Current defence-related research grants, investment and sponsorships

A crucial part of the technology used in hybrid and fully electric propulsion systems for naval ships is the electric Main Propulsion Motor (MPMs), which need to operate at low rotational speeds with high torque, requiring efficiency and reliability for safety reasons. This research project aims to research and build a scalable model for advanced MPMs and their power systems, focusing on creating high-power, low-speed motors that optimise performance and control. This research will help enhance the effectiveness and capability of Australia’s naval assets, contributing to national security and technological leadership in the maritime sector.

This project complements the existing research program titled Motor Performance – Model Development and Validation through experimentation, collection and provision of motor and converter validation data under a range of operating conditions. The project includes research and development of modelling and simulation techniques of multi-phase motors and their drives to predict various performance characteristics. The work also includes research into smart control techniques, as well as the design, build and validation of a multi-phase research motor under ‘realistic’ marine loads and conditions.

This research project will help the Australian Government develop a science and technology capability in high-powered marine electrical Main Propulsion Motors and their associated high-powered electrical drives. This research builds on existing works and seeks to further research in the following key areas: research and development of accurate modelling, simulation techniques, and validation of multi-phase motors and their drives to predict various electrical, mechanical, electromagnetic, thermal and acoustic performance characteristics.

This research project continues to build on existing works and seek to further research into development of accurate modelling and simulation techniques of multi-phase motors, drive and associated systems to predict various mechanical performance characteristics. The project also includes conducting research into advanced control techniques to optimise targeted performance characteristics during both healthy and faulted operating conditions. This research will also validate modelling, simulation and control methods under both healthy and faulted conditions using the research motor.

The project aims to develop a new approach to assessing the risks and potential impact of malicious software, leveraging historical knowledge and combining obfuscation-resilient static analysis and dynamic analysis with behavioural fingerprints. The main goals are to create detailed attack profiles to understand the malware’s behaviour, context and actions and help determine scope, cost and impact of threats. In addition, the project aims to develop effective, efficient threat mitigations and triage strategies, while finding the balance between computational efficiency and the ability to detect malware effectively. This project will help ensure defence systems can effectively protect against sophisticated malware threats.

The University’s Centre for Advanced Training Systems will develop a training system for use by the Army Combat Training Centre to help individuals and teams understand and manage their mental and physiological state under cognitive load. The Cognitive Load Mitigation Training System (CLMTS) aims to alleviate the negative impact of cognitive load on decision-making and situational awareness by teaching staff awareness and mitigation strategies. The CLMTS will include a computer-based training program and cognitive load assessment tool, designed to support staff in developing a clear and personalised understanding of what cognitive load ‘feels like’ such that they can apply appropriate mitigation strategies.

The project focuses on the human element of cyber security. Human behaviour, and biases in decision making are key contributors to cybersecurity risks. The project objectives include conducting a comprehensive literature review to identify and understand the human touchpoints within cybersecurity systems and developing a preliminary Human Cyber Assessment Model that incorporates these human factors.

This project will examine how to build stronger cybersecurity defence teams made up of humans working alongside AI bots. Automated machine learning systems reduce the cognitive burden on human cyber analysts by filtering information. However, effective coordination of human-bot teams is a challenge. Cyber attackers can quickly adapt to changing conditions and find flaws in automated systems. This research will address how to manage, observe, and improve hybrid teams that are made up of humans and autonomous machines, particularly in the face of cyber adversaries. This multi-university project involves the University of Newcastle, Macquarie University, University of Melbourne, University of Wisconsin-Madison, Carnegie Mellon University, University of California San Diego, and Penn State.

The human gut microbiome is a diverse ecosystem of bacteria, organisms, fungi, and viruses intricately linked to human health. Evidence has revealed a bi-directional communication network between the gut microbiome and the central nervous system, which is involved in aspects of cognition, social behaviour, anxiety and stress. Active soldiers face environmental pressures that can impact the gut microbiome, increasing gut permeability and gut symptoms. Such responses have been linked to impaired cognitive performance, fatigue, disordered sleep and ‘brain fog’. This research will involve a comprehensive analysis of soldiers ‘cognobiome’ (the human, microbial and environmental interactions that affect cognition), to optimise cognitive and psychological performance.

Thermal destruction is an important step during waste processing. While all organic molecules are susceptible to thermal decomposition, the speed and effectiveness of this process can depend on factors like temperature, air flow and the timeframe of exposure to heat. The presence of chemicals and fine particles can also affect the breakdown. Incomplete combustion may lead to the emission of potentially harmful byproducts. This project aims to better understand how these factors influence breakdown to ensure safer water processing.

This project aims to improve the measurement and prediction of Coronal Mass Ejections (CMEs) originating from the Sun, which can trigger space weather events with the potential to disrupt space assets. The focus is on gaining a better understanding of CME velocity and magnetic fields, as these factors are key to predicting their arrival and impact on Earth. Given the challenges of observing these properties in the highly dynamic inner heliosphere, the project will develop new remote sensing techniques using ground-based radio telescopes to infer the magnetic field strength and orientation. This research will improve our knowledge of CMEs and improve space weather forecasting, thereby reducing potential risks to Earth’s space environment.

Cyber-attacks are increasing in both frequency and severity, but an asymmetry exists between defenders and attackers: attackers routinely exploit defenders’ human biases and limitations, tricking legitimate users into bad decisions, but not vice versa. The Reimagining Security with Cyberpsychology-Informed Network Defences (ReSCIND) program aims to use cyberpsychology to understand and influence attacker decision-making. The program will develop defences that use innovative methods to influence attackers’ cognitive biases and limitations, making their efforts more difficult and less effective.