Asset Intelligence: Maximising Operational Effectiveness for Digital Era . The primary aim of this project is to develop an innovative lifecycle semantic–based decision making approach through asset intelligence so as to maximize the operational effectiveness maintenance, repair and rehabilitation planning of infrastructure assets, such as concrete pavement. The research intends to address an important gap by providing logical formalisms and real-time capability to life-cycle asset information t ....Asset Intelligence: Maximising Operational Effectiveness for Digital Era . The primary aim of this project is to develop an innovative lifecycle semantic–based decision making approach through asset intelligence so as to maximize the operational effectiveness maintenance, repair and rehabilitation planning of infrastructure assets, such as concrete pavement. The research intends to address an important gap by providing logical formalisms and real-time capability to life-cycle asset information through computational intelligence. The expected outcome will be an intelligent asset management platform that provides structured and semantically enriched lifecycle asset information for optimised solutions to help reduce the cost, time and effort in asset information storage and retrieval, and decision-making. Read moreRead less
Bridge performance assessment through advanced sensing and modelling. Bridge performance assessment through advanced sensing and modelling. This project aims to create cyber infrastructure to manage and maintain civil infrastructure, specifically bridges. Current sensor data interpretation approaches are not good at assessing the performance of civil infrastructure or evaluating the reserve capacity; in particular, they do not adequately account for high levels of systematic modelling uncertaint ....Bridge performance assessment through advanced sensing and modelling. Bridge performance assessment through advanced sensing and modelling. This project aims to create cyber infrastructure to manage and maintain civil infrastructure, specifically bridges. Current sensor data interpretation approaches are not good at assessing the performance of civil infrastructure or evaluating the reserve capacity; in particular, they do not adequately account for high levels of systematic modelling uncertainties. This project intends to ease the current scientific data interpretation bottleneck. Expected outcomes are better infrastructure management and maintenance planning, fewer redundant interventions, modified infrastructure and improved future design.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100909
Funder
Australian Research Council
Funding Amount
$350,000.00
Summary
Innovative Soft-computing for Condition Assessment of Large Infrastructure. Health conditions of large infrastructure, such as bridges, have been difficult to determine due to their large scales, associated incomplete data and high uncertainties in measurement and system identification. This project will develop an innovative condition assessment method based on the advancements in structural dynamics analysis, multi-objective topology and soft-computing techniques, for reliably evaluating the h ....Innovative Soft-computing for Condition Assessment of Large Infrastructure. Health conditions of large infrastructure, such as bridges, have been difficult to determine due to their large scales, associated incomplete data and high uncertainties in measurement and system identification. This project will develop an innovative condition assessment method based on the advancements in structural dynamics analysis, multi-objective topology and soft-computing techniques, for reliably evaluating the health conditions of large infrastructure. The outcomes will enhance the current practices in infrastructure asset management to deliver timely retrofitting and extended life cycle. The development will provide benefits to Australia by enhancing operational efficiency and preventing catastrophic failure of infrastructure.Read moreRead less
Condition-Based Maintenance Optimisation for Queensland’s Railways. Rail maintainers currently use time-based (scheduled) approaches to balance the costs and benefits of inspections and maintenance. Changing to condition-based maintenance has the potential to reduce costs and improve track condition. This project aims to enable this approach for rail by developing: 1) new track degradation prediction techniques combining Big Data and engineering knowledge; 2) new on-board sensing capabilities fo ....Condition-Based Maintenance Optimisation for Queensland’s Railways. Rail maintainers currently use time-based (scheduled) approaches to balance the costs and benefits of inspections and maintenance. Changing to condition-based maintenance has the potential to reduce costs and improve track condition. This project aims to enable this approach for rail by developing: 1) new track degradation prediction techniques combining Big Data and engineering knowledge; 2) new on-board sensing capabilities for frequent, low-cost track monitoring; 3) novel inspection and maintenance optimisation methods to efficiently allocate resources. The knowledge generated by this project is expected to decrease maintenance costs, safety risk, and track closures and therefore enhance the affordability and reliability of rail travel.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH180100010
Funder
Australian Research Council
Funding Amount
$4,918,357.00
Summary
ARC Research Hub for Smart Next Generation Transport Pavements. The ARC Research Hub for Smart Next Generation Transport Pavements aims to make road, airport and dockyard pavements smart, low cost, long-lasting, safe, green and adaptable to future transport demands. Australia’s road network, upon which the nation depends for its economic and social prosperity, is at risk due to increases in passenger and freight load degradation of the road network, and material and expertise scarcity. The Hub w ....ARC Research Hub for Smart Next Generation Transport Pavements. The ARC Research Hub for Smart Next Generation Transport Pavements aims to make road, airport and dockyard pavements smart, low cost, long-lasting, safe, green and adaptable to future transport demands. Australia’s road network, upon which the nation depends for its economic and social prosperity, is at risk due to increases in passenger and freight load degradation of the road network, and material and expertise scarcity. The Hub will deliver new materials and modelling, smart construction, and rehabilitation systems required for future demands, while enhancing road safety and reducing environmental impact.
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Discovery Early Career Researcher Award - Grant ID: DE160101137
Funder
Australian Research Council
Funding Amount
$373,536.00
Summary
The whole is greater than its parts: Improving rail safety through teamwork. This project seeks to develop a train driving risk model that includes human factors, to enable rail organisations to better identify and mitigate safety risks. Train driving is a cognitively demanding task in which errors can quickly lead to catastrophic consequences. Signals passed at danger (SPADs) occur when a train goes past a red light. Despite significant investment in better signalling and communications infrast ....The whole is greater than its parts: Improving rail safety through teamwork. This project seeks to develop a train driving risk model that includes human factors, to enable rail organisations to better identify and mitigate safety risks. Train driving is a cognitively demanding task in which errors can quickly lead to catastrophic consequences. Signals passed at danger (SPADs) occur when a train goes past a red light. Despite significant investment in better signalling and communications infrastructure, SPAD rates remain unacceptably high and are projected to rise. SPAD risk is currently managed with a retrospective approach that fails to consider non-technical human factors such as time pressure, workload and team communications. By including non-technical dimensions, this project seeks to develop a comprehensive model to explain and prevent SPADs.Read moreRead less
Improving road network operations under non-recurrent events. This project aims to develop an innovative approach for improving Road Network Operations (RNO) under non-recurrent events through analysis of big data and images. The outcomes of this project can not only improve the mobility of people, but also provide improved safety outcomes for all users of the transport network. It will help optimise traffic control strategies and traffic designs, reduce the maintenance cost for road infrastruc ....Improving road network operations under non-recurrent events. This project aims to develop an innovative approach for improving Road Network Operations (RNO) under non-recurrent events through analysis of big data and images. The outcomes of this project can not only improve the mobility of people, but also provide improved safety outcomes for all users of the transport network. It will help optimise traffic control strategies and traffic designs, reduce the maintenance cost for road infrastructure and improve quality of life.Read moreRead less
Seismic analysis of cracking and deformations in concrete gravity dams. This project aims to establish a rational predictive capability for the responses of concrete gravity dams subject to extreme design earthquakes. This will include the development of innovative numerical methods for effective modelling of crack propagation and closure, large slips on crack faces and weak interfaces, dam-reservoir interaction, dam-foundation interaction and automatic mesh generation. The expected outcomes of ....Seismic analysis of cracking and deformations in concrete gravity dams. This project aims to establish a rational predictive capability for the responses of concrete gravity dams subject to extreme design earthquakes. This will include the development of innovative numerical methods for effective modelling of crack propagation and closure, large slips on crack faces and weak interfaces, dam-reservoir interaction, dam-foundation interaction and automatic mesh generation. The expected outcomes of the project will be a significantly improved prediction tool. It is also anticipated that the project will result in improvements in dam and public safety, and more efficient use of funds for dam safety upgrades and management.Read moreRead less
Predictive Analytics and Real-time Traffic Control for Urban Corridors. This project aims to develop predictive data analytics and real-time traffic control and safety models for multimodal management of urban corridors, serving two salient objectives: (1) optimising person-throughput of multimodal traffic; while (2) minimising safety risks for all modes. The outcome will be an automated, sensor-based platform to monitor traffic flows from all modes and make proactive and coordinated control dec ....Predictive Analytics and Real-time Traffic Control for Urban Corridors. This project aims to develop predictive data analytics and real-time traffic control and safety models for multimodal management of urban corridors, serving two salient objectives: (1) optimising person-throughput of multimodal traffic; while (2) minimising safety risks for all modes. The outcome will be an automated, sensor-based platform to monitor traffic flows from all modes and make proactive and coordinated control decisions in real-time. The expected benefits are profound; the developed algorithms and platform will significantly reduce traffic congestion, travel delays and safety risks for all modes of transport, especially for vulnerable road users (e.g. pedestrians and cyclists).Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC230100015
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Training Centre for Whole Life Design of Carbon Neutral Infrastructure. This Centre aims to transform the capability of civil infrastructure stakeholders to design, construct, operate and dispose of infrastructure in a carbon neutral way. By training industry-embedded PhDs and postdocs in the methodology and technology required to design out excess carbon of infrastructure in its whole life, this Centre expects to lead the world in sustainable infrastructure design, enabling a new generation ....ARC Training Centre for Whole Life Design of Carbon Neutral Infrastructure. This Centre aims to transform the capability of civil infrastructure stakeholders to design, construct, operate and dispose of infrastructure in a carbon neutral way. By training industry-embedded PhDs and postdocs in the methodology and technology required to design out excess carbon of infrastructure in its whole life, this Centre expects to lead the world in sustainable infrastructure design, enabling a new generation of infrastructure design in Australia and internationally. Achieving carbon neutral infrastructure in its whole life will bring significant far-reaching benefits, including equipping industry with tools required to meet Australia’s emission reduction targets as well as economic, commercial, environmental, and social gains.Read moreRead less