Engys Presentation Harshad Joshi September 2018
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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.
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Engys Presentation Harshad Joshi September 2018
- 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
- 7. IES Consulting Services Model Creation & Review QSAS / GSAS Post-occupancy EvaluationLEED BREEAM Commissioning BIM Mentoring Bid Support Building Tuning Green Star Green Mark GRIHA Estidama Portfolio Lifecycle Building Energy Audits CFD Studies Crowd Movement LCA Solar Risk Assessment Pollutant Studies Value Engineering Performance Optimisation Comfort Studies Data Centres Cleanroom Simulations Design Optimisation Masterplanning Site Assessment Daylight Concept Assessment Crowd Movement Title 24 UK Building Regs Australia/NZ Buildings Regs Feasibility Studies Irish 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
- 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