Description
Digital simulation is used by engineers as never before to describe the physical world and envision potential catastrophic events during design. Nonetheless, we are far from being able to trust our digital high-fidelity models, because of their complexity, their modelling limitations, and their error-prone setup process. Verification and validation - V&V - lie at the basis of a sound engineering analysis. Very often probability distributions are used to achieve V&V via Monte Carlo simulation for the verification and via Bayesian analysis for the validation. In the research we challenge these approaches providing an alternative route to V&V based on intervals and p-boxes.Intervals provide a more rigorous way than Monte Carlo simulation to verify digital models, even though there isn't a universal formula for its application to every model. In this first part of the talk I will present the technological challenges related to the projection of intervals through digital models, and also what is currently possible to bypass the existing limitations. In spite of their rigour, intervals can not be propagated through the so called black-box models and therefore alternative strategies commonly based on sampling will be presented. Nonetheless, engineering models, however complex, are seldom black-boxes, but rather a long and intricate list of interconnected logical instructions. The possibility of performing the uncertainty propagation by means of intermediate compilers that are capable of replacing the ordinary arithmetic operations with the equivalent uncertain version is proposed.
| Period | 22 Oct 2019 |
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| Held at | University of Oxford, United Kingdom |
| Degree of Recognition | International |