Verification & Validation
We verify that the model is solved correctly (numerics) and that it truly describes reality (comparison with data and experiments).
Numerical simulation lets us explore dozens of scenarios and optimize the design without spending on hardware and wrong prototypes. But a simulation is only as good as its validation: that's why we always check results against physics and against data.
We use computational methods derived from advanced scientific research, chosen according to the phenomenon to describe — not a single software for everything.
In major scientific research, no numerical result is accepted without verification. We apply the same standard.
We verify that the model is solved correctly (numerics) and that it truly describes reality (comparison with data and experiments).
Mesh and convergence analysis: results must not depend on how the problem was discretized.
We quantify computational error and compare with known cases and benchmarks, so predictions have explicit margins.
Results with their uncertainty: you know how much to trust the number.
Comparison between configurations to choose the best before building.
Errors are found on the computer, not in the workshop or at the customer.
We choose the right method and validate the results: reliable predictions to build on.
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