Optimal Design and Performance Evaluation of Lightweight Inerter Systems (LwIS) for Seismic Response Mitigation

An inerter system, based on electromechanical similarity theory and vibration mitigation and isolation technology, represents a category of vibration damping systems. These systems typically improve damping performance by increasing mass or inertia, a method often found to be inefficient, leading to inadequate damping and limited applicability in real-world engineering scenarios. The lightweight inerter system (LwIS) introduced herein offers a more flexible and efficient means of altering structural inertia. Initially, this paper establishes the motion control equations for LwIS, followed by a stochastic analysis to derive the analytical expression for the root mean square displacement under Gaussian white noise excitation. A parametric analysis of LwIS is subsequently conducted, developing a displacement-based parametric strategy. Design examples for single-degree-of-freedom (SDOF) engineering structures under various requirements are provided, demonstrating the validity of LwIS’s optimal parameters through responses to simple harmonic excitation and seismic impacts. The findings indicate that the optimization approach of LwIS, unlike traditional methods, simultaneously addresses the displacement performance of the primary structure and the deformation efficiency of the damping element, thereby facilitating comprehensive optimization. Four optimal design parameters for LwIS are identified, underscoring its applicability to stochastic excitation and a broader range of load cases, thus enhancing its practicality in engineering contexts. LwIS’s design philosophy aims to improve deformation efficiency through an increased deformation enhancement coefficient in the damping element, enhancing damping performance, controlling seismic responses, and achieving superior energy dissipation. The optimal parameters, smaller in value, maximize the potential of the inerter system, aligning with the dual objectives of performance optimization and lightweight design, consequently reducing engineering costs.