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

在当前的COVID-19大流行期间，病毒通过呼出气溶胶的空气传播可能是新感染率快速增长的一个解释。 通过在公共建筑中采取可行的措施可以降低感染COVID-19的风险，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，表面清洁和卫生协议，修改空间配置，该项目旨在研究一种新型的智能通风控制策略，基于指标，在正常模式和流行模式下运行，适用于普通公共建筑（例如，办公楼、教学楼、零售店）。这些建筑物的设计和运作默认在正常条件下。需要研究的问题是，在现有公共建筑中已经安装了现有的HVAC设备和系统的情况下，是否可以通过智能通风控制来修改操作，通过使用来自室外的更清洁的空气稀释空间中的空气，以降低居住者的感染风险。在大流行下，公共建筑的通风控制是一项重大挑战。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）通过计算流体动力学（CFD）模拟的风险分析，获得大多数常见公共建筑中不同HVAC系统的最低通风率，以潜在降低感染风险; 2）通过数值研究和有限的现场实验，建立公共建筑空间内二氧化碳浓度与潜在感染风险之间的科学关联，以更好地监测感染风险;以及3）通过能源性能和CFD模拟的联合模拟，评估一种新型智能通风控制策略，该策略可以在正常运行和大流行病下的运行之间切换。COVID-19对社会经济产生了巨大影响，而公共建筑中的智能通风控制可以减轻这种影响，以降低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，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.