Damage Detection of the Rod in the Crossflow Using Surrogate-Based Modelling-Reference-Cited by-同舟云学术

Damage Detection of the Rod in the Crossflow Using Surrogate-Based Modelling

Published:2021-10-01 Issue:5 Volume:58 Page:50-62
ISSN:2255-8896
Container-title:Latvian Journal of Physics and Technical Sciences
language:en
Short-container-title:

Author:

Upnere S.¹²,Auzins J.¹

Affiliation:

1. Institute of Mechanics and Mechanical Engineering , Riga Technical University , 6B Kipsalas Str. , Riga , Latvia

2. Ventspils University of Applied Sciences , 101 Inzenieru Str ., Ventspils , Latvia

Abstract

Abstract An effective and accurate methodology is developed to create an inverse surrogate model for the mass reduction analysis of the rod in the rod bundle inserted in the crossflow. The performance of two surrogate modelling approaches has been evaluated. These models are the Response Surface Method and Legendre polynomial approximations. The relationship between dominant frequencies, support stiffness and rod mass derived from Computational Fluid Dynamics simulations is used as input data for approximations. The selection of sample points is implemented with a new type of orthogonal design. The results have shown that the proposed methodology can reliably replace the finite volume model and drastically reduce computational time.

Publisher

Walter de Gruyter GmbH

Subject

Psychiatry and Mental health,Neuropsychology and Physiological Psychology

Link

https://www.sciendo.com/pdf/10.2478/lpts-2021-0039

Reference20 articles.

1. 1. Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response surface methodology: Process and product optimization using designed experiments. New York: John Wiley & Sons.

2. 2. Khaledi, K., Miro, S., Konig, M., & Schanz, T. (2014). Robust and Reliable Metamodels for Mechanized Tunnel Simulations. Computers and Geotechnics, 61, 1–12.

3. 3. Forrester, A., & Keane, A. (2009). Recent Advances in Surrogate-Based Optimization. Progress in Aerospace Science, 45 (1–3), 50–79.

4. 4. Filho, U., Antunes, A., Bastos, S., & Lyra, P. (2015). Minimization of Vortex Induced Vibrations Using Surrogate Based Optimization. Structural and Multidisciplinary Optimization, 52 (4), 717–735.

5. 5. Banyay, G. A., Shields, M. D., & Brigham, J. C. (2019). Efficient Global Sensitivity Analysis for Flow-Induced Vibration of a Nuclear Reactor Assembly Using Kriging Surrogates. Nuclear Engineering and Design, 341, 1–15.