[ars]

This is why I hate seeing computer modeling used as science. You get out of it what [assumptions] you put into it.

I'm not saying there's never a use for it, but only in areas with established information to see how it will develop (a weather forecast is a great example), it should never be used to generate the information (i.e. fill in gaps in experimentation or observation).

[pomian]

Also in cases where the physics can truly be modeled. Usually there are so many assumptions, simplifications, and added constants, made so that the math can work, that the model is only applicable in very specific or simplistic cases. Then when proven effective for those cases, it gets applied in the wild, and assumed correct. We have seen many simplistic models from the dos days, upgraded to windows - yet the math hasn't changed. Simplifications made for 1990 computers, linearity for example, are used model non linear events.