The CSIR’s Design and Optimisation Research Group focuses on developing and applying both mathematical and computational systems and tools, to enable effective decision-making that informs design and optimisation of integrated and complex systems. Research interests include developing computational and data-driven models, validating and verifying simulation methods, applying modelling and simulation approaches to analyse complex systems, and designing and developing multidisciplinary systems and tools to support South African industries. Our primary goal is to act as a driver for radical increase in the speed of product design and radical decrease in production costs and in-service performance.

Value proposition

The world is changing and becoming increasingly complex, requiring the development of technologies capable of addressing problems in integrated and complex systems as is always the case in real world applications.  Emerging activities within Industry 4.0 call for additional actions that allow computational modelling to be more discoverable, usable, and integrate-able with the overall digitalisation. The group aspires to contribute to make an impact by developing systems and tools for emerging computational modelling technologies, namely:

• Data-driven modelling and design
• Integrated multiscale modelling

These technologies have the potential to bring about broader societal impacts on issues of environmental emissions, waste production, natural resource depletion, innovation, economic development, and quality of life. Direct economic impacts for industry include savings on the costs of experiments and faster turnaround time on the development of new complex and integrated systems.  

Capabilities

The research group conducts research in a variety of subject areas and current activities include developing systems and tools for fluid structure interaction, solid mechanics, molecular modelling, computational fluid dynamics, chemical process engineering, finite element modelling, discrete element modelling, design optimization, and data-driven modelling. Computational modelling capabilities include mechanical engineering, chemical engineering, materials science, applied physics, chemistry, mathematical sciences, data-driven science, and use of high-performance computing.

Researchers use a variety of computational software packages and hardware, spanning from local desktop workstations to national Centre for High Performance Computing resources.