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  • Open Access

    ARTICLE

    Probabilistic Collocation used in a Two-Step approach for \\efficient uncertainty quantification in computational fluid dynamics.

    G.J.A. Loeven1,2, H. Bijl3

    CMES-Computer Modeling in Engineering & Sciences, Vol.36, No.3, pp. 193-212, 2008, DOI:10.3970/cmes.2008.036.193

    Abstract In this paper a Two-Step approach is presented for uncertainty quantification for expensive problems with multiple uncertain parameters. Both steps are performed using the Probabilistic Collocation method. The first step consists of a sensitivity analysis to identify the most important parameters of the problem. The sensitivity derivatives are obtained using a first or second order Probabilistic Collocation approximation. For the most important parameters the probability distribution functions are propagated using the Probabilistic Collocation method using higher order approximations. The Two-Step approach is demonstrated for flow around a NACA0012 airfoil with eight uncertain parameters in the free stream conditions and geometry.… More >

  • Open Access

    ARTICLE

    Three Dimensional Acoustic Shape Sensitivity Analysis by Means of Adjoint Variable Method and Fast Multipole Boundary Element Approach

    C.J. Zheng1, H.B. Chen1, T. Matsumoto2, T. Takahashi2

    CMES-Computer Modeling in Engineering & Sciences, Vol.79, No.1, pp. 1-30, 2011, DOI:10.3970/cmes.2011.079.001

    Abstract A fast multipole boundary element approach to the shape sensitivity analysis of three dimensional acoustic wave problems is developed in this study based on the adjoint variable method. The concept of material derivative is employed in the derivation. The Burton-Miller formula which is a linear combination of the conventional and normal derivative boundary integral equations is adopted to cope with the non-uniqueness problem when solving exterior acoustic wave problems. Constant elements are used to discretize the boundary surface so that the strongly- and hyper-singular boundary integrals contained in the formulations can be evaluated explicitly and the numerical process can be… More >

  • Open Access

    ARTICLE

    Acoustic Design Shape and Topology Sensitivity Formulations Based on Adjoint Method and BEM

    T. Matsumoto1, T. Yamada1, T. Takahashi1, C.J. Zheng2, S. Harada1

    CMES-Computer Modeling in Engineering & Sciences, Vol.78, No.2, pp. 77-94, 2011, DOI:10.3970/cmes.2011.078.077

    Abstract Shape design and topology sensitivity formulations for acoustic problems based on adjoint method and the boundary element method are presented and are applied to shape sensitivity analysis and topology optimization of acoustic field. The objective function is assumed to consist only of boundary integrals and quantities defined at certain number of discrete points. The adjoint field is defined so that the sensitivity of the objective function does not include the unknown sensitivity coefficients of the sound pressures and particle velocities on the boundary and in the domain. Since the final sensitivity expression does not have the sensitivity coefficients of the… More >

  • Open Access

    ARTICLE

    Topological Derivative-Based Optimization of Micro-Structures Considering Different Multi-Scale Models

    E.A. de Souza Neto1, S. Amstutz2, S.M. Giusti3, A.A. Novotny3

    CMES-Computer Modeling in Engineering & Sciences, Vol.62, No.1, pp. 23-56, 2010, DOI:10.3970/cmes.2010.062.023

    Abstract A recently proposed algorithm for micro-structural optimization, based on the concept of topological derivative and a level-set domain representation, is applied to the synthesis of elastic and heat conducting bi-material micro-structures. The macroscopic properties are estimated by means of a family of multi-scale constitutive theories where the macroscopic strain and stress tensors (temperature gradient and heat flux vector in the heat conducting case) are defined as volume averages of their microscopic counterparts over a Representative Volume Element (RVE). Several finite element-based examples of micro-structural optimization are presented. Three multi-scale models, providing an upper and a lower bound for the macroscopic… More >

  • Open Access

    ARTICLE

    Natural neighbour Petrov-Galerkin Method for Shape Design Sensitivity Analysis

    Kai Wang1, Shenjie Zhou1,2, Zhifeng Nie1, Shengli Kong1

    CMES-Computer Modeling in Engineering & Sciences, Vol.26, No.2, pp. 107-122, 2008, DOI:10.3970/cmes.2008.026.107

    Abstract The natural neighbour Petrov-Galerkin method (NNPG) is one of the special cases of the generalized meshless local Petrov-Galerkin method (MLPG). This paper demonstrates the NNPG can be successfully used in design sensitivity analysis in 2D elasticity. The design sensitivity analysis method based on the local weak form (DSA-LWF) in the NNPG context is proposed. In the DSA-LWF, the local weak form of governing equation is directly differentiated with respect to design variables and discretized with NNPG to obtain the sensitivities of structural responds. The calculation of derivatives of shape functions with respect to design variables is avoided. No background meshes… More >

  • Open Access

    ARTICLE

    Identification of dynamical systems with fractional derivative damping models using inverse sensitivity analysis

    R Sivaprasad1,2, S Venkatesha1, C S Manohar1,3

    CMC-Computers, Materials & Continua, Vol.9, No.3, pp. 179-208, 2009, DOI:10.3970/cmc.2009.009.179

    Abstract The problem of identifying parameters of time invariant linear dynamical systems with fractional derivative damping models, based on a spatially incomplete set of measured frequency response functions and experimentally determined eigensolutions, is considered. Methods based on inverse sensitivity analysis of damped eigensolutions and frequency response functions are developed. It is shown that the eigensensitivity method requires the development of derivatives of solutions of an asymmetric generalized eigenvalue problem. Both the first and second order inverse sensitivity analyses are considered. The study demonstrates the successful performance of the identification algorithms developed based on synthetic data on one, two and a 33… More >

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