Martinez Iñigo, Bruse Jan L, Florez-Tapia Ane M, Viles Elisabeth, Olaizola Igor G
Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián 20009, Spain.
TECNUN School of Engineering, University of Navarra, Donostia-San Sebastián 20018, Spain.
Build Environ. 2022 Jan;207:108495. doi: 10.1016/j.buildenv.2021.108495. Epub 2021 Nov 10.
Recent evidence suggests that SARS-CoV-2, which is the virus causing a global pandemic in 2020, is predominantly transmitted via airborne aerosols in indoor environments. This calls for novel strategies when assessing and controlling a building's indoor air quality (IAQ). IAQ can generally be controlled by ventilation and/or policies to regulate human-building-interaction. However, in a building, occupants use rooms in different ways, and it may not be obvious which measure or combination of measures leads to a cost- and energy-effective solution ensuring good IAQ across the entire building. Therefore, in this article, we introduce a novel agent-based simulator, ArchABM, designed to assist in creating new or adapt existing buildings by estimating adequate room sizes, ventilation parameters and testing the effect of policies while taking into account IAQ as a result of complex human-building interaction patterns. A recently published aerosol model was adapted to calculate time-dependent carbon dioxide (CO) and virus quanta concentrations in each room and inhaled CO and virus quanta for each occupant over a day as a measure of physiological response. ArchABM is flexible regarding the aerosol model and the building layout due to its modular architecture, which allows implementing further models, any number and size of rooms, agents, and actions reflecting human-building interaction patterns. We present a use case based on a real floor plan and working schedules adopted in our research center. This study demonstrates how advanced simulation tools can contribute to improving IAQ across a building, thereby ensuring a healthy indoor environment.
最近的证据表明,导致2020年全球大流行的新冠病毒主要通过室内环境中的空气气溶胶传播。这就要求在评估和控制建筑物的室内空气质量(IAQ)时采用新策略。室内空气质量通常可以通过通风和/或规范人与建筑物交互的政策来控制。然而,在建筑物中,居住者使用房间的方式各不相同,而且哪种措施或措施组合能带来成本效益高且节能的解决方案,以确保整个建筑物的良好室内空气质量,可能并不明显。因此,在本文中,我们介绍了一种基于智能体的新型模拟器ArchABM,旨在通过估计合适的房间尺寸、通风参数,并在考虑复杂的人与建筑物交互模式导致的室内空气质量的情况下测试政策效果,来协助创建新建筑或改造现有建筑。我们采用了一个最近发表的气溶胶模型,来计算每个房间随时间变化的二氧化碳(CO)和病毒量子浓度,以及每个居住者一天内吸入的CO和病毒量子,以此作为生理反应的一种度量。由于其模块化架构,ArchABM在气溶胶模型和建筑布局方面具有灵活性,这允许实现更多模型、任意数量和尺寸的房间、智能体以及反映人与建筑物交互模式的行动。我们基于研究中心采用的实际平面图和工作时间表展示了一个用例。这项研究展示了先进的模拟工具如何有助于改善整个建筑物的室内空气质量,从而确保健康的室内环境。