Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Procurement Case Study and Decision-making Strategies

Objectives The procurement research of Sydney Opera House FM Exemplar Project aims to develop innovative methods and guidelines for the procurement of FM services, applicable to iconic and / or performing arts centre facilities, or facilities with similar FM functions. The initial procurement report in June 2005 analysed the strategic objectives and operational requirements that provide ‘demand statements’ as evaluation criteria in the service procurement process. The subsequent interim procurement report in September 2005 discussed the elements contributing to the criteria for decision-making in the service procurement process. This procurement report concentrates on the research on procurement strategies and innovative methods using a case study approach. The objectives of this report are: • to investigate service procurement methods and process in iconic and/or performing arts centre facilities; • to showcase FM innovation in Sydney Opera House through a case study; • to establish a preliminary decision-making framework and guidelines for selection of appropriate FM procurement routes to provide a useful model for FM community. Findings Findings from this procurement research are presented as follows. • FM innovation and experience of Sydney Opera House • Innovative procurement methods and processes, drawn from a case study of Sydney Opera House as exemplar • An integrated performance framework to link maintenance service functions to high level organisational objective and strategies • Procurement methods and contract outcomes, focusing on building maintenance and cleaning services of Sydney Opera House • Multi-dimensional assessment of Service Providers • General decision-making strategies and guidelines for selection of appropriate FM procurement routes Further Research Whilst the Sydney Opera House case study emphasises the experience of Sydney Opera House, a study of procurement strategies and methods from published research and FM good practice will supply facilities managers with alternative procurement routes. Further research on the procurement theme will develop a final decision-making model for the procurement of FM services, drawn from the evaluation of the case study outcomes, as well as FM good practice and findings from current published research.

Final Report : learning system for life prediction of infrastructure

The project has further developed two programs for the industry partners related to service life prediction and salt deposition. The program for Queensland Department of Main Roads which predicts salt deposition on different bridge structures at any point in Queensland has been further refined by looking at more variables. It was found that the height of the bridge significantly affects the salt deposition levels only when very close to the coast. However the effect of natural cleaning of salt by rainfall was incorporated into the program. The user interface allows selection of a location in Queensland, followed by a bridge component. The program then predicts the annual salt deposition rate and rates the likely severity of the environment. The service life prediction program for the Queensland Department of Public Works has been expanded to include 10 common building components, in a variety of environments. Data mining procedures have been used to develop the program and increase the usefulness of the application. A Query Based Learning System (QBLS) has been developed which is based on a data-centric model with extensions to provide support for user interaction. The program is based on number of sources of information about the service life of building components. These include the Delphi survey, the CSIRO Holistic model and a school survey. During the project, the Holistic model was modified for each building component and databases generated for the locations of all Queensland schools. Experiments were carried out to verify and provide parameters for the modelling. These included instrumentation of a downpipe, measurements on pH and chloride levels in leaf litter, EIS measurements and chromate leaching from Colorbond materials and dose tests to measure corrosion rates of new materials. A further database was also generated for inclusion in the program through a large school survey. Over 30 schools in a range of environments from tropical coastal to temperate inland were visited and the condition of the building components rated on a scale of 0-5. The data was analysed and used to calculate an average service life for each component/material combination in the environments, where sufficient examples were available.

Supporting ICT diffusion in Australian construction organisations

Construction organisations comprise geographically dispersed virtually-linked suborganisations that work together to realise projects. They increasingly do so using information and communication technology (ICT) to communicate, coordinate their activities and to solve complex problems. One salient problem they face is how to effectively use requisite ICT tools. One important tool at their disposal is the self-help group, a body of people that organically spring up to solve shared problems. The more recognised term for this organisational form is a community of practice (COP). COPs generate knowledge networks that enhance and sustain competitive advantage and they are also used to help COP members actually use ICT tools. Etienne Wenger defines communities of practice as “groups of people informally bound together by shared expertise and passion for a joint enterprise” (Wenger and Snyder 2000, p139). This ‘chicken-or-egg’ issue about needing a COP to use the tools that are needed to effective broaden COPs (beyond co-located these groups) led us to explore how best to improve the process of ICT diffusion through construction organisations— primarily using people supported by technology that improves knowledge sharing. We present insights gained from recent PhD research results in this area. A semistructured interview approach was used to collect data from ICT strategists and users in the three large Australian construction organisations that are among the 10 or so first tier companies by annual dollar turnover in Australia. The interviewees were categorised into five organisational levels: IT strategist, implementer, project or engineering manager, site engineer and foreman. The focus of the study was on the organisation and the way that it implements ICT diffusion of a groupware ICT diffusion initiative. Several types of COP networks from the three Australian cases are identified: withinorganisation COP; institutional, implementer or technical support; project manager/engineer focussed; and collegial support. Also, there are cross-organisational COPs that organically emerge as a result of people sharing an interest or experience in something significant. Firstly, an institutional network is defined as a strategic group, interested in development of technology innovation within an organisation. This COP principally links business process domain experts with an ICT strategist.

Ultrafine particles in indoor air of a school : possible role of secondary organic aerosols

The aim of this work was to investigate ultrafine particles (< 0.1 μm) in primary school classrooms, in relation to the classrooms activities. The investigations were conducted in three classrooms during two measuring campaigns, which together encompassed a period of 60 days. Initial investigations showed that under the normal operating conditions of the school there were many occasions in all three classrooms where indoor particle concentrations increased significantly compared to outdoor levels. By far the highest increases in the classroom resulted from art activities (painting, gluing and drawing), at times reaching over 1.4 x 105 particle cm-3. The indoor particle concentrations exceeded outdoor concentrations by approximately one order of magnitude, with a count median diameter ranging from 20-50 nm. Significant increases also occurred during cleaning activities, when detergents were used. GC-MS analysis conducted on 4 samples randomly selected from about 30 different paints and glues, as well as the detergent used in the school, showed that d-limonene was one of the main organic compounds of the detergent, however, it was not detected in the samples of the paints and the glue. Controlled experiments showed that this monoterpene, emitted from the detergent, reacted with O3 (at outdoor ambient concentrations ranging from 0.06-0.08ppm) and formed secondary organic aerosols. Further investigations to identify other liquids which may be potential sources of the precursors of secondary organic aerosols, were outside the scope of this project, however, it is expected that the problem identified by this study could be more widely spread, since most primary schools use liquid materials for art classes, and all schools use detergents for cleaning. Further studies are therefore recommended to better understand this phenomenon and also to minimize school children exposure to ultrafine particles from these indoor sources.

Factors affecting reproductive performance of the prawn, Penaeus monodon

The growth of the Penaeus monodon prawn aquaculture industry in Australia is hampered by a reliance on wild-caught broodstock. This species has proven difficult to breed from if broodstock are reared in captivity. Studies were therefore carried out to investigate factors controlling reproduction and influencing egg quality. Results of the studies revealed that patterns of nutrient accumulation during early ovary development are altered by captive conditions, possibly contributing to reduce larval quality. The sinus gland hormones were shown, together with the environment, to regulate two stages of ovary development. In a separate study it was further revealed that the hormone methyl farnesoate (MF) could negatively regulate the final stages of ovary development. Lastly it was shown that broodstock reared in captivity are less likely to mate and that this is due to inherent problems in both the male and the female prawns.

Natural enemies of Paropsis atomaria Olivier (Coleoptera: Chrysomelidae) in south-eastern Queensland eucalypt plantations

Abstract A field survey for natural enemies of Paropsis atomaria was conducted at two south-eastern Queensland Eucalyptus cloeziana plantation sites during 2004–2005. Primary egg and larval parasitoids and associated hyperparasitoids were identified to genus or species, and parasitism rates were determined throughout the season. Predators were identified to family level but their impact was not quantified. P. atomaria adults were also examined as potential hosts for parasitic mites and nematodes. An undescribed species of Neopolycystus (Pteromalidae) was the major primary egg parasitoid species reared from egg batches, parasitising half of all egg batches collected. Three hyperparasitoid species (Baeoanusia albifunicle (Encyrtidae), Neblatticida sp. (Encyrtidae) and Aphaneromella sp. (Platygasteridae) were present, representing around one-quarter to one-third of all emergent wasps; this is the first host association record for Neopolycystus–B. albifunicle. In contrast to populations of P. atomaria from the Australian Capital Territory, primary larval parasitism was very low, around 1%, and attributable only to the tachinid flies Anagonia sp. and Paropsivora sp. However, the presence of the sit-and-wait larval hyperparasitoid, Perilampus sp. (Perilampidae) was high, emerging from around 17% of tachinid pupae, with planidia infesting a further 40% of unparasitised hosts. Three species of podapolipid mites parasitised sexually mature P. atomaria adults, while no nematodes were found in this study. Spiders were the most common predators and their abundance was positively correlated with P. atomaria adult and egg numbers. Although natural enemy species composition was identical between our two study sites, significant differences in abundance and frequency were found between sites

Case-control study of early childhood caries in Australia

The aim of this case-control study of 617 children was to investigate early childhood caries (ECC) risk indicators in a non-fluoridated region in Australia. ECC cases were recruited from childcare facilities, public hospitals and private specialist clinics to source children from different socioeconomic backgrounds. Non-ECC controls were recruited from the same childcare facilities. A multinomial logistic modelling approach was used for statistical analysis. The results showed that a large percentage of children tested positive for Streptococcus mutans if their mothers also tested positive. A common risk indicator found in ECC children from childcare facilities and public hospitals was visible plaque (OR 4.1, 95% CI 1.0-15.9, and OR 8.7, 95% CI 2.3-32.9, respectively). Compared to ECC-free controls, the risk indicators specific to childcare cases were enamel hypoplasia (OR 4.2, 95% CI 1.0-18.3), difficulty in cleaning child's teeth (OR 6.6, 95% CI 2.2-19.8), presence of S. mutans (OR 4.8, 95% CI 0.7-32.6), sweetened drinks (OR 4.0, 95% CI 1.2-13.6) and maternal anxiety (OR 5.1, 95% CI 1.1-25.0). Risk indicators specific to public hospital cases were S. mutans presence in child (OR 7.7, 95% CI 1.3-44.6) or mother (OR 8.1, 95% CI 0.9-72.4), ethnicity (OR 5.6, 95% CI 1.4-22.1), and access of mother to pension or health care card (OR 20.5, 95% CI 3.5-119.9). By contrast, a history of chronic ear infections was found to be protective for ECC in childcare children (OR 0.28, 95% CI 0.09-0.82). The biological, socioeconomic and maternal risk indicators demonstrated in the present study can be employed in models of ECC that can be usefully applied for future longitudinal studies.

Field and Service Robotics Results of the 5th International Conference

The 5th International Conference on Field and Service Robotics (FSR05) was held in Port Douglas, Australia, on 29th - 31st July 2005, and brought together the worlds' leading experts in field and service automation. The goal of the conference was to report and encourage the latest research and practical results towards the use of field and service robotics in the community with particular focus on proven technology. The conference provided a forum for researchers, professionals and robot manufacturers to exchange up-to-date technical knowledge and experience. Field robots are robots which operate in outdoor, complex, and dynamic environments. Service robots are those that work closely with humans, with particular applications involving indoor and structured environments. There are a wide range of topics presented in this issue on field and service robots including: Agricultural and Forestry Robotics, Mining and Exploration Robots, Robots for Construction, Security & Defence Robots, Cleaning Robots, Autonomous Underwater Vehicles and Autonomous Flying Robots. This meeting was the fifth in the series and brings FSR back to Australia where it was first held. FSR has been held every 2 years, starting with Canberra 1997, followed by Pittsburgh 1999, Helsinki 2001 and Lake Yamanaka 2003.

Development of descriptor tools for the characterization of Australian sugar mill evaporator scale

Cleaning of sugar mill evaporators is an expensive exercise. Identifying the scale components assists in determining which chemical cleaning agents would result in effective evaporator cleaning. The current methods (based on x-ray diffraction techniques, ion exchange/high performance liquid chromatography and thermogravimetry/differential thermal analysis) used for scale characterisation are difficult, time consuming and expensive, and cannot be performed in a conventional analytical laboratory or by mill staff. The present study has examined the use of simple descriptor tests for the characterisation of Australian sugar mill evaporator scales. Scale samples were obtained from seven Australian sugar mill evaporators by mechanical means. The appearance, texture and colour of the scale were noted before the samples were characterised using x-ray fluorescence and x-ray powder diffraction to determine the compounds present. A number of commercial analytical test kits were used to determine the phosphate and calcium contents of scale samples. Dissolution experiments were carried out on the scale samples with selected cleaning agents to provide relevant information about the effect the cleaning agents have on different evaporator scales. Results have shown that by simply identifying the colour and the appearance of the scale, the elemental composition and knowing from which effect the scale originates, a prediction of the scale composition can be made. These descriptors and dissolution experiments on scale samples can be used to provide factory staff with an on-site rapid process to predict the most effective chemicals for chemical cleaning of the evaporators.

Membrane filtration of clarified juice

A membrane filtration plant using suitable micro or ultra-filtration membranes has the potential to significantly increase pan stage capacity and improve sugar quality. Previous investigations by SRI and others have shown that membranes will remove polysaccharides, turbidity and colloidal impurities and result in lower viscosity syrups and molasses. However, the conclusion from those investigations was that membrane filtration was not economically viable. A comprehensive assessment of current generation membrane technology was undertaken by SRI. With the aid of two pilot plants provided by Applexion and Koch Membrane Systems, extensive trials were conducted at an Australian factory using clarified juice at 80–98°C as feed to each pilot plant. Conditions were varied during the trials to examine the effect of a range of operating parameters on the filtering characteristics of each of the membranes. These parameters included feed temperature and pressure, flow velocity, soluble solids and impurity concentrations. The data were then combined to develop models to predict the filtration rate (or flux) that could be expected for nominated operating conditions. The models demonstrated very good agreement with the data collected during the trials. The trials also identified those membranes that provided the highest flux levels per unit area of membrane surface for a nominated set of conditions. Cleaning procedures were developed that ensured the water flux level was recovered following a clean-in-place process. Bulk samples of clarified juice and membrane filtered juice from each pilot were evaporated to syrup to quantify the gain in pan stage productivity that results from the removal of high molecular weight impurities by membrane filtration. The results are in general agreement with those published by other research groups.

Green cane impact on sugar processing : ISSCT process workshop 2008

The ISSCT Process Section workshop held in Réunion 20–23 October 2008 was attended by 51 delegates from 10 countries. The theme was Green cane impact on sugar processing. The workshop provided a valuable and timely opportunity to review and discuss the impact on factory operations and performance from a green cane supply that could include significant levels of trash. It was particularly relevant to those mills that were considering options to boost their biomass intake for increased co-generation capacity. Several of the speakers related their experiences with processing ‘whole of crop’ cane supplies through the factory. Speakers detailed the problems and increased losses that were incurred when processing cane with high trash levels. The consensus of the delegates was that the best scenario would involve a cane-cleaning plant at the factory so that only clean cane would be processed through the factory. The forum recommended that more research was required to address the issues of increased impurities in the process streams associated with high trash levels. Site visits to the two factories and a cane-delivery station were arranged as part of the workshop.

Development and evaluation of hydrocarbon sorbent materials with the aid of chemometrics

Hydrocarbon spills on roads are a major safety concern for the driving public and can have severe cost impacts both on pavement maintenance and to the economy through disruption to services. The time taken to clean-up spills and re-open roads in a safe driving condition is an issue of increasing concern given traffic levels on major urban arterials. Thus, the primary aim of the research was to develop a sorbent material that facilitates rapid clean-up of road spills. The methodology involved extensive research into a range of materials (organic, inorganic and synthetic sorbents), comprehensive testing in the laboratory, scale-up and field, and product design (i.e. concept to prototype). The study also applied chemometrics to provide consistent, comparative methods of sorbent evaluation and performance. In addition, sorbent materials at every stage were compared against a commercial benchmark. For the first time, the impact of diesel on asphalt pavement has been quantified and assessed in a systematic way. Contrary to conventional thinking and anecdotal observations, the study determined that the action of diesel on asphalt was quite rapid (i.e. hours rather than weeks or months). This significant finding demonstrates the need to minimise the impact of hydrocarbon spills and the potential application of the sorbent option. To better understand the adsorption phenomenon, surface characterisation techniques were applied to selected sorbent materials (i.e. sand, organo-clay and cotton fibre). Brunauer Emmett Teller (BET) and thermal analysis indicated that the main adsorption mechanism for the sorbents occurred on the external surface of the material in the diffusion region (sand and organo-clay) and/or capillaries (cotton fibre). Using environmental scanning electron microscopy (ESEM), it was observed that adsorption by the interfibre capillaries contributed to the high uptake of hydrocarbons by the cotton fibre. Understanding the adsorption mechanism for these sorbents provided some guidance and scientific basis for the selection of materials. The study determined that non-woven cotton mats were ideal sorbent materials for clean-up of hydrocarbon spills. The prototype sorbent was found to perform significantly better than the commercial benchmark, displaying the following key properties: • superior hydrocarbon pick-up from the road pavement; • high hydrocarbon retention capacity under an applied load; • adequate field skid resistance post treatment; • functional and easy to use in the field (e.g. routine handling, transportation, application and recovery); • relatively inexpensive to produce due to the use of raw cotton fibre and simple production process; • environmentally friendly (e.g. renewable materials, non-toxic to environment and operators, and biodegradable); and • rapid response time (e.g. two minutes total clean-up time compared with thirty minutes for reference sorbents). The major outcomes of the research project include: a) development of a specifically designed sorbent material suitable for cleaning up hydrocarbon spills on roads; b) submission of patent application (serial number AU2005905850) for the prototype product; and c) preparation of Commercialisation Strategy to advance the sorbent product to the next phase (i.e. R&D to product commercialisation).

Investigating the hydrodynamic performance of a gross pollutant trap

Field studies show that the internal screens in a gross pollutant trap (GPT) are often clogged with organic matter, due to infrequent cleaning. The hydrodynamic performance of a GPT with fully blocked screens was comprehensively investigated under a typical range of onsite operating conditions. Using an acoustic Doppler velocimeter (ADV), velocity profiles across three critical sections of the GPT were measured and integrated to examine the net fluid flow at each section. The data revealed that when the screens are fully blocked, the flow structure within the GPT radically changes. Consequently, the capture/retention performance of the device rapidly deteriorates. Good agreement was achieved between the experimental and the previous 2D computational fluid dynamics (CFD) velocity profiles for the lower GPT inlet flow conditions.