The goal of “as-built” computational modeling is to incorporate the most representative geometry and material information for an (fabricated or legacy) object into simulations. While most engineering finite element simulations are based on an object’s idealized “as-designed” configuration with information obtained from technical drawings or computer-aided design models, as-built modeling uses nondestructive characterization and metrology techniques to provide the feature information. By incorporating more representative geometry and material features as initial conditions, the uncertainty in the simulation results can be reduced, providing a more realistic understanding of the event and object being modeled. In this paper, key steps and technology areas in the as-built modeling framework are: (1) inspection using nondestructive characterization and metrology techniques; (2) data reduction (signal and image processing including artifact removal, data sensor fusion, and geometric feature extraction); and (3) engineering and physics analysis using finite element codes. We illustrate the process with a cylindrical phantom and include a discussion of the key concepts and areas that need improvement. Our results show that reasonable as-built initial conditions based on a volume overlap criteria can be achieved and that notable differences between simulations of the as-built and as-designed configurations can be observed for a given load case. Specifically, a volume averaged difference of accumulated plastic strain of 3% and local spatially varying differences up to 10%. The example presented provides motivation and justification to engineering teams for the additional effort required in the as-built modeling of high value parts. Further validation of the approach has been proposed as future work.
As-Built Modeling of Objects for Performance Assessment
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Kokko, E. J., Martz, H. E., Jr., Chinn, D. J., Childs, H. R., Jackson, J. A., Chambers, D. H., Schneberk, D. J., and Clark, G. A. (June 29, 2006). "As-Built Modeling of Objects for Performance Assessment." ASME. J. Comput. Inf. Sci. Eng. December 2006; 6(4): 405–417. https://doi.org/10.1115/1.2353856
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