Vibration characteristics of tall buildings braced by shear walls and thin-walled open-section structures

2008 ◽  
Vol 17 (1) ◽  
pp. 203-216 ◽  
Author(s):  
Sid Ahmed Meftah ◽  
Abdelouahed Tounsi
2014 ◽  
Vol 84 ◽  
pp. 335-343 ◽  
Author(s):  
Alberto Carpinteri ◽  
Giuseppe Lacidogna ◽  
Bartolomeo Montrucchio ◽  
Sandro Cammarano

2021 ◽  
Vol 8 (1) ◽  
pp. 307-318
Author(s):  
Giuseppe Nitti ◽  
Giuseppe Lacidogna ◽  
Alberto Carpinteri

Abstract In this paper, an original analytical formulation to evaluate the natural frequencies and mode shapes of high-rise buildings is proposed. The methodology is intended to be used by engineers in the preliminary design phases as it allows the evaluation of the dynamic response of high-rise buildings consisting of thin-walled closed- or open-section shear walls, frames, framed tubes, and dia-grid systems. If thin-walled open-section shear walls are present, the stiffness matrix of the element is evaluated considering Vlasov’s theory. Using the procedure called General Algorithm, which allows to assemble the stiffness matrices of the individual vertical bracing elements, it is possible to model the structure as a single equivalent cantilever beam. Furthermore, the degrees of freedom of the structural system are reduced to only three per floor: two translations in the x and y directions and a rigid rotation of the floor around the vertical axis of the building. This results in a drastic reduction in calculation times compared to those necessary to carry out the same analysis using commercial software that implements Finite Element models. The potential of the proposed method is confirmed by a numerical example, which demonstrates the benefits of this procedure.


2020 ◽  
Vol 44 ◽  
pp. 402-409 ◽  
Author(s):  
Giuseppe Lacidogna ◽  
Giuseppe Nitti ◽  
Domenico Scaramozzino ◽  
Alberto Carpinteri

Author(s):  
Sayed Behzad Talaeitaba ◽  
Farshid Khamseh ◽  
Mohammad Ebrahim Torki

1972 ◽  
Vol 39 (3) ◽  
pp. 779-785 ◽  
Author(s):  
A. I. Soler

Equations of motion are derived for coupled extension, flexure, and torsion of pretwisted curved bars of thin-walled, open section. The derivation is based on energy principles and includes inertia terms. The major effect of initial pretwist is to allow coupling of all possible beam deformation modes; however, if the bar is straight and has two axes of symmetry, pretwist causes coupling only between the two bending modes, and between extension and torsion. The governing equations are presented in first-order form, and a numerical technique is suggested for the case of space varying pretwist. It is suggested that these equations may form the basis for a simplified study of the effect of superelevation on the static and dynamic response of curved highway bridges. Finally, a simple straight beam with uniform pretwist is studied to compare effects of pretwist and restrained torsion in a thin-walled beam of open section.


Author(s):  
Dongqi Jiang ◽  
Shanquan Liu ◽  
Tao Chen ◽  
Gang Bi

<p>Reinforced concrete – steel plate composite shear walls (RCSPSW) have attracted great interests in the construction of tall buildings. From the perspective of life-cycle maintenance, the failure mode recognition is critical in determining the post-earthquake recovery strategies. This paper presents a comprehensive study on a wide range of existing experimental tests and develops a unique library of 17 parameters that affects RCSPSW’s failure modes. A total of 127 specimens are compiled and three types of failure modes are considered: flexure, shear and flexure-shear failure modes. Various machine learning (ML) techniques such as decision trees, random forests (RF), <i>K</i>-nearest neighbours and artificial neural network (ANN) are adopted to identify the failure mode of RCSPSW. RF and ANN algorithm show superior performance as compared to other ML approaches. In Particular, ANN model with one hidden layer and 10 neurons is sufficient for failure mode recognition of RCSPSW.</p>


2019 ◽  
Vol 134 ◽  
pp. 442-459 ◽  
Author(s):  
Jingfeng Wang ◽  
Wanqian Wang ◽  
Yaming Xiao ◽  
Bo Yu

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