Design of ultra-thin composite deployable shell structures through machine learning
| Author(s): |
Miguel Bessa
Sergio Pellegrino |
|---|---|
| Medium: | conference paper |
| Language(s): | English |
| Conference: | Interfaces: Architecture, Engineering, Science, Annual Meeting of the International Association of Shell & Spatial Structures (IASS), Hamburg, 25-27 September 2017 |
| Published in: | Interfaces: Architecture . Engineering . Science |
| Year: | 2017 |
| Abstract: | A data-driven computational framework is applied for the design of optimal ultra-thin deployable structures with improved buckling behavior. High-fidelity computational analyses and machine learning are used to construct design charts that are shown to guide the structural design. |
Structure Types
- About this
data sheet - Reference-ID
10077840 - Published on:
20/04/2018 - Last updated on:
05/03/2019
Structurae cooperates with
