A platform for research: civil engineering, architecture and urbanism
Linked mathematical–informational modeling of perforated steel plate shear walls
Abstract Steel plate shear walls have come to be considered as an appropriate system for resisting lateral loads due to earthquakes and wind, especially in tall structures, for their flexible, energy dissipation and suitable post-buckling behaviors. This paper presents prediction ways for the mechanical behavior of shear walls. In this study, two different methods are suggested to consider the intricate hysteretic behavior of perforated shear walls. To use the benefits of both mathematical and informational presentations, a novel method, a linked modeling skeleton, is created and demonstrated through representing the complex behavior of perforated shear walls.
Highlights Represent an approach to the prediction of force-displacement curves by mathematical modeling. The learning capabilities of neural networks are used to model the pinched behavior of perforated shear walls. A neural network structure is developed to model the path dependency of the shear wall behavior. By employing behavioral models to estimate the F–D behavior, analytical expressions for evaluating major shear wall parameters, such as initial stiffness and ultimate force, are derived.
Linked mathematical–informational modeling of perforated steel plate shear walls
Abstract Steel plate shear walls have come to be considered as an appropriate system for resisting lateral loads due to earthquakes and wind, especially in tall structures, for their flexible, energy dissipation and suitable post-buckling behaviors. This paper presents prediction ways for the mechanical behavior of shear walls. In this study, two different methods are suggested to consider the intricate hysteretic behavior of perforated shear walls. To use the benefits of both mathematical and informational presentations, a novel method, a linked modeling skeleton, is created and demonstrated through representing the complex behavior of perforated shear walls.
Highlights Represent an approach to the prediction of force-displacement curves by mathematical modeling. The learning capabilities of neural networks are used to model the pinched behavior of perforated shear walls. A neural network structure is developed to model the path dependency of the shear wall behavior. By employing behavioral models to estimate the F–D behavior, analytical expressions for evaluating major shear wall parameters, such as initial stiffness and ultimate force, are derived.
Linked mathematical–informational modeling of perforated steel plate shear walls
Abdollahzadeh, G.R. (author) / Ghobadi, F. (author)
Thin-Walled Structures ; 94 ; 512-520
2015-05-04
9 pages
Article (Journal)
Electronic Resource
English
Linked mathematical–informational modeling of perforated steel plate shear walls
Online Contents | 2015
|Nonlinear seismic analysis of perforated steel plate shear walls
Online Contents | 2014
|Nonlinear seismic analysis of perforated steel plate shear walls
Elsevier | 2013
|Internal Perforated-Steel-Plate Connections for CLT Shear Walls
TIBKAT | 2021
|Perforated Steel Plate Shear Walls for Tunable Seismic Resistance
British Library Conference Proceedings | 2013
|