Effects of surface air temperature on thermal performance of vertical ground heat exchangers

Peer Reviewe

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]

Influence of geology and hydrogeology on heat rejection from residential basements in urban areas

Urbanization and limited land availability have resulted in the increased utilization of underground structures including residential basements in largely populated cities such as London, with an average addition of 200 basements per year in some boroughs. Residential basements kept at a comfortable temperature level throughout the year significantly contribute to heat fluxes in the subsurface as well as an increase in ground temperature. Understanding the ground thermal status is crucial in managing the significant geothermal energy potential in urban areas as well as the sustainable development of the urban underground, and in maintaining the energy efficiency of underground structures. In this proof-of-concept study, a 3D finite element approach accounting for coupled heat transfer and groundwater flow in the ground was used to investigate the influence of ground conditions on the heat rejection rate from basements. A detailed analysis was made of ground, above ground and underground built environment characteristics. This study demonstrates that the amount of heat from basements rejected to the ground constitutes a significant percentage of the total heat loss from buildings, particularly in the presence of groundwater flow. The extent of thermal disturbance in the ground varies depending on the ground characteristics. The volume of thermally disturbance ground inversely correlates with the groundwater flow rate in ground mainly consisting of highly permeable material. However, a direct correlation exists when the thickness of permeable soil layer decreases. A larger horizontal to vertical ratio of ground thermal disturbance is observed when the thickness of permeable soil layer increases

Large-scale urban underground hydro-thermal modelling - A case study of the Royal Borough of Kensington and Chelsea, London.

The shallow subsurface of dense cities is increasingly exploited for various purposes due to the significant rise in urban populations. Past research has shown that underground activities have a significant impact on local subsurface temperatures. However, the resulting spatial variability of ground temperature elevations on a city-scale is not well understood due to the lack of sufficient information and modelling complexity at such large scales. Resilient and sustainable planning of underground developments and geothermal exploitation in the short and long-term necessitate more detailed, more reliable knowledge of subsurface thermal status. This paper investigates the impact of some common underground heat sources such as train tunnels and residential basements on subsurface temperature elevation on a large scale and highlights the influence of local geology, hydrogeology, density, and type and arrangement of the heat sources on ground thermal disturbance. To tackle the size issues and computational expenses of such a large-scale problem, a semi-3D hydro-thermal numerical approach is presented to capture the combined influence of underground built environment characteristics coupled with ground properties on ground temperature elevation within the Royals Borough of Kensington and Chelsea (RBKC), London. Numerical results show that the extent of ground thermal disturbance is mostly affected by geological and hydrogeological characteristics in permeable ground (River Terrace Deposits). Density and spatial distribution of heat sources, however, are critical parameters in ground temperature evaluation in highly impermeable ground such as London Clay Formation. The locality of temperature rise and potential ground energy within immediate impermeable ground surrounding heat sources versus significantly large extent of ground thermal disturbance in permeable ground, highlights the significant dependency of ground thermal state and geothermal potential at the studied site to the ground and underground built environment characteristics and necessitates a better understanding of shallow subsurface thermal state for a sustainable and resilient urban underground development.This work was funded under the Global University Alliance (Cambridge Centre for Smart Infrastructure and Construction, University of California, Berkeley, and National University of Singapore) and in collaboration with the British Geological Survey (BGS) (EPSRC reference: EP/N021614/1)

Multi-fidelity approach to Bayesian parameter estimation in subsurface heat and fluid transport models

The increased use of the urban subsurface for competing purposes, such as anthropogenic infrastructures and geothermal energy applications, leads to an urgent need for large-scale sophisticated modelling approaches for coupled mass and heat transfer. However, such models are subject to large uncertainties in model parameters, the physical model itself and in available measured data, which is often rare. Thus, the robustness and reliability of the computer model and its outcomes largely depend on successful parameter estimation and model calibration, which are hampered by the computational burden of large-scale coupled models. To tackle this problem, we develop a novel Bayesian approach for parameter estimation, which allows us to account for different sources of uncertainty, is capable of dealing with sparse field data and makes optimal use of the output data from expensive numerical model runs. This is achieved by combining output data from different models that represent the same physical problem, but at different levels of fidelity, e.g. reflected by different spatial resolution. By applying this new approach to a 1D analytical heat transfer model and a large-scale semi-3D numerical model while using synthetic data, we show that the accuracy and precision of parameter estimation by this multi-fidelity framework by far exceeds the standard single-fidelity results. The consideration of different error terms in the Bayesian framework also allows assessment of the model bias and the discrepancy between the different fidelity levels. These are emulated by Gaussian Process models, which facilitate re-iteration of the parameter estimation without additional model runs

Bayesian parameter inference for shallow subsurface modeling using field data and impacts on geothermal planning

Understanding the subsurface is crucial in building a sustainable future, particularly for urban centers. Importantly, the thermal effects that anthropogenic infrastructure, such as buildings, tunnels, and ground heat exchangers, can have on this shared resource need to be well understood to avoid issues, such as overheating the ground, and to identify opportunities, such as extracting and utilizing excess heat. However, obtaining data for the subsurface can be costly, typically requiring the drilling of boreholes. Bayesian statistical methodologies can be used towards overcoming this, by inferring information about the ground by combining field data and numerical modeling, while quantifying associated uncertainties. This work utilizes data obtained in the city of Cardiff, UK, to evaluate the applicability of a Bayesian calibration (using GP surrogates) approach to measured data and associated challenges (previously not tested) and to obtain insights on the subsurface of the area. The importance of the data set size is analyzed, showing that more data are required in realistic (field data), compared to controlled conditions (numerically-generated data), highlighting the importance of identifying data points that contain the most information. Heterogeneity of the ground (i.e., input parameters), which can be particularly prominent in large-scale subsurface domains, is also investigated, showing that the calibration methodology can still yield reasonably accurate results under heterogeneous conditions. Finally, the impact of considering uncertainty in subsurface properties is demonstrated in an existing shallow geothermal system in the area, showing a higher than utilized ground capacity, and the potential for a larger scale system given sufficient demand

Bayesian parameter inference for shallow subsurface modeling using field data and impacts on geothermal planning

Understanding the subsurface is crucial in building a sustainable future, particularly for urban centers. Importantly, the thermal effects that anthropogenic infrastructure, such as buildings, tunnels, and ground heat exchangers, can have on this shared resource need to be well understood to avoid issues, such as overheating the ground, and to identify opportunities, such as extracting and utilizing excess heat. However, obtaining data for the subsurface can be costly, typically requiring the drilling of boreholes. Bayesian statistical methodologies can be used towards overcoming this, by inferring information about the ground by combining field data and numerical modeling, while quantifying associated uncertainties. This work utilizes data obtained in the city of Cardiff, UK, to evaluate the applicability of a Bayesian calibration (using GP surrogates) approach to measured data and associated challenges (previously not tested) and to obtain insights on the subsurface of the area. The importance of the data set size is analyzed, showing that more data are required in realistic (field data), compared to controlled conditions (numerically-generated data), highlighting the importance of identifying data points that contain the most information. Heterogeneity of the ground (i.e., input parameters), which can be particularly prominent in large-scale subsurface domains, is also investigated, showing that the calibration methodology can still yield reasonably accurate results under heterogeneous conditions. Finally, the impact of considering uncertainty in subsurface properties is demonstrated in an existing shallow geothermal system in the area, showing a higher than utilized ground capacity, and the potential for a larger scale system given sufficient demand

3D numerical modelling of vertical ground heat exchangers

© 2014 Dr. Asal BidarmaghzTo mitigate the impacts of climate change, the demand for renewable energy technologies with low greenhouse gas (GHG) emissions is rapidly becoming a global priority. Direct geothermal systems use shallow ground as a heat source and sink for heating and cooling buildings, using ground heat exchangers (GHEs) and ground source heat pumps (GSHPs). Substituting common heating and cooling systems with geothermal technologies can reduce energy consumption by up to 75% and thus greenhouse gas emissions, since 91% of electricity comes from fossil fuels in Australia. In GSHP systems, heat is exchanged between the ground (via the “primary circuit”) and buildings (secondary circuit) using a ground source heat pump. The ground heat exchangers (GHEs) are the major components of the primary circuit comprising pipes embedded into the ground. The focus of this research is on vertical closed-loop GHEs. In these ground loops, heat is transferred between the ground and the heat pump via the carrier fluid circulating in the pipes. The relatively high installation costs of GHEs make the GSHP systems struggle for a more widespread worldwide adaption of the technology. Therefore, a more accurate and powerful modelling tool is desirable to help design GHEs more efficiently (e.g., thermally and economically). Such models are developed in this work to accurately predict thermal performance of GHEs. There are several analytical solutions and numerical models available for simulating GHE thermal performance. However, most of their assumptions and the associated limitations may lead to an inaccurate prediction of GHE thermal performance under specific circumstances. The aim of this study is to develop a modelling tool to accurately simulate the complex heat transfer process in the ground and GHEs in short and long time scales. Based on first principles, the model helps to improve the understanding of heat transfer process in GHEs. Therefore, a more efficient system can be achieved in the design phase. Parametric analyses on different design factors are conducted under steady state and transient conditions to fulfil this purpose. In addition, to evaluate the transient thermal performance of GHEs in long term operations (e.g., 25 years), GHE and GHE-fields are simulated and temperature variations that occur in the ground, grout and the fluid are evaluated for different GHE lengths and configurations as well as for different climate conditions. The transient effect of different energy consumption patterns on GHE thermal performance is also investigated in this study and GHE thermal performance under intermittent and continuous operations are compared. The results show that GHE thermal performance can be significantly increased making these systems more economically justifiable. Numerical simulations show that to accurately evaluate thermal performance of GHEs in long-term operations (e.g., 25 years), the realistic axial-radial heat transfer should be accounted for in the models. Ignoring the axial heat transfer (especially from the ground surface) may lead to a conservative selection of GHE depth, geometry and configuration. It is also observed that GSHP systems with intermittent operation significantly increase the efficiency of the ground loop system

Endangering trust in health services: using ambulances to arrest protesters in Iran

[Extract] Since the beginning of the nationwide protests in Iran in September 2022, ambulances have been seriously misused for non-medical transports to suppress the recent protests in Iran such as detention and transfer of the protesters, and transfer of military forces. This can lead to a loss of public trust in the healthcare system in Iran. Using ambulances for non-medical purposes during armed conflict violates International Humanitarian Law (IHL), which seeks to protect healthcare professionals and infrastructures, ambulances, and injured people. While the situation of protest and civil uprisings in Iran is not considered an armed conflict, these protections should apply given the provisions of Human Rights Law (HRL) and customary International Human Rights Law (IHRL)