A quantitative assessment of the model form error of friction models across different interface representations for jointed structures
Autor: | Matthew R. W. Brake, Clayton R. Little, Justin H. Porter, Nidish Narayanaa Balaji |
---|---|
Rok vydání: | 2022 |
Předmět: |
Physical model
Mechanical Engineering Modal analysis Mathematical analysis Mode (statistics) Aerospace Engineering Slip (materials science) Computer Science Applications Nonlinear system Hysteresis Control and Systems Engineering Signal Processing Representation (mathematics) Rayleigh quotient Civil and Structural Engineering Mathematics |
Zdroj: | Mechanical Systems and Signal Processing. 163:108163 |
ISSN: | 0888-3270 |
DOI: | 10.1016/j.ymssp.2021.108163 |
Popis: | Hysteretic models are widely used to model frictional interactions in joints to recreate experimental behavior. However, it is unclear which models are best suited for fitting or predicting the responses of structures. The present study evaluates 26 friction model/interface representation combinations to quantify the model form error. A Quasi-Static Modal Analysis approach (termed Rayleigh Quotient Nonlinear Modal Analysis) is adopted to calculate the nonlinear system response, and a Multi-Objective Optimization is solved to fit experimental data of the first mode of the Brake-Reus Beam. Optimized parameters from the first mode are applied to the second and third bending modes to quantify the predictive ability of the models. Formulations for both tracing full hysteresis loops and recreating hysteresis loops from a single loading curve (Masing assumptions) are considered. Smoothly varying models applied to a five patch representation showed the highest flexibility (for fitting mode 1) and good predictive potential (for modes 2 and 3). For a second formulation, which uses 152 frictional elements to represent the interface, the physically motivated spring in series with a Coulomb slip model (elastic dry friction) has high error for fitting mode 1 and performs near the middle for predicting higher modes. For both interface representation, the best fit models are not the most physical, but rather the ones with the most parameters (as expected); however, the more physical models perform somewhat better for predicting the higher modes. |
Databáze: | OpenAIRE |
Externí odkaz: |