Feature extraction for structural dynamics model validation
- Los Alamos National Laboratory
- UNIV OF TOKYO
- UNIV OF SHEFFIELD
This study focuses on defining and comparing response features that can be used for structural dynamics model validation studies. Features extracted from dynamic responses obtained analytically or experimentally, such as basic signal statistics, frequency spectra, and estimated time-series models, can be used to compare characteristics of structural system dynamics. By comparing those response features extracted from experimental data and numerical outputs, validation and uncertainty quantification of numerical model containing uncertain parameters can be realized. In this study, the applicability of some response features to model validation is first discussed using measured data from a simple test-bed structure and the associated numerical simulations of these experiments. issues that must be considered were sensitivity, dimensionality, type of response, and presence or absence of measurement noise in the response. Furthermore, we illustrate a comparison method of multivariate feature vectors for statistical model validation. Results show that the outlier detection technique using the Mahalanobis distance metric can be used as an effective and quantifiable technique for selecting appropriate model parameters. However, in this process, one must not only consider the sensitivity of the features being used, but also correlation of the parameters being compared.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC52-06NA25396
- OSTI ID:
- 1040824
- Report Number(s):
- LA-UR-10-07534; LA-UR-10-7534; TRN: US201211%%193
- Resource Relation:
- Conference: IMAC XXIX A Conference and Exposition on Structural Dynamics ; January 31, 2011 ; Jacksonville, FL
- Country of Publication:
- United States
- Language:
- English
Similar Records
VALIDATION OF TRANSIENT STRUCTURAL DYNAMICS SIMULATIONS: AN EXAMPLE
Uncertainty quantification tools for multiphase gas-solid flow simulations using MFIX