Home / Journals / CMES / Vol.83, No.3, 2012
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  • Open Access

    ARTICLE

    An Adaptive Extended Kalman Filter Incorporating State Model Uncertainty for Localizing a High Heat Flux Spot Source Using an Ultrasonic Sensor Array

    M.R. Myers1, A.B. Jorge2, D.E. Yuhas3, D.G. Walker1
    CMES-Computer Modeling in Engineering & Sciences, Vol.83, No.3, pp. 221-248, 2012, DOI:10.3970/cmes.2012.083.221
    Abstract An adaptive extended Kalman filter is developed and investigated for a transient heat transfer problem in which a high heat flux spot source is applied on one side of a thin plate and ultrasonic pulse time of flight is measured between spatially separated transducers on the opposite side of the plate. The novel approach is based on the uncertainty in the state model covariance and leverages trends in the extended Kalman filter covariance to drive changes to the state model covariance during convergence. This work is an integral part of an effort to develop a system capable of locating the… More >

  • Open Access

    ARTICLE

    Large Rotation Analyses of Plate/Shell Structures Based on the Primal Variational Principle and a Fully Nonlinear Theory in the Updated Lagrangian Co-Rotational Reference Frame

    Y.C. Cai1, S.N. Atluri2
    CMES-Computer Modeling in Engineering & Sciences, Vol.83, No.3, pp. 249-274, 2012, DOI:10.3970/cmes.2012.083.249
    Abstract This paper presents a very simple finite element method for geometrically nonlinear large rotation analyses of plate/shell structures comprising of thin members. A fully nonlinear theory of deformation is employed in the updated Lagrangian reference frame of each plate element, to account for bending, stretching and torsion of each element. An assumed displacement approach, based on the Discrete Kirchhoff Theory (DKT) over each element, is employed to derive an explicit expression for the (18x18) symmetric tangent stiffness matrix of the plate element in the co-rotational reference frame. The finite rotation of the updated Lagrangian reference frame relative to a globally… More >

  • Open Access

    ARTICLE

    Local Moving Least Square - One-Dimensional IRBFN Technique: Part I - Natural Convection Flows in Concentric and Eccentric Annuli

    D. Ngo-Cong1,2, N. Mai-Duy1, W. Karunasena2, T. Tran-Cong1,3
    CMES-Computer Modeling in Engineering & Sciences, Vol.83, No.3, pp. 275-310, 2012, DOI:10.3970/cmes.2012.083.275
    Abstract In this paper, natural convection flows in concentric and eccentric annuli are studied using a new numerical method, namely local moving least square - one dimensional integrated radial basis function networks (LMLS-1D-IRBFN). The partition of unity method is used to incorporate the moving least square (MLS) and one dimensional-integrated radial basis function (1D-IRBFN) techniques in an approach that leads to sparse system matrices and offers a high level of accuracy as in the case of 1D-IRBFN method. The present method possesses a Kronecker-Delta function property which helps impose the essential boundary condition in an exact manner. The method is first… More >

  • Open Access

    ARTICLE

    Local Moving Least Square - One-Dimensional IRBFN Technique: Part II- Unsteady Incompressible Viscous Flows

    D. Ngo-Cong1,2, N. Mai-Duy1, W. Karunasena2, T. Tran-Cong1,3
    CMES-Computer Modeling in Engineering & Sciences, Vol.83, No.3, pp. 311-352, 2012, DOI:10.3970/cmes.2012.083.311
    Abstract In this study, local moving least square - one dimensional integrated radial basis function network (LMLS-1D-IRBFN) method is presented and demonstrated with the solution of time-dependent problems such as Burgers' equation, unsteady flow past a square cylinder in a horizontal channel and unsteady flow past a circular cylinder. The present method makes use of the partition of unity concept to combine the moving least square (MLS) and one-dimensional integrated radial basis function network (1D-IRBFN) techniques in a new approach. This approach offers the same order of accuracy as its global counterpart, the 1D-IRBFN method, while the system matrix is more… More >

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