Multi-hazard resilient hybrid modular structures. This project aims to develop the next generation of multi-hazard resilient modular construction methods for efficient, affordable and sustainable buildings. New demountable modular connections will be developed and the response of hybrid modular buildings to multiple hazards such as wind, earthquake, blast and impact will be investigated through a combination of experimental, numerical, and analytical studies. The project will develop knowledge o ....Multi-hazard resilient hybrid modular structures. This project aims to develop the next generation of multi-hazard resilient modular construction methods for efficient, affordable and sustainable buildings. New demountable modular connections will be developed and the response of hybrid modular buildings to multiple hazards such as wind, earthquake, blast and impact will be investigated through a combination of experimental, numerical, and analytical studies. The project will develop knowledge of the structural behaviour of hybrid modular buildings, and expects to deliver design methods and robust simplified models for building design purposes. This project will advance construction techniques and practices for resilient hybrid modular buildings.Read moreRead less
Innovative Data Driven Techniques for Structural Condition Monitoring . Safe and sustainable infrastructure involves the development and application of structural monitoring and assessment techniques for condition evaluation. This project develops an innovative structure condition monitoring approach based on the emerging digital technologies on image processing, data analytics and machine learning techniques, for better infrastructure asset management under operational environment. Expected out ....Innovative Data Driven Techniques for Structural Condition Monitoring . Safe and sustainable infrastructure involves the development and application of structural monitoring and assessment techniques for condition evaluation. This project develops an innovative structure condition monitoring approach based on the emerging digital technologies on image processing, data analytics and machine learning techniques, for better infrastructure asset management under operational environment. Expected outcomes of this project enhance the capacity to conduct the operational monitoring and data interpretation to deliver the best life cycle performance of infrastructure. This project should provide significant benefits to Australia in infrastructure asset management by reducing the interruption of infrastructure operations.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL190100014
Funder
Australian Research Council
Funding Amount
$2,871,982.00
Summary
New Technologies for Delivering Sustainable Free-form Architecture. This project aims to harness the full potential of digital technologies to significantly enhance the performance and reduce the environmental impact of free-form architecture of the future. The research expects to establish a fundamentally new computational platform capable of producing diverse and competitive designs, and an environmentally friendly manufacturing process for realising such designs. Expected outcomes include an ....New Technologies for Delivering Sustainable Free-form Architecture. This project aims to harness the full potential of digital technologies to significantly enhance the performance and reduce the environmental impact of free-form architecture of the future. The research expects to establish a fundamentally new computational platform capable of producing diverse and competitive designs, and an environmentally friendly manufacturing process for realising such designs. Expected outcomes include an unprecedented cloud-based interactive design tool, and a novel minimum-waste manufacturing technology for fabricating mass-customised building components. This project will transform the architecture, engineering and construction (AEC) sector and make the Australian manufacturing industry more competitive globally.Read moreRead less
AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in d ....AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in data mining and interpretation. Expected outcomes of the project include novel AI assisted approaches to conduct probabilistic structural condition monitoring with sensitive features and future structural performance prediction. This will provide significant benefits to infrastructure asset owners to reduce maintenance costs.Read moreRead less
Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through dee ....Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through deep learning with structural conditions and load-carrying capacities obtained from vibration tests and finite element model analysis for efficient structural damage detection and quantification. The project will lead to effective structural health monitoring and enhance structural safety and reduce maintenance costs. Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE210100057
Funder
Australian Research Council
Funding Amount
$650,000.00
Summary
Australian Stress Engineering Facility. This project aims to radically enhance the Australian capability for residual stress measurements and damage analysis. This project is expected to revolutionise stress engineering research in Australia by providing access to a state-of-the-art measurement capability that will enable on-site measurements at manufacturing plants and in laboratories. Expected outcomes of this project include the development and optimisation of advanced manufacturing and maint ....Australian Stress Engineering Facility. This project aims to radically enhance the Australian capability for residual stress measurements and damage analysis. This project is expected to revolutionise stress engineering research in Australia by providing access to a state-of-the-art measurement capability that will enable on-site measurements at manufacturing plants and in laboratories. Expected outcomes of this project include the development and optimisation of advanced manufacturing and maintenance technologies for civil engineering structures. This should provide significant benefits in safety, reliability and economic impact to Australian researchers in academia and industry across manufacturing, civil, transport, defence and medical sectors.Read moreRead less
Mitigating the Severity of Level Crossing Accidents and Derailments. Ongoing increases in the number of level crossings and heavy road vehicles cause more frequent and severe level crossing accidents and derailments. Despite the use of active warning systems, each year, on average, 100 level crossing accidents occur in Australia. With a view to mitigating these crashes, this research aims to formulate theories for reduction in crash energy and effective wheel constraints to prevent derailment by ....Mitigating the Severity of Level Crossing Accidents and Derailments. Ongoing increases in the number of level crossings and heavy road vehicles cause more frequent and severe level crossing accidents and derailments. Despite the use of active warning systems, each year, on average, 100 level crossing accidents occur in Australia. With a view to mitigating these crashes, this research aims to formulate theories for reduction in crash energy and effective wheel constraints to prevent derailment by modifying the levels of road and rail crossings and providing guard rails in the recesses of these modified level crossings. The theories are intended be developed using nonlinear dynamic computational methods and laboratory experiments. The outcomes are expected to enable reduction in the severity of level crossing accidents and hence save lives and costs of derailment.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
Beyond the limits of corrosion detection in inaccessible areas. The project will develop a new technology for medium-range corrosion mapping in inaccessible areas of infrastructure. This will overcome the limitations of existing corrosion inspection techniques for corrosion inspection at inaccessible areas. The project will create a new concept and generate new knowledge on accurate corrosion mapping in inaccessible areas. The expected outcomes are significant improvements in the capability and ....Beyond the limits of corrosion detection in inaccessible areas. The project will develop a new technology for medium-range corrosion mapping in inaccessible areas of infrastructure. This will overcome the limitations of existing corrosion inspection techniques for corrosion inspection at inaccessible areas. The project will create a new concept and generate new knowledge on accurate corrosion mapping in inaccessible areas. The expected outcomes are significant improvements in the capability and practicability over existing corrosion inspection technologies adopted by industry for a wide range of infrastructure, in particular the Oil and Gas, Mining, Energy and Water infrastructure, as well as improving the reliability and cost-efficiency of the corrosion inspection.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE210100025
Funder
Australian Research Council
Funding Amount
$468,000.00
Summary
Electron microscopy facilities for in-situ materials characterisation. This project aims to significantly strengthen our national capability in high resolution in-situ transmission electron microscopy through the introduction of special in-situ specimen holders and an imaging detector. The project expects to advance knowledge critical for the design of advanced materials with outstanding properties. Expected outcomes of this project will provide critical support for thorough understanding of how ....Electron microscopy facilities for in-situ materials characterisation. This project aims to significantly strengthen our national capability in high resolution in-situ transmission electron microscopy through the introduction of special in-situ specimen holders and an imaging detector. The project expects to advance knowledge critical for the design of advanced materials with outstanding properties. Expected outcomes of this project will provide critical support for thorough understanding of how the microstructures of materials affect their mechanical, thermal, electrical, and magnetic properties and will facilitate strategic collaborations among Australian scientists. This should promote Australia’s global leadership in materials research and advanced manufacturing.Read moreRead less