Application of radial basis functions to linear and nonlinear structural analysis problems

被引:31
|
作者
Tiago, C. M. [1 ]
Leitao, V. M. A. [1 ]
机构
[1] Univ Tecn Lisboa, ICIST, Dept Engn Civil & Arquitectura, Inst Super Tecn, P-1049001 Lisbon, Portugal
关键词
D O I
10.1016/j.camwa.2006.04.008
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The basic characteristic of the techniques generally known as meshless methods is the attempt to reduce or even to eliminate the need for a discretization (at least, not in the way normally associated with traditional finite element techniques) in the context of numerical solutions for boundary and/or initial value problems. The interest in meshless methods is relatively new and this is why, despite the existence of various applications of meshless techniques to several problems of mechanics (as well as to other fields), these techniques are still relatively unknown to engineers. Furthermore, and compared to traditional finite elements, it may be difficult to understand the physical meaning of the variables involved in the formulations. As an attempt to clarify some aspects of the meshless techniques, and simultaneously to highlight the ease of use and the ease of implementation of the algorithms, applications are made, in this work, to structural analysis problems. The technique used here consists of the definition of a global approximation for a given variable of interest (in this case, components of the displacement field) by means of a superposition of a set of conveniently placed (in the domain and on the boundary) radial basis functions (RBFs). In this work various types of one-dimensional problems are analyzed, ranging from the static linear elastic case, free vibration and linear stability analysis (for a beam on elastic foundation), to physically nonlinear (damage models) problems. To further complement the range of problems analysed, the static analysis of a plate on elastic foundation was also addressed. Several error measures are used to numerically establish the performance of both symmetric and nonsymmetric approaches for several global RBFs. The results obtained show that RBF collocation leads to good approximations and very high convergence rates. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1311 / 1334
页数:24
相关论文
共 50 条
  • [31] Elasto-Plastic Analysis of Structural Problems Using Atomic Basis Functions
    Kozulic, V.
    Gotovac, B.
    CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2011, 80 (3-4): : 251 - 274
  • [32] Application of radial basis functions in solving fuzzy integral equations
    Asari, Sh. S.
    Amirfakhrian, M.
    Chakraverty, S.
    NEURAL COMPUTING & APPLICATIONS, 2019, 31 (10): : 6373 - 6381
  • [33] Application of Radial Basis Functions to Represent Optical Freeform Surfaces
    Cakmakci, Ozan
    Kaya, Ilhan
    Fasshauer, Gregory E.
    Thompson, Kevin P.
    Rolland, Jannick P.
    INTERNATIONAL OPTICAL DESIGN CONFERENCE 2010, 2010, 7652
  • [34] IMAGE WARPING BY RADIAL BASIS FUNCTIONS - APPLICATION TO FACIAL EXPRESSIONS
    ARAD, N
    DYN, N
    REISFELD, D
    YESHURUN, Y
    CVGIP-GRAPHICAL MODELS AND IMAGE PROCESSING, 1994, 56 (02): : 161 - 172
  • [35] Application of radial basis functions in solving fuzzy integral equations
    Sh. S. Asari
    M. Amirfakhrian
    S. Chakraverty
    Neural Computing and Applications, 2019, 31 : 6373 - 6381
  • [36] Application of image repairing algorithm based on radial basis functions
    School of Automatic, WUT, Wuhan 430070, China
    不详
    Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban), 2006, 4 (678-681):
  • [37] APPLICATION OF PIECEWISE-LINEAR POLYNOMIAL FUNCTIONS IN ANALYSIS OF EIGENVALUE PROBLEMS
    LIOU, CT
    CHOU, YS
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 1987, 18 (12) : 2359 - 2367
  • [38] NONLINEAR MODELING AND PREDICTION BY SUCCESSIVE APPROXIMATION USING RADIAL BASIS FUNCTIONS
    HE, XD
    LAPEDES, A
    PHYSICA D, 1994, 70 (03): : 289 - 301
  • [39] Intuitionistic Fuzzy Radial Basis Functions Network for modeling of nonlinear dynamics
    Todorov, Yancho
    Koprinkova-Hristova, Petia
    Terziyska, Margarita
    2017 21ST INTERNATIONAL CONFERENCE ON PROCESS CONTROL (PC), 2017, : 410 - 415
  • [40] INTERPOLATION BY PIECEWISE-LINEAR RADIAL BASIS FUNCTIONS .2.
    LIGHT, WA
    CHENEY, EW
    JOURNAL OF APPROXIMATION THEORY, 1991, 64 (01) : 38 - 54