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
Industrial Transformation Training Centres - Grant ID: IC180100030
Funder
Australian Research Council
Funding Amount
$3,925,357.00
Summary
ARC Training Centre for Transforming Maintenance through Data Science. The ARC Training Centre for Transforming Maintenance through Data Science aims to equip practising engineers and Australian graduates with the next generation of data science methods for the maintenance sector. The Centre plans to introduce timely and cost-efficient maintenance scheduling by developing data-intensive mathematical and computational algorithms for asset management and fault prediction. The Centre’s overarching ....ARC Training Centre for Transforming Maintenance through Data Science. The ARC Training Centre for Transforming Maintenance through Data Science aims to equip practising engineers and Australian graduates with the next generation of data science methods for the maintenance sector. The Centre plans to introduce timely and cost-efficient maintenance scheduling by developing data-intensive mathematical and computational algorithms for asset management and fault prediction. The Centre’s overarching objectives are to enable development and adoption of new practices to improve productivity and asset reliability for industry and to foster a new maintenance technology service sector for national and international markets.Read moreRead less
Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proa ....Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proactive sewer management including network-wide real-time control. The project aims to generate significant social, environmental and economic benefits by enabling utilities to better protect public and environmental health, reduce sewer odour and greenhouse gas emissions, and extend sewer asset life.Read moreRead less
Novel test and design methods for base course reinforced flexible pavements. This project aims to develop the mechanics of geosynthetic-reinforced flexible pavements as an urgent need for the Australian pavement industry to build more sustainable and economical roads. Novel laboratory test apparatus and in-situ test programs, and mathematical models will be developed, for the first time, to capture the responses of reinforced base courses in a complete and optimised way to determine the paramete ....Novel test and design methods for base course reinforced flexible pavements. This project aims to develop the mechanics of geosynthetic-reinforced flexible pavements as an urgent need for the Australian pavement industry to build more sustainable and economical roads. Novel laboratory test apparatus and in-situ test programs, and mathematical models will be developed, for the first time, to capture the responses of reinforced base courses in a complete and optimised way to determine the parameters for pavement design and performance evaluation. The outcomes will enable reliable prediction of reinforced pavement behaviour, leading to better-performing geosynthetic products and more resilient pavements, reduced material usage and damage in pavements, and less environmental impact and maintenance cost.Read moreRead less
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.Read moreRead less
Next generation nondestructive inspection using guided-wave mixing. This project aims to develop a novel approach for early damage detection. It relies on a systematic experimental investigation of nonlinear ultrasonic interaction between different input wave modes in the presence of damage, so as to identify optimal mode selections and operating parameters that will maximise the sensitivity to particular forms of structural damage. The effects of in-service loading on wave-mixing response, and ....Next generation nondestructive inspection using guided-wave mixing. This project aims to develop a novel approach for early damage detection. It relies on a systematic experimental investigation of nonlinear ultrasonic interaction between different input wave modes in the presence of damage, so as to identify optimal mode selections and operating parameters that will maximise the sensitivity to particular forms of structural damage. The effects of in-service loading on wave-mixing response, and non-contact detection suitable for hard-to-inspect surface conditions, will also be investigated. The new developments will help transform existing schedule-based maintenance practice to a condition-based maintenance paradigm, to achieve significant cost savings in maintenance.Read moreRead less
Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expect ....Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expected outcomes include protocol to accurately monitor emissions, models to predict emission under various conditions, and mitigation guideline for typical plant configurations. The anticipated benefit is a significant reduction in GHG emissions from urban water industry and support it to meet net-zero-emission goal by 2050.Read moreRead less
Stress Evaluation with Non-Linear Guided Waves. This project plans to investigate a novel approach for in situ measurement of stress in structures based on an internal resonance phenomenon for nonlinear guided waves. Monitoring the stress level of critical structural components is important to ensure structural safety. The project plans to derive the requirements for this internal resonance and its dependence on stress analytically and verify them experimentally for both simple waveguides and mo ....Stress Evaluation with Non-Linear Guided Waves. This project plans to investigate a novel approach for in situ measurement of stress in structures based on an internal resonance phenomenon for nonlinear guided waves. Monitoring the stress level of critical structural components is important to ensure structural safety. The project plans to derive the requirements for this internal resonance and its dependence on stress analytically and verify them experimentally for both simple waveguides and more realistic structures. The expected outcome is the demonstration of the feasibility of a new inexpensive method for continuous monitoring of applied or thermally-induced stresses, which is of great importance in several engineering contexts, such as modern railway track rails, pipelines or pre-stressed strands in concrete structures.Read moreRead less
Cost Effective Pipeline Condition Assessment Using Paired Pressure Sensor Arrays. Water distribution networks represent society's most important infrastructure asset. They are buried pipes and are often old and deteriorating. Cost-effective methods to assess their physical condition are urgently needed. This research will develop a novel and advanced approach to determine the interior condition of pipes quickly and effectively using small water hammer pulses or waves. Paired pressure sensor arra ....Cost Effective Pipeline Condition Assessment Using Paired Pressure Sensor Arrays. Water distribution networks represent society's most important infrastructure asset. They are buried pipes and are often old and deteriorating. Cost-effective methods to assess their physical condition are urgently needed. This research will develop a novel and advanced approach to determine the interior condition of pipes quickly and effectively using small water hammer pulses or waves. Paired pressure sensor arrays will be used to measure reflections of the waves in pipes and these methods will enable finer resolution and identification of pipeline faults, such as wall thickness loss and leakage while at the same time allowing operational continuity. The outcome will be powerful tools to more cost effectively manage these crucial assets.Read moreRead less