Simulation Validation And Interpretation

3. Uncertainty analysis

• Separate numerical, parametric, and model-form uncertainty.
• For stochastic methods, report confidence intervals and effective sample quality.
• For deterministic solvers, report discretization and solver tolerance effects.

4. Sensitivity and robustness

• Identify high-impact parameters and interactions.
• Test robustness to plausible perturbations in assumptions.
• Flag brittle conclusions that change under minor parameter shifts.

5. Interpretation and decisions

• State what is strongly supported, weakly supported, and unknown.
• Tie conclusions directly to validated metrics and uncertainty bounds.
• Provide next experiments or simulations needed to reduce key uncertainty.

Domain notes

• FDTD: include numerical dispersion and boundary absorber quality checks.
• FEM: include element-quality checks, conditioning concerns, and BC sensitivity.
• Monte Carlo and transport: include variance convergence, bias controls, and seed reproducibility.
• Medical physics: separate research interpretation from clinical decision support unless externally validated.

Reporting template

• Objective and modeled quantity.
• Verification evidence.
• Validation evidence.
• Uncertainty table with dominant contributors.
• Interpretation with confidence level.
• Actionable next steps.

Red flags

• No mesh or timestep study but strong quantitative claims.
• Benchmark mismatch explained only qualitatively.
• Uncertainty omitted from key decision plots/tables.
• Conclusions presented outside validated domain of the model.