Inverse methods for characterization of contact areas in mechanical systems

Published

Conference Paper

© The Society for Experimental Mechanics, Inc. 2019. In computational structural dynamics problems, the ability to calibrate numerical models to physical test data often depends on determining the correct constraints within a structure with mechanical interfaces. These interfaces are defined as the locations within a built-up assembly where two or more disjointed structures are connected. In reality, the normal and tangential forces arising from friction and contact, respectively, are the only means of transferring loads between structures. In linear structural dynamics, a typical modeling approach is to linearize the interface using springs and dampers to connect the disjoint structures, then tune the coefficients to obtain sufficient accuracy between numerically predicted and experimentally measured results. This work explores the use of a numerical inverse method to predict the area of the contact patch located within a bolted interface by defining multi-point constraints. The presented model updating procedure assigns contact definitions (fully stuck, slipping, or no contact) in a finite element model of a jointed structure as a function of contact pressure computed from a nonlinear static analysis. The contact definitions are adjusted until the computed modes agree with experimental test data. The methodology is demonstrated on a C-shape beam system with two bolted interfaces, and the calibrated model predicts modal frequencies with <3% total error summed across the first six elastic modes.

Full Text

Duke Authors

Cited Authors

  • Fronk, M; Eschen, K; Starkey, K; Kuether, RJ; Brink, A; Walsh, T; Aquino, W; Brake, M

Published Date

  • January 1, 2019

Published In

Volume / Issue

  • 1 /

Start / End Page

  • 45 - 56

Electronic International Standard Serial Number (EISSN)

  • 2191-5652

International Standard Serial Number (ISSN)

  • 2191-5644

International Standard Book Number 13 (ISBN-13)

  • 9783319742793

Digital Object Identifier (DOI)

  • 10.1007/978-3-319-74280-9_5

Citation Source

  • Scopus