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Lecture Objectives. Analyze some examples related to natural ventilation Introduce particle dynamics modeling . External flow. Wind profile. Buoyancy driven indoor flow. Important parameters Geometry Heat sources Intensity (defined temperature or heat flux) Distribution
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Lecture Objectives • Analyze some examples related to natural ventilation • Introduce particle dynamics modeling
External flow Wind profile
Buoyancy driven indoor flow Important parameters • Geometry • Heat sources • Intensity (defined temperature or heat flux) • Distribution • Change (for unsteady-state problem) • Openings Defined • Pressure • Velocity
Energy Simulation Program Air Flow Program Coupling Twall,CFM, Tsupply Data: geometry weather materials IAQ V,T,… Energy cons. Tnear surface, h surface
COUPLING METHODS One-directional coupling (Quasi steady state CFD simulation)
Particulate matters (PM) • Properties • Size, density, liquid, solid, combination, … • Sources • Airborne, infiltration, resuspension, ventilation,… • Sinks • Deposition, filtration, ventilation (dilution),… • Distribution - Uniform and nonuniform • Human exposure
Properties ASHRAE Transaction 2004
Particle size distribution ASHRAE Transaction 2004 Ventilation system affect the PM concentration in indoor environment !
Human exposure ASHRAE Transaction 2004
Two basic approaches for modeling of particle dynamics • Lagrangian Model • particle tracking • For each particle ma=SF • Eulerian Model • Multiphase flow (fluid and particles) • Set of two systems of equations
m∙a=SF Lagrangian Modelparticle tracking A trajectory of the particle in the vicinity of the spherical collector is governed by the Newton’s equation Forces that affect the particle • (rVvolume) particle∙dvx/dt=SFx • (rVvolume) particle∙dvy/dt=SFy • (rVvolume) particle∙dvz/dt=SFz System of equation for each particle Solution is velocity and direction of each particle
Lagrangian Modelparticle tracking Basic equations - momentum equation based on Newton's second law Drag force due to the friction between particle and air - dp is the particle's diameter, - p is the particle density, - up and u are the particle and fluid instantaneous velocities in the i direction, - Fe represents the external forces (for example gravity force). This equation is solved at each time step for every particle. The particle position xi of each particle are obtained using the following equation: For finite time step
Algorithm for CFD and particle tracking Unsteady state airflow Steady state airflow Airflow (u,v,w) for time step Airflow (u,v,w) Steady state Injection of particles Injection of particles Particle distribution for time step Particle distribution for time step Airflow (u,v,w) for time step + Particle distribution for time step + Particle distribution for time step + Particle distribution for time step +2 ….. ….. One way coupling Case 1 when airflow is not affected by particle flow Case 2 particle dynamics affects the airflow Two way coupling
Eulerian Model • Solve several sets of NS equations • Define the boundary conditions in-between phases Multiphase/Mixture Model • Mixture model • Secondary phase can be granular • Applicable for solid-fluid simulations • Granular physics • Solve total granular pressure to momentum equation • Use Solids viscosity for dispersed solid phase • Density difference should be small. • Useful mainly for liquid-solids multiphase systems There are models applicable for particles in the air
Multiphase flow Multiphase flow can be classified in the following regimes: • gas-liquid or liquid-liquid flows • gas-solid flows • particle-laden flow: discrete solid particles in a continuous gas • pneumatic transport: flow pattern depends on factors such as solid loading, Reynolds numbers, and particle properties. Typical patterns are dune flow, slug flow, packed beds, and homogeneous flow. • fluidized beds: consist of a vertical cylinder containing particles where gas is introduced through a distributor. • liquid-solid flows • three-phase flows
Multiphase Flow Regimes Fluent user manual 2006