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| Content Provider | Tech Science Press |
|---|---|
| Author | Ammar, Amine Cueto, Elias Keunings, Roland Abisset-chavanne, Emmanuelle Chinesta, Francisco Suresh, G. Advani Scheuer, Adrien Advani, Suresh |
| Abstract | Describing the orientation state of the particles is often critical in fibre suspen-sion applications. Macroscopic descriptors, the so-called second-order orientation tensor (or moment) leading the way, are often preferred due to their low computational cost. Clo-sure problems however arise when evolution equations for the moments are derived from the orientation distribution functions and the impact of the chosen closure is often unpre-dictable. In this work, our aim is to provide macroscopic simulations of orientation that are cheap, accurate and closure-free. To this end, we propose an innovative data-based approach to the upscaling of orientation kinematics in the context of fibre suspensions. Since the physics at the microscopic scale can be modelled reasonably enough, the idea is to conduct accurate offline direct numerical simulations at that scale and to extract the corresponding macroscopic descriptors in order to build a database of scenarios. During the online stage, the macroscopic descriptors can then be updated quickly by combining adequately the items from the database instead of relying on an imprecise macroscopic model. This methodology is presented in the well-known case of dilute fibre suspensions (where it can be compared against closure-based macroscopic models) and in the case of suspensions of confined or electrically-charged fibres, for which state-of-the-art closures proved to be inadequate or simply do not exist. |
| Related Links | https://www.techscience.com/CMES/v117n3/33283 |
| Starting Page | 367 |
| Ending Page | 386 |
| ISSN | 15261492 |
| DOI | 10.31614/cmes.2018.04278 |
| Issue Number | 3 |
| Journal | Computer Modeling in Engineering & Sciences (CMES) |
| Volume Number | 117 |
| e-ISSN | 15261506 |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | data-driven upscaling Fibre suspensions closure approximations. |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science Applications |
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