If, as George Box famously claimed, all models are wrong, then the decision to use model predictions to support any decision is a judgement under uncertainty. The uncertainty is epistemic in nature, we don’t know how wrong (inaccurate) model predictions are. To tackle this uncertainty, we need to learn more about the model and it’s predictions. But what do we need to learn, and how much learning is needed before we are able to accept the use of modeling and simulations in our decision making process?
In this presentation, we considered how to establish the use of model predictions as a means of compliance when dealing with system qualification and certification requirements. The decision to use a model for such purposes is one with high consequence. There is potential for large delays, high cost and even risk to life if the decision is wrong. We asked the question of acceptance as one of trust, and by considering the many dimensions of trust show how different approaches to tools, processes and people are necessary to build the confidence and credibility required to use model predictions for high-consequence decisions.
Weapon/Platform Synthetics Subject Matter Expert | Systems Design Airborne Systems at MBDA UK Ltd
Scott Shaw is an aerospace engineer with almost 30 years of experience. He began his career at Cranfield University where he researched and taught computational aerodynamics with a particular interest in the development of credible computational aerodynamics tools for high-speed flows. In 2006 he left academia to help Airbus establish computational means as the primary tool for the prediction of aerodynamic loads and handling qualities in the A350 programme. He held a number of roles in both the U.K. and Germany within the CFD department before becoming responsible for Process Operator Environment where he led activities to integrate computational engineering within the design processes across the flight physics domain. In 2017 he returned to the U.K. to join MBDA where he works within the Systems Design - Airborne Systems capability team as the SME for weapon/platform synthetics providing advice on the application of digital engineering to weapon integration programmes.
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