78 L.G. Horta et al. while the impact response suggest a need to increase the modulus. Although this finding seems paradoxical, it only points out the importance of using multiple tests and different types of tests for calibration of models. In fact, a static test would have helped tremendously in solving this dilemma. 7.7 Concluding Remarks The paper discussed results from modal and impact tests along with the corresponding analysis of a composite fuselage section fabricated by the Sikorsky Aircraft Corporation under the US Army’s SARAP. Two model calibration metrics were used throughout the paper to evaluate the model adequacy. Metric 1 measured the proximity of the model response to test, which, when used in conjunction with statistical sampling, allows users to construct analytical bounds of the response of interest. In contrast, Metric 2 compared the basis vectors or impact shapes that made up the response from test and analysis. This approach is analogous to comparing vibration modes in a modal test. In fact, the connection between vibration and impact shapes was established and used for pre-test vibration analysis. In the end, target modes recovered from the vibration test suggested that the overall stiffness of the model needed to be reduced. Photogrammetry data from 16 targets (3 directions per target) was used to compute calibration metrics and to assess model adequacy post-test. Using the metrics and the parameter uncertainty representation, the model is irreconcilable with test. However, achievable levels of agreement in terms of displacements were established. More importantly, data from two distinct tests –a modal test and an impact test– suggested drastically different changes in the model parameters. Specifically, the vibration data suggested that the overall modulus needed to be reduced while the impact data suggested that the modulus should have been increased. References 1. Jackson KE, Littell JD, Horta LG, Annett MS, Fasanella EL, Seal MD (2013) Impact testing and simulation of composite airframe structures. To appear as NASA TM 2. Hallquist JQ (2010) LS-DYNA keyword user’s manual. Version 971, Revision 5.0, Livermore Software Technology Company, Livermore, CA, May 2010 3. Horta LG, Reaves MC, Annett MS, Jackson KE (2011) Multi-dimensional calibration of impact models. Chapter 15. In: Aeronautics and astronautics. Edited by Max Mulder, Published by Intech, Croatia. ISBN 978-953-307-473-3. 307- 473-3, pp. 441–457 4. Oberkampf WL, Barone MF (2006) Measures of agreement between computation and experiment. Validation metrics. Journal of Computational Physics 217:5–56 5. Schwer LE (2007) Validation metrics for response histories: perspectives and case studies. Engineering with Computers 23(4):295–309 6. Juang J-N, Horta LG, Phan M (1992) System/observer/controller identification toolbox. NASA TM 107566, February 1992 7. Horta LG, Juang J-N, Chen C-W (1996) Frequency domain identification toolbox. NASA TM 109039, September 1996
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