The unifying drive of the CDT in Next Generation Computational Modelling is education, application and further development of state-of-the-art computer simulation methodology to advance insight and progress in academia and industry.
Computer simulation methodology includes:
We believe that advances in computational modelling methodology must happen in the context of real world research challenges from research domains in industry and academia. CDT research projects will generally be aligned with research challenges within the research domains listed below. In each of these domains the University of Southampton has a significant track record in computational research and an international reputation for research excellence.
Innovative engineering remains a key strength of the UK, and one that is increasingly dependent on fast and accurate computational models. In traditional areas of computational engineering such as structures, fluid dynamics and turbulence, fluid-structure interactions, and aero acoustics, the models are often (but not always) relatively well established but the desired accuracy is not achievable with today's computational resources.
Computational challenges in computational engineering include:
Advanced materials, including nanomaterials and devices, metamaterials and composites, have been identified by David Willetts as one of the eight great technologies to push the UK's economy forward: A significant research investment is taking place in the area of multi-functional nanoelectronics where functional nanomaterials couple stress, electric polarisation, magnetization, photonic and thermal properties, and metamaterials which can be used for a wide range of applications, including sensors, actuators, tailored waveguides, data storage, and data processing. Advanced materials are a major component of UK exports, and open up completely new commercial opportunities with strong growth potential.
Computational challenges in advanced material modelling include:
Autonomous agent systems, e.g., smart infrastructure, unmanned air vehicles, sensor networks, algorithmic trading and intelligent cybersecurity, is a key emerging area, explicitly recognised by both the UK's Minister for Science and Chancellor.
Simulation modelling is central to the development of autonomous agent systems that can be relied upon. The increasing deployment of autonomous systems in dynamic, uncertain, critical and possibly hazardous environments (e.g., war zones, disaster recovery, emerging markets, national infrastructure) creates demand for
There is an increasing need for computational modelling at the medical research interface to interpret clinical and next generation sequencing (NGS) data in the context of increasingly vast repositories of biological information, to drive drug design, and to improve the organisation and deployment of healthcare resources.
Bioinformatic modelling and simulation provides the key link between extraordinary computational power and productive medical science. Novel simulation approaches are imperative within a pharma industry that must rationalise and interpret experimentally observed behaviour at the molecular level in order to generate profitable lines of experimental inquiry. Moreover, simulation is becoming an increasingly important tool for complex health-care organizations which must overcome critical organizational, logistical and resource challenges if they are to manage themselves and deliver care efficiently and effectively to an ageing and ever more demanding population, with limited budgets, advancing medical technology and increased expectations.
Computational challenges in healthcare and biomedicine include: