• Computational Structural Engineering
• /
• v.5 no.1
• /
• pp.97-108
• /
• 1992

This paper is an attempt to account for the uncertainty of the residual strength in the reliability analysis of structural systems. For this purpose the stochastic finite element method(SFEM) is linked to the system reliability analysis procedure. The stochastic finite element is known to be able to a more explicitly consider the effect of uncerainties of material and geometric variables on those of load effects in structural analysis procedure. The method has been applied to system as well as component reliability analysis of a plane structure. Comparison of the results by the present approach is made with the method in which the residual strength of failed component is treated as deterministic variable. Several case studies have been carried to show the effect of uncertainty in residual strength of a member after failure. Is has been conformed that reidual strength very much affect the system reliability level. It can be, hence, concluded that the uncertainties in the post-ultirnate behaviour may have to be taken into account in the system reliability analysis for a better a ssessment of the system reliability especially for a structure of which member behaviour is modelled as asemi-brittle model. And then the stochastic finite element method can efficiently evaluate the system reliability.

• Korea-Australia Rheology Journal
• /
• v.16 no.1
• /
• pp.1-15
• /
• 2004

The computation of viscoelastic flow using neural networks and stochastic simulation (CVFNNSS) is developed from the point of view of Eulerian CONNFFESSIT (calculation of non-Newtonian flows: finite elements and stochastic simulation techniques). The present method is based on the combination of radial basis function networks (RBFNs) and Brownian configuration fields (BCFs) where the stress is computed from an ensemble of continuous configuration fields instead of convecting discrete particles, and the velocity field is determined by solving the conservation equations for mass and momentum with a finite point method based on RBFNs. The method does not require any kind of element-type discretisation of the analysis domain. The method is verified and its capability is demonstrated with the start-up planar Couette flow, the Poiseuille flow and the lid driven cavity flow of Hookean and FENE model materials.

• Computational Structural Engineering
• /
• v.7 no.1
• /
• pp.125-134
• /
• 1994

Response variability of reinforced concrete frame subjected to material property randomness has been evaluated with the aid of the finite element method. The spatial variation of Young's modulus is assumed to be a two-dimensional homogeneous stochastic process. Young's Modulus of concrete material has been investigated based on the uiaxial strength of concrete cylinder. Direct Monte Carlo simulation method is used to investigate the response of reinforced concrete frame due to the variation of Young's modulus with the Neumann expansion method and the pertubation method. The results by three analytic methods are compared with those by deterministic finite element analysis. These stochastic technique may be an efficient tool for evaluating the structural safety and reliability of reinforced concrete structures.

• Structural Engineering and Mechanics
• /
• v.39 no.4
• /
• pp.541-558
• /
• 2011

This paper presents an analysis of stochastic eigenvalue problem of plane bar structures. Particular attention is paid to the effect of spatial variations of the flexural properties of the structure on the first four eigenvalues. The problem of spatial variations of the structure properties and their effect on the first four eigenvalues is analyzed in detail. The stochastic eigenvalue problem was solved independently by stochastic finite element method (stochastic FEM) and Monte Carlo techniques. It was revealed that the spatial variations of the structural parameters along the structure may substantially affect the eigenvalues with quite wide gap between the two extreme cases of zero- and full-correlation. This is particularly evident for the multi-segment structures for which technology may dictate natural bounds of zero- and full-correlation cases.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.19 no.8
• /
• pp.1822-1831
• /
• 1995

A general formulation of the design optimization problem with the random parameters is presented here. The formulation is based on the stochastic finite element second-order perturbation method ; it takes into full account of the stress and displacement constraints together with the rates of change of the random variables. A method of direct differentiation for calculating the sensitivity coefficients in regard to the governing equation and the second-order perturbed equation is derived. A gradient-based nonlinear programming technique is used to solve the problem. The numerical results are specifically noted, where the stiffness parameter and external load are treated as random variables.

• Smart Structures and Systems
• /
• v.26 no.3
• /
• pp.311-318
• /
• 2020

The goal of this study is to analytically and non-stochastically generate structural uncertainty behaviors of isotropic beams and laminated composite plates under plane stress conditions by using an interval finite element method. Uncertainty parameters of structural properties considering resistance and load effect are formulated by interval arithmetic and then linked to the finite element method. Under plane stress state, the isotropic cantilever beam is modeled and the laminated composite plate is cross-ply lay-up [0/90]. Triangular shape with a clamped-free boundary condition is given as geometry. Through uncertainties of both Young's modulus for resistance and applied forces for load effect, the change of structural maximum deflection and maximum von-Mises stress are analyzed. Numerical applications verify the effective generation of structural behavior uncertainties through the non-stochastic approach using interval arithmetic and immediately the feasibility of the present method.

• Structural Engineering and Mechanics
• /
• v.4 no.6
• /
• pp.703-715
• /
• 1996

In stochastic analysis, the randomness of the structural parameters is taken into consideration and the response variability is obtained in addition to the conventional (mean) response. In the present paper the structural response variability of plate structure is calculated using the weighted integral method and is compared with the results obtained by different methods. The stochastic field is assumed to be normally distributed and to have the homogeneity. The decomposition of strain-displacement matrix enabled us to extend the formulation to the stochastic analysis with the quadratic elements in the weighted integral method. A new auto-correlation function is derived considering the uncertainty of plate thickness. The results obtained in the numerical examples by two different methods, i.e., weighted integral method and Monte Carlo simulation, are in a close agreement. In the case of the variable plate thickness, the obtained results are in good agreement with those of Lawrence and Monte Carlo simulation.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.19 no.4
• /
• pp.387-407
• /
• 2015

This paper analyzes the $h{\times}p$ version of the finite element method for optimal control problems constrained by elliptic partial differential equations with random inputs. The main result is that the $h{\times}p$ error bound for the control problems subject to stochastic partial differential equations leads to an exponential rate of convergence with respect to p as for the corresponding direct problems. Numerical examples are used to confirm the theoretical results.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.36 no.1
• /
• pp.116-127
• /
• 1994

A reliability analysis model for the frame structure which grafts the discretized ideal plastic method to the stochastic finite element method is introduced. The proposed method simmulates realistically the sequencial occurrence of plastic hinges and yields the probability of failure directly from the geometrical and material properties of a frame structure. The presented method can also take into account the uncertainties inherent in loads and resisten- ces through the stochastic finite element technique. The analysis results are compared with those of the Monte Carlo Simmulation, the Bound Theory, and the fs-unzipping method, and show good agreement.

• Smart Structures and Systems
• /
• v.10 no.2
• /
• pp.89-110
• /
• 2012

This study was intended to efficiently perform the probabilistic optimal safety assessment of steel cable-stayed bridges (SCS bridges) using stochastic finite element analysis (SFEA) and expected life-cycle cost (LCC) concept. To that end, advanced probabilistic finite element algorithm (APFEA) which enables to execute the static and dynamic SFEA considering aleatory uncertainties contained in random variable was developed. APFEA is the useful analytical means enabling to conduct the reliability assessment (RA) in a systematic way by considering the result of SFEA based on linearity and nonlinearity of before or after introducing initial tensile force. The appropriateness of APFEA was verified in such a way of comparing the result of SFEA and that of Monte Carlo Simulation (MCS). The probabilistic method was set taking into account of analytical parameters. The dynamic response characteristic by probabilistic method was evaluated using ASFEA, and RA was carried out using analysis results, thereby quantitatively calculating the probabilistic safety. The optimal design was determined based on the expected LCC according to the results of SFEA and RA of alternative designs. Moreover, given the potential epistemic uncertainty contained in safety index, failure probability and minimum LCC, the sensitivity analysis was conducted and as a result, a critical distribution phase was illustrated using a cumulative-percentile.