5,013 research outputs found
Performance assessment of urban precinct design: a scoping study
Executive Summary: Significant advances have been made over the past decade in the development of scientifically and industry accepted tools for the performance assessment of buildings in terms of energy, carbon, water, indoor environment quality etc. For resilient, sustainable low carbon urban development to be realised in the 21st century, however, will require several radical transitions in design performance beyond the scale of individual buildings. One of these involves the creation and application of leading edge tools (not widely available to built environment professions and practitioners) capable of being applied to an assessment of performance across all stages of development at a precinct scale (neighbourhood, community and district) in either greenfield, brownfield or greyfield settings. A core aspect here is the development of a new way of modelling precincts, referred to as Precinct Information Modelling (PIM) that provides for transparent sharing and linking of precinct object information across the development life cycle together with consistent, accurate and reliable access to reference data, including that associated with the urban context of the precinct.
Neighbourhoods are the âbuilding blocksâ of our cities and represent the scale at which urban design needs to make its contribution to city performance: as productive, liveable, environmentally sustainable and socially inclusive places (COAG 2009). Neighbourhood design constitutes a major area for innovation as part of an urban design protocol established by the federal government (Department of Infrastructure and Transport 2011, see Figure 1). The ability to efficiently and effectively assess urban design performance at a neighbourhood level is in its infancy.
This study was undertaken by Swinburne University of Technology, University of New South Wales, CSIRO and buildingSMART Australasia on behalf of the CRC for Low Carbon Living
improving query performance using distributed computing
Data warehouses are used to store large amounts of data. This data is often
used for On-Line Analytical Processing (OLAP) where short response times are
essential for on-line decision support. One of the most important requirements
of a data warehouse server is the query performance. The principal aspect from
the user perspective is how quickly the server processes a given query: âthe
data warehouse must be fastâ. The main focus of our research is finding
adequate solutions to improve query response time of typical OLAP queries and
improve scalability using a distributed computation environment that takes
advantage of characteristics specific to the OLAP context. Our proposal
provides very good performance and scalability even on huge data warehouses
- âŠ