Preliminary tools assisting collected building performance measurements

Investigating on-site building performance in architectural science is increasing. However, the simplest forms of measurement often lack any analytical support other than presentation on a time-series plot. Here, we present instrumentation and analytical tools to assist in reporting building performance. The intention is to explore formats for observing performance of buildings based on collected data. Sometimes data are presented directly, but more often, information is revealed by calculation. We introduce examples of tools pertaining to interior-exterior climatic comparisons, occupant comfort and thermal performance, such as weather data plotted against a neutral temperature so that adaptive model comfort tolerances can be illustrated. We plot the interior and exterior air condition on the ASHRAE psychrometric chart to understand conditioning requirements. Other tools calculate the ISO 7730 (Fanger) comfort model, and an adaptive model of comfort is provided for the interior measurements alongside an 80 – 90% comfort band. These tools add value to reporting data by displaying in several formats, so the researcher can observe and report quickly and clearly on the potential of various conditioning periods within a building.A case study is presented for a house in Darwin during the wet-season.

Progress on building energy labelling techniques

The building sector consumes around 30–40 per cent of the primary energy in most developed countries. The importance of labelling buildings as a national strategy for energy efficiency is well recognized worldwide. The last 10–15 years have seen an emergence of programmes in different parts of the world. As seen in the United States, European Union, South America and Asia, there is a collection of rating systems or tools internationally, designed with the intention of evaluating the design, construction and operation of buildings. This study presents an overview and critical reflection on the progress on building energy labelling techniques in recent years. The scope of labelling, methodology and methods of implementation are discussed in detail.

TMI for urban resilience : measuring and mapping long-term climate change effects on soil moisture

The effect of climate change on the shallow expansive foundation conditions of resident dwellings is costing several hundred billion dollars worldwide. The design and costs of constructing or repairing residential footings is greatly influenced by the degree of ground movement, which is driven by the magnitude of change in soil moisture. The impacts of climate change on urban infrastructure are expected to include accelerated degradation of materials and foundations of buildings and facilities, increased ground movement, changes in ground water affecting the chemical structure of foundations, and fatigue of structures from extreme storm events. Previous research found that residential houses that were built less than five years ago have suffered major cracks and other damage caused by slab movement after record rainfall. The Thornthwaite Moisture Index (TMI) categorises climate on the basis of rainfall, temperature, potential evapotranspiration and the water holding capacity of the soil. Originally TMI was mainly used to map soil moisture conditions for agriculture but soon became a method to predict pavement and foundation changes. Few researchers have developed TMI maps for Australia, but generally, their accuracy is low or unknown, and their use is limited. The aims of this paper are: (1) To produce accurate maps of TMI for the state of Victoria for 100 years (1913 to 2012) in 20 year periods using long-term historical climatic data and advanced spatial statistics methods in GIS, and (2) Analyse the spatial and temporal changes of TMI in Victoria. Preliminary results suggest that a better understanding of climate change through long-term TMI mapping can assist urban planning and guide construction regulations towards the development of cities which are more resilient.

An early-stage design decision-support tool for selecting building assemblies to minimise a building's life cycle energy demand

The significant effects of the building industry on the natural environment are well documented and improving the environmental performance of buildings is an on-going challenge. This is particularly the case for projects with restrictive budgets and timelines and because many existing environmental assessment tools are designed to be used too late in the design process. The use of tools during the early design stages may assist in achieving greater improvements in a building’s environmental performance. However, user-friendly tools with the ability to comprehensively compare environmental information between various building assemblies and materials, which can be easily adopted during the early design stages of a project, are not readily available. This paper presents the progress to date in developing a tool which supports building designers in identifying and selecting preferred building assemblies with the aim of minimising a building’s life cycle energy demand. The tool is based on comprehensive energy performance data for a broad range of building assemblies across all Australian climate zones. Allowing for adjustments to a set of pre-defined and user-defined assemblies the designer is able to see how assemblies perform in relation to each other. This provides valuable information to support decision-making relating to minimising the life cycle energy demand of buildings.

Land management practices associated with house loss in wildfires.

Losses to life and property from unplanned fires (wildfires) are forecast to increase because of population growth in peri-urban areas and climate change. In response, there have been moves to increase fuel reduction--clearing, prescribed burning, biomass removal and grazing--to afford greater protection to peri-urban communities in fire-prone regions. But how effective are these measures? Severe wildfires in southern Australia in 2009 presented a rare opportunity to address this question empirically. We predicted that modifying several fuels could theoretically reduce house loss by 76%-97%, which would translate to considerably fewer wildfire-related deaths. However, maximum levels of fuel reduction are unlikely to be feasible at every house for logistical and environmental reasons. Significant fuel variables in a logistic regression model we selected to predict house loss were (in order of decreasing effect): (1) the cover of trees and shrubs within 40 m of houses, (2) whether trees and shrubs within 40 m of houses was predominantly remnant or planted, (3) the upwind distance from houses to groups of trees or shrubs, (4) the upwind distance from houses to public forested land (irrespective of whether it was managed for nature conservation or logging), (5) the upwind distance from houses to prescribed burning within 5 years, and (6) the number of buildings or structures within 40 m of houses. All fuel treatments were more effective if undertaken closer to houses. For example, 15% fewer houses were destroyed if prescribed burning occurred at the observed minimum distance from houses (0.5 km) rather than the observed mean distance from houses (8.5 km). Our results imply that a shift in emphasis away from broad-scale fuel-reduction to intensive fuel treatments close to property will more effectively mitigate impacts from wildfires on peri-urban communities.