This special section of the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems: Part B comprises ten papers related to recent advances and emerging approaches on response analysis and optimization of energy harvesting dynamic systems in presence of uncertainties. A concerted effort was made to achieve broad geographic representation, while the invited papers are characterized by rich thematic and methodological diversity and present developments on both fundamental research and engineering applications.
More specifically, the contributions can be categorized with respect to the following three distinct themes: (1) Numerical methods for stochastic response analysis, reliability-based design, and performance assessment of energy harvesters; (2) Uncertainty quantification and modeling of energy harvesters; and (3) Inerter-based energy harvesters subject to random excitations.
In the first theme, Grigoriu developed a method, based on Monte Carlo simulation and by relying on Slepian's model, for calculating excursion statistics of the voltage process above a specified threshold generated by primary-absorber harvesting systems subject to Gaussian stationary excitation processes. These excursion statistics can be viewed as performance metrics, and can be potentially used for optimizing the configuration and parameters of energy harvesting systems in random environments. Further, Petromichelakis et al. developed a Wiener path integral based methodology for stochastic analysis and reliability-based design of nonlinear piezoelectric energy harvesters modeled in part using fractional derivatives. The accuracy of the proposed methodology was verified versus Monte Carlo analysis for a wide range of harvesters. Alevras leveraged the concept of stochastic resonance to improve harvested power from harmonic excitations with additive Gaussian noise accounting for the nonlinear effects of the energy harvesting circuitry. A numerical path integral technique was employed to expedite parametric analyses, and recommendations on beneficial circuitry layouts and their parameters were reported. Finally, Arena et al. proposed the use of a trapezoidal storm model to assess the reliability of oscillating water column (OWC) devices, used for energy harvesting from sea waves, against extreme weather conditions. It was shown that peak response statistics of a nonlinear model of the harvester derived by Monte Carlo simulation analysis using the proposed model compare well with data from recorded storm time-histories, thus confirming the suitability of the adopted storm model for safety checks of OWC devices prior to site installation.
Contributing to the second theme, Poblete et al. proposed and applied a Bayesian updating technique in conjunction with a transitional Markov chain Monte Carlo simulation for estimating the electromechanical properties of piezoelectric energy harvesters based on available experimental data. Moreover, Rajarathinam and Ali explored the feasibility of using a vibration absorber for harvesting energy due to random excitation, and in presence of parametric uncertainties. Optimal electrical and mechanical parameter values were reported related to a two degrees-of-freedom linear system. Finally, Wang et al. presented a methodology for nonparametric uncertainty quantification of bimorph piezoelectric energy harvesters modeled by standard finite element software. The effects of uncertainty to mass, stiffness, and electromechanical coupling matrices to the harvested power were quantified, demonstrating the robustness of strongly coupled harvesters.
The third theme includes the contribution of Shen et al., who explored the potential of linear systems equipped with tuned inerter devices to be used for energy harvesting under both white noise and colored noise stochastic excitations. To this aim, they performed theoretical and parametric analyses for selecting optimal inerter parameters, and for determining the combined system power output. Further, Asai et al. conducted real-time hybrid testing of an electromagnetic motor with an embedded tuned inerter for energy generation from a randomly excited linear single-degree-of-freedom structure. Experimentally measured power generation performance matched well simulated data derived from a numerical model of the motor controlled via a Kalman filtering approach. It was found that the inclusion of the tuned inerter benefits significantly the energy harvesting. Finally, Giaralis assessed numerically the potential of an energy harvesting enabled dynamic vibration absorber featuring an inerter element for simultaneously improving vibration suppression and energy generation performances as inertance scales-up through gearing. Favorable results were reported for single- and multi-degrees-of-freedom host structures subject to random white noise excitations for various vibration absorber and primary structure properties.
The Guest Editors acknowledge the leadership by Professor Bilal Ayyub gratefully. Further, they express their appreciation to each and every one of the authors whose contributions constitute the very basis for the fruition and success of this special section.
