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CFD webinar
Ensure Thermal Comfort and
Energy Efficiency with CFD
1. Brief of thermal comfort and energy efficiency in LEED buildings
2. How is thermal comfort assessed? (PMV/PPD/MRT)
3. How can SimScale CFD help evaluate thermal comfort?
4. Our Case: Analysis of an office space
○ Project overview
○ Simulation setup
○ Results
■ Thermal comfort
■ Energy consumption
○ Importance of insulation
○ Air supply temperature
5. Key learnings / Conclusion
Today’s Application
Thermal comfort and
energy efficiency
● ASHRAE 55 standard:
○ “Thermal comfort is the condition of mind
that expresses satisfaction with the thermal
environment and is assessed by subjective
evaluation.”
● How can this be assessed?
○ Using predicted mean vote (PMV) and
percentage of people dissatisfied (PPD)
Today’s Application
What is thermal comfort?
Thermal Comfort
How can SimScale CFD help evaluate thermal comfort?
CFD Computed Values
● Air temperature (°C)
● Mean radiant temperature (MRT)
● Air speed (m/s)
Thermal Comfort Parameter Inputs
● Clothing coefficient (clo)
● Metabolic rate (met) / activity level
● Relative air humidity (%)
Airspeed (v)
Metabolic Rate (M)
Clothing Coefficient (clo) (image source)
(image source)What environmental
factors contribute to
thermal comfort?
Understanding Thermal Comfort
Relative Humidity (RH):
Mean Radiant Temperature (MRT):
What environmental
factors contribute to
thermal comfort?
Understanding Thermal Comfort
Understanding Thermal Comfort
What is mean radiant
temperature?
● A way to express the influence of
surface temperatures on
occupant comfort
● One scalar value (on SimScale)
● Size-weighted average across all
domain surface temperatures
Office Thermal Comfort in Qatar
Example case
● Identify the ideal setup so that all occupants are in a
state of comfort. Variables to consider:
○ Wall insulation
○ Cool air supply rate and temperature
● Aiming at a value of predicted mean vote (PMV)
between -0.5 to 0.5
● Using the least amount of energy
Project Objectives
Our Case: Office Thermal Comfort In Qatar
Velocity streamlines from an HVAC diffuser in an office space
● 5x5m office space
● 4 occupants
○ Wearing short sleeve clothing (0.65 clo)
○ Typing metabolic rate (1.15 met)
○ Relative air humidity (65)
● 4 workstations emitting 72 W of heat
● Middle Eastern summer conditions: 42°C
outside
Scenario Overview
4 Colleagues 80 W each
4 Workstations 72 W each
Defining thermal
insulation
2 Existing external walls
The lower this value, the
less heat will be
transferred through the
wall
The lower this value, the
less heat will be
transferred through the
window
Defining thermal
insulation
Window
Added solar radiation
Defining thermal
insulation
2 Internal walls:
Considered to be adiabatic
Well insulated ceiling and floor:
0.18 U-Value
● One air supply for simplicity (19.85 °C)
● Air change rate between 6-8 changes per hour
ensure indoor air quality
● Two outlets in the room corners
Project Overview
The scenario
● Different ceiling diffusers:
1. Generate different patterns (swirls, jets, etc.)
2. Drop and throw values to consider
● Diffusers usually use the Coandă effect to
distribute the air around the room
Diffuser selection
The scenario
Our candidate
Low pressure
zone causing
Coanda effect
CAD model import
Simulation setup
Analyze results
1
3
Thermal Comfort
Analysis with SimScale
2
Results
Occupant 2: Warm 2.08
Occupant 1: Warm 1.8
Occupant 3: Warm 1.9
Occupant 4: Warm
1.78
How is the thermal comfort of
occupants (PMV Values)?
Results
The occupants are feeling
too warm! (by ASHRAE 55 -
ISO 7730 standards)
What is the air speed in the room?
Results
Note the Coandă effect
from the diffuser
The overall air speed stays well below
the 0.8m/s value recommended by
ASHRAE for comfort.
Low air speed around
0.2m/s near the occupants
What is the temperature in the room?
Results
Cold air coming from
the diffuser
Radiation from the warmer walls
impacts the thermal comfort of
those closest
Uneven distribution of temperature, not
likely to be comfortable for all.
Average temperature
is 27.1°C!
Let’s quickly validate how much
energy is gained by the air
Results
Temperature difference (Outlet-Inlet)
26.97- 19.85 degrees = 7.12 degrees
7.12 x 0.1453 x 1004 = 1039 Watts
Mass flow rate
0.1453 kg/s
Specific heat (how much energy is
required to increase the temperature
of m3 of air by 1 degree)
What can we actually change?
Results
1038 Watts = 320 + 288 + 431
Occupants
(fixed)
Desktops
(fixed)
Energy coming through the
walls+window
(this is all we can change)
Let’s make the building “green(er)” by
insulating its walls!
Design decision
Let’s run the case with
these new values
We are still far from our target
comfort range (-0.5:0.5)
Occupant 2:
Warm 1.94 (was 2.08)
Occupant 1:
Warm 1.68 (was 1.8)
Occupant 3:
Warm 1.88 (was 1.9)
Occupant 4:
Warm 1.64 (was 1.78)
How can we improve
the situation?
Let’s lower supply
temperature.
Results
Very minimal effect of changing the
insulation – new strategy needed
Average temperature
is 26.56°C!
Putting this minor energy saving
into real world terms:
Results - Better Insulated walls
Purely through insulation, the
room absorbs 64W less
For 3800 of sunshine hours per year @4.3 USD/kWh,
this translates to 1052 USD/Year!
Better, but still out of our target
range (-0.5:0.5)
Occupant 2:
Slightly Warm 1.44 (was 1.94)
Occupant 1:
Slightly warm 1.19 (was 1.88)
Occupant 3:
Slightly warm 1.35 (was 1.88)
Occupant 4:
Slightly warm 1.15 (was 1.64)
Results
How does the 18C supply perform?
Average temperature
is 25.43°C
We still haven’t achieved thermal comfort for our
occupants
Results
2 options remain:
1. Increase the air supply speed (preferred option)
a. We need to be sure we stay below 0.8 m/s but have
plenty of scope
1. Lower the supply temperature (more expensive option)
○ At present the difference between the room and inlet
temperature is 9°C
○ We would need at least a 14C or lower inlet temperature
■ It would be costly to cool the ambient air this far
Let’s optimize the design to find the ideal supply flow rate
Results
Multiple simulation runs
in parallel
Results
With an 18C supply, let’s compare the airspeed in the room
x2.5 flow rate - 0.304 m³/s x3 flow rate - 0.364 m³/s
Very acceptable air speed
around our occupants
x2.5 flow rate - 0.304 m³/s x3 flow rate - 0.364 m³/s
Results
With an 18C supply, let’s compare PMV
Occupant 2:
Neutral
0.22
Occupant 1:
Neutral -0.01
Occupant 3:
Neutral 0.13
Occupant 4:
Neutral -0.047
Occupant 4:
Neutral 0.035
Occupant 3:
Neutral 0.27
Occupant 1:
Neutral 0.1
Occupant 2:
Neutral 0.37
Flow Rate: 0.304 m³/s
Occupant 4:
Neutral 0.035
Occupant 3:
Neutral 0.27
Occupant 1:
Neutral 0.1
Occupant 2:
Neutral 0.37
Results
Conclusion and key learnings
In this project
● We assessed and quantified how much energy could be
saved with improved wall insulation
● We found that we need a different cooling strategy than
purely insulation
We have learned that:
● CFD is a highly valuable tool to:
○ Assess thermal comfort
○ Determine energy consumption
○ Optimize the design to solve the problem
● Many simulations can be run for different scenarios, and
compared to observe the impact of:
○ Different types of insulation
○ Increasing or lowering the supply flow rate
○ Modifying the supply temperature
Airflow streamlines
colored by temperature

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How to Ensure Thermal Comfort and Energy Efficiency with CFD

  • 1. CFD webinar Ensure Thermal Comfort and Energy Efficiency with CFD
  • 2. 1. Brief of thermal comfort and energy efficiency in LEED buildings 2. How is thermal comfort assessed? (PMV/PPD/MRT) 3. How can SimScale CFD help evaluate thermal comfort? 4. Our Case: Analysis of an office space ○ Project overview ○ Simulation setup ○ Results ■ Thermal comfort ■ Energy consumption ○ Importance of insulation ○ Air supply temperature 5. Key learnings / Conclusion Today’s Application Thermal comfort and energy efficiency
  • 3. ● ASHRAE 55 standard: ○ “Thermal comfort is the condition of mind that expresses satisfaction with the thermal environment and is assessed by subjective evaluation.” ● How can this be assessed? ○ Using predicted mean vote (PMV) and percentage of people dissatisfied (PPD) Today’s Application What is thermal comfort?
  • 4. Thermal Comfort How can SimScale CFD help evaluate thermal comfort? CFD Computed Values ● Air temperature (°C) ● Mean radiant temperature (MRT) ● Air speed (m/s) Thermal Comfort Parameter Inputs ● Clothing coefficient (clo) ● Metabolic rate (met) / activity level ● Relative air humidity (%)
  • 5. Airspeed (v) Metabolic Rate (M) Clothing Coefficient (clo) (image source) (image source)What environmental factors contribute to thermal comfort? Understanding Thermal Comfort
  • 6. Relative Humidity (RH): Mean Radiant Temperature (MRT): What environmental factors contribute to thermal comfort? Understanding Thermal Comfort
  • 7. Understanding Thermal Comfort What is mean radiant temperature? ● A way to express the influence of surface temperatures on occupant comfort ● One scalar value (on SimScale) ● Size-weighted average across all domain surface temperatures
  • 8. Office Thermal Comfort in Qatar Example case
  • 9. ● Identify the ideal setup so that all occupants are in a state of comfort. Variables to consider: ○ Wall insulation ○ Cool air supply rate and temperature ● Aiming at a value of predicted mean vote (PMV) between -0.5 to 0.5 ● Using the least amount of energy Project Objectives Our Case: Office Thermal Comfort In Qatar Velocity streamlines from an HVAC diffuser in an office space
  • 10. ● 5x5m office space ● 4 occupants ○ Wearing short sleeve clothing (0.65 clo) ○ Typing metabolic rate (1.15 met) ○ Relative air humidity (65) ● 4 workstations emitting 72 W of heat ● Middle Eastern summer conditions: 42°C outside Scenario Overview 4 Colleagues 80 W each 4 Workstations 72 W each
  • 11. Defining thermal insulation 2 Existing external walls The lower this value, the less heat will be transferred through the wall
  • 12. The lower this value, the less heat will be transferred through the window Defining thermal insulation Window Added solar radiation
  • 13. Defining thermal insulation 2 Internal walls: Considered to be adiabatic Well insulated ceiling and floor: 0.18 U-Value
  • 14. ● One air supply for simplicity (19.85 °C) ● Air change rate between 6-8 changes per hour ensure indoor air quality ● Two outlets in the room corners Project Overview The scenario
  • 15. ● Different ceiling diffusers: 1. Generate different patterns (swirls, jets, etc.) 2. Drop and throw values to consider ● Diffusers usually use the Coandă effect to distribute the air around the room Diffuser selection The scenario Our candidate Low pressure zone causing Coanda effect
  • 16. CAD model import Simulation setup Analyze results 1 3 Thermal Comfort Analysis with SimScale 2
  • 18. Occupant 2: Warm 2.08 Occupant 1: Warm 1.8 Occupant 3: Warm 1.9 Occupant 4: Warm 1.78 How is the thermal comfort of occupants (PMV Values)? Results The occupants are feeling too warm! (by ASHRAE 55 - ISO 7730 standards)
  • 19. What is the air speed in the room? Results Note the Coandă effect from the diffuser The overall air speed stays well below the 0.8m/s value recommended by ASHRAE for comfort. Low air speed around 0.2m/s near the occupants
  • 20. What is the temperature in the room? Results Cold air coming from the diffuser Radiation from the warmer walls impacts the thermal comfort of those closest Uneven distribution of temperature, not likely to be comfortable for all. Average temperature is 27.1°C!
  • 21. Let’s quickly validate how much energy is gained by the air Results Temperature difference (Outlet-Inlet) 26.97- 19.85 degrees = 7.12 degrees 7.12 x 0.1453 x 1004 = 1039 Watts Mass flow rate 0.1453 kg/s Specific heat (how much energy is required to increase the temperature of m3 of air by 1 degree)
  • 22. What can we actually change? Results 1038 Watts = 320 + 288 + 431 Occupants (fixed) Desktops (fixed) Energy coming through the walls+window (this is all we can change)
  • 23. Let’s make the building “green(er)” by insulating its walls! Design decision Let’s run the case with these new values
  • 24. We are still far from our target comfort range (-0.5:0.5) Occupant 2: Warm 1.94 (was 2.08) Occupant 1: Warm 1.68 (was 1.8) Occupant 3: Warm 1.88 (was 1.9) Occupant 4: Warm 1.64 (was 1.78) How can we improve the situation? Let’s lower supply temperature. Results Very minimal effect of changing the insulation – new strategy needed Average temperature is 26.56°C!
  • 25. Putting this minor energy saving into real world terms: Results - Better Insulated walls Purely through insulation, the room absorbs 64W less For 3800 of sunshine hours per year @4.3 USD/kWh, this translates to 1052 USD/Year!
  • 26. Better, but still out of our target range (-0.5:0.5) Occupant 2: Slightly Warm 1.44 (was 1.94) Occupant 1: Slightly warm 1.19 (was 1.88) Occupant 3: Slightly warm 1.35 (was 1.88) Occupant 4: Slightly warm 1.15 (was 1.64) Results How does the 18C supply perform? Average temperature is 25.43°C
  • 27. We still haven’t achieved thermal comfort for our occupants Results 2 options remain: 1. Increase the air supply speed (preferred option) a. We need to be sure we stay below 0.8 m/s but have plenty of scope 1. Lower the supply temperature (more expensive option) ○ At present the difference between the room and inlet temperature is 9°C ○ We would need at least a 14C or lower inlet temperature ■ It would be costly to cool the ambient air this far
  • 28. Let’s optimize the design to find the ideal supply flow rate Results Multiple simulation runs in parallel
  • 29. Results With an 18C supply, let’s compare the airspeed in the room x2.5 flow rate - 0.304 m³/s x3 flow rate - 0.364 m³/s Very acceptable air speed around our occupants
  • 30. x2.5 flow rate - 0.304 m³/s x3 flow rate - 0.364 m³/s Results With an 18C supply, let’s compare PMV Occupant 2: Neutral 0.22 Occupant 1: Neutral -0.01 Occupant 3: Neutral 0.13 Occupant 4: Neutral -0.047 Occupant 4: Neutral 0.035 Occupant 3: Neutral 0.27 Occupant 1: Neutral 0.1 Occupant 2: Neutral 0.37
  • 31. Flow Rate: 0.304 m³/s Occupant 4: Neutral 0.035 Occupant 3: Neutral 0.27 Occupant 1: Neutral 0.1 Occupant 2: Neutral 0.37
  • 32. Results Conclusion and key learnings In this project ● We assessed and quantified how much energy could be saved with improved wall insulation ● We found that we need a different cooling strategy than purely insulation We have learned that: ● CFD is a highly valuable tool to: ○ Assess thermal comfort ○ Determine energy consumption ○ Optimize the design to solve the problem ● Many simulations can be run for different scenarios, and compared to observe the impact of: ○ Different types of insulation ○ Increasing or lowering the supply flow rate ○ Modifying the supply temperature Airflow streamlines colored by temperature