Long-term chemically induced crumbling of unsaturated brittle geomaterials. This project will investigate the crumbling of geomaterials such as soil and rock by analysing the microscopic mechanisms controlling their deterioration in acidic water. The project will help predict weathering processes using an experimentally validated theory and innovative pore-scale numerical simulations. Expected outcomes include a detailed knowledge of the multi-scale interactions between brittle geomaterials and ....Long-term chemically induced crumbling of unsaturated brittle geomaterials. This project will investigate the crumbling of geomaterials such as soil and rock by analysing the microscopic mechanisms controlling their deterioration in acidic water. The project will help predict weathering processes using an experimentally validated theory and innovative pore-scale numerical simulations. Expected outcomes include a detailed knowledge of the multi-scale interactions between brittle geomaterials and acidic water, leading to accurate forecasts of the long-term response of large-scale geotechnical structures. This project should provide significant benefits by improving soil management for mining remediation, increasing carbon dioxide storage efficiency, and preventing the deterioration of tailings dams.Read moreRead less
Paving the way to greener roads and healthier waterways. Waste tyre permeable pavement is emerging as an effective stormwater surge mitigation solution. Yet, its behaviour under traffic loads and varied environmental conditions are not fully understood which undermines industry confidence in this technology. This project aims to advance the engineering of waste tyre permeable pavements by creating new knowledge on their mechanical and hydrological performance. The project will develop design gui ....Paving the way to greener roads and healthier waterways. Waste tyre permeable pavement is emerging as an effective stormwater surge mitigation solution. Yet, its behaviour under traffic loads and varied environmental conditions are not fully understood which undermines industry confidence in this technology. This project aims to advance the engineering of waste tyre permeable pavements by creating new knowledge on their mechanical and hydrological performance. The project will develop design guidelines, identify the governing mechanisms and develop a performance prediction framework based on laboratory and field tests, and advanced numerical modelling. The mechanisms of performance from micro to macro level will be identified, generating knowledge for industry to support widespread uptake.Read moreRead less
Soft-Rigid Bonded Granular Mixes: Particle Scale Study to Field Predictions. Globally 1.5 Billion and in Australia 56 million tyres reach their end of life with less than 5% recycled. This project aims to create new knowledge and predictive models for the behaviour of bonded soft tyre and rigid rock aggregates through a multi-scale approach from particle scale investigation to large-scale observation and modelling. This will create new knowledge into the behaviour of this unconventional three-p ....Soft-Rigid Bonded Granular Mixes: Particle Scale Study to Field Predictions. Globally 1.5 Billion and in Australia 56 million tyres reach their end of life with less than 5% recycled. This project aims to create new knowledge and predictive models for the behaviour of bonded soft tyre and rigid rock aggregates through a multi-scale approach from particle scale investigation to large-scale observation and modelling. This will create new knowledge into the behaviour of this unconventional three-phase granular mixes; soft, rigid aggregates bonded with polymer binders. The project will provide significant benefits in diverting millions of tyres from landfills and illegal dumps and a more competitive and environmentally sensitive infrastructure industry.Read moreRead less
Modelling surface stresses in crystalline plates. This project intends to improve our understanding of the influence of surface stress on bending in anisotropic crystalline plates. Micro/nanoelectro-mechanical systems as transducers, switches, logic gates, actuators and sensors are widely used in fields of biotechnology, medicine, automotive, civionics, avionics and defence. A key issue that affects the accuracy and reliability of these systems is how to correctly predict the size-dependent surf ....Modelling surface stresses in crystalline plates. This project intends to improve our understanding of the influence of surface stress on bending in anisotropic crystalline plates. Micro/nanoelectro-mechanical systems as transducers, switches, logic gates, actuators and sensors are widely used in fields of biotechnology, medicine, automotive, civionics, avionics and defence. A key issue that affects the accuracy and reliability of these systems is how to correctly predict the size-dependent surface stress of the structural components in the systems. The project aims to quantify the relations between the change in surface stress and the bending of structures with micro/nanoscale thickness and arbitrary crystallographic symmetry. Expected project outcomes may lead to significant advancement in overcoming the current shortcomings in designing micro/nanoelectro-mechanical devices.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
Discovery Early Career Researcher Award - Grant ID: DE200100892
Funder
Australian Research Council
Funding Amount
$419,889.00
Summary
Next-generation, prefabricated, modular, solar heating and cooling system. This project aims to develop a new window design that can reduce the heating of buildings caused by the sun in warm weather and reduce heat loss from buildings in cool weather. This project expects to generate new knowledge on the interaction between solar radiation and the convection of air inside a cavity within the window design. The expected outcome is a framework that can be used to optimize window designs for buildi ....Next-generation, prefabricated, modular, solar heating and cooling system. This project aims to develop a new window design that can reduce the heating of buildings caused by the sun in warm weather and reduce heat loss from buildings in cool weather. This project expects to generate new knowledge on the interaction between solar radiation and the convection of air inside a cavity within the window design. The expected outcome is a framework that can be used to optimize window designs for buildings under various weather conditions. This should allow quick and easy fabrication and implementation of the designs in existing and new buildings, and the windows should significantly reduce building heating and cooling costs.Read moreRead less
Next Generation Bridge Monitoring using Novel Synergic Identification. Over 70% of the bridges in Australia are made of prestressed concrete, yet many do not meet the requirements of current Australian Standards. This project aims to provide a cost-effective system for monitoring bridges in real time along with systems that track the prestressing force and rate of damage for ongoing health assessment and necessary repairs. The use of innovative engineering techniques, solving long standing probl ....Next Generation Bridge Monitoring using Novel Synergic Identification. Over 70% of the bridges in Australia are made of prestressed concrete, yet many do not meet the requirements of current Australian Standards. This project aims to provide a cost-effective system for monitoring bridges in real time along with systems that track the prestressing force and rate of damage for ongoing health assessment and necessary repairs. The use of innovative engineering techniques, solving long standing problems of engineers, will enable the safe operation of bridges, which play a primary role in Australia’s national transport system. Improved methodology for turning tired infrastructure into ‘smart bridges’ will be developed and commissioned first in Australia and then applied internationally.Read moreRead less