Abstract
While numerical modeling is an important tool in many areas of engineering, caution must be exercised when developing and applying these models. This is especially true when models are developed under calibration conditions, which is referred to herein as the calibration domain, and applied to predict (or forecast) outcomes under a different set of conditions, which is referred to as the forecasting domain. This work discusses a case study of predictive capability of a simple model away from its calibration domain. The application is to predict the payload that a quadcopter is able to lift. Model development is supported by two calibration experiments. The first experiment measures displacements obtained by attaching masses to various springs; it is used to develop a model that predicts displacement as a function of weight. The second experiment measures displacements resulting from spinning propeller blades of various dimensions; it is used to develop a model that predicts displacement as a function of blade diameter and revolutions-per-minute. Both models are combined to predict the payload that a quadcopter can lift, which represents an extrapolated forecast because conditions of the quadcopter differ from those under which the models are calibrated. Finally the quadcopter is tested experimentally to assess the predictive accuracy of the model. This application illustrates a preliminary thought process to ultimately determine how models developed in calibration domains perform in forecasting domains. (Approved for unlimited, public release, LA-UR-16-24484.)
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Acknowledgments
The authors acknowledge the support of the 2016 Dynamics Summer School at Los Alamos National Laboratory (LANL), and the Advanced Scientific Computing program and Advanced Certification Campaign. Los Alamos National Security, L.L.C., operates LANL under contract DE-AC52-06NA25396 on behalf of the National Nuclear Security Administration of the U.S. Department of Energy.
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Graybill, P., Tarekegn, E., Tomkinson, I., Van Buren, K., Hemez, F., Cogan, S. (2017). A Case Study in Predictive Modeling Beyond the Calibration Domain. In: Barthorpe, R., Platz, R., Lopez, I., Moaveni, B., Papadimitriou, C. (eds) Model Validation and Uncertainty Quantification, Volume 3. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-54858-6_4
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DOI: https://doi.org/10.1007/978-3-319-54858-6_4
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