Controlling coastlines while generating power. The Project aims to produce strategies for protecting coasts from storms using farms of wave-energy machines, which also generate electricity. Increasing lengths of coast need protection as the climate changes, but conventional barriers create permanent environmental impacts and are a sunk cost usually borne by the taxpayer. The Project expects to derive a strategy for the setting of each machine in the farm, so that they collectively absorb or refl ....Controlling coastlines while generating power. The Project aims to produce strategies for protecting coasts from storms using farms of wave-energy machines, which also generate electricity. Increasing lengths of coast need protection as the climate changes, but conventional barriers create permanent environmental impacts and are a sunk cost usually borne by the taxpayer. The Project expects to derive a strategy for the setting of each machine in the farm, so that they collectively absorb or reflect damaging waves under severe conditions. Under normal conditions, enough wave energy to sustain environmental processes would pass through. Sales of electricity would help to pay back the capital cost. Outcomes would include reduced coastal-erosion costs and a low-intermittency energy supply.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC190100017
Funder
Australian Research Council
Funding Amount
$3,703,664.00
Summary
ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource ....ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource attributes, maximising value ‘on the fly’. Benefits will include increasing certainty on product quality and maximising throughput and recovery. Outcomes will include new tools to rapidly model geological and geometallurgical uncertainty with sensor inputs, to track the resource to product and enhance interpretation.Read moreRead less
A Novel Inline High-Efficiency Motor/Pump System. Around 19% of the world’s and 30% of the Australia’s electric energy is consumed by pump technologies. Significant energy savings are possible if the major components of pump systems, including inverter, motor and pump, operate at their maximum possible efficiency under varying loads. A novel pump design in this project accommodates integrated electronics in a submersible housing. A seal-less design helps mitigate several aspects of pump failure ....A Novel Inline High-Efficiency Motor/Pump System. Around 19% of the world’s and 30% of the Australia’s electric energy is consumed by pump technologies. Significant energy savings are possible if the major components of pump systems, including inverter, motor and pump, operate at their maximum possible efficiency under varying loads. A novel pump design in this project accommodates integrated electronics in a submersible housing. A seal-less design helps mitigate several aspects of pump failure and its in-line structure reduces assembly cost. Accurately measured efficiency maps will be utilised to demonstrate the non-linear relationship between motor and pump quantities as well as developing models for indirectly estimating feedback quantities and achieving the highest system efficiency.Read moreRead less
Visual intelligence for safe vehicle operation in industrial environment. Visual intelligence for safe vehicle operation in industrial environment. This project aims to develop safety devices for loosely constrained environments with public access, building on visual-based collision avoidance technology in controlled industrial settings. Increasing productivity in industrial workplaces creates a need for faster industrial vehicles. At fruit and vegetable markets and construction sites, forklift ....Visual intelligence for safe vehicle operation in industrial environment. Visual intelligence for safe vehicle operation in industrial environment. This project aims to develop safety devices for loosely constrained environments with public access, building on visual-based collision avoidance technology in controlled industrial settings. Increasing productivity in industrial workplaces creates a need for faster industrial vehicles. At fruit and vegetable markets and construction sites, forklift drivers, crane operators and crews are under pressure to move faster. The need for higher speed and the enormous human and financial cost of unsafe operations create opportunities for the deployment of intelligent safety devices. The expected outcomes of this project are safer public industrial environments, reductions in work related injuries, injury compensation costs and associated societal burdens.Read moreRead less
Intelligent collision avoidance system for mobile industrial platforms. This project will develop a collision prevention system for mobile industrial platforms that enhances existing artificial vision perception systems to mimic human eye capabilities. The outcomes of this project will result in significant reductions in work related injuries, injury compensation costs and associated societal burdens.
From data to action: a new process for developing injury countermeasures. This project aims to understand how reporting systems can improve workplace safety. Workplace injury affects over 600 000 Australian workers per year at a cost of approximately $60 billion. Although the introduction of incident reporting systems has enabled organisations to better understand the causes of injuries, how to translate this knowledge into effective countermeasures remains ambiguous. Moreover, it is not clear w ....From data to action: a new process for developing injury countermeasures. This project aims to understand how reporting systems can improve workplace safety. Workplace injury affects over 600 000 Australian workers per year at a cost of approximately $60 billion. Although the introduction of incident reporting systems has enabled organisations to better understand the causes of injuries, how to translate this knowledge into effective countermeasures remains ambiguous. Moreover, it is not clear whether adopting incident reporting systems actually leads to a safety benefit. This research intends to tackle these critical knowledge gaps by developing, implementing, and testing a process for translating incident reporting system outputs into appropriate and effective injury countermeasures, and then evaluating the safety effects of adopting the new incident reporting and learning cycle.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environme ....ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environments. EII will address 3 tightly coupled research themes: Ability to interoperate across existing heterogenous platforms & applications; Efficient processing of very large data sets; Technology adoption & impact. Generic results will be applicable to e-science and large business information systems installations.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC220100003
Funder
Australian Research Council
Funding Amount
$4,930,205.00
Summary
ARC Training Centre for Biofilm Research and Innovation . The ARC Training Centre for Biofilm Research and Innovation aims to transform biofouling management strategies for maritime platforms by building on local and international expertise to mentor and train the next generation of interdisciplinary scientists and engineers. Anticipating evolving regulatory stringency, this project expects to establish a dynamic environment for industry partners, students and scientists to collaborate and devel ....ARC Training Centre for Biofilm Research and Innovation . The ARC Training Centre for Biofilm Research and Innovation aims to transform biofouling management strategies for maritime platforms by building on local and international expertise to mentor and train the next generation of interdisciplinary scientists and engineers. Anticipating evolving regulatory stringency, this project expects to establish a dynamic environment for industry partners, students and scientists to collaborate and develop biofilm management strategies. Expected outcomes include new and enhanced collaborations that advance and translate knowledge to better manage biofouling. The significant benefits will include a generation of industry-focused researchers critical for growing Australia’s Defence industry.Read moreRead less
Transition to Customer Response Driven Networks. The project seeks to develop an electrical network costing framework that appropriately rewards customers who act to reduce network stress. The solution to the existing explosion in distribution network costs is to develop customer-responsive solutions in demand management and use of storage. The aim of this project is to develop a framework for network costs that is driven by local congestion and which would reward customer-responsive solutions. ....Transition to Customer Response Driven Networks. The project seeks to develop an electrical network costing framework that appropriately rewards customers who act to reduce network stress. The solution to the existing explosion in distribution network costs is to develop customer-responsive solutions in demand management and use of storage. The aim of this project is to develop a framework for network costs that is driven by local congestion and which would reward customer-responsive solutions. The vision is that the aggregator would provide customers with communications/control equipment that would automate the changes in the responsiveness so that customer-generated load shifting would act to limit peaks.Read moreRead less