Hybrid Construction using Seawater, Sea Sand and Fibre Reinforced Polymer. Conventional concrete is made using fresh water and river sand. This project aims to develop a novel hybrid construction system using seawater, sea sand and industrial waste, together with fibre reinforced polymer (FRP) and stainless steel (SS), for use in civil engineering infrastructure in marine environments. To date there has been little work to understand the degradation kinetics and mechanisms of FRP and SS in such ....Hybrid Construction using Seawater, Sea Sand and Fibre Reinforced Polymer. Conventional concrete is made using fresh water and river sand. This project aims to develop a novel hybrid construction system using seawater, sea sand and industrial waste, together with fibre reinforced polymer (FRP) and stainless steel (SS), for use in civil engineering infrastructure in marine environments. To date there has been little work to understand the degradation kinetics and mechanisms of FRP and SS in such complicated corrosive environments. The project plans to provide a design methodology to ensure confidence in the safety of critical infrastructure such as bridges, highways, dams, airports, offshore piles and artificial islands. The proposed system would save fresh water and reduce damage to river ecosystems, carbon dioxide emissions and construction costs.Read moreRead less
A novel quantitative risk assessment framework for fractured rock slopes. Rock slope instabilities present grave risks to life and to the serviceability of major Australian infrastructure such as mines, roads and railways, and to coastal recreation areas. This project aims at developing tools for the quantitative risk assessment of fractured rock slopes based on rigorous rock mechanics, numerical methods and probabilistic methods.
The research outcomes will improve our understanding of natural ....A novel quantitative risk assessment framework for fractured rock slopes. Rock slope instabilities present grave risks to life and to the serviceability of major Australian infrastructure such as mines, roads and railways, and to coastal recreation areas. This project aims at developing tools for the quantitative risk assessment of fractured rock slopes based on rigorous rock mechanics, numerical methods and probabilistic methods.
The research outcomes will improve our understanding of natural and engineering rock slopes, reduce the uncertainties in the prediction of the safety of infrastructures, and thus minimize the loss and damage. The research outcomes can also be used to maintain workplace safety in mining environments and avoid disruptions to production.
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Discovery Early Career Researcher Award - Grant ID: DE200101293
Funder
Australian Research Council
Funding Amount
$426,717.00
Summary
Dynamic Fracturing and Energy Release Mechanisms in Heterogeneous Materials. The prediction of fracturing behaviour in geomaterials (i.e. rock, soil and concrete) under dynamic/impact loads is essential in dealing with a wide range of engineering problems including excavation and mining, blasting and fragmentation, earthquake engineering, impact cratering, and protective structure design However, current knowledge and modelling capabilities of these applications remains empirically based. This p ....Dynamic Fracturing and Energy Release Mechanisms in Heterogeneous Materials. The prediction of fracturing behaviour in geomaterials (i.e. rock, soil and concrete) under dynamic/impact loads is essential in dealing with a wide range of engineering problems including excavation and mining, blasting and fragmentation, earthquake engineering, impact cratering, and protective structure design However, current knowledge and modelling capabilities of these applications remains empirically based. This project aims to investigate fundamental issues governing the dynamic fracturing of geomaterials and apply this knowledge to advance the understanding and modelling capacity of dynamic fractures in geomaterials.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