ILLINOISROCSTAR LLC — Department of Energy SBIR Phase I: 18a

Description

As modeling and simulation become even more prevalent and important in industry, government, and academic research, it becomes critical to enable tools for ensuring that the results of those simulations are accurate with quantified confidence. The sciences of sensitivity analysis, uncertainty quantification, and optimization are active areas of research, but have known baseline techniques that should be applied to simulation work much more often than they currently are. The issues standing in the way of wider use are tied to accessibility of tools, understanding of the techniques, and the need for their application. A government-developed toolset is available for use that assists in addressing the accessibility issue. However, understanding the tools and the need for their use is currently less wide-spread. Further, the tools need to be “democratized” by addressing user workflows with streamlined input generation and output analysis to enable timely feedback and insight generation. This project introduces these tools into a graphical web-browser-based cloud computing simulation toolset that will bring these techniques and tools to a much wider audience, initially focusing on chemistry and materials science simulation. Techniques for producing sensitivity analyses and uncertainty quantifications for molecular dynamics simulations will be formulated and documented. Prototype user interfaces will be developed using an existing cloud computing system to demonstrate the feasibility of the techniques, and the possibilities for workflow streamlining for these types of analyses. Multiscale simulation requirements will be investigated. Sensitivity, uncertainty quantification, and optimization calculations are all analyses that most simulation professionals know should be done, but in many cases are not. This is for the most part due to cost and difficulty. Allowing the production of these advanced analyses in a widely available commercial product will be useful for advancing the state-of-the-art in simulation across many industries and scientific area, and will also cut costs and improve results.