A comparative study on optimization of multiple essentially nonlinear isolators attached to a pipe conveying fluid. (July 2020)

• Record Type: Journal Article
• Authors: Khazaee, Mostafa; Khadem, S.E.; Moslemi, Amin; Abdollahi, Ali
• Is Part Of: Mechanical systems and signal processing. Volume 141(2020)
• Publication Date: 2020-07
• Subjects: Nonlinear energy sink -- Stochastic optimization -- Multi-objective optimization -- Pipe conveying fluid -- Parallel NESs -- Series NESs; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2019.106442
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: Stochastic optimization of NESs attached to fluid-filled pipes is studied. Parallel and series configurations are considered for NESs. The results are compared to deterministic optimization method. It has been proven that the presented approach yields a robust design. The presented method can deal with various sources of uncertainties. Abstract: In recent years, nonlinear energy sinks (NES) have been recognized as a promising method for passive vibration control of pipes conveying fluid due to their advantages over the classic tuned mass damper (TMD). Nevertheless, it has been shown that their performance is highly sensitive to uncertainties, and they are only effective in a narrow range of flow velocities and external excitations. Therefore, uncertainties in both design and aleatory parameters must be considered in their optimal design. For the first time, this article investigates stochastic optimization of multiple NESs configured in parallel and series configurations attached to a simply supported pipe conveying fluid. The main goal of this optimization approach is to overcome the inherent sensitivity of NES performance and increase the efficiency range of that. The optimization problem is based on a multi-objective model, with the aim of maximizing the expected value of the NES efficiency estimated from the monte-carlo (MC) simulations, as well as minimizing the corresponding standard deviation. Stiffness property, damping, mass ratio, and location of NES are considered as random design parameters. The distributions of NESs efficiency for stochastic based optimizations are compared to deterministic optima. The results demonstrate that the stochastic optima are much more robust than the deterministic one, and is able to deal with various sources of uncertainties particularly in initial excitation and flow velocity. It is observed that there is an optimal number for NESs in both configurations, above which the performance would not be improved and maybe reduced by increasing the number of them. Also, comparing the present work to other similar works, yields a satisfying result.