Computationally efficient analysis and design optimization of vibrational energy harvesters at the infrastructure scale

Abstract

Recently, computational methodologies have been developed that are tailored to scenarios where a nominal structural model is modified by local features, such as uncertainty in the connection models between structural subsystems or the augmentation of a structural system with energy dissipation devices. In these methodologies, the locality of these features is exploited to yield computational efficiency gains of several orders of magnitude, often reducing computational demands from days to minutes. Additionally, researchers over the last decade have actively studied converting ambient vibration response kinetic energy into electrical energy. Results from the application of the algorithms to two structural models of high-rise buildings equipped with one harvester on the roof and distributed harvesters throughout the upper levels are discussed, specifically the computational efficiency of the method. Additionally, the design parameters of the harvester(s) are often difficult to determine, specifically the mass ratio, stiffness and damping. The computationally efficient methods have also been applied to determine optimal harvester(s) design parameters to maximize the power generated. Results from the design optimizations show that the distributed harvester configuration can generate equal or more power than one harvester with equivalent mass. This potentially allows for more flexibility when incorporating these devices into the overall structural system design.