This document discusses using computational fluid dynamics (CFD) to expand the analysis capabilities of dynamic simulation models (DSMs) for building design. It provides examples of how CFD can provide more detailed thermal comfort and airflow information than DSMs alone for spaces like offices, atriums, and data centers. By importing boundary conditions from DSM results, CFD can model local temperature variations and complex airflow patterns to help optimize HVAC system design.

1. Dynamic Simulation Model to
CFD:
Expanding the Horizons of the
analysis for Built Environment
Harshad Joshi
CFD Project Leader, IES Ltd

2. Abstract
The dynamic simulation model (DSM) is a cost and time effective way of
analysing thermal comfort and energy requirements within a building. However,
there are analysis limitations with this approach only due to the nature of the
geometry created and physics being simulated. Many spaces within building
types require micro-analysis to ensure the systems work in the way the design
intends.
This talk will present a few examples ranging from offices and shopping centres
to data halls on how connecting the DSM with CFD allows us to gain a greater
insight into thermal comfort and design systems much better.
The talk will also feature the use of CFD to expand the thermal comfort analysis
outside the building to maximise the use of the built environment.

3. Pioneers of Building Simulation
VE Technology & IES people at the core of all we do
Located in Glasgow, Dublin, Paris, Atlanta, San Francisco, Vancouver, Pune, Dubai &
Melbourne
In over 140+ countries IES are helping…
Architects, Engineers, FMs, Cost Consultants,
BREEAM Assessors, LEED Assessors, Developers, ESCOs, Contractors, Local
Authorities, Governments
& Academia

4. Better Buildings, Smarter Cities

5. An Integrated Approach

6. VIRTUAL ENVIRONMENT

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Building Regs

8. Dynamic Simulation Model (DSM)
Dynamic Thermal Model:
Each room has lumped air volume – single air
temperature. Apache uses algorithms to
calculate surface heat transfer coefficients for
convective heat transfer from air volume to
fabric.
Unsteady one-dimensional heat transfer by
conduction. Apache uses finite difference
numerical solution in one dimension through
fabric only. Simplified form of the Fourier
equation which is itself a simplified form of the
general energy equation used in MicroFlo
Apache employs shortwave and longwave
surface radiation heat transfer models

9. DSM Results Limitations
• Only one value for any variable
• Results cannot be practically applicable to:
– Spaces with high aspect ratio like large open plan offices, tall
atriums.
– Spaces with very concentrated heat gains where local temperature
variations are under scrutiny like datacentres
– Spaces where flow patterns are the thing under investigation like
cleanrooms

10. Overcoming Limitations
• Use DSM as the starting point
• Input the necessary details in the IES VE model which is the
DSM
• Details include:
– Envelope Constructions
– Internal gains like people, equipment, lighting
– Schedule for gains
– Weather file/location
– HVAC systems

11. Importing from DSM Results
• Surface temperatures for the envelopes
• Convective component of internal gains
• Strength of humidity of sources
• Flow rates from HVAC system

12. Office in London

13. Objectives
• Typical Summer conditions
• Air flow patterns
• Air Temperature patterns
• Predicted Mean Vote Patterns

14. CFD Model

15. CFD Model
Linear slot lights
(Shown in yellow)
High level extract

16. Supply Diffusers
Free area = 25%

17. Trench grilles
Effective free area
Grille body

18. CFD Mesh
• 12 million
cells
• Run time
~3hrs
• 144 cores
(4 nodes
on EPCC)
• HelyxHex
Mesh

19. Some Boundary Conditions
Floor Area 285 m2
Floor to Ceiling height 3.2m
Air Temperature Set point 23.5°C
Circular Floor Diffusers Supply velocity 3.1m/s
Circular Floor Diffusers Supply Air Temperature 18°C
Trench Grille Supply Velocity 0.09m/s
Trench Grille Supply Air Temperature 16°C
Clothing 0.8 clo
Metabolic Rate 1 met

20. Sample Results
North-west Corner South-east Corner

21. Sample Results
Predicted Mean Vote
(1.5m above the floor)
Air Temperature
(1.5m above the floor)

22. Multi-storey Atrium in Amsterdam

23. Objectives
• Compare effect of adding heat pipes close to façade on
thermal comfort of occupants
• Winter conditions
• Air Temperature
• Air Speed
• Local Mean Radiant Temperature

24. CFD Model
Supplies
Extracts

25. CFD Model
Heat Pipes

26. CFD Mesh
• 24 million
cells
• Run time
~5hrs
• 144 cores
(4 nodes
on EPCC)
• HelyxHex
Mesh

27. Some Boundary Conditions
Floor Area ~1700m2
Floor to Ceiling height 12m
Air Temperature Set point 17.5°C
Diffusers Supply velocity 0.5m/s
Circular Floor Diffusers Supply Air Temperature 28°C
Heat Pipe heat addition ~360W/m

28. Sample Results: Air Temperature
Without Heat Pipes With Heat Pipes

29. Sample Results: Local Mean Radiant Temperature
Without Heat Pipes With Heat Pipes

30. Sample Results: Air Speed
Without Heat Pipes With Heat Pipes

31. Data Centre

32. Objectives
• Compare ideal setup v/s a ‘leaky’ setup
• Air flow patterns
• Air temperature profiles
• Rack inlet/outlet temperature

33. Ideal Racks

34. Leaky Racks

35. CFD Mesh
• 23 million
cells
• Run time
~7hrs
• 144 cores
(4 nodes
on EPCC)
• HelyxHex
Mesh

36. Some Boundary Conditions
Floor Area ~850m2
Floor to Ceiling height 4m
Cold Side Temperature 23°C
Hot side Temperature 35°C
Number of racks 320
Rack Load ~1.3MW

37. Sample Results: Air Temperature
Ideal Racks Leaky Racks

38. Engys Advantages for IES
• Extremely cost effective
• Access to on-demand HPC cluster means quick turn around
time
• Prompt and helpful technical support

39. Thank You
Questions?