Evaluation of a Moments-Based Formulation for the Transport and Deposition of Small Inertia Aerosols

Abstract

This paper introduces and evaluates a formulation for the modeling of transport and wall deposition of aerosols, written in terms of moments of the particle size distribution (PSD). This formulation allows coupling the moment methods with computational fluid dynamics (CFD) to track the space and time evolution of the PSD of an aerosol undergoing transport, deposition and coagulation. It consists in applying the quadrature method of moments (QMOM) to the diffusion-inertia model of Zaichik et al. [6], associated with the dynamic boundary layer (DBL) approach of Simonin [8] for wall deposition. After presenting the QMOM formulation of the transport equation and of the DBL wall function, the paper presents several test cases in which the method is compared to existing experimental and numerical results. It is shown that the moment formulation of the model does not introduce particular bias compared to its concentration-based formulation. This extension of the diffusion-inertia/DBL approach to the QMOM method hence allows modeling with a good numerical efficiency and at building scale the dynamics of aerosols undergoing transport and modification of their PSD through coagulation and deposition. NOMENCLATURE Latin letters A abscissas (m) D BBrownian diffusivity (m 2 .s -1 ) D f fractal dimension

Simulation of airborne nanoparticles transport, deposition and aggregation: Experimental validation of a CFD-QMOM approach

“…Such modeling can be used to track the particle size distribution of a nano-sized aerosol from its emission to the whole indoor environment, with immediate applications in the field of exposure modeling and computer aided design of protective equipments or ventilation strategies. As this model has also been validated for micro-sized aerosols undergoing transport, deposition and sedimentation in a recent paper (Guichard et al, 2014a), the use of this modeling approach extends to various indoor situations where aerosol size ranges from a few nanometers to a few micrometers.…”

“…The size of this cell is specified as its center follows the constraint 30 y   , where y  is the dimensionless wall distance, according to the practical recommendation of Nerisson et al (2011). The implementation of the complete model into a commercial CFD solver is further detailed in Guichard et al (2014a). In the present paper, this model was implemented in the commercial code ANSYS Fluent 15.0.…”

“…In this context, we showed (Guichard et al, 2014b) that the DAE-QMOM approach of Gimbun et al (2009) was particularly well suited to solve the modelling of aerosol undergoing aggregation in turbulent indoor air conditions with a high quadrature order. A complete CFD model, which used this DAE-QMOM approach for the aggregation of the particulate phase was then presented (Guichard et al, 2014a). It accounts for the transport, the Brownian and turbulent aggregation and the deposition of aerosols with particle size ranging from a few nanometers to a few micrometers.…”

“…So far, these drawbacks prevented a straightforward experimental validation of CFD models designed for airborne nanoparticles transport and aggregation, until recently an experiment was specially designed (Belut and Christophe, 2016). The purpose of the present paper is hence to evaluate the performance of the nano-aerosols dynamics model described in Guichard et al (2014a) as compared to this experimental work. This paper considers the case of two different types of aerosols, namely sodium chloride and copper oxide particles, presenting distinct PSDs, which are steadily injected in an aggregation chamber at moderate Reynolds number.…”

Distribution of non-spherical nanoparticles in turbulent flow of ventilation chamber considering fluctuating particle number density

“…They found that the total number concentration reaches a peak soon after particle emission starts, and the number size distribution can be assumed as a bimodal shape. Guichard and Belut [13] combined the quadrature method of moments with a diffusion inertia model to simulate the dispersion of small and medium inertial aerosols in a ventilation chamber, and evaluated it in various test cases. Guichard and Belut [14] simulated numerically the nanoparticle distribution in a chamber ventilated by a turbulent flow at moderate Reynolds numbers, and showed that the highest reduction of particle number corresponds to the smallest and least compact nanoparticles.…”