422 Computational Methods in Multi-uncertainty, Multi-physics and Multi-scale Problems

Chenfeng Li, Swansea University
Francisco MA Pires, University of Porto
D Roger J Owen, Swansea University
 
The development of multi-uncertainty, multi-physics and multi-scale models has received significant attention over the last two decades. New mathematical formulations and numerical solution strategies allied to the increase in computational power/cost ratio have fostered a dramatic growth in this rapidly expanding field. Research activity in this area has been devoted to the development and combination of different analytic tools (homogenization, asymptotic analysis) and computational methods (parallel computing, stochastic analysis, code coupling) for application in fields as diverse as material processing, medical surgery, oil & gas development, etc. Such developments have played a central role in the understanding of the interaction between multi-physics and multi-uncertainty phenomena taking place at multiple scales in space and time. It is also true that in many scientific and engineering problems, the challenges associated with multi-scale and multi-uncertainty often arise together and may be even coupled, and therefore a synthesized solution approach is required. Such challenges are continually emerging, mainly driven by advanced industrial applications, and are driving some of the most prominent research activities in computational mechanics and computational engineering.
In the most general format, the proposed MS targets the latest advances in the modelling of multi-uncertainty, multi-physics and multi-scale problems. The MS welcomes the following (but not exhaustive) list of topics:

• Stochastic modelling, probabilistic engineering, reliability and risk assessment
• Computer simulation of multi-physics processes/systems
• Computational homogenization and multi-scale modelling
• Computational coupling strategies
• High-performance computing related to the 3M (multi-scale, multi-physics and multi-uncertainty) challenges
• Relevant scientific and industrial applications