As Built Learning Exchange

Navigation

Design Based Performance Gain

Published: 04 April 2011 / Amendment 1 / BCA 2011

...excerpt only - see the bottom of the page link to download the full text.

DESIGN: VISUAL ELEMENTS THAT DRIVE PERFORMANCE GAIN

In simple terms, “Modelling software” calculates the heating and cooling loads required to condition space in the house, “design” determines the capacity of the house to “harvest” energy and “construction” determines the capacity of the house to “control” the inward and/or outward flow of energy. The house star rating is a measure the gap between deemed loads and house self-sufficiency (0-Star rating = nil, 10-Star rating = self sufficient).

In the context of this project, “design” decisions range from the house floor plan and making better orientation choices through to decisions about glazing configuration (size, orientation, shading, ventilation etc), room configuration (open or separated spaces, internal doors etc), selections (external colours, floor coverings etc).

These are the visual elements that drive performance gain (or loss).

MODELLING PROCESS AND OUTCOMES

For each of the 25 houses used in the project, Baseline House (see Sidebar Note) data was generated for eight orientations in each of the four nominated Climate Zones (see Sidebar Note).

Modelling Presumptions
The underlying presumptions that shaped the design investigation sequence were:
  • If design affects thermal performance, then comparing different plan configurations should produce indicative design based performance differences.
  • If orientation affects thermal performance, then there should be a best to worst-case performance outcome cycle.
  • If shading affects thermal performance, then the location (orientation) of a cabana or verandah should affect performance outcomes.If internal doors are added to reduce the overall thermal load (less conditioned space), then building thermal performance will improve.
  • If there are differences in the way Climate Zones “work”, then ventilation type improvements (window open area, ceiling fans) should differentiate between “insulation” and “ventilation” bias zones.
Design Type Performance Comparison
Four single storey houses were selected to test for differences in Baseline House performance that could be attributed to design. The two “indicative” design types (see Figure 1) used were:
  • Games to rear corner.
  • Narrow lot side living.

In addition to the Baseline House data, additional Modelling was done to investigate the performance impact of design changes that are likely to be made at the “sales change” stage.   The changes investigated were:

  • Cabana location and orientation.
  • Changing window configuration and glazing area.
  • Adding internal doors.
  • Left and right hand plan versions.
  • Selection changes.
Variables That Affect Performance
Variables that seem to affect design based performance improvement are:
  • Design – Whilst typical design types are nominated, individual house plans vary and these variations affect performance behaviour.
  • Climate Zone – There is little useful data available to inform designers about the climate profile that is “typical” to each Climate Zone. Project research seemed to identify indicative behaviour patterns (Bickley = low impact of cross ventilation, high impact of insulation, Swanbourne = high impact of cross ventilation, lower impact of insulation). This suggests better design outcomes could be achieved if industry was provided with better Climate Zone information.
  • Orientation – Modelling outcomes suggest that some design types have a large best to worst-case outcome gap whilst other types show little variation as the orientation changes.
  • Shading – Modelling outcomes showed houses as having a Heating load (cold house) bias. Locating windows or orienting the house to improve winter (northern) sun harvesting will be less effective if northern windows are shaded by a cabana, verandah or the like.
  • Zoning – Assessor decisions about combining or separating spaces (zones) can significantly affect performance outcomes. How the opening between rooms or spaces is designed (documented) influences assessor decision-making, as does interpreting assessment protocols that are not always easily applied to local practice design.
Assessment Data and Limitations
Given the above, the information provided is only intended as a guide as to the likely benefit that can be attributed to design decision-making. Per house assessment outcomes will vary depending on the design, orientation, material, assessment presumptions and the like.

Project data is reported as follows:

  • Figures 2(a-c) – Baseline House data in eight orientations and four Climate Zones.
  • Figure 3 – Single storey Baseline House best and worst-case orientation frequency.

For each of the Baseline Houses, three sets of thermal performance data were reported:

  • Star rating (see Sidebar Note) – BERS reports in 0.5 Star increments and AccuRate reports in 0.1 Star increments (FirstRate was not used in this project).Total MJ load (MJ/m2.annum) – the sum of reported heating and cooling loads, expressed as a MJ/m2 of conditioned floor area.
  • Heating and Cooling MJ loads – the proportion of the Total MJ load attributed to heating (winter) and cooling (summer) conditioned spaces.

Click the link below to download the full text version of the Local Practice Note: Design Based Performance Gain

Building Professional Registration or Login Required

To download the file design-based-performance-gain-amendment-1.pdf you need to login to the As-Built Learning Exchange. If you are a Building Professional and you do not have login access, you will need to register.