Environmental and Societal Resilience
Natural and man-made disasters constitute a major threat for the economy, environment, and communities. Our research aims at providing unprecedented situation awareness and decision support for mitigating, responding, and recovering from disasters. Our research considers how to improve situation awareness and decision support for strategic, tactical, and real-time planning and post-recovery efforts. These decisions involve multiple complex infrastructures, multiple agencies, and multiple stakeholders from state and federal agencies, to local councils and communities.
In addition, our research also considers environmental and societal resilience, understanding how to preserve our fragile ecosystems and how to keep our cities liveable.
Power System Restoration
Blackouts are one of the major sources of human suffering and economic costs after significant disasters. Data61 ORG develops state-of-art power restoration tools, integrating both logistics and power systems aspects. The goal is to schedule repair crews to fix network components in order to minimise the size of the blackouts over time. The problem is extremely challenging computationally and solution techniques must deal with a stressed network, for which solving the power flow equations is particularly difficult. ORG members have pioneered some novel algorithmic optimisation techniques for power restoration of transmission systems. Some of these techniques have been deployed in collaboration with our partner, the Los Alamos National Laboratories, to mitigate the effects of hurricanes on the coastal areas of the United States.
Data61 ORG, in conjunction with its partners in emergency services in Australia and the United States, is developing state-of-the-art simulation and evacuation algorithms for major flood and fires. Our simulation algorithms use 2-D hydro-dynamic models and high-performance computing, while our optimisation algorithms push the frontier in optimisation and aim at incorporating realistic human behaviors. The resulting systems, and the associated GIS and 3D visualisation platforms, have been validated on large-scale scenarios, where hundreds of thousands of people must be evacuated in suburban areas and major cities.
Data61 ORG pursues research in human dynamics to support its work in disaster management. The goal is to understand human behavior in emergency and panic situations, which can then be used in simulation and optimisation tools. The group also studies the role of social media and crowd-sourcing in emergency situations, identifying the potential benefits and the risks involved in deploying these technologies.
Our research is powered by a host of different technologies.
Simulation and Forecasting
Our simulation algorithms take input forecasts (eg., precipitation levels) and readings from sensors (eg., gauge levels) to simulate the extent and consequences of the disaster with unprecedented speeds. Our simulation tools for flood predication use 2-D hydro-dynamic models and high-performance computing.
Our optimisation algorithms use simulation results to identify the strategic and tactical decisions to mitigate the effect of disasters, suggest operational best-responses, and improve post-disaster recovery efforts. Computational disaster management involves some of the most complex optimisation applications: They combine multiple challenging combinatorial subproblems (e.g., routing, location, and inventory), uncertainty, time constraints, complex objective functions, and multiple objectives. In addition, many of these problems are decentralised and Data61 ORG aims at designing mechanisms to incentivising different agencies to cooperate.
Our 3-D visualisation engine uses fundamental advances in computer graphics and graphics cards to produce real-time, immersive 3D views of the disaster, providing unrivalled situation awareness. Data61 3D is a high-level, multi-platform 3D visualisation tool aimed at users who are not expert in 3D graphics. Besides its usability, its main goal is to be able to display millions of complex objects efficiently.