A temperature-robust level-set approach for eigenfrequency optimization

Abstract

The optimization of target eigenfrequencies is crucial for several engineering applications, including dynamical systems. Micro-electro-mechanical systems (MEMS) used in time-keeping applications, for example, require exceptional frequency stability. Most eigenfrequency structural optimization methods focus on a deterministic approach, often neglecting potential fluctuations in operational conditions. Among these, temperature variations have long been known to have a detrimental effect on the natural frequencies of a structure. In this work, we show how eigenfrequency optimization can be applied to the field of structural dynamics while minimizing the variance of natural frequencies caused by external temperature uncertainties. To accomplish this, we employ a level-set optimization algorithm, known for its computational efficiency and ability to define crisp interfaces.