A gradient-based optimization approach for the detection of partially connected surfaces using vibration tests


Journal Article

© 2018 Elsevier B.V. The integrity of engineering structures is often compromised by embedded surfaces that result from incomplete bonding during the manufacturing process, or initiation of damage from fatigue or impact processes. Examples include delaminations in composite materials, incomplete weld bonds when joining two components, and internal crack planes that may form when a structure is damaged. In many cases the areas of the structure in question may not be easily accessible, thus precluding the direct assessment of structural integrity. In this paper, we present a gradient-based, partial differential equation (PDE)-constrained optimization approach for solving the inverse problem of interface detection in the context of steady-state dynamics. An objective function is defined that represents the difference between the model predictions of structural response at a set of spatial locations, and the experimentally measured responses. One of the contributions of our work is a novel representation of the design variables using a density field that takes values in the range [0,1]andraised and raised to an integer exponent that promotes solutions to be near the extrema of the range. The density field is combined with the penalty method for enforcing a zero gap condition and realizing partially bonded surfaces. The use of the penalty method with a density field representation leads to objective functions that are continuously differentiable with respect to the unknown parameters, enabling the use of efficient gradient-based optimization algorithms. Numerical examples of delaminated plates are presented to demonstrate the feasibility of the approach.

Full Text

Duke Authors

Cited Authors

  • Aquino, W; Bunting, G; Miller, ST; Walsh, TF

Published Date

  • March 1, 2019

Published In

Volume / Issue

  • 345 /

Start / End Page

  • 323 - 335

International Standard Serial Number (ISSN)

  • 0045-7825

Digital Object Identifier (DOI)

  • 10.1016/j.cma.2018.11.002

Citation Source

  • Scopus