Publications

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Advancements in our capabilities to accurately model physical systems using high resolution finite element models have led to increasing use of models for prediction of physical system responses. Yet models are typically not used without first demonstrating their accuracy or, at least, adequacy. In high consequence applications where model predictions are used to make decisions or control operations involving human life or critical systems, a movement toward accreditation of mathematical model predictions via validation is taking hold. Model validation is the activity wherein the predictions of mathematical models are demonstrated to be accurate or adequate for use within a particular regime. Though many types of predictions can be made with mathematical models, not all predictions have the same impact on the usefulness of a model. For example, predictions where the response of a system is greatest may be most critical to the adequacy of a model. Therefore, a model that makes accurate predictions in some environments and poor predictions in other environments may be perfectly adequate for certain uses. The current investigation develops a general technique for validating mathematical models where the measures of response are weighted in some logical manner. A combined experimental and numerical example that demonstrates the validation of a system using both weighted and non-weighted response measures is presented.

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Accurate material models are fundamental to predictive structural finite element models. Because potting foams are routinely used to mitigate shock and vibration of encapsulated components in electro/mechanical systems, accurate material models of foams are needed. A linear-viscoelastic foam constitutive model has been developed to represent the foam's stiffness and damping throughout an application space defined by temperature, strain rate or frequency and strain level. Validation of this linear-viscoelastic model, which is integrated into the Salinas structural dynamics code, is being achieved by modeling and testing a series of structural geometries of increasing complexity that have been designed to ensure sensitivity to material parameters. Both experimental and analytical uncertainties are being quantified to ensure the fair assessment of model validity. Quantitative model validation metrics are being developed to provide a means of comparison for analytical model predictions to observations made in the experiments. This paper is one of several recent papers documenting the validation process for simple to complex structures with foam encapsulated components. This paper specifically focuses on model validation over a wide temperature range and using a simple dumbbell structure for modal testing and simulation. Material variations of density and modulus have been included. A double blind validation process is described that brings together test data with model predictions.

Accurate material models are fundamental to predictive structural finite element models. Because potting foams are routinely used to mitigate shock and vibration of encapsulated components in electro/mechanical systems, accurate material models of foams are needed. A linear-viscoelastic foam constitutive model has been developed to represent the foam's stiffness and damping throughout an application space defined by temperature, strain rate or frequency and strain level. Validation of this linear-viscoelastic model, which is integrated into the Salinas structural dynamics code, is being achieved by modeling and testing a series of structural geometries of increasing complexity that have been designed to ensure sensitivity to material parameters. Both experimental and analytical uncertainties are being quantified to ensure the fair assessment of model validity. Quantitative model validation metrics are being developed to provide a means of comparison for analytical model predictions to observations made in the experiments. This paper is one of several recent papers documenting the validation process for simple to complex structures with foam encapsulated components. This paper specifically focuses on model validation over a wide temperature range and using a simple dumbbell structure for modal testing and simulation. Material variations of density and modulus have been included. A double blind validation process is described that brings together test data with model predictions.

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