Structural Properties of Tall Diagrid Buildings Using a Neural Dynamic Model for Design Optimization

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 (H/B) from 1 to 4, diagrid angles (θ) between 45° and 90°, and diagrid densities (ρd) 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.