SBIR Phase I: A platform for simulating the combined effect of human behavior and environment on airborne infectious spread (COVID-19)

SBIR 第一阶段：模拟人类行为和环境对空气传播传染病（COVID-19）综合影响的平台

• 批准号: 2151672
• 负责人: Adam Ryason
• 金额: $ 25.58万
• 依托单位: INTELLIGENT MEDICINE INC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2151672&HistoricalAwards=false
• 关键词: SBIR; Phase; platform; simulating; combined

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to minimize infection by contagious diseases, such as COVID-19. This project advances a cloud-based platform for simulating particle flow in heavily populated, dynamic environments. It will enable facility managers and health/ safety stakeholders to simulate viral particle dispersion in indoor environments for design and mitigation procedures (disinfection, evacuation, etc.). This technology can play a role in mitigating the ongoing effects of the current COVID-19 pandemic and better prepare facilities for the next pandemic. This Small Business Innovation Research (SBIR) Phase I project supports facility planning and response of infectious disease outbreaks. The project advances a hybrid computational approach to utilizing multi-scale fluid analysis for faster-than-real-time multimodal simulation. The research objectives are to: (1) create a simulation platform that can parallelize equations and perform at near real-time or real-time, which will provide a means to simulate multimodal interactions in real buildings, such as contamination spread in fluid flow, when analyzed with human behavior and mobility; (2) characterize and validate the results of the simulator by measuring particle spread in multiple real building scenarios. It is anticipated that the simulation results of particle trajectory and surface contamination will be at least as accurate as state-of-the-art high-fidelity computational fluid dynamic techniques, but delivered in real time. This project will provide an environment and behavior-specific simulation essential for optimizing airflow and facility controls to reducing airborne infectious transmission.This 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.

该小企业创新研究 (SBIR) 第一阶段项目的更广泛影响/商业潜力是最大限度地减少 COVID-19 等传染病的感染。该项目开发了一个基于云的平台，用于模拟人口稠密的动态环境中的颗粒流。 它将使设施管理者和健康/安全利益相关者能够模拟室内环境中的病毒颗粒扩散，以进行设计和缓解程序（消毒、疏散等）。这项技术可以在减轻当前 COVID-19 大流行的持续影响方面发挥作用，并为下一次大流行更好地准备设施。该小型企业创新研究 (SBIR) 第一阶段项目支持设施规划和传染病爆发应对。该项目提出了一种混合计算方法，利用多尺度流体分析进行比实时更快的多模态模拟。研究目标是：（1）创建一个可以并行化方程并近实时或实时执行的仿真平台，这将提供一种模拟真实建筑物中多模态相互作用的方法，例如流体流动中的污染扩散，当对人类行为和流动性进行分析时； (2) 通过测量多个真实建筑场景中的颗粒扩散来表征和验证模拟器的结果。预计颗粒轨迹和表面污染的模拟结果将至少与最先进的高保真计算流体动力学技术一样准确，但是实时交付的。该项目将提供特定于环境和行为的模拟，对于优化气流和设施控制以减少空气传播传染病传播至关重要。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。