To ensure the validity of these assumptions, various methods can be employed:
Experimental Validation: Comparing model predictions with experimental data helps in assessing the accuracy of the assumptions. Sensitivity Analysis: This involves changing the parameters related to the assumptions and observing the impact on model outputs. Literature Comparison: Comparing the assumptions and results with previously published studies provides an additional layer of validation.
