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Lecture Objectives. Finish Thermal Comfort and Air Quality analyses in CFD Start particle modeling. Thermal comfort. Temperature and relative humidity. Thermal comfort. Velocity Can create draft Draft is related to air temperature, air velocity, and turbulence intensity.

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Presentation Transcript
slide1
Lecture Objectives

Finish

  • Thermal Comfort and
  • Air Quality analyses in CFD

Start particle modeling

thermal comfort
Thermal comfort

Temperature and relative humidity

thermal comfort1
Thermal comfort

Velocity

Can create draft

Draft is related to air temperature,

air velocity, and turbulence intensity.

thermal comfort2
Thermal comfort

Mean radiant

temperature

potential problems

Asymmetry

Warm ceiling (----)

Cool wall (---)

Cool ceiling (--)

Warm wall (-)

prediction of thermal comfort
Prediction of thermal comfort
  • Predicted Mean Vote (PMV)
  • + 3 hot
  • + 2 warm
  • + 1 slightly warm
  • PMV = 0 neutral
  • -1 slightly cool
  • -2 cool
  • -3 cold
  • PMV = [0.303 exp ( -0.036 M ) + 0.028 ] L
  • L - Thermal load on the body
  • L = Internal heat production – heat loss to the actual environment
  • L = M - W - [( Csk + Rsk + Esk ) + ( Cres + Eres )]
  • Predicted Percentage Dissatisfied (PPD)
  • PPD = 100 - 95 exp [ - (0.03353 PMV4 + 0.2179 PMV2)]

Empirical correlations

Ole Fanger

iaq parameters
IAQ parameters

Number of ACH

quantitative indicator

ACH - for total air

- for fresh air

Ventilation effectiveness

qualitative indicator

takes into account air distribution in the space

Exposure

qualitative indicator

takes into account air distribution and source position and intensity

iaq parameters1
IAQ parameters
  • Age-of-air

air-change effectiveness (EV)

  • Specific Contaminant Concentration

contaminant removal effectiveness e

single value iaq indicators e v and
Single valueIAQ indicatorsEv and ε
  • Contaminant removal effectiveness (e)
  • concentration at exhaust
  • average contaminant concentration

Contamination level

  • 2. Air-change efficiency (Ev)
  • shortest time for replacing the air
  • average of local values of age of air

Air freshness

air change efficiency e v
Depends only on airflow pattern in a room

We need to calculate age of air (t)

Average time of exchange

What is the age of air at the exhaust?

Type of flow

Perfect mixing

Piston (unidirectional) flow

Flow with stagnation and short-circuiting flow

Air-change efficiency (Ev)
contaminant removal effectiveness e
Contaminant removal effectiveness (e)
  • Depends on:
    • position of a contaminant source
    • Airflow in the room
  • Questions

1) Is the concentration of pollutant in the room with stratified flow larger or smaller that the concentration with perfect mixing?

2) How to find the concentration at exhaust of the room?

differences and similarities of e v and e
Ev= 0.41

e= 0.19

e= 2.20

Differences and similarities of Evande

Depending on the

source position:

- similar or

- completely different

air quality

particulate matters pm
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
particles properties and sources
ParticlesProperties and sources

ASHRAE Transaction 2004

slide15
Properties

ASHRAE

Transaction 2004

two basic approaches for modeling of particle dynamics
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
lagrangian model particle tracking
m∙a=SFLagrangian 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 model particle tracking1
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
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

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