Associate Professor Veronica Soebarto discussed how building simulation can be used to predict building performance, improve designs, diagnose existing buildings, optimize solutions, and ensure code compliance. Simulation allows assessment of thermal performance, energy usage, indoor environmental quality, and life cycle costs. However, studies show large discrepancies often occur between simulated and actual building performance. Key reasons for differences include problems in design assumptions, construction variations from design, and operational factors not accounted for in simulations.

1. The Environment Institute
Where ideas grow
Assoc. Prof. Veronica Soebarto
Will simulation-based assessments and
decisions save our built environment?

2. Environment Institute Seminar Series 2009
Will simulation-based assessments and decisions
save our built environment?
Associate Professor Veronica Soebarto
School of Architecture, Landscape Architecture and Urban Design
The University of Adelaide

3. What is building simulation?
• Modelling a building design (with computer programs) to predict how it would look, stand,
perform (thermally, acoustically, visually, economically …)

4. Why simulate building (design)?
Building simulation can:
• predict future performance
• diagnose existing performance
to:
• improve design
• meet users’ requirements
• optimise solutions
• save energy, save $$$
• comply with the codes

5. Thermal & Environmental Simulation
This presentation focuses on
thermal and environmental simulation of building designs

6. Brief history
• 18th century: study of heat transmission in buildings by Isaac Newton’s Scale of the
degrees of heat and Jean Claude Eugène Péclet’s principles of heat flow through building
elements)
• Early 20th century: American Society of Heating and Ventilating Engineers, Louis Allen
Harding’s heat losses by transmission through various building materials
• 1940-60’s : steady state calculation
• 1970’s: dynamic response of construction elements with steady state HVAC system
modelling
• 1980’s and beyond: dynamic integrated modelling – thermal, visual, acoustics
• 1990’s: simulation used in building codes

7. Basic calculations
The site: External environment:
Shadowing Temperature
Reflections Humidity
Solar radiation
The building: Wind
Overall thermal
resistance
Fenestration
Infiltration
Internal admittance
Absorptivities
The occupants:
Occupancy
Operation schedules
(eg. windows, lights,
appliances)
The Plant/equip: Internal environment: temperature, humidity, air
Plant types movement, light
efficiencies Energy consumption: heating, cooling,
Schedule of ventilation, lighting, equipment
operation Economic assessment: life cycle costs

8. Basic calculations
In air-conditioned buildings:
• Load calculations (heating and cooling) based on:
– Heat transfers at the building envelope (eg. Q = ∑ (U x A (To – Ti)) + ∑ (SHGC x A x Total solar irradiance)*)
including infiltration and ventilation
– Internal heat generations (people, lights, appliances) and use patterns
• Energy use calculations based on:
– Load calculations
– Plant equipment types, efficiency, usage (J = ∑ Q / efficiency)
– Lighting and appliances types, power density, usage
• Economic assessment (Life cycle costs) based on:
– Energy calculations
– Economic parameters (discount and inflation rates, unit prices, first costs, maintenance costs)
– To calculate operating cost and total life cycle costs (PV)
* in a steady state calculation only

9. Basic calculations
In non air-conditioned buildings:
• Thermal comfort ‘calculations’ based on:
– Heat transfers at the building envelope
– Internal heat generations and use patterns
To calculate:
– Indoor temperature, humidity, air flow to determine level of comfort
– Using comfort models, eg. PMV, discomfort hours, adaptive models
• No load and energy use calculations

10. Example: Improve design
Work by Kent Neo
Overhang – shading studies

11. Example: Improve design
Percent of time when indoor space is within
75
70
comfort range (%)
65
60
55
50
45
40
1 2 3 4 5 6 7 8 9 10 11 12
Month
Alternative 1 Alternative 2 Alternative 3

12. Example: Understand phenomena
Modified
Original
Rammed earth house
Effect of adding insulation to rammed earth walls
on indoor temperature
Soebarto, V. (2009). Using simulation to predict the indoor performance of houses using
Insulated rammed earth / reverse masonry veneer rammed earth walls. Proceedings of Building Simulation 2009. IBPSA, Glasgow, 27-30 Jul.

13. Example: Understand phenomena
30.0
25.0 Rammed Insulated
earth
Temperature (degC)
20.0
15.0
10.0
Rammed earth house 5.0
0.0
1/07
1/07
2/07
2/07
3/07
3/07
4/07
4/07
5/07
5/07
6/07
7/07
7/07
8/07
8/07
9/07
9/07
10/07
10/07
11/07
11/07
12/07
12/07
13/07
14/07
14/07
outside temp C House 2 House 3
Temperature differences between rammed earth
house and insulated RE house
Soebarto, V. (2007). A study of the indoor thermal performance of rammed earth
houses. Towards solutions for a liveable future: progress, practice, performance, people:
Insulated rammed earth / reverse masonry veneer Proceedings of the 41st Annual Conference of the Architectural Science Association
ANZAScA, Geelong, Australia, November 14-16 2007, Geelong, Vic., Deakin University

14. Example: Meet user requirements
Comfort zone

15. Example: Meet target
Will the total energy use and cost exceed the target?

16. Examples: Optimisation
Soebarto, V. (2008). Performance assessment. In Chapter 2: Trends, Promotion and Performance. Bioclimatic Housing. Innovative Designs
for Warm Climates. R. Hyde (ed.). Earthscan. P. 82.

17. GJ/sq.m.year
2.7
2.8
2.9
3.1
3.2
3.3
3.4
3.5
3
Status Quo
Daylighting
R-12 Wall
Examples: Comparing solutions
Natural
Ventilation
Double Pane
Windows
Energy
Conservation
Plan
Nat-Vent &
EC Plan

18. Example: Code compliance

19. Code Compliance – Energy rating
• In Australia – Energy Efficiency Provisions were introduced in Building Code of Australia in
2003 (residential), 2006 (non residential)
• The objective is to reduce greenhouse gas emissions (by efficiently using energy)
• Residential: “A building must have, to the degree necessary, a level of thermal performance
to facilitate the efficient use of energy for artificial heating and cooling and a level of water
use performance to facilitate the efficient use of water”
• Non residential: “A building, including its services, must have, to the degree necessary,
features that facilitate the efficient use of energy appropriate to..” not only heating and
cooling but also to maintain “the systems and components appropriate to the function and
use of the building.”
• Compliance methods:
– Deemed to satisfy
– Performance approach with computer simulation:
• Stated value target (ie. Star rating or annual energy consumption)
• Reference building

20. Home Energy Rating (Australia)
The site: External environment:
Shadowing Temperature
Reflections Humidity
Solar radiation
The building: Wind
Overall thermal
resistance From weather data base
Fenestration based on Standardised
Infiltration Climatic Zone
Internal admittance
Absorptivities
The occupants:
Standardised
user profiles and
thermostat settings
Internal environment: temperature
Energy Loads: heating and cooling
Star Rating: minimum 5 Stars

21. Non rating mode (temperature profiles)

22. Energy rating mode

23. Environmental Assessments
• Assessing environmental performance of buildings, not just energy
• Voluntary
• In Australia:
– Green Star (Green Building Council of Australia):
• ”a comprehensive, national, voluntary environmental rating scheme that evaluates the
environmental design and achievements of buildings.” (www.gbcaus.org)
• built on existing systems and tools overseas (BREEAM, UK; LEED, US) and VicUrban
– NABERS (National Australian Built Environment Rating System):
• First developed by DEH, Utas and Exergy Australia; now managed by NSW Department of
Environment, Climate Change and Water)
• “a performance-based rating system for existing building”

24. Environmental Assessments
• Green Star evaluates:
• Management
• Indoor Environment Quality
• Energy  based on simulation/prediction, then rated with ABGR/NABERS
• Transport
• Water
• Materials
• Land Use & Ecology
• Emissions
• Innovation

25. Environmental Assessments

26. Environmental Assessments
One Star 10 - 19 pts
Two Star 20 - 29 pts
Three Star 30 - 44 pts
Four Star 45 - 59 pts Best Practice
Five Star 60 - 74 pts Australian Excellence
Six Star 75+ pts World Leader
http://www.sensational-adelaide.com/index.php?Itemid=4&id=213&option=com_content&task=view
http://www.designbuild-network.com/projects/tower1/tower12.html
http://www.sensational-adelaide.com/index.php?Itemid=4&id=12&option=com_content&task=view

27. Environmental Assessments
• NABERS:
• For homes: energy, water
• For offices: energy (ABGR), water, waste, indoor environment
• For retail: energy, water (in a development stage)
• Base one actual performance /records

28. Simulation vs Actual
What we found:
• Large discrepancies often occur between simulated and actual performance
• Star ratings do not correlate with actual performance

29. Simulation vs Actual (residential)
Previous studies to look at correlation between AccuRate predictions and actual heating and
cooling by Williamson et al. 2001 (31 houses) and Williamson et al. 2007 (22 houses) show that
there is no correlation between Star rating and energy use or GHG produced.

30. Simulation vs Actual (residential)
Williamson, T. J., O'Shea, S., & Menadue, V. (2001). NatHERS: Science and Non-Science. In W. Osterhaus & J. McIntosh (Eds.), Proc. of 35th ANZAScA
Conference. School of Architecture, Victoria University of Wellington, NZ: Australia and New Zealand Architectural Science Association.

31. Simulation vs Actual (residential)
House 1 House 2 House 3

32. Simulation vs Actual (residential)
HOUSE 1 HOUSE 2 HOUSE 3
STARS 3.4 Stars (of 10) 6.1 Stars 4.5 Stars
Predicted heating “energy” 12.57 GJ 10.28 GJ 17.7 GJ
„Actual‟ heating energy 8.93 GJ total 5.76 GJ minimal
Predicted cooling “energy” 5.6 GJ 1.7 GJ 2 GJ
„Actual‟ cooling energy 0 0 0
heating cooling
8.93 (TOTAL)
House 1 House 1
12.57 5.6
5.76
House 2 House 2
10.28 1.7
House 3 House 3
17.7 2
0 5 10 15 20 0 5 10 15 20
Predicted 'Actual' Predicted Actual

33. Simulation vs Actual (Nat-Vent houses)
160
Actual Heating & Cooling (MJ/m2)
140
120
100
80
60 y = 3.3747x + 55.887
R² = 0.0115
40
20
0
0 1 2 3 4 5 6 7
Star Rating
Star rating vs Actual Heating & Cooling in
non AC houses*
* Based on monitoring work by Soebarto (1999 – 2006)

34. Simulation vs Actual (Commercial)
(Bannister, P. 2009. Why good buildings go bad while some are just born that way. Equilibrium, Feb., pp. 24-32)

35. Simulation vs Actual (Commercial)
• Torcellini et al. (2004) – reviewed 6 high performance building in USA performed worse than
predicted
• Diamond et al. (2006) – reviewed 21 LEED certified buildings, on average 1% better than
predicted but with large variability
• Owens, Turner and Frankel (2008) – reviewed 121 LEED certified building, on average 25% energy
savings but with large variability (25% perform worse than expected)
• Abbaszabeh et al. (2006), Bunn (2007), Leaman et al. (2007), Paevere et al. (2008) – POE of green
vs conventional buildings showed that green occupants have higher satisfaction in green buildings
except for noise control and overall lighting
Torcellini, P. A., Deru, M., Griffith, B., Long, N., Pless, S., Judkoff, R. and Crawley, D. (2004). Lessons learned from the field evaluation of six high-
performance buildings. ACEEE Summer Study on Energy Efficiency of Buildings, California.
Diamond, R., Opitz, M., Hicks, T., Von Neida, B. and Herrara, S. (2006). Evaluating the energy performance of the first generation of LEED-certified
commercial buildings.ACEEE Summer Study on Energy Efficiency in Buildings: 3/41-3/52.
Owens, B, Frankel, M. and Turner, C. The Energy Performance of LEED Buildings. National Building Institute and USGBC. Available
http://www.newbuildings.org/downloads/LEED_presentation_11-13s.pdf. Accessed 18 October 2009.
Abbaszadeh, S., L. Zagreus, D. Lehrer and C. Huizenga, 2006. Occupant Satisfaction with Indoor Environmental Quality in Green Buildings. Proceedings,
Healthy Buildings 2006, Vol. III, 365-370, Lisbon, Portugal, June.
Leaman, A., Thomas, L. and Vandenberg, M. (2007). "'Green" buildings: What Australian building users are saying." Ecolibrium vol. 6, no. No 10, pp. 22-
30.
Paevere, P.*, Brown, S.*, Leaman, A.*, Luther, M. and Adams, R.* (2008) Indoor Environment Quality and Occupant Productivity in the CH2 Building, in
Greg Foliente, Thomas Luetzkendorf, Peter Newton and Phillip Paevere (eds), Proceedings of the 2008 International Scientific Committee World
Sustainable Building Conference (SB08), pp. 222-229, Cooperative Research Centre for Construction Innovation, Australia

36. Why different?
DESIGN & SIMULATION
• Problems in design (esp. in commercial buildings) – in reality the systems selected
are not as efficient as predicted
• Not all operational issues are taken into account in design and simulation
• Not all appliances (plug loads) are taken into account in simulation model
• Oversizing
• Conflicts between many design briefs
CONSTRUCTION AND COMMISSIONING
• Final as-built buildings differ from the one simulated
• Omission of important parts due to costs
• Buildings not commissioned properly, resulting in knowledge transfer gap
OPERATION
• Actual occupancy different from prediction
• (Experimental) technologies not perform as expected/predicted
• Systems are too complex, vulnerable for errors in operation
• Poor maintenance, poor operation
Newsham, B. (2009). Post-occupancy evaluation of energy and indoor environment quality in green buildings: a review. NRCC-51211.
National Research Council Canada
Bannister, P. 2009. Why good buildings go bad while some are just born that way. Equilibrium, Feb., pp. 24-32.
Bordass, B. 2009. Building performance in the age of consequences. Proceedings of Building Simulation 2009. International Building
Performance Simulation Association, Glasgow, 27-30 July.

37. Why different?
This was not taken into
account
St Lucia House

38. Suggestions
DESIGN
• Naturally ventilated house designs need to be assessed differently
• Use profiles in the simulation need to reflect what actually happens
• Conduct sensitivity analysis to see the impact of possible changes in operation
CONSTRUCTION AND COMMISSIONING
• Address and solve problems as described
OPERATION
• Address and solve problems as described

39. Sensitivity analysis with simulation
13000
35.0%
12000
30.0%
Predicted Annual Energy Use (kWh)
Difference from Base Case 11000
25.0%
10000
20.0%
9000
15.0%
Base case: 8000
10.0%
5.0%
7000
Wall: R2.5
Roof: R3.5
0.0%
6000
Double glazed
Temp 22-26 Temp 22-24 Window 20% Window 50% Base + Appl. Last + Appl.
Temp 21-26 Temp 22-26 Temp 22-24 Window 20% Window 50% Base + Appl. Last + Appl.
Temp: 21 (winter) 26 (summer) open
open open
open
Appliances: 7.5 W/m2

40. Sensitivity analysis with simulation
L/h=1 no overhang overhangs
200 lux 500 lux daylighting
30% 60% glazing
1 l/s/sqm 10 l/s/sqm nat ventilation
20 W/sqm 40 W/sqm lights&power
23.5 deg C 20.5 deg C AC temp
+/- 3 deg C +/- 1.5 deg C AC range
10 sqm/person 8 sqm/person occ density
9-8 0.7 occupancy 9-6 full occupancy occ profile
opaque blinds translucent blinds retrofit blinds
@10m neighbours @ 'real' distances neighbours
low-e single pane tinted single pane + hi U non-green
-20% -10% 0% 10% 20% 30% 40% 50%
Sensitivity range in annual emissions
PEARCE, L. (2006) A systemic approach to the sensitivity analysis of the energy performance of a multi story office
building. In Investigating the Roles and Challenges of Building Performance Simulation in Achieving a Sustainable
Built Environment: Proceedings of the IBPSA Australasia 2006 Conference. pp 51-58.

41. Conclusion
• Don’t believe that building design that is simulated and rated well means the building will
perform well in reality.
• Discrepancies between simulated/rated and actual performance do occur and can be quite
significant.
• Will simulation-based assessments and decisions save our built environment?
Yes, but only if the problems are addressed and the following occurs after the building is
built:
– Fine tuning of the building systems
– Continuous monitoring
– Proper operation and maintenance
– Educating the users.