Risk EvaLuatIon fAst iNtelligent Tool (RELIANT) for COVID19
Risk EvaLuatIon fAst iNtelligent Tool (RELIANT) for COVID19
批准号:
EP/V036777/1
负责人:
Andrea Cammarano
金额:
$172.92万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --
中文摘要
点击翻译按钮获取中文摘要
英文摘要
This project brings together unique expertise in Computational and Experimental Fluid Dynamics, Model Reduction and Artificial Intelligence, to identify solutions for the management of people and spaces in the current pandemic and post lockdown.A new interactive tool is proposed that evaluates the risk of infection in the indoor environment from droplets and aerosols generated when breathing, talking, coughing and sneezing. This capability will become more critical as winter approaches and building ventilation will need to be limited for comfort considerations. The fluid dynamic behaviour of droplets and aerosols, the effect of using face masks as well as other parameters such as room volume, ventilation and number of occupants are considered. A datahub capable of storing, curating and managing heterogeneous data from sources internal and external to the project will be created. A synergetic experimental and numerical approach will be undertaken. These will complement the existing literature and data from other EPSRC-funded projects providing suitable datasets with adequate resolution in time and space for all the relevant features. To support experiments and numerical simulations, reduced order models capable of interpolating and extrapolating the scenarios collected in the database will be used. This will permit the estimation of droplet and aerosol concentrations and distributions in unknown scenarios at low-computational cost, in near real-time. A state-of-the-art AI-based framework, incorporating descriptive, predictive and prescriptive techniques will extract the knowledge from the data and drive the decision-making process and provide in near real-time the assessment of risk levels.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
登录
查看更多内容
Real-time Updating of Dynamic Social Networks for COVID-19 Vaccination Strategies
实时更新动态社交网络以制定 COVID-19 疫苗接种策略
DOI:
10.1101/2021.03.11.21253356
发表时间:
2021
期刊:
影响因子:
--
作者:
[Cheng S]
通讯作者:
Cheng S
Optimised Adjoint Sensitivity Analysis Using Adjoint Guided Mesh Adaptivity Applied to Neutron Detector Response Calculations
使用伴随引导网格自适应性的优化伴随灵敏度分析应用于中子探测器响应计算
DOI:
10.3390/en15145102
发表时间:
2022
期刊:
Energies
影响因子:
3.2
作者:
[Buchan A]
通讯作者:
Buchan A
DOI:
10.1016/j.ijhydene.2023.06.086
发表时间:
2023-06
期刊:
International Journal of Hydrogen Energy
影响因子:
7.2
作者:
[Mohsen Esfandiary;Seifolah Saedodin;Nader Karimi]
通讯作者:
Mohsen Esfandiary;Seifolah Saedodin;Nader Karimi
DOI:
10.1016/j.buildenv.2022.108938
发表时间:
2022-03
期刊:
Building and Environment
影响因子:
7.4
作者:
[Alex Dmitrewski;Miguel Molina-Solana;Rossella Arcucci]
通讯作者:
Alex Dmitrewski;Miguel Molina-Solana;Rossella Arcucci
DOI:
10.1007/s10915-022-02059-4
发表时间:
2023-01-01
期刊:
JOURNAL OF SCIENTIFIC COMPUTING
影响因子:
2.5
作者:
[Cheng, Sibo, Chen, Jianhua, Arcucci, Rossella]
通讯作者:
Arcucci, Rossella
共 7 条
国内基金
海外基金
基于重要农地保护LESA(Land Evaluation and Site Assessment)体系思想的高标准基本农田建设研究
-
批准号:41340011
-
项目类别:专项基金项目
-
资助金额:20.0万元
-
批准年份:2013
-
负责人:钱凤魁
-
依托单位: