This is the problem with models. They're not perfect, lot's variables cannot be modeled or accounted for, so you have to make assumptions. You can strive for accuracy all you want, you can create functions for your model so it agrees with a range experimental results, outside of that range the model is useless. Inside of that range the model is approximate at best. No matter what, when you assume you make an ass out of you and me. The more assumptions you make the more of an ass you come across as.