Abstract
As is well known, classical continuum theories fail to adequately describe material behavior when the scale of applied loads approaches the scale of the material structure (e.g., atoms, grains, cracks, pores) and when locality requirements are not satisfied, i.e., there are long-range forces affecting the body (e.g., atomic interactions). A thin film possessing a columnar structure is an example of such a physical system since any deformation of the film results in interaction between the columns. These interaction forces are transferred to the film substrate and certainly introduce a non-local affect on the otherwise continuous substrate. The analysis in this work begins by establishing the kinematics relationships for a two-dimensional discrete model of a unit cell for the entire structure. The total strain energy of the unit cell is calculated and used to develop Lagrange's equations in this quasi-static case. These equations provide the basis for the continuum governing equations, which are determined through a homogenization process. Homogenization is carried out by applying Taylor series expansions to the displacement fields, the result of which may be thought of in light of a micropolar (or Cosserat) continuum equivalent to the discrete model described above. Numerical results are yet to be obtained and will be presented at the meeting. The goals of this work are to use micropolar theories to account for non-local affects and to develop models that can be used in finite element calculations to simulate and predict the mechanical properties of columnar thin films both during deposition and in service.
Original language | English (US) |
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State | Published - 2004 |
Event | European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2004 - Jyvaskyla, Finland Duration: Jul 24 2004 → Jul 28 2004 |
Other
Other | European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2004 |
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Country/Territory | Finland |
City | Jyvaskyla |
Period | 7/24/04 → 7/28/04 |
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Applied Mathematics