Condition Monitoring of Aircraft Propulsion for Automated Diagnostics. The integrity of the steering system is crucial for the safe operation of autonomous vehicles. This project aims at developing a new condition monitoring system able to diagnose steering faults earlier, provide a root-cause-analysis of malfunctions, and estimate associated failure risks in the future. The outcomes of this project will be a better understanding of steering faults and their effect on autonomous driving, timely ....Condition Monitoring of Aircraft Propulsion for Automated Diagnostics. The integrity of the steering system is crucial for the safe operation of autonomous vehicles. This project aims at developing a new condition monitoring system able to diagnose steering faults earlier, provide a root-cause-analysis of malfunctions, and estimate associated failure risks in the future. The outcomes of this project will be a better understanding of steering faults and their effect on autonomous driving, timely diagnostics and prognostics and innovative proactive control measures that mitigate their impact on autonomous driving quality and safety. The expected benefits for the automotive industry and end-users include increased safety and reliability of steering systems, and higher confidence in autonomous driving.Read moreRead less
Quantitative structural health assessment of large membrane-like structures. This project aims to develop a new approach, based on remote sensing and computational modelling, to assess and manage the structural health of large floating covers used for odour control and biogas harvesting to prevent unexpected failures. The project has potential benefits for high-value-added manufacturing and maintenance of these floating covers by Australian industry.
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
A novel physical-digital approach for the assessing a large critical asset. This project aims to deliver an artificial intelligence-enabled decision-making tool to maintain and manage the floating covers of vast lagoons that treat raw sewage. The cover harvests the biogas released from the anaerobic digestion of sewage for electric power generation that exceeds the plant’s requirement. The approach involves an innovative thermographic technique and exploits transfer learning to adapt neural netw ....A novel physical-digital approach for the assessing a large critical asset. This project aims to deliver an artificial intelligence-enabled decision-making tool to maintain and manage the floating covers of vast lagoons that treat raw sewage. The cover harvests the biogas released from the anaerobic digestion of sewage for electric power generation that exceeds the plant’s requirement. The approach involves an innovative thermographic technique and exploits transfer learning to adapt neural networks trained on lab-scale and synthetic data to field implementation. The outcome is a machine learning framework to optimise biogas harvesting and renewable energy generation, and to avoid structural failure, that is capable of continuous improvement to take into account improved data and/or modelling capabilities.Read moreRead less
Pipeline backfill reimagined to provide in-line corrosion protection. This project aims to innovate new resistive pipeline backfill materials, associated construction methods and numerical techniques to minimise corrosion at network level, considering interference effects among adjacent pipelines. In contrast to only providing mechanical support, this project will envision backfill for in-line corrosion protection by elucidating its role in pipeline corrosion. The expected outcomes are very effe ....Pipeline backfill reimagined to provide in-line corrosion protection. This project aims to innovate new resistive pipeline backfill materials, associated construction methods and numerical techniques to minimise corrosion at network level, considering interference effects among adjacent pipelines. In contrast to only providing mechanical support, this project will envision backfill for in-line corrosion protection by elucidating its role in pipeline corrosion. The expected outcomes are very effective and low-cost approach and tools to provide in-line protection, in contrast to other protection methods that are expensive and not always possible. The project will bring significant economic benefits by addressing corrosion-induced pipe failures for urban centres, where underground space is heavily congested.
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Next-generation smart water network for performance-driven asset management. This project aims to develop smart water network systems and techniques for continuous monitoring and early detection of structural failure in water distribution systems. Water assets are critical infrastructure, and they consist of a network of buried pipes that are old and deteriorating, with an annual maintenance overhead exceeding $1billion per year in Australia. This project is expected to deliver next-generation s ....Next-generation smart water network for performance-driven asset management. This project aims to develop smart water network systems and techniques for continuous monitoring and early detection of structural failure in water distribution systems. Water assets are critical infrastructure, and they consist of a network of buried pipes that are old and deteriorating, with an annual maintenance overhead exceeding $1billion per year in Australia. This project is expected to deliver next-generation smart water technology that enables continuous assessment of the actual performance of water pipe networks, guide “just in time” pipe replacement and optimise operations. This technology will assist asset managers to make informed decisions, strategically prioritise investment and extend asset life.Read moreRead less
Smart Pipe Condition Assessment in Water Distribution Systems. The project aims to develop an urgently needed smart pipe fault diagnosis, characterisation and prognosis system. Analysis techniques will be used for the detailed mapping of buried pipe condition between access points using micro-sized transient pressure waves. Water assets are critical infrastructure and they consist of a network of pipes that are often old and deteriorating. The annual maintenance cost exceeds $1b per year in Aus ....Smart Pipe Condition Assessment in Water Distribution Systems. The project aims to develop an urgently needed smart pipe fault diagnosis, characterisation and prognosis system. Analysis techniques will be used for the detailed mapping of buried pipe condition between access points using micro-sized transient pressure waves. Water assets are critical infrastructure and they consist of a network of pipes that are often old and deteriorating. The annual maintenance cost exceeds $1b per year in Australia. The outcome will be a next-generation tool that allows water utilities to move from reactive emergency repairs to proactive repair and predictive replacement. This will enable performance-driven asset management, extending asset life and replacing deteriorated high-risk pipe sections in a timely manner.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
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
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