• Computational Structural Engineering
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• v.3 no.3
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• pp.125-131
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• 1990

A finite element technique for the time dependent large structural problems is presented. It is based on the error estimation for the bases of solution spaces. An a-posteriori energy norm of residual error serves as the error indicator. Mode shapes which are calculated by scaling the Ritz vectors are applied to discretize the continuous spatial domain. Finally, the performance of the proposed methods is demonstrated by solving simple examples.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.1031-1032
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• 2009

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.10a
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• pp.112-120
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• 1992

The use of Pre-processor for building structural analysis used to rely upon filling up fixed format data, which was ineffective and error-prone. This research attempts to integrate structural analysis system with DBMS and CAD system in order to make it easy to exchange data between pre-process, analysis, and post-process stages. Automatic generation of database from pre-process stage allows easy preparation of main input data for other structural analysis programs. CAD system with some sub-programs written in LISP and C works as a graphic user interface. This approach gives an easy, effective and error-free way of inputing data for structural analysis.

• Journal of the Korean Society of Safety
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• v.8 no.3
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• pp.64-72
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• 1993

A large prropotion of structural failures are due to human error at the design stage of a structural engineering project, and many of these failures could have been prevented if there had been proper design checking. Analyses of the data from the 6 engineering firms and 24 professional engineer practitioners are shown on diagrams, also applicated for suggested models; overview checking. And then analyzed results of current work in this area, which examine the effects of error magnitude, are compared to the limit data obtained from the surveys. Overview checking only is analyzed of three typical design checking processes; self checking; Independent detailed checking, and overview checking.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.79-84
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• 1990

The modal parameter estimations of linear multi-degree-of-freedom structural dynamic systems are carried out in time domain. For this purpose, the equation of motion is transformed into the autoregressive and moving average model with auxiliary stochastic input (ARMAX) model. The parameters of the ARMAX model are estimated by using the sequential prediction error method. Then, the modal parameters of the system are obtained thereafter. Experimental results are given for a 3-story building model subject to ground exitations.

• Structural Engineering and Mechanics
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• v.4 no.1
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• pp.1-8
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• 1996

A new error measure for a static finite element analysis is proposed. This error measure is a modification to the Zienkiewicz and Zhu energy norm. The new error estimator is a global error measure for the analysis and is independent of finite element model size and internal stresses, hence it is readily transportable to other error calculations. It is shown in this paper the the new error estimator also produces conservative error measurements, making it a suitable procedure to adopt in commerical packages.

• Structural Engineering and Mechanics
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• v.29 no.5
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• pp.469-488
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• 2008

Finite element methods have often been used for structural analyses of various mechanical problems. When finite element analyses are utilized to resolve mechanical systems, numerical uncertainties in the initial data such as structural parameters and loading conditions may result in uncertainties in the structural responses. Therefore the initial data have to be as accurate as possible in order to obtain reliable structural analysis results. The typical finite element method may not properly represent discrete systems when using uncertain data, since all input data of material properties and applied loads are defined by nominal values. An interval finite element analysis, which uses the interval arithmetic as introduced by Moore (1966) is proposed as a non-stochastic method in this study and serves a new numerical tool for evaluating the uncertainties of the initial data in structural analyses. According to this method, the element stiffness matrix includes interval terms of the lower and upper bounds of the structural parameters, and interval change functions are devised. Numerical uncertainties in the initial data are described as a tolerance error and tree graphs of uncertain data are constructed by numerical uncertainty combinations of each parameter. The structural responses calculated by all uncertainty cases can be easily estimated so that structural safety can be included in the design. Numerical applications of truss and frame structures demonstrate the efficiency of the present method with respect to numerical analyses of structural uncertainties.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.515-516
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• 2010

• Structural Engineering and Mechanics
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• v.74 no.4
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• pp.547-557
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• 2020

In this paper, an automatic adaptive mesh refinement procedure is presented for two-dimensional problems on the basis of a new probabilistic error estimator. First-order perturbation theory is employed to determine the lower and upper bounds of the structural displacements and stresses considering uncertainties in geometric sizes, material properties and loading conditions. A new probabilistic error estimator is proposed to reduce the mesh dependency of the responses dispersion. The suggested error estimator neglects the refinement at the critical points with stress concentration. Therefore, the proposed strategy is combined with the classic adaptive mesh refinement to achieve an optimal mesh refined properly in regions with either high gradients or high dispersion of the responses. Several numerical examples are illustrated to demonstrate the efficiency, accuracy and robustness of the proposed computational algorithm and the results are compared with the classic adaptive mesh refinement strategy described in the literature.

• Communications for Statistical Applications and Methods
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• v.22 no.4
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• pp.349-359
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• 2015

We study a semiparametric Bayesian approach to small area estimation under a nested error linear regression model with area level covariate subject to measurement error. Consideration is given to radial basis functions for the regression spline and knots on a grid of equally spaced sample quantiles of covariate with measurement errors in the nested error linear regression model setup. We conduct a hierarchical Bayesian structural measurement error model for small areas and prove the propriety of the joint posterior based on a given hierarchical Bayesian framework since some priors are defined non-informative improper priors that uses Markov Chain Monte Carlo methods to fit it. Our methodology is illustrated using numerical examples to compare possible models based on model adequacy criteria; in addition, analysis is conducted based on real data.