To ensure their reliability, simulation results should be validated against what?

Validation of simulation results is crucial for ensuring that the model accurately represents the real-world system it is simulating. The most effective way to achieve this is by comparing the outcomes of the simulation with experimental data and known solutions. This approach allows for a direct assessment of the simulation's accuracy and credibility, as it demonstrates whether the model can replicate established results under the same conditions.

Using experimental data provides a benchmark from real-world scenarios, allowing engineers and researchers to see if the simulation results align with what has actually been observed. Similarly, known solutions serve as a theoretical standard that can be used to ensure that the computational methods employed in the simulation are sound and that the results are mathematically valid.

Other methods, such as comparing variations produced by the same simulation, may help in analyzing the stability or sensitivity of the model, but they do not offer a concrete measure of the simulation's validity. Therefore, relying on experimental data and known solutions is the most reliable method of validation, establishing a strong foundation for the integrity and usability of the simulation results.