ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

A semi-intrusive stochastic perturbation method for lift prediction and global sensitivity analysis

Suryawanshi, Anup and Ghosh, Debraj (2017) A semi-intrusive stochastic perturbation method for lift prediction and global sensitivity analysis. In: AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING, 31 (3, SI). pp. 277-285.

Full text not available from this repository. (Request a copy)
Official URL: http://doi.org/10.1017/S0890060417000178

Abstract

Sensitivity analysis plays an important role in finding an optimal design of a structure under uncertainty. Quantifying relative importance of random parameters, which leads to a rank ordering, helps in developing a systematic and efficient way to reach the optimal design. In this work, lift prediction and sensitivity analysis of a potential flowaround a submerged body is considered. Such flow is often used in the initial design stage of structures. The flow computation is carried out using a vortex-panel method. A few parameters of the submerged body and flow are considered as random variables. To improve the accuracy in lift prediction in a computationally efficient way, a new semi-intrusive stochastic perturbation method is proposed. Accordingly, a perturbation is applied at the linear system solving level involving the inuence coefficient matrix, as opposed to using perturbation in the lift quantity itself. This proposed method, which is partially analogous to the intrusive or Galerkin projection methods in spectral stochastic finite element methods, is found to be more accurate than using perturbation directly on the lift and faster than a direct simulation. The proposed semi-intrusive stochastic perturbation method is found to yield faster estimates of the Sobol' indices, which are used for global sensitivity analysis. From global sensitivity analysis, the flow parameters are found to be more important than the parameters of the submerged body.

Item Type: Journal Article
Publication: AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING
Additional Information: Copy right for this article belongs to the CAMBRIDGE UNIV PRESS, 32 AVENUE OF THE AMERICAS, NEW YORK, NY 10013-2473 USA
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Date Deposited: 01 Sep 2017 09:06
Last Modified: 01 Sep 2017 09:06
URI: http://eprints.iisc.ac.in/id/eprint/57711

Actions (login required)

View Item View Item