Modeling and simulation of complex systems.

Simulation of complex systems has evolved into a research discovery tool but has not yet been employed to the degree called for in many energy technology development areas. Such models and simulations, drawing upon the dramatic scale up of computational power and associated architectures and algorithmic innovation, can address complex systems with many degrees of freedom and with multiple length and time scales of interest. These system characteristics are important for many energy technology challenges. They are crucial for characterizing natural systems such as the atmosphere, ocean, biosphere couplings crucial for understanding climate and for social systems such as the global economy and its response to energy and environmental policy change or the dynamics of emerging "gigacities." Advancing the methodologies for analyzing and simulating complex nonlinear systems will be important for avoiding the unintended consequences that so often arise when energy issues are addressed in isolation from complex technical, policy, social and behavioral feedbacks.

The Advanced Systems, Modelling and Simulation Research Group undertakes leading research into challenging complex systems problems involving enterprises, people, processes and technologies. Our research advances modelling and simulation methods to provide greater insight and understanding, encompassing a wide range of methods from abstract mathematical representations, sophisticated computer simulations through to hardware in the loop simulation. The focus of this research is not only on development of better modelling and simulation methodologies, but also on the application of state of the art techniques to help understand and predict the behaviour of complex systems. Applications for our research span many industry sectors including aerospace, automotive, construction, counter-terrorism, defence, energy, healthcare, manufacturing, transport and virtual engineering.

At the heart of our approach is the strong desire to balance stakeholder perspectives with input from engineering and non-engineering disciplines. This application of a multi-disciplinary systems engineering methodology is key to performing the cross-domain trade-offs required to deliver future optimal solutions.

Verification, validation and assurance are foremost in our minds as we develop appropriate model based systems engineering solutions.

_________________________________________