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

Carl Scarth, Sondipon Adhikari, Pedro Higino Cabral, Gustavo H.C. Silva, Alex Pereira do Prado

Computer Methods in Applied Mechanics and Engineering, Volume: 345, Pages: 283 - 301

Swansea University Author: Sondipon Adhikari

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DOI (Published version): 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 uncertai...

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Published in: Computer Methods in Applied Mechanics and Engineering
ISSN: 00457825
Published: 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa45491
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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.
Keywords: Stochastic finite element, Random field, Monte Carlo simulation, Uncertainty quantification, Aircraft wing
College: Faculty of Science and Engineering
Start Page: 283
End Page: 301

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