Biomateriomics by Steven W. Cranford & Markus J. Buehler

Author:Steven W. Cranford & Markus J. Buehler
Language: eng
Format: epub
Publisher: Springer Netherlands, Dordrecht

6.2 Advantages of Modeling and Computation

There is an apparent disconnect between theoretical model building (i.e. closed-form solutions to problems) and experimental results. To validate any predictive theory (about the failure strength of a material, for example), one is inclined to make comparisons with experiments. However, analytical models typically contain unknown parameters, which have to be fitted to computational or empirical results. Indeed, many fields have retroactively uncovered the “truth” behind such parameters, and one can invoke the colloquial idiom “hindsight is 20/20”. Modeling and computational simulation provides an alternative route. A well parameterized material model is as commensurable as a physical specimen. Moreover, unlike a physical sample, you cannot lose, break, or ruin a model (you can, however, forget how to formulate it!). Once created, a model, like an idea, cannot be destroyed.2 The advantages of modeling and computational investigation are numerous, for example, through simulation you can: Focus on specific material behaviors: There can be a disconnect between experimental procedures and intended material response. Computational modeling allows a one-to-one correspondence between simulation and response, allowing idealized and isolated material testing.

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