Experimental and numerical data of thermal response tests executed in groups of energy piles connected in series.

The use of energy piles as heat exchangers for Ground Source Heat Pump (GSHP) systems, providing heating and cooling, is a well researched application worldwide [1]. However, a broader implementation in practice still faces resistance, mainly because of the lack of accessible, easy to implement design methods and uncertainty regarding the thermo-mechanical effects. These issues need to be addressed to close the gap between research and practice. This work presents data of a full-scale thermal response test (TRT) undertaken in a group of eight energy screw piles connected in series, that are part of an operational GSHP system of a building located in Melbourne, Australia. The temperature was measured in the inlet and outlet of the pipe circuit (circulating water temperature) and at the bottom of each pile (external pipe wall temperature). Besides providing insights regarding the thermal performance of short energy pile groups, the test was used to validate a finite element numerical model (FEM). The model was then used to expand the database of thermal performance of energy pile groups by simulating several long thermal response tests, considering different energy pile group geometries, configurations and material properties. The experimental data presented can be used for analyses and validation of thermal modelling methodologies that consider the group effect of energy piles, given the lack of TRTs performed in groups of energy piles reported in literature. Moreover, the extensive set of simulated data can be analysed to understand the thermal behaviour of energy pile groups and evaluate how alternative simpler heat transfer models, feasibly applied in industry practice, perform in a range of scenarios that could be encountered in daily practice.

X-ray computed tomography images and network data of sands under compression.

Ottawa sand and Angular sand consist of particles with distinct shapes. The x-ray computed tomography (XCT) image stacks of their in-situ confined compressive testings are provided in this paper. For each image stack, a contact network, a thermal network and a network feature - edge betweenness centrality - of each edge in the networks are also provided. The readers can use the image data to construct digital sands with applications of (1) extracting microstructural parameters such as particle size, particle shape, coordination number and more network features; (2) analysing mechanical behaviour and transport processes such as fluid flow, heat transfer and electrical conduction using either traditional simulation tools such as finite element method and discrete element method or newly network models which could be built based on the network files available here.

Impacts of underground climate change on urban geothermal potential: Lessons learnt from a case study in London.

While urban underground is being increasingly used for various purposes, two concerns should be addressed with respect to the urban underground climate change: i) how much energy has been stored in urban subsurface due to the heat rejection from underground heated spaces (such as tunnels and basements) and ii) how much of the thermal demand of a city or district can be supplied by harvesting this accumulative thermal energy in the ground. However, our understanding of the temperature rise in the ground and of the geothermal potential of urban subsurface is still limited. This paper quantifies the geothermal potential for a 12 km2 densely populated borough in central London by considering the spatio-temporal temperature variation in the ground owing to continuous rejection of heat into the ground, coupled with the effect of geothermal extraction capacity. A large-scale transient semi-3D geothermal subsurface model of the site is developed, and the thermal interaction between underground heated spaces, geothermal energy extraction systems and the ground and groundwater are simulated. The concurrent heat rejection and extraction processes in the subsurface are computed so that the most influencing parameters of the subsurface on its geothermal potential are identified. Results show that up to 50% of the borough's total heat demand can be supplied via geothermal installations leading to around 33% reduction in CO2 emission. The geothermal extraction efficiency in sand and gravel primarily depends on the ground conditions such as the thickness of the permeable layer and the groundwater flow regime. In impermeable ground such as clay, however, the underground built environment such as heated spaces have shown to have a significant impact on improving the geothermal extraction efficiency.

Preferential flow pathways in a deforming granular material: self-organization into functional groups for optimized global transport.

Existing definitions of where and why preferential flow in porous media occurs, or will occur, assume a priori knowledge of the fluid flow and do not fully account for the connectivity of available flow paths in the system. Here we propose a method for identifying preferential pathways through a flow network, given its topology and finite link capacities. Using data from a deforming granular medium, we show that the preferential pathways form a set of percolating pathways that is optimized for global transport of interstitial pore fluid in alignment with the applied pressure gradient. Two functional subgroups emerge. The primary subgroup comprises the main arterial paths that transmit the greatest flow through shortest possible routes. The secondary subgroup comprises inter- and intra-connecting bridges that connect the primary paths, provide alternative flow routes, and distribute flow through the system to maximize throughput. We examine the multiscale relationship between functionality and subgroup structure as the sample dilates in the lead up to the failure regime where the global volume then remains constant. Preferential flow pathways chain together large, well-connected pores, reminiscent of force chain structures that transmit the majority of the load in the solid grain phase.

A Laboratory Study on Non-Invasive Soil Water Content Estimation Using Capacitive Based Sensors.

Soil water content is an important parameter in many engineering, agricultural and environmental applications. In practice, there exists a need to measure this parameter rather frequently in both time and space. However, common measurement techniques are typically invasive, time-consuming and labour-intensive, or rely on potentially risky (although highly regulated) nuclear-based methods, making frequent measurements of soil water content impractical. Here we investigate in the laboratory the effectiveness of four new low-cost non-invasive sensors to estimate the soil water content of a range of soil types. While the results of each of the four sensors are promising, one of the sensors, herein called the "AOGAN" sensor, exhibits superior performance, as it was designed based on combining the best geometrical and electronic features of the other three sensors. The performance of the sensors is, however, influenced by the quality of the sensor-soil coupling and the soil surface roughness. Accuracy was found to be within 5% of volumetric water content, considered sufficient to enable higher spatiotemporal resolution contrast for mapping of soil water content.

Carrier fluid temperature data in vertical ground heat exchangers with a varying pipe separation.

The dataset in this article is related to shallow geothermal energy systems, which efficiently provide renewable heating and cooling to buildings, and specifically to the performance of the vertical ground heat exchangers (GHE) embedded in the ground. GHEs incorporate pipes with a circulating (carrier) fluid, exchanging heat between the ground and the building. The data show the average and inlet temperatures of the carrier fluid circulating in the pipes embedded in the GHEs (which directly relate to the performance of these systems). These temperatures were generated using detailed finite element modelling and comprise part of the daily output of various one-year simulations, accounting for numerous design parameters (including different pipe geometries) and ground conditions. An expanded explanation of the data as well as comprehensive analyses on how they were used can be found in the article titled "Ground-source heat pump systems: the effect of variable pipe separation in ground heat exchangers" (Makasis N, Narsilio GA, Bidarmaghz A, Johnston IW, 2018) [1].

Cost and performance data for residential buildings fitted with GSHP systems in Melbourne Australia.

The data reported in this article presents actual installation costs and performance data for a selection of residential Ground Source Heat Pump (GSHP) systems in Melbourne, Australia. The installation cost data includes five main cost components: ground loop installation, head pipe installation, heat pump, mechanical room installation, and fittings. The performance data presented here includes timestamp, air temperature and thermal loading. A more comprehensive analysis of this data may be obtained from the article entitled "Economic analysis of vertical ground source heat pump systems in Melbourne" (Q. Lu, G.A. Narsilio, G.R. Aditya, I.W. Johnston, 2017) [1].

Machine learning framework for analysis of transport through complex networks in porous, granular media: A focus on permeability.

We present a data-driven framework to study the relationship between fluid flow at the macroscale and the internal pore structure, across the micro- and mesoscales, in porous, granular media. Sphere packings with varying particle size distribution and confining pressure are generated using the discrete element method. For each sample, a finite element analysis of the fluid flow is performed to compute the permeability. We construct a pore network and a particle contact network to quantify the connectivity of the pores and particles across the mesoscopic spatial scales. Machine learning techniques for feature selection are employed to identify sets of microstructural properties and multiscale complex network features that optimally characterize permeability. We find a linear correlation (in log-log scale) between permeability and the average closeness centrality of the weighted pore network. With the pore network links weighted by the local conductance, the average closeness centrality represents a multiscale measure of efficiency of flow through the pore network in terms of the mean geodesic distance (or shortest path) between all pore bodies in the pore network. Specifically, this study objectively quantifies a hypothesized link between high permeability and efficient shortest paths that thread through relatively large pore bodies connected to each other by high conductance pore throats, embodying connectivity and pore structure.

Estimating vertical and lateral pressures in periodically structured montmorillonite clay particles.

Given a montmorillonitic clay soil at high porosity and saturated by monovalent counterions, we investigate the particle level responses of the clay to different external loadings. As analytical solutions are not possible for complex arrangements of particles, we employ computational micromechanical models (based on the solution of the Poisson-Nernst-Planck equations) using the finite element method, to estimate counterion and electrical potential distributions for particles at various angles and distances from one another. We then calculate the disjoining pressures using the Van't Hoff relation and Maxwell stress tensor. As the distance between the clay particles decreases and double-layers overlap, the concentration of counterions in the micropores among clay particles increases. This increase lowers the chemical potential of the pore fluid and creates a chemical potential gradient in the solvent that generates the socalled 'disjoining' or 'osmotic' pressure. Because of this disjoining pressure, particles do not need to contact one another in order to carry an 'effective stress'. This work may lead towards theoretical predictions of the macroscopic load deformation response of montmorillonitic soils based on micromechanical modelling of particles.

Estimating vertical and lateral pressures in periodically structured montmorillonite clay particles

Given a montmorillonitic clay soil at high porosity and saturated by monovalent counterions, we investigate the particle level responses of the clay to different external loadings. As analytical solutions are not possible for complex arrangements of particles, we employ computational micromechanical models (based on the solution of the Poisson-Nernst-Planck equations) using the finite element method, to estimate counterion and electrical potential distributions for particles at various angles and distances from one another. We then calculate the disjoining pressures using the Van't Hoff relation and Maxwell stress tensor. As the distance between the clay particles decreases and double-layers overlap, the concentration of counterions in the micropores among clay particles increases. This increase lowers the chemical potential of the pore fluid and creates a chemical potential gradient in the solvent that generates the socalled 'disjoining' or 'osmotic' pressure. Because of this disjoining pressure, particles do not need to contact one another in order to carry an 'effective stress'. This work may lead towards theoretical predictions of the macroscopic load deformation response of montmorillonitic soils based on micromechanical modelling of particles.

Dada uma argila montmorilonítica de alta porosidade e saturada por counteríons monovalentes, investigamos as respostas da argila ao nível de partículas para diferentes cargas externas. Como soluções analíticas não são possíveis para arranjos complexos de partículas, empregamos modelos computacionais micro-mecânicos (baseados na solução das equações de Poisson-Nernst-Planck), utilizando o método de elementos finitos, para estimar counteríons e distribuições de potencial elétrico para partículas em diversos ângulos e distâncias uma da outra. Nós então calculamos as pressões de separação usando a relação de Van't Hoff e a tensão de cisalhamento de Maxwell. À medida que a distância entre as partículas de argila diminui e as duplas camadas se sobrepõem, a concentração de counteríons nos microporos entre as partículas de argila aumenta. Este aumento reduz o potencial químico do fluido nos poros e cria um gradiente de potencial químico no solvente, que gera a chamado pressão 'osmótica' ou de 'separação'. Devido a esta pressão de separação, as partículas não precisam de contato entre si, a fim de exercer uma 'tensão efetiva'. Este trabalho pode conduzir a previsões teóricas da resposta macroscópica a carga de deformação em solos montmoriloníticos baseado na modelação micromecânica das partículas.