Discovery Early Career Researcher Award - Grant ID: DE240101422
Funder
Australian Research Council
Funding Amount
$467,760.00
Summary
Chameleon-Inspired Building Envelope for the Australian Building Sector. The project aims to develop an intelligent reflective coating that can act like a chameleon skin on a building surface, allowing sunlight to reflect efficiently in summer and be absorbed in winter without using pigments or dyes. The research will reveal how microstructural architecture can mimic a chameleon skin on building envelopes to address the critical challenge of this technology, which is overcooling in winter. The e ....Chameleon-Inspired Building Envelope for the Australian Building Sector. The project aims to develop an intelligent reflective coating that can act like a chameleon skin on a building surface, allowing sunlight to reflect efficiently in summer and be absorbed in winter without using pigments or dyes. The research will reveal how microstructural architecture can mimic a chameleon skin on building envelopes to address the critical challenge of this technology, which is overcooling in winter. The expected outcome is a smart coating technology that is easy to manufacture on small and large scales with no winter penalty, compatible with even, uneven and rough surfaces, free from the use of pigment and durable under sunlight. Read moreRead less
Assessment of Dynamic Pile Driving Using Machine Learning. This project aims at developing new technology to determine ground properties and foundation capacity in real-time during pile installation by adopting rigorous numerical simulation, laboratory experiments and artificial intelligence-based computational model. Although impact driving is used commonly to install piles on site, there is no technology currently available to interpret collected data accurately and in real-time to provide liv ....Assessment of Dynamic Pile Driving Using Machine Learning. This project aims at developing new technology to determine ground properties and foundation capacity in real-time during pile installation by adopting rigorous numerical simulation, laboratory experiments and artificial intelligence-based computational model. Although impact driving is used commonly to install piles on site, there is no technology currently available to interpret collected data accurately and in real-time to provide live feedback and optimise construction processes. This research will provide new machine learning model to assess the ground and foundation characteristics during construction, and will increase certainty in infrastructure investment in Australia particularly for costly transport assets and infrastructure.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100123
Funder
Australian Research Council
Funding Amount
$427,318.00
Summary
Digital Twin to Manage Safety in Large-scale Transport Infrastructure Asset. This project aims to improve safety during the construction of transport assets by integrating the Internet of Things with image processing technologies to develop a digital twin framework. The developed framework will provide the construction organisations with the ability to create strategies and solutions needed to improve the safety of construction in real-time. The outcomes of this project will aid effective decisi ....Digital Twin to Manage Safety in Large-scale Transport Infrastructure Asset. This project aims to improve safety during the construction of transport assets by integrating the Internet of Things with image processing technologies to develop a digital twin framework. The developed framework will provide the construction organisations with the ability to create strategies and solutions needed to improve the safety of construction in real-time. The outcomes of this project will aid effective decision-making and thus enable the managerial actions required to eliminate workplace accidents. Improving safety performance not only augments productivity but also allows the economic and social benefits of transport infrastructure assets to be realised.Read moreRead less