Optimization under Uncertainty of a Chain of Nonlinear Resonators using a Field Representation

TL;DR

This paper presents a robust stochastic optimization method combined with a field representation to design nonlinear resonator chains that effectively mitigate vibrations despite uncertainties, enabling advanced wave manipulation.

Contribution

It introduces a novel approach integrating a tailored stochastic optimization algorithm with a field formulation for designing nonlinear resonator chains under uncertainty.

Findings

Robust designs outperform constant property designs.

Field representation reduces optimization dimensionality.

Nonlinearities enable enhanced vibration mitigation.

Abstract

Chains of resonators in the form of spring-mass systems have long been known to exhibiting interesting properties such as band gaps. Such features can be leveraged to manipulate the propagation of waves such as the filtering of specific frequencies and, more generally, mitigate vibrations and impact. Adding nonlinearities to the system can also provide further avenues to manipulate the propagation of waves in the chain and enhance its performance. This work proposes to optimally design such a chain of resonators to mitigate vibrations in a robust manner by accounting for various sources of design uncertainties (e.g., nonlinear stiffness) and aleatory uncertainties (e.g., loading). The stochastic optimization algorithm is tailored to account for discontinuities in the chain response due to the presence of nonlinearities. In addition, a field formulation is used to define the properties of the resonators along the chain and reduce the dimensionality of the optimization problem. It is shown that the combination of the stochastic optimization algorithm and the field representation leads to robust designs that could not be achieved with optimal properties constant over the chain.