Novel high-dimensional multiple failure mode Gaidai reliability methodology for renewable energy harvesting

The design and development of economically viable durable Energy Harvesters (EH) with extended service time requires thorough experimental investigations. Representative physical measurements or extensive Monte Carlo Simulations (MCS) constitute valuable input for industrial design, structural safety and reliability. Wind tunnel experiments, measuring GalloPing EH (GPEH) dynamics were carried out under realistic windspeed conditions. GPEH excessive vibro-dynamics was investigated, utilizing a novel multi-modal structural reliability approach. Investigated piezoelectric wind EH device utilized cantilever beam support sub-structure. By means of free vibration tests, EH’s damping coefficient, cantilever beam stiffness, and effective mass were experimentally assessed. Realistic aerodynamic environmental loads were experimentally reproduced by means of extensive wind tunnel tests. Key finding of this case study lies within successful benchmarking of the state-of-the-art multi-modal reliability method, enabling accurate prognostics of the EH system’s structural failure or damage. The latter constitutes a valuable benefit of the suggested reliability methodology, as existing risk assessment techniques often struggle to tackle dynamic system’s multi-dimensionality, accompanied with complex inter-correlations across GPEH system's critical parts. Conservative design choices for the system's characteristic values and failure thresholds discussed. Existing structural reliability methods suffer from the "curse of dimensionality", i.e., it is challenging to apply univariate Extreme Value Theory (EVT)-based methods to systems with dimensionality higher than two. This investigation aimed to establish novel multi-modal design method for GPEH structural damage risk assessment, particularly suitable for high-dimensional structural systems, exhibiting multiple vibrational failure modes. Current research presents a straightforward, yet efficient methodology for accurate evaluation of failure (hazard or damage) risks for multidimensional, nonlinear green dynamic GPEH systems.