• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1920-1929
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• 1994

The stochastic finite element method(SFEM) based structural optimal design is presented. Random system response including uncertainties for the design variable is calculated with first order perturbation method. A method for calculating the sensitivity coefficients is developed using the equilibrium equation and first-order perturbed equation. Numerical results are presented for a truss, frame and plate structures with displacement and stress constraints. The sensitivity calculation proposed here is compared with finite difference method. A nonlinear programming technique is used to solve the problem. The procedure is easily incorporated with existing deterministic structural optimization.

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

• Structural Engineering and Mechanics
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• v.84 no.2
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• pp.207-224
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• 2022

The mechanical behavior of prestressed concrete haunched beams (PSHBs) was investigated in depth using a finite element modeling technique in this study. The efficiency of finite element modeling was investigated in the first stage by taking into account a previous study from the literature. The first stage's findings suggested that finite element modeling might be preferable for modeling PSHBs. In the second stage of the research, a comprehensive parametric study was carried out to determine the effect of each parameter on PSHB load capacity, including haunch angle, prestress level, compressive strength, tensile reinforcement ratio, and shear span to depth ratio. PSHBs and prestressed concrete rectangular beams (PSRBs) were also compared in terms of capacity. Stochastic analysis was used in the third stage to define the uncertainty in PSHB capacity by taking into account uncertainty in geometric and material parameters. Standard deviation, coefficient of variation, and the most appropriate probability density function (PDF) were proposed as a result of the analysis to define the randomness of capacity of PSHBs. In the study's final section, a new equation was proposed for using symbolic regression to predict the load capacity of PSHBs and PSRBs. The equation's statistical results show that it can be used to calculate the capacity of PSHBs and PSRBs.

• Bulletin of the Korean Mathematical Society
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• v.51 no.3
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• pp.847-862
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• 2014

Finite element approximation solutions of the optimal control problems for stochastic Stokes equations with the forcing term perturbed by white noise are considered. Error estimates are established for the fully coupled optimality system using Brezzi-Rappaz-Raviart theory. Numerical examples are also presented to examine our theoretical results.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.157-164
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• 1998

An elasto-plastic stochastic finite element method is developed to evaluate the probability of failure of the underground structure. The Mohr-Coulomb failure criteria is adopted for yield condition. The material properties such as the elastic modulus and the cohesion are assumed to be statistically independent random variables which are modeled as spatial stochastic fields. The displacements around the excavated area and the probability of the failure are examined by varying the coefficient of variance for each variables. It is found that the developed procedure can provide the proper probabilistic information about the failure of the underground structure

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.1
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• pp.54-62
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• 1994

The expanding technique of the Stochastic Finite Element Method(SFEM) is proposed in this paper for adapting direct integration methods in stochastical dynamic analysis of structures. Grafting the direct integration methods and the SFEM together, one can deal with nonlinear structures and nonstationary process problems without any restriction. The stochastical central diffrence and stochastic Houbolt methods are introduced to show the expanding technique, and their adaptabilities are discussed. Results computed by the proposed method (the Stochastic Finite Element Method in Dynamics: SFEMD) for two degree-of-free- dom system are compared with those obtained by Monte Carlo Simulation.

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

• Computers and Concrete
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• v.15 no.2
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• pp.259-277
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• 2015

The lack of experimental studies on the mechanical behavior of reinforced concrete (RC) haunched beams leads to difficulties in statistical and reliability analyses. This study performs stochastic and reliability analyses of the ultimate shear capacity of RC haunched beams based on nonlinear finite element analysis. The main aim of this study is to investigate the influence of uncertainty in material properties and geometry parameters on the mechanical performance and shear capacity of RC haunched beams. Firstly, 65 experimentally tested RC haunched beams and prismatic beams are analyzed via deterministic nonlinear finite element method by a special program (ATENA) to verify the efficiency of utilized numerical models, the shear capacity and the crack pattern. The accuracy of nonlinear finite element analyses is verified by comparing the results of nonlinear finite element and experiments and both results are found to be in a good agreement. Afterwards, stochastic analyses are performed for each beam where the RC material properties and geometry parameters are assigned to take probabilistic values using an advanced simulating procedure. As a result of stochastic analysis, statistical parameters are determined. The statistical parameters are obtained for resistance bias factor and the coefficient of variation which were found to be equal to 1.053 and 0.137 respectively. Finally, reliability analyses are accomplished using the limit state functions of ACI-318 and ASCE-7 depending on the calculated statistical parameters. The results show that the RC haunched beams have higher sensitivity and riskiness than the RC prismatic beams.

• Structural Engineering and Mechanics
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• v.15 no.4
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• pp.381-394
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• 2003

While constructing multistorey buildings with reinforced concrete framed structures it is a common practice to provide parking space for vehicles at the ground floor level. This floor will generally consist of open frames without any infilled walls and is called an open-storey. From a post disaster damage survey carried out, it was noticed that during the January 26, 2001 Bhuj (Gujarat, India) earthquake, a large number of reinforced concrete framed buildings with open-storey at ground floor level, suffered extensive damage and in some cases catastrophic collapse. This has brought into sharp focus the need to carry out systematic studies on the seismic vulnerability of such buildings. Determination of vulnerability requires realistic structural response estimations taking into account the stochasticity in the loading and the system parameters. The stochastic finite element method can be effectively used to model the random fields while carrying out such studies. This paper presents the details of stochastic finite element analysis of a five-storey three-bay reinforced concrete framed structure with open-storey subjected to standard seismic excitation. In the present study, only the stochasticity in the system parameters is considered. The stochastic finite element method used for carrying out the analysis is based on perturbation technique. Each random field representing the stochastic geometry/material property is discretised into correlated random variables using spatial averaging technique. The uncertainties in geometry and material properties are modelled using the first two moments of the corresponding parameters. In evaluating the stochastic response, the cross-sectional area and Young' modulus are considered as independent random fields. To study the influence of correlation length of random fields, different correlation lengths are considered for random field discretisation. The spatial expectations and covariances for displacement response at any time instant are obtained as the output. The effect of open-storey is modelled by suitably considering the stiffness of infilled walls in the upper storey using cross bracing. In order to account for changes in soil conditions during strong motion earthquakes, both fixed and hinged supports are considered. The results of the stochastic finite element based seismic analysis of reinforced concrete framed structures reported in this paper demonstrate the importance of considering the effect of open-storey with appropriate support conditions to estimate the realistic response of buildings subjected to earthquakes.

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