Design of ultra-thin composite deployable shell structures through machine learning
| Autor(en): |
Miguel Bessa
Sergio Pellegrino |
|---|---|
| Medium: | Tagungsbeitrag |
| Sprache(n): | Englisch |
| Tagung: | Interfaces: Architecture, Engineering, Science, Annual Meeting of the International Association of Shell & Spatial Structures (IASS), Hamburg, 25-27 September 2017 |
| Veröffentlicht in: | Interfaces: Architecture . Engineering . Science |
| Jahr: | 2017 |
| Abstrakt: | 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. |
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