The development of simulation in all domains allows one to believe in the fantasy that numerical simulations will be sufficient to develop the systems of the future, when all the multi-physics aspects will be perfectly mastered. All this assumes that the simulation models give perfect satisfaction. In this context, full field measurement such as digital image correlation (DIC) help engineers get the most information of a testing campaign and provide a valuable tool to build trust in simulation results. But DIC reveals that test/FEA correlation tools currently aren't up to the tasks, and are creating a bottleneck in the analysis workflow.
Being able to rely on a data fusion platform proves valuable to build trust in the simulation predictions across the structure. The EikoTwin platform was designed to aggregate full-field results as well as individual sensor contributions. Having a comprehensive view of model errors is necessary to start building confidence in materials, interfaces, boundary conditions, as well as estimating simulation uncertainties.
Presenter: Florent MATHIEU, EikoSim
