Digital-twin Co-evolution using Continuous Validation

In a continuous improvement design-operation continuum, model-based digital twins are used throughout. However, to make correct decisions, the model must remain a valid representation of the real-world system it twins. If a system only performs its cyclic operation, it may fail to collect the right data to detect when the model invalidation occurs. To tackle this challenge, we propose a workflow that works with continuous validation, in which a system's digital twin continuously performs validation experiments, such that trust can be placed on the validity of the model.