Recently, there has been a drive to create more efficient designs of vehicles. This has led to the use of new materials and more rigorous optimization of components. As the design envelope is pushed and new materials are explored, it is more important than ever to ensure that designs are based on a model that has been validated. Currently, a typical validation consists of a simple point-to-point comparison. This method assumes that the model has identified the areas of high stress correctly, and leaves the rest of the model un-validated.This thesis proposes a method to validate computational models using image decomposition and digital image correlation.Digital image correlation is capable of producing full-field strain maps with on the order of 105 to 106 data points. The challenge then becomes comparing the massive amounts of experimental and simulation data.Image decomposition provides a way to reduce those data sets to less than 100 moments while preserving the original information. These compressed data sets can be compared more easily than the original data.As a part of the validation process, the DIC system was calibrated according to a recently published draft ISO standard.Finally, two studies are presented which use image decomposition to compare simulation and experimental results.The first involves an aluminum plate with a hole loaded in tension.The second is a composite protective panel which is bolted at one end and loaded compressively.
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