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Modeling of indoor airflow and dispersion of aerosols using immersed boundary and random flow generation methods

机译:使用沉浸边界和随机流生成方法对室内气流和气溶胶扩散进行建模

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Numerical modeling of environmental flows involves complex geometry, moving bodies, multi-phase flow, and buoyant jet effects. An in-house CFD code has been developed using finite volume and immersed boundary methods. The transport and dispersion of virus-laden aerosols in a ventilated room is investigated by this numerical code. The uniqueness of this numerical code is that it can efficiently compute small-scale turbulent flow in which most commercial CFD software will suffer from large numerical error. Random flow generation (RFC) [33] is an ideal choice for small-scale turbulence for low-Reynolds number flow in a ventilated room. In addition, Lagrangian stochastic (LS) walk model is applied to directly compute probability density function (PDF) of aerosols and estimate the risk factor of aerosol dispersion from a point source. The present study focuses on aerosols with small diameter (<10 μm) in which the effects of evaporation on the dispersion of aerosols could be neglected. Different location of aerosol sources and a typical ventilation layout are discussed in detail. The numerical results with PDF yield more useful quantitative information to assess the risk area of virus transport in a ventilated room than that shown in random trajectories of particles as widely reported in the literature. This study provides valuable information for ventilation control strategies with respiratory protection, such as enhanced air exchange, air filtration rate, and improved airflow patterns to reduce indoor infection risk via airborne virus laden droplets.
机译:环境流动的数值模型涉及复杂的几何形状,运动的物体,多相流动和浮力喷射效应。内部CFD代码已使用有限体积和浸入边界方法开发。通过该数字代码研究了载有病毒的气溶胶在通风室内的运输和扩散。该数字代码的独特之处在于它可以有效地计算小规模的湍流,而大多数商业CFD软件都将遭受小数值的湍流。随机流生成(RFC)[33]是通风室内低雷诺数流小规模湍流的理想选择。另外,应用拉格朗日随机(LS)步行模型直接计算气溶胶的概率密度函数(PDF)并从点源估计气溶胶扩散的危险因素。本研究的重点是小直径(<10μm)的气溶胶,其中蒸发对气溶胶分散的影响可以忽略。详细讨论了气溶胶源的不同位置和典型的通风布局。与文献中广泛报道的相比,PDF的数值结果提供了更多有用的定量信息,以评估通风室中病毒运输的风险区域,而无规律地显示粒子的轨迹。这项研究为呼吸控制的通风控制策略提供了有价值的信息,例如增强的空气交换,空气过滤率和改善的气流模式,以通过载有病毒的飞沫降低室内感染的风险。

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