côté and Konrad (2005), and Massman et al. (2008) models. Results demonstrate that for the test soils studied, the thermal conductivity of the fire-heated soils was slightly lower than that of the control soils for all observed water contents. Modeling results show that the Campbell et al. (1994) model gave the best agreement over the full range of water contents when proper fitting parameters were employed. Further studies are needed to evaluate the significance of including the influence of fire burn on the thermal properties of soils in modeling studies.

Simulating the thermal operating conditions in the thermal wells of ground-source heat-pump heat supply systems. Part II: Consideration of porous moisture phase transitions in soil

The mathematical model describing unsteady thermal operating conditions of ground-source heat-pump (GSHP) heat supply systems that takes into account porous moisture condensation/evaporation processes and that is laid down in the basis of the corresponding block of the INSOLAR.GSHP.12 software system is considered. The results of numerical and laboratory experiments confirming that the GSHP performance efficiency depends essentially on the phase transition processes of moisture contained in the soil strata porous space are presented. The problem of correctly taking into account the heat of porous moisture condensation/evaporation phenomena in simulating the thermal processes occurring in the soil strata surrounding GSHP thermal wells is considered. A mathematical description of porous moisture condensation/evaporation processes for a vertical thermal well in the cylindrical coordinate system is given. A numerical experiment on estimating the effect the porous moisture condensation/evaporation processes have on the soil thermal conditions was carried out after the mathematical model had been implemented in a software block. The presented results obtained from the performed numerical experiment show that the temperature levels of soil adjacent to the thermal well determined with and without taking the heat of porous moisture condensation processes may differ from each other by more than 3°C. The results from experimentally approbating the application of a so-called effective soil thermal conductivity coefficient that takes into account the latent heat of porous moisture phase transitions in soil in modeling the GSHP thermal operating conditions are presented. The results of the performed experiments show that porous moisture phase transitions may have a very significant influence on the effective thermal conductivity of soil. The effective thermal conductivity values of soil may differ from each other by several times depending on the soil system operating conditions.

Simulating the thermal operating conditions in the thermal wells of ground-source heat-pump heat supply systems. Part I: Porous moisture freezing processes in soil

The mathematical models laid down in the new blocks of the INSOLAR.GSHP.12 software system simulating unsteady operating conditions of ground-source heat-pump (GSHP) heat supply systems are presented. The new model blocks take into account the effect the freezing of porous moisture in soil has on the GSHP system performance efficiency. Illustration is given to the need of taking into account the porous moisture freezing/thawing processes in soil, and the results from investigations devoted to the opening possibilities of constructing adaptive GSHP systems with controlled intensity of heat transfer in the soil-thermal well system are presented. The development of software simulating the porous moisture phase state variation processes in soil was preceded by development of mathematical equations representing the thermal conditions of soil body involving porous moisture freezing/thawing processes. A description of these equations is also given in the article. In constructing the mathematical model, the notion “effective thermal conductivity” of soil was introduced for taking into account the latent heat of phase transition that releases during the freezing of moisture. The above-mentioned effective thermal conductivity of soil involves two components: the soil thermal conductivity coefficient itself and an additional term modifying the thermal conductivity value for taking into account the influence of phase transition. For quantitatively evaluating the soil effective thermal conductivity component that takes into account the influence of phase transition, the soil freezing zone radius around the thermal well was determined. The obtained analytic solutions have been implemented in the form of computer program blocks, after which a “numerical experiment” was carried out for estimating the effect the porous moisture freezing/thawing processes have on the soil thermal conditions. It was demonstrated during that experiment that the soil thermal conductivities determined without taking the porous moisture freezing/thawing phase transitions can differ from those determined with taking these transitions into account by a factor of 2 or more. A conclusion has been drawn from these findings about the importance of taking the phase transition phenomena into account in modeling the parameters of thermal wells and of the GSHP system as a whole.

New model to evaluate the effective thermal conductivity of three-phase soils

The aim of the present paper is to present a new model without empirical constants to evaluate the effective thermal conductivity of three-phase soils. In the model the soil is made of a quasi-spherical solid grain, and is surrounded by two phases, which can be air and water or air and ice. The effective thermal conductivity is obtained theoretically by the integration of the steady-state heat conduction equation under the thermal assumption of parallel heat fluxes. This new model allows to evaluate the effective thermal conductivity of soils with porosity (ratio between the volume of the voids and the total one) in the range between 0.0349 and 0.4734 at all degrees of saturation (ratio between the water volume and the void one) from dryness up to saturation. Comparisons with experimental data of unfrozen and frozen soils confirm that the model can predict the effective thermal conductivity with a fairly good agreement without using any empirical constant.

Heat conduction and heat storage characteristics of soils

Based on a randomly mixed model, in which the constituent parts of the multi-phase medium are all cubic in shape, uniform in size and randomly dispersed, the effective thermal conductivity of the medium is obtained from the thermal properties and volume fractions of the components. Compared with the experimental data, the present model can give fine predictions of the effective thermal conductivity of soils. Factors related to the thermal conductivity and heat storage coefficient of the soil are investigated, and the results show that the effective thermal properties of the soil dependent on the type of soil, the porosity, the degree of saturation and the state of the water. In addition, the difference of the thermal characteristics between the frozen and unfrozen soils is discussed.

Inter-particle contact heat transfer model: an extension to soils at elevated temperatures

A simple ‘inter-particle contact heat transfer’ model for predicting effective thermal conductivity of soils at moderate temperatures (0–30°C) has been extended up to 90°C. The extended model accounts for latent heat transport by water vapour diffusion in soil air above the permanent wilting point; below that point, the soil thermal conductivity is approximated by linear interpolation without latent heat effect. By and large the best results are obtained when the latent heat is used only in the ‘self consistent approximation’ model with an overall root mean square error of 35% for all soils under consideration or 26% when excluding volcanic soils. This option can also be applied to moderate temperatures at which the enhanced heat transfer is negligibly small. Copyright © 2005 John Wiley & Sons, Ltd.