CMMI-EPSRC: Modeling and Monitoring of Urban Underground Climate Change
CMMI-EPSRC: Modeling and Monitoring of Urban Underground Climate Change
批准号:
EP/T019425/1
负责人:
Ruchi Choudhary
金额:
$53.54万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --
中文摘要
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英文摘要
OverviewIn dense urban areas, the underground is exploited for a variety of purposes, including transport, additional residential/commercial spaces, storage, and industrial processes. With the rise in urban populations and significant improvements in construction technologies, the number of subsurface structures is expected to grow in the next decade, leading to subsurface congestion. Recently emerging data indicate a significant impact of underground construction on subsurface temperature and there is extensive evidence of underground temperature rise at the local scale. Although it is well known that urbanization coupled with climate change is amplifying the urban heat island effect above ground, the extent of the underground climate change at the city scale is unknown because of (i) limited work on modeling the historical and future underground climate change at large scale and (ii) very limited long-term underground temperature monitoring. The hypothesis of this research is that (a) the high ground temperature around tunnels and underground basements, b) the observed temperature increase within the aquifer, and (c) inefficiency in ventilation of the underground railway networks, necessitate more detailed and reliable knowledge of urban underground thermal status. The project will develop a framework for monitoring and predicting temperature and groundwater distributions at high resolutions in the presence of underground heat sources and sinks. This can be achieved via a combination of numerical modelling, continuous temperature and groundwater monitoring and statistical analyses. The ultimate goal is for every city to generate reliable maps of underground climate, with the ability to understand the influence of future urbanization scenarios.MeritThe objective of this joint NSF-EPSRC research is to advance understanding of the impacts of the urban underground on subsurface temperature increase at the city-scale. A low cost and reliable underground weather station using the fiber optic sensing technologies will be developed and installed at sites in London and San Francisco. A high-performance computing based thermo-hydro coupled underground climate change code will be developed to simulate the temperature and groundwater variation with time at the whole city scale. The main scientific deliverable from the district- and city-scale numerical simulations and the experimental temperature monitoring is a series of archetype emulators, which are defined based on the geological characteristics, above ground built environment, such as surface and buildings types, and the density and type of the underground structures. These archetype emulators will allow efficient city-scale modelling and enable application of the methodology to any other city or region with similar characteristics of above and underground built environment. This new knowledge will make possible to consider precise thermal conditions around underground structures in urban areas as well as facilitate efficient utilization of geothermal resources for both heating and cooling purposes.
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DOI:
10.1051/e3sconf/202020507002
发表时间:
2020
期刊:
E3S Web of Conferences
影响因子:
--
作者:
[Kreitmair M]
通讯作者:
Kreitmair M
Demonstration of a city-scale geothermal resource assessment using a statistical archetypes-based approach
使用基于统计原型的方法演示城市规模的地热资源评估
DOI:
10.5194/egusphere-egu24-16846
发表时间:
2024
期刊:
影响因子:
--
作者:
[Kreitmair M]
通讯作者:
Kreitmair M
Large-scale urban underground hydro-thermal modelling - A case study of the Royal Borough of Kensington and Chelsea, London.
大型城市地下水热模型 - 以伦敦肯辛顿和切尔西皇家自治市为例。
DOI:
10.17863/cam.47266
发表时间:
2020
期刊:
影响因子:
--
作者:
[Bidarmaghz A]
通讯作者:
Bidarmaghz A
DOI:
10.1016/j.enbuild.2021.110841
发表时间:
2021-02
期刊:
Energy and Buildings
影响因子:
6.7
作者:
[W. Choi;R. Choudhary;R. Ooka]
通讯作者:
W. Choi;R. Choudhary;R. Ooka
Bayesian parameter inference for shallow subsurface modeling using field data and impacts on geothermal planning
使用现场数据进行浅层地下建模的贝叶斯参数推断及其对地热规划的影响
DOI:
10.1017/dce.2022.32
发表时间:
2022
期刊:
Data-Centric Engineering
影响因子:
--
作者:
[Kreitmair M]
通讯作者:
Kreitmair M
共 7 条
B-bem: The Bayesian building energy management Portal
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批准号:EP/L024454/1
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项目类别:Research Grant
-
资助金额:$57.46万
-
财政年份:2014
-
负责人:Ruchi Choudhary
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依托单位:
海外基金