Machine learning-based surrogate models for predicting the optimized weight and prestress level of double-curvature cable domes-Reference-Cited by-同舟云学术

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Machine learning-based surrogate models for predicting the optimized weight and prestress level of double-curvature cable domes

Published:2024-10 Issue: Volume:203 Page:112215
ISSN:0263-8231
Container-title:Thin-Walled Structures
language:en
Short-container-title:Thin-Walled Structures

Author:

Ahmed Elshaimaa A.^ORCID,El Damatty Ashraf A.

Publisher

Elsevier BV

Reference47 articles.

1. The role of prestress and its optimization in cable domes design;Quagliaroli;Comput. Struct.,2015

2. The Georgia Dome and beyond: achieving lightweight-longspan structures;Levy,1994

3. The design and construction of two cable domes for the Korean Olympics;Geiger,1986

4. Negative Gaussian curvature cable dome and its feasible prestress design;Guo;J. Aerosp. Eng.,2016

5. NURBS-based form-finding algorithm for double-curvature cable domes;Ahmed;J. Eng. Struct.,2023

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