Sustainable subdivisions – review of technologies for integrated water services

Water is a current major global, national and local issue. Historic drought and unprecedented restriction levels are now substantially influencing almost all Australia’s major cities. Residential design and adoption of appropriate technologies plays a key role in urban water efficiency. This project, the first of the CRC-CI Sustainable subdivisions program with a focus on water, explores the existing technologies available for sustainable suburbs.

Report : enabling team collaboration with pervasive and mobile computing : cost benefit analysis methodology

Construction is an information intensive industry in which the accuracy and timeliness of information is paramount. It observed that the main communication issue in construction is to provide a method to exchange data between the site operation, the site office and the head office. The information needs under consideration are time critical to assist in maintaining or improving the efficiency at the jobsite. Without appropriate computing support this may increase the difficulty of problem solving. Many researchers focus their research on the usage of mobile computing devices in the construction industry and they believe that mobile computers have the potential to solve some construction problems that leads to reduce overall productivity. However, to date very limited observation has been conducted in terms of the deployment of mobile computers for construction workers on-site. By providing field workers with accurate, reliable and timely information at the location where it is needed, it will support the effectiveness and efficiency at the job site. Bringing a new technology into construction industry is not only need a better understanding of the application, but also need a proper preparation of the allocation of the resources such as people, and investment. With this in mind, an accurate analysis is needed to provide clearly idea of the overall costs and benefits of the new technology. A cost benefit analysis is a method of evaluating the relative merits of a proposed investment project in order to achieve efficient allocation of resources. It is a way of identifying, portraying and assessing the factors which need to be considered in making rational economic choices. In principle, a cost benefit analysis is a rigorous, quantitative and data-intensive procedure, which requires identification all potential effects, categorisation of these effects as costs and benefits, quantitative estimation of the extent of each cost and benefit associated with an action, translation of these into a common metric such as dollars, discounting of future costs and benefits into the terms of a given year, and summary of all cost and benefit to see which is greater. Even though many cost benefit analysis methodologies are available for a general assessment, there is no specific methodology can be applied for analysing the cost and benefit of the application of mobile computing devices in the construction site. Hence, the proposed methodology in this document is predominantly adapted from Baker et al. (2000), Department of Finance (1995), and Office of Investment Management (2005). The methodology is divided into four main stages and then detailed into ten steps. The methodology is provided for the CRC CI 2002-057-C Project: Enabling Team Collaboration with Pervasive and Mobile Computing and can be seen in detail in Section 3.

Report : review of the literature : maintenance and rehabilitation costs for roads (Risk-based Analysis)

Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C.

Report : development of a methodology for assessing variation in maintenance and rehabilitation costs

In the previous research CRC CI 2001-010-C “Investment Decision Framework for Infrastructure Asset Management”, a method for assessing variation in cost estimates for road maintenance and rehabilitation was developed. The variability of pavement strength collected from a 92km national highway was used in the analysis to demonstrate the concept. Further analysis was conducted to identify critical input parameters that significantly affect the prediction of road deterioration. In addition to pavement strength, rut depth, annual traffic loading and initial roughness were found to be critical input parameters for road deterioration. This report presents a method developed to incorporate other critical parameters in the analysis, such as unit costs, which are suspected to contribute to a certain degree to cost estimate variation. Thus, the variability of unit costs will be incorporated in this analysis. Bruce Highway located in the tropical east coast of Queensland has been identified to be the network for the analysis. This report presents a step by step methodology for assessing variation in road maintenance and rehabilitation cost estimates.

Report : stochastic analysis of road asset data for maintenance cost prediction

Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.

Final report : a software diagnostic tool for evaluating distress mechanisms in bridges exposed to aggressive environments

Durability issues of reinforced concrete construction cost millions of dollars in repair or demolition. Identification of the causes of degradation and a prediction of service life based on experience, judgement and local knowledge has limitations in addressing all the associated issues. The objective of this CRC CI research project is to develop a tool that will assist in the interpretation of the symptoms of degradation of concrete structures, estimate residual capacity and recommend cost effective solutions. This report is a documentation of the research undertaken in connection with this project. The primary focus of this research is centred on the case studies provided by Queensland Department of Main Roads (QDMR) and Brisbane City Council (BCC). These organisations are endowed with the responsibility of managing a huge volume of bridge infrastructure in the state of Queensland, Australia. The main issue to be addressed in managing these structures is the deterioration of bridge stock leading to a reduction in service life. Other issues such as political backlash, public inconvenience, approach land acquisitions are crucial but are not within the scope of this project. It is to be noted that deterioration is accentuated by aggressive environments such as salt water, acidic or sodic soils. Carse, 2005, has noted that the road authorities need to invest their first dollars in understanding their local concretes and optimising the durability performance of structures and then look at potential remedial strategies.

Upper body musculoskeletal disorders among Australian occupational therapy students

Although upper body musculoskeletal disorders (MSDs) represent an increasingly important issue for university students, few if any studies have targeted the occupational therapy faculty. Given this dearth of information, it was considered necessary to investigate a cross-section of Australian occupational therapy students by means of an established questionnaire survey. Completed replies were obtained from 95.7%, 100% and 97.7% (n = 44, 55 and 48) of students in the first, second and fourth years of a large occupational therapy school in northern Queensland, Australia.---------- The 12-month period prevalence of MSDs was as follows: neck (67.4%), shoulder (46.3%) and upper back (39.5%). Three-quarters of all students (75.5%) reported an MSD occurring in at least one of these body regions. Over half (56.5%) reported an MSD over 2 days' duration in the past year. Almost 40% (39.5%) reported an MSD that had affected their daily life, while one-quarter (25.2%) needed some type of treatment.---------- Logistic regression indicated that students aged over 21 years were almost four times more likely to report shoulder-related MSD (OR 3.7, 95%CI: 1.4-10.2). Year of study in the occupational therapy course was another important MSD correlate, with adjusted odds ratios ranging from 3.3 at the upper back (OR 3.3, 95%CI: 1.2-9.6) to 10.9 at the neck (OR 10.9, 95%CI: 3.2-43.8). Computer usage also incurred a certain degree of risk, with students who spent over 5 hours per week on the computer having an increased risk of MSD at the neck (OR 5.0, 95%CI: 1.3-21.5) and shoulder (OR 4.7, 95%CI: 1.4-18.3).---------- Overall, this study suggests that Australian occupational therapy students have a large burden from MSDs in the upper body region, even more so than other student groups and some working populations. Since the distribution of MSD risk is not uniform among them, interventions to help reduce these conditions need to be carefully targeted. Further longitudinal investigations would also be useful in determining the mechanisms and contributory factors for MSDs among this unique student population.

Determinants of pre-hospital care non-usage for patients with emergency care needs [including commentary by Snooks H.]

Objective-To establish the demographic, health status and insurance determinants of pre-hospital ambulance non-usage for patients with emergency medical needs. Methods-Triage category, date of birth, sex, marital status, country of origin, method and time of arrival, ambulance insurance status, diagnosis, and disposal were collected for all patients who presented over a four month period (n=10 229) to the emergency department of a major provincial hospital. Data for patients with urgent (n=678) or critical care needs (n=332) who did not use pre-hospital care were analysed using Poisson regression. Results-Only a small percentage (6.6%) of the total sample were triaged as having urgent medical needs or critical care needs (3.2%). Predictors of usage for those with urgent care needs included age greater than 65 years (prevalence ratio (PR)=0.54; 95% confidence interval (CI)= 0.35 to 0.83), being admitted to intensive care or transferred to another hospital (PR=0.62; 95% CI=0.44 to 0.89) or ward (PR=0.72; 95% CI=0.56 to 0.93) and ambulance insurance status (PR=0.67; 95% CI=052 to 0.86). Sex, marital status, time of day and country of origin were not predictive of usage and non-usage. Predictors of usage for those with critical care needs included age 65 years or greater (PR=0.45; 95% CI=0.25 to 0.81) and a diagnosis of trauma (PR=0.49; 95% CI=0.26 to 0.92). A non-English speaking background was predictive of non-usage (PR=1.98; 95% CI=1.06 to 3.70). Sex, marital status, time of day, triage and ambulance insurance status were not predictive of non-usage. Conclusions-Socioeconomic and medical factors variously influence ambulance usage depending on the severity or urgency of the medical condition. Ambulance insurance status was less of an influence as severity of condition increased suggesting that, at a critical level of urgency, patients without insurance are willing to pay for a pre-hospital ambulance service.

HVAC system size – getting it right

There is evidence that many heating, ventilating & air conditioning (HVAC) systems, installed in larger buildings, have more capacity than is ever required to keep the occupants comfortable. This paper explores the reasons why this can occur, by examining a typical brief/design/documentation process. Over-sized HVAC systems cost more to install and operate and may not be able to control thermal comfort as well as a “right-sized” system. These impacts are evaluated, where data exists. Finally, some suggestions are developed to minimise both the extent of, and the negative impacts of, HVAC system over-sizing, for example: • Challenge “rules of thumb” and/or brief requirements which may be out of date. • Conduct an accurate load estimate, using AIRAH design data, specific to project location, and then resist the temptation to apply “safety factors • Use a load estimation program that accounts for thermal storage and diversification of peak loads for each zone and air handling system. • Select chiller sizes and staged or variable speed pumps and fans to ensure good part load performance. • Allow for unknown future tenancies by designing flexibility into the system, not by over-sizing. For example, generous sizing of distribution pipework and ductwork will allow available capacity to be redistributed. • Provide an auxiliary tenant condenser water loop to handle high load areas. • Consider using an Integrated Design Process, build an integrated load and energy use simulation model and test different operational scenarios • Use comprehensive Life Cycle Cost analysis for selection of the most optimal design solutions. This paper is an interim report on the findings of CRC-CI project 2002-051-B, Right-Sizing HVAC Systems, which is due for completion in January 2006.

Necessary skills and practices required for effective participation in high bandwidth design team activities

Technology is continually changing, and evolving, throughout the entire construction industry; and particularly in the design process. One of the principal manifestations of this is a move away from team working in a shared work space to team working in a virtual space, using increasingly sophisticated electronic media. Due to the significant operating differences when working in shared and virtual spaces adjustments to generic skills utilised by members is a necessity when moving between the two conditions. This paper reports an aspect of a CRC-CI research project based on research of ‘generic skills’ used by individuals and teams when engaging with high bandwidth information and communication technologies (ICT). It aligns with the project’s other two aspects of collaboration in virtual environments: ‘processes’ and ‘models’. The entire project focuses on the early stages of a project (i.e. design) in which models for the project are being developed and revised. The paper summarises the first stage of the research project which reviews literature to identify factors of virtual teaming which may affect team member skills. It concludes that design team participants require ‘appropriate skills’ to function efficiently and effectively, and that the introduction of high band-width technologies reinforces the need for skills mapping and measurement.

The journey to delivered value in Australian procurement

In line with developments overseas Australian clients are turning to considerations of value in project procurement. Until the 1980s the industry operated in a largely traditional manner however the extremely adversarial behaviour exhibited during towards the end of the decade led to a number of significant events and initiatives including the publication of “No Dispute”, the Gyles Royal Commission into the Building Industry, the Construction Industry Development Agency (CIDA) and the work of the Australian Procurement and Construction Council (APCC). A number of research projects in progress in the CRC for Construction Innovation (CRC CI) are focussing on the assessment of value and methodologies to support the delivery of value in the procurement and management of engineering and construction projects. This paper charts the emergence of several key drivers in the process and illustrates how they can be integrated into a comprehensive Decision Support System that balances value to stakeholders with project imperatives and incorporates a lessons learned data base which enriches the decision making process to optimise delivery method design and selection.

Collaboration using BIM : results of cooperative research centre for construction innovation projects

This paper discusses the issues with sharing information between different disciplines in collaborative projects. The focus is on the information itself rather than the wider issues of collaboration. A range of projects carried out by the Cooperative Research Centre for Construction Innovation (CRC CI) in Australia is used to illustrate the issues.

Contemporary New Zealand coefficients for the Trauma Injury Severity Score: TRISS(NZ)

Aims – To develop local contemporary coefficients for the Trauma Injury Severity Score in New Zealand, TRISS(NZ), and to evaluate their performance at predicting survival against the original TRISS coefficients. Methods – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until presentation at Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Coefficients were estimated using ordinary and multilevel mixed-effects logistic regression models. Results – 1735 eligible patients were identified, 1672 (96%) injured from a blunt mechanism and 63 (4%) from a penetrating mechanism. For blunt mechanism trauma, 1250 (75%) were male and average age was 38 years (range: 15-94 years). TRISS information was available for 1565 patients of whom 204 (13%) died. Area under the Receiver Operating Characteristic (ROC) curves was 0.901 (95%CI: 0.879-0.923) for the TRISS(NZ) model and 0.890 (95% CI: 0.866-0.913) for TRISS (P<0.001). Insufficient data were available to determine coefficients for penetrating mechanism TRISS(NZ) models. Conclusions – Both TRISS models accurately predicted survival for blunt mechanism trauma. However, TRISS(NZ) coefficients were statistically superior to TRISS coefficients. A strong case exists for replacing TRISS coefficients in the New Zealand benchmarking software with these updated TRISS(NZ) estimates.

Using a longitudinal model to estimate the effect of methicillin-resistant staphylococcus aureus infection on length of stay in an intensive care unit

Healthcare-associated methicillin-resistant Staphylococcus aureus(MRSA) infection may cause increased hospital stay or, sometimes, death. Quantifying this effect is complicated because it is a time-dependent exposure: infection may prolong hospital stay, while longer stays increase the risk of infection. We overcome these problems by using a multinomial longitudinal model for estimating the daily probability of death and discharge. We then extend the basic model to estimate how the effect of MRSA infection varies over time, and to quantify the number of excess ICU days due to infection. We find that infection decreases the relative risk of discharge (relative risk ratio = 0.68, 95% credible interval: 0.54, 0.82), but is only indirectly associated with increased mortality. An infection on the first day of admission resulted in a mean extra stay of 0.3 days (95% CI: 0.1, 0.5) for a patient with an APACHE II score of 10, and 1.2 days (95% CI: 0.5, 2.0) for a patient with an APACHE II score of 30. The decrease in the relative risk of discharge remained fairly constant with day of MRSA infection, but was slightly stronger closer to the start of infection. These results confirm the importance of MRSA infection in increasing ICU stay, but suggest that previous work may have systematically overestimated the effect size.

Building information modelling : an issue of adoption and change management

Building Information Modelling (BIM) is an IT enabled technology that allows storage, management, sharing, access, update and use of all the data relevant to a project through out the project life-cycle in the form of a data repository. BIM enables improved inter-disciplinary collaboration across distributed teams, intelligent documentation and information retrieval, greater consistency in building data, better conflict detection and enhanced facilities management. While the technology itself may not be new, and similar approaches have been in use in some other sectors like Aircraft and Automobile industry for well over a decade now, the AEC/FM (Architecture, Engineering and Construction/ Facilities Management) industry is still to catch up with them in its ability to exploit the benefits of the IT revolution. Though the potential benefits of the technology in terms of knowledge sharing, project management, project co-ordination and collaboration are near to obvious, the adoption rate has been rather lethargic, inspite of some well directed efforts and availability of supporting commercial tools. Since the technology itself has been well tested over the years in some other domains the plausible causes must be rooted well beyond the explanation of the ‘Bell Curve of innovation adoption’. This paper discusses the preliminary findings of an ongoing research project funded by the Cooperative Research Centre for Construction Innovation (CRC-CI) which aims to identify these gaps and come up with specifications and guidelines to enable greater adoption of the BIM approach in practice. A detailed literature review is conducted that looks at some of the similar research reported in the recent years. A desktop audit of some of the existing commercial tools that support BIM application has been conducted to identify the technological issues and concerns, and a workshop was organized with industry partners and various players in the AEC industry for needs analysis, expectations and feedback on the possible deterrents and inhibitions surrounding the BIM adoption.