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논문 기본 정보

자료유형
학술저널
저자정보
Lee, Dongkyu (Architectural Engineering Research Department, Steel Structure Research Laboratory, Research Institute of Industrial Science & Technology) Park, Sungsoo (Department of Architectural Engineering, Pusan National University) Shin, Soomi (Department of Architectural Engineering, Pusan National University)
저널정보
테크노프레스 Structural engineering and mechanics : An international journal Structural engineering and mechanics : An international journal 제29권 제5호
발행연도
2008.1
수록면
469 - 488 (20page)

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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.

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