41 research outputs found

    The FSP Boundary Science Driver Plan

    Full text link

    CFD validation in OECD/NEA t-junction benchmark.

    Get PDF
    When streams of rapidly moving flow merge in a T-junction, the potential arises for large oscillations at the scale of the diameter, D, with a period scaling as O(D/U), where U is the characteristic flow velocity. If the streams are of different temperatures, the oscillations result in experimental fluctuations (thermal striping) at the pipe wall in the outlet branch that can accelerate thermal-mechanical fatigue and ultimately cause pipe failure. The importance of this phenomenon has prompted the nuclear energy modeling and simulation community to establish a benchmark to test the ability of computational fluid dynamics (CFD) codes to predict thermal striping. The benchmark is based on thermal and velocity data measured in an experiment designed specifically for this purpose. Thermal striping is intrinsically unsteady and hence not accessible to steady state simulation approaches such as steady state Reynolds-averaged Navier-Stokes (RANS) models.1 Consequently, one must consider either unsteady RANS or large eddy simulation (LES). This report compares the results for three LES codes: Nek5000, developed at Argonne National Laboratory (USA), and Cabaret and Conv3D, developed at the Moscow Institute of Nuclear Energy Safety at (IBRAE) in Russia. Nek5000 is based on the spectral element method (SEM), which is a high-order weighted residual technique that combines the geometric flexibility of the finite element method (FEM) with the tensor-product efficiencies of spectral methods. Cabaret is a 'compact accurately boundary-adjusting high-resolution technique' for fluid dynamics simulation. The method is second-order accurate on nonuniform grids in space and time, and has a small dispersion error and computational stencil defined within one space-time cell. The scheme is equipped with a conservative nonlinear correction procedure based on the maximum principle. CONV3D is based on the immersed boundary method and is validated on a wide set of the experimental and benchmark data. The numerical scheme has a very small scheme diffusion and is the second and the first order accurate in space and time, correspondingly. We compare and contrast simulation results for three computational fluid dynamics codes CABARET, Conv3D, and Nek5000 for the T-junction thermal striping problem that was the focus of a recent OECD/NEA blind benchmark. The corresponding codes utilize finite-difference implicit large eddy simulation (ILES), finite-volume LES on fully staggered grids, and an LES spectral element method (SEM), respectively. The simulations results are in a good agreement with experimenatl data. We present results from a study of sensitivity to computational mesh and time integration interval, and discuss the next steps in the simulation of this problem

    Filtered Pose Graph for Efficient Kinect Pose Reconstruction

    Get PDF
    Being marker-free and calibration free, Microsoft Kinect is nowadays widely used in many motion-based applications, such as user training for complex industrial tasks and ergonomics pose evaluation. The major problem of Kinect is the placement requirement to obtain accurate poses, as well as its weakness against occlusions. To improve the robustness of Kinect in interactive motion-based applications, real-time data driven pose reconstruction has been proposed. The idea is to utilize a database of accurately captured human poses as a prior to optimize the Kinect recognized ones, in order to estimate the true poses performed by the user. The key research problem is to identify the most relevant poses in the database for accurate and efficient reconstruction. In this paper, we propose a new pose reconstruction method based on modelling the pose database with a structure called Filtered Pose Graph, which indicates the intrinsic correspondence between poses. Such a graph not only speeds up the database poses selection process, but also improves the relevance of the selected poses for higher quality reconstruction. We apply the proposed method in a challenging environment of industrial context that involves sub-optimal Kinect placement and a large amount of occlusion. Experimental results show that our real-time system reconstructs Kinect poses more accurately than existing methods

    Motion Reconstruction Using Sparse Accelerometer Data

    No full text

    LBMD: A Layer-based Mesh Data structure Tailored for Generic API Infrastructures

    No full text
    corecore