Model Simplification by Asymptotic Order of Magnitude Reasoning

Kenneth Man-kam Yip

One of the hardest problems in reasoning about a physical system is finding an approximate model that is mathematically tractable and yet captures the essence of the problem. Approximate models in science are often constructed by informal reasoning based on consideration of limiting cases, knowledge of relative importance of terms in the model, and understanding of gross features of the solution. We show how an implemented program can combine such knowledge with a heuristic simplification procedure and an inequality reasoner to simplify difficult fluid equations.

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