4. Model Calibration and Model Validation

Model validation is an accuracy check that compares simulation results with independent experimental data, while model calibration (or updating) deliberately adjusts uncertain parameters to improve the model’s predictive fit, two distinct steps that must never be conflated.

Calibration is indispensable when parameters such as joint stiffness-damping in structural dynamics or surface emissivity and contact resistances in thermal analyses cannot be measured directly; engineers solve an inverse problem against modal shapes or temperature arrays to estimate them.

Credible practice tunes only those unmeasurable parameters and uses broad response data to avoid over-fitting, leaving directly measurable properties like Young’s modulus untouched.

Once calibration is complete, validation must confront the calibrated model with new experiments (different loads, boundary conditions, or environments) to test genuine predictive power instead of recycling the same data set.

Guidelines from ASME V&V 20 and NAFEMS formalise this “calibrate-then-validate” workflow and require documented evidence of both steps when models support design certification or regulatory review.

Failing to keep the two activities separate, or re-running validation on the calibration data, creates a false sense of certainty that auditors and regulators increasingly view as a serious credibility gap.