RAPID: Smart Ventilation Control May Reduce Infection Risk for COVID-19 in Public Buildings

RAPID：智能通风控制可降低公共建筑中 COVID-19 的感染风险

• 批准号: 2029690
• 负责人: Zheng O'Neill
• 金额: $ 12.54万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2021-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2029690&HistoricalAwards=false
• 关键词: RAPID; Smart; Ventilation; Control; May

During the current COVID-19 pandemic, airborne transmission of the virus through exhaled aerosols is a likely explanation for the rapid rate of new infections. The risk of infection with COVID-19 could be reduced by employing feasible measures in public buildings, such as smart and enhanced Heating, Ventilation, and Air- conditioning (HVAC) design and operations, higher humidity levels, surface cleaning and hygiene protocols, revised spatial configuration, etc. This project aims to investigate a novel smart ventilation control strategy using a CO2-based indicator to operate under a normal mode and a pandemic mode as appropriate for common public buildings (e.g., office buildings, classroom buildings, retail stores). These buildings are designed and operated in normal conditions by default. The question to be studied is that, with the current HVAC equipment and systems already installed in existing public buildings, can operations be modified via smart ventilation control by diluting the air in a space with cleaner air from outdoors to reduce infection risk for occupants. Ventilation controls in public buildings under a pandemic represent significant challenges. In this project, the research team will look into the problem of potentially reducing infection risk with coronavirus through three objectives: 1) Obtain a minimum ventilation rate for different HVAC systems in most common public buildings to potentially reduce infection risk through a risk analysis with Computational Fluid Dynamics (CFD) simulations; 2) Establish a scientific correlation between CO2 concentration with the potential infection risk in spaces in public buildings to better monitor the infection risk with numerical studies and limited field experiments; and 3) Evaluate a novel smart ventilation control strategy that can switch between normal operation and operation under a pandemic through a co-simulation of energy performance and CFD simulations. COVID-19 has generated immense social-economic impact, which may be mitigated by the proposed smart ventilation control in public buildings to reduce the risk of being infected with COVID-19 during occupation of public buildingsThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在当前的 COVID-19 大流行期间，病毒通过呼出的气溶胶在空气中传播可能是新感染率快速上升的原因。 通过在公共建筑中采取可行的措施，例如智能和增强的供暖、通风和空调 (HVAC) 设计和操作、更高的湿度水平、修订后的表面清洁和卫生规程，可以降低感染 COVID-19 的风险该项目旨在研究一种新颖的智能通风控制策略，使用基于二氧化碳的指标在正常模式和大流行模式下运行，适用于常见的公共建筑（例如办公楼、教学楼、零售商店） 。这些建筑物默认在正常条件下设计和运行。要研究的问题是，在现有公共建筑已安装的暖通空调设备和系统的情况下，能否通过智能通风控制来修改操作，用室外更清洁的空气稀释空间内的空气，以降低居住者的感染风险。大流行期间公共建筑的通风控制面临着重大挑战。在这个项目中，研究团队将通过三个目标来研究潜在降低冠状病毒感染风险的问题：1）通过计算风险分析，获得最常见公共建筑中不同暖通空调系统的最低通风率，以潜在降低感染风险。流体动力学 (CFD) 模拟； 2）建立公共建筑空间CO2浓度与潜在感染风险之间的科学关联，通过数值研究和有限的现场实验更好地监测感染风险； 3) 评估一种新颖的智能通风控制策略，该策略可以通过能源性能和 CFD 模拟的联合仿真在正常运行和大流行情况下运行之间切换。 COVID-19 产生了巨大的社会经济影响，可以通过拟议的公共建筑智能通风控制来减轻这种影响，以减少公共建筑占用期间感染 COVID-19 的风险。该奖项反映了 NSF 的法定使命，并被认为是值得的通过使用基金会的智力优势和更广泛的影响审查标准进行评估来获得支持。