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    A Refined Methodology for Calibrating Premium Connection Make-ups

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    Ostergaard_EB_T_2013.pdf (29.60Mb)
    Downloads: 839
    Date
    2013-03-21
    Author
    Ostergaard, Erik Barr
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    Abstract
    Digital Image Correlation is used to generate high-spatial-density full-field displacement
    and strain data of a connection box outer diameter for use in the calibration of finite element
    make-up models. Image acquisition and data processing techniques are discussed and best
    practice recommendations are made. 3D-wedge models consisting of a twenty-degree sweep of
    the connection geometry are generated from manufacturer supplied profiles. Deformation
    plasticity material models are developed from identified minimum strength material coupons.
    Axisymmetric and 3D meshing schemes are used to capture the geometric complexity, supply
    enough resolution to represent seal performance, and provide a solution in an acceptable
    timeframe. Several techniques for achieving good contact resolution are presented. The
    mechanics of the full 3D connection makeup are decomposed into simple idealized
    representations. Finite element boundary conditions are developed to adequately represent the
    360-degree make-up mechanics in a wedge section. The wedge model is loaded to achieve a
    torque-rotation coupling which satisfies the experimental make-up conditions. This model
    displays a much improved ability to capture box outer diameter strain and displacement fields,
    and thus better represents the mechanics of a connection make-up. A 3D inspired axisymmetric
    pretension loading scheme is developed which enables the 3D-wedge seal conditions to be
    replicated in a computationally efficient axisymmetric form for connection performance
    evaluation. Seal metrics are developed and converged to evaluate connection sealing capabilities
    in the power-tight configuration. Modeling error metrics are developed, and the final 3D-wedge
    model is evaluated relative to the experimental DIC data.
    URI
    http://hdl.handle.net/10919/19294
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    • Masters Theses [20800]

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