Random field simulation over curved surfaces: applications to computational structural mechanics

Scarth, C., Adhikari, S. , Cabral, P.H., Silva, G.H.C. and Prado, A.P.D. (2019) Random field simulation over curved surfaces: applications to computational structural mechanics. Computer Methods in Applied Mechanics and Engineering, 345, pp. 283-301. (doi: 10.1016/j.cma.2018.10.026)

Abstract

It is important to account for inherent variability in the material properties in the design and analysis of engineering structures. These properties are typically not homogeneous, but vary across the spatial coordinates within a structure, as well as from specimen to specimen. This form of uncertainty is commonly modelled using random fields within the Stochastic Finite Element Method. Simulation within this framework can be complicated by the dependence of a random field’s correlation function upon the geometry of the domain over which it is defined. In this paper, a new method is proposed for simulating random fields over a general two-dimension curved surface, represented as a finite element mesh. The covariance function is parametrised using the geodesic distance, evaluated using the solution to the ‘discrete geodesic problem,’ and a point discretisation approach is subsequently applied in order to sample the random field at the nodes of the model. The major contribution of the present work is the development of a methodology for simulating random fields over curved surfaces of arbitrary geometry, with a focus upon non-intrusive application to industrial finite element models using ‘off the shelf’ commercial software. In order to demonstrate the potential impact of the proposed approach, the algorithm is applied in an uncertainty quantification case study concerning vibration and buckling of an industrial composite aircraft wing model.

• Item Type: Articles
• Additional Information: The authors acknowledge the financial support received from Engineering Research Network Wales (Sêr Cymru National Research Networks) with Grant No. NRN 102.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Adhikari, Professor Sondipon
• Authors: Scarth, C., Adhikari, S., Cabral, P.H., Silva, G.H.C., and Prado, A.P.D.
• College/School: College of Science and Engineering > School of Engineering > Infrastructure and Environment
• Journal Name: Computer Methods in Applied Mechanics and Engineering
• Publisher: Elsevier
• ISSN: 0045-7825
• ISSN (Online): 1879-2138
• Published Online: 02 November 2018

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