Stochastic stability analysis of steel tubes with random initial imperfections

Vryzidis, Isaak; Stefanou, George; Papadopoulos, Vissarion

doi:10.1016/j.finel.2013.09.002

Cited by 27 publications

(10 citation statements)

References 32 publications

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“…In the latter example, a separable correlation structure was prescribed with respect to axial and circumferential directions, thereby explicitly accounting for the geometry. More recent effort towards experimental measurement, and stochastic simulation of geometric imperfections in cylindrical shells may be found in [17,18,19].…”

Section: Introductionmentioning

confidence: 99%

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

Scarth

Adhikari

Cabral

et al. 2019

Computer Methods in Applied Mechanics and Engineering

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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 the proposed approach, the algorithm is applied in an uncertainty quantification case study concerning vibration and buckling of an industrial composite aircraft wing model.

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Section: Introductionmentioning

confidence: 99%

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

Scarth

Adhikari

Cabral

et al. 2019

Computer Methods in Applied Mechanics and Engineering

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show abstract

“…Moreover, the stochastic imperfection modal method (SIMM) is widely used to assess the buckling of structures, which investigates conditions where uncertain system parameters are modeled by implementing the probabilistic theory. In [1,2,[12][13][14][15], uncertain structural parameters are modeled as random variables with known probability density functions, and samples of imperfect structures can be generated using the Monte Carlo simulation. A stochastic finite element (FE) approach has been developed in [16,17] to investigate the uncertain buckling behavior of structures involving random geometric properties.…”

Section: Introductionmentioning

confidence: 99%

PSO‐Based Approach for Buckling Analysis of Shell Structures with Geometric Imperfections

Luo

Zhang

2019

Mathematical Problems in Engineering

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The buckling loads of shell structures are sensitive to initial geometric imperfections. Conventional methods used to model geometric imperfections cannot determine the accuracy of buckling loads with high computational efficiency. A new computational approach based on particle swarm optimization (PSO) is proposed to obtain the lower bound of the buckling load of shell structures with geometric imperfections. The proposed approach assumes a nodal geometric position using uncertain parameters. The buckling loads of the shell structures are then optimized using the PSO-based approach. Both academic and practical numerical examples have been thoroughly investigated. Thus, the applicability and accuracy of the proposed method is critically validated.

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“…Fundamentals of the analysis of random fields are described in Vanmarcke (1983). Random fields describe the random variability of most structural material and geometrical properties very precisely (Bucher 2006;Vryzidis et al 2013;Chen et al 2016). Taking into account random fields is crucial in the accurate prediction of system performances, especially field-sensitive failures like buckling (Xi 2015).…”

Section: Introductionmentioning

confidence: 99%

Random Fields of Initial Out of Straightness Leading to Column Buckling

Kala

Valeš

Jönsson

2017

Journal of Civil Engineering and Management

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The elastic load-carrying capacity and buckling trajectory of steel columns under compression with open and hollow cross-sections, whose axis is curved by spatial random fields, are studied in the article. As a result of the spatial curvature of the axis the cross-sections are subjected to compression, bending and torsion from the onset of loading. Numerical simulations are performed using the geometrically non-linear model created using the ANSYS software package. Each simulation run has input random realizations of yield strength and the random field generated using the Latin Hypercube Sampling method. In the plane perpendicular to a perfectly straight column axis, the random observations of deformation trajectories of a node in the middle of the column height are studied. The increasing compression load moves the node along the curve path (open sections) or along the linear path (hollow sections). Large discrepancies in the deformation trajectories of open sections (curvilinear paths) and hollow sections (linear paths) were observed from the comparison of simulation runs. The average and design load-carrying capacities of compressed columns with open cross-sections are lower in comparison to columns with hollow cross-sections due to the lower efficiency of open cross-sections in torsion.

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Stochastic stability analysis of steel tubes with random initial imperfections

Cited by 27 publications

References 32 publications

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

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

PSO‐Based Approach for Buckling Analysis of Shell Structures with Geometric Imperfections

Random Fields of Initial Out of Straightness Leading to Column Buckling

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