Transforming Uncertainty into Predictive Power

High-resolution models are now the norm – but reliable decisions are not. In many technical applications, uncertainties in parameters and input data have a greater impact on the validity of simulations than numerical accuracy itself.

Our research group combines computational mechanics, uncertainty quantification and digital twins to make simulations relevant to decision-making. We integrate uncertainties directly into mechanical modelling and develop efficient methods to predict their impact on system behaviour and performance metrics. In this way, we enable evidence-based decision-making for complex technical systems.