Structural Properties of Tall Diagrid Buildings Using a Neural Dynamic Model for Design Optimization
Publication: Journal of Structural Engineering
Volume 148, Issue 3
Abstract
The development of structural systems is a constantly evolving process to guarantee safety and serviceability against natural hazards. As a result, diagrid structural systems became a current trend in tubular mid- and high-rise building structures for their significant lateral stiffness and aesthetic potential. Their unique geometric configuration allows the efficient distribution of internal forces that lead to optimal structural designs. However, existing design codes and provisions do not provide specific guidelines for their design under earthquake and wind loading. For this reason, this paper studies the properties of steel diagrid structures, including optimal diagrid angle, diagrid density, and fundamental period, as a function of geometric parameters. This study uses a large set of structural models with aspect ratios () from 1 to 4, diagrid angles () between 45° and 90°, and diagrid densities () between 3 and 12. The structural design of each model is obtained using a soft-computing optimization algorithm, denominated hybrid counter propagation neural dynamic (CPND) model, that determines member sizes from a database of commercially available W-shapes following ASCE 7-16 standard and AISC-15 steel construction manual. This investigation confirms that the optimal diagrid angle increases with height, highlights the importance of diagrid density in structural design, and demonstrates the effect of the diagrid angle on the fundamental period. A new set of equations are proposed for: (1) the optimal diagrid angle as a function of height, and (2) the fundamental period of diagrid structures as a function of angle and height. The proposed equations allow the estimation of structural properties for the design of steel diagrid structures.
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Data Availability Statement
The data, models, and codes used during the study are available in the DesignSafe-CI online repository located in Palacio-Betancur and Gutierrez Soto (2021) at https://doi.org/10.17603/ds2-gtby-j328. The code generated to investigate the patented neural dynamic model (US patent 5,815,394 issued on September 29, 1998) is proprietary.
Acknowledgments
The authors acknowledge Professor Hojjat Adeli and Professor Hyo Seon Park for the permission to implement the patented neural dynamic model (US patent 5,815,394 issued date on September 29, 1998) in this research.
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History
Received: May 17, 2021
Accepted: Oct 18, 2021
Published online: Dec 21, 2021
Published in print: Mar 1, 2022
Discussion open until: May 21, 2022
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Cited by
- Chengqing Liu, Dibing Xu, Diagrid Core-tube Structure Seismic Performance Based on Equivalent Stiffness Ratio of Inner and Outer Tubes, KSCE Journal of Civil Engineering, 10.1007/s12205-023-0677-9, (2023).