Designing the next generation of geosynthetic liner systems . The project aims to improve the effectiveness of geosynthetic liner systems to contain emerging contaminants such as per-and poly-fluoroalkyl substances (PFASs) for better protection of Australian groundwater resources. The project expects to experimentally validate theory to improve predictive models for performance of geosynthetic liner systems. Expected outcomes include new and updated design guidelines for effective environmental ....Designing the next generation of geosynthetic liner systems . The project aims to improve the effectiveness of geosynthetic liner systems to contain emerging contaminants such as per-and poly-fluoroalkyl substances (PFASs) for better protection of Australian groundwater resources. The project expects to experimentally validate theory to improve predictive models for performance of geosynthetic liner systems. Expected outcomes include new and updated design guidelines for effective environmental protection against PFASs and establishment of new approaches for predicting functional containment lifetimes of liner systems. These outcomes are expected to benefit the waste and remediation industries by influencing next-generation design regulations to ensure long-term environmental protection from PFAS.Read moreRead less
Non-contact Integrity Assessment of Façade Panels of High-rise Buildings. Disintegration of the external façade (with tiles, plates, etc.) of high-rise buildings presents a great challenge and a threat to community. This project develops fundamental knowledge and algorithms that underpin the deployment of a new technique for fast and automated quantitative integrity assessment of façade units of high-rise buildings, integrating mechanisms of directional acoustic waves, vibro-acoustics of façade ....Non-contact Integrity Assessment of Façade Panels of High-rise Buildings. Disintegration of the external façade (with tiles, plates, etc.) of high-rise buildings presents a great challenge and a threat to community. This project develops fundamental knowledge and algorithms that underpin the deployment of a new technique for fast and automated quantitative integrity assessment of façade units of high-rise buildings, integrating mechanisms of directional acoustic waves, vibro-acoustics of façade tiles or panels, laser sensing technology, deep learning algorithms and drone technology. Outcomes of this project are critical for implementing the new technology for enhanced safety to community and the development of new procedures for driving down maintenance costs of the external façade of high-rise buildings.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
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
Hydrogen carbon waste into concrete: AI assisted nanoscience approach. The carbon waste from hydrogen production will be converted into carbon nanosheets on abundant construction materials for the creation of stronger and more durable concrete. Cutting-edge nanoscience-based experiments, as well as sophisticated modelling techniques including machine learning and finite element modelling, will be employed. The findings will drive advances in clean hydrogen production, carbon waste utilisation, c ....Hydrogen carbon waste into concrete: AI assisted nanoscience approach. The carbon waste from hydrogen production will be converted into carbon nanosheets on abundant construction materials for the creation of stronger and more durable concrete. Cutting-edge nanoscience-based experiments, as well as sophisticated modelling techniques including machine learning and finite element modelling, will be employed. The findings will drive advances in clean hydrogen production, carbon waste utilisation, cement hydration, nanotechnology and concrete technology for the next generation of an upskilled workforce and the promotion of a circular economy. This project will be carried out in collaboration with Australian and international renowned experts in computational modelling, nanomaterials and concrete materials.Read moreRead less