A modeling and uncertainty quantification framework for a flexible structure with macrofiber composite actuators operating in hysteretic regimes
Source abstract
Abstract
Macrofiber composites are low cost, durable, and flexible piezoceramic devices that are presently being considered for applications that include shape control of airfoils for improved flight performance, vibration, and noise suppression and energy harvesting. However, macrofiber composites also exhibit hysteresis and constitutive nonlinearities that need to be incorporated in models and model-based control designs to achieve their full capability. In this article, we combine constitutive relations, constructed using the homogenized energy model for ferroelectric hysteresis, with Euler–Bernoulli theory to construct a dynamic macrofiber composite model that quantifies a range of rate-dependent hysteretic behavior of macrofiber composites. Using homogenizing strategies, the macrofiber composite patch is treated as a monolithic material with effective parameters. We initially calibrate the model by estimating parameters through a least squares fit to a subset of the measured data. We find that the estimated parameters yield very accurate fits for quasi-static hysteresis. The estimated parameters also provide reasonably accurate predictions for a range of frequencies that include the first two harmonics. Second, we employ an adaptive Markov chain Monte Carlo algorithm to construct densities and analyze the correlation between parameters. The kernel density estimates derived from the Markov chain Monte Carlo chains imply that most of the model parameters exhibit non-Gaussian distributions.
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Research context
OpenAlex topics: Probabilistic and Robust Engineering Design · Topology Optimization in Engineering · Elasticity and Material Modeling
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Center for Research in Scientific Computation, Department of Mathematics, North Carolina State University, Raleigh, NC, USA
Statistical and Applied Mathematical Sciences Institute (SAMSI), Department of Mathematics, North Carolina State University, Raleigh, NC, USA
Department of Mechanical Engineering, Florida State University, Tallahassee, FL, USA
References (45)
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