The present study dictates the behavior of shear wall under a seismic event in slender high rise buildings, and studies the effect of height, location and distribution of shear wall in slender high rise building with and without boundary elements induced by the effect of an earthquake. Shear walls are located at the sides of the building, to counter the earthquake forces. This study is carried out in a 12 storeys building using
SAP2000 software. The obtained results disclose that the behavior of the structure is definitely affected by the height and location of shear walls in slender high rise building. The stresses are concentrated at the limit between the shear wall region and the upper non shear wall especially for shear walls without columns. Displacements are doubled between the shear wall region and the upper non shear wall especially for shear
walls without columns.
shear walls; stress concentrations; SAP2000; general building capacity; stiffness; shear wall distribution/position; time history analysis; high rise building
Civil and Architectural Constructions, Sohag University, Faculty of Industrial Education, Egypt
We have performed a design optimization of a stiffened panel with curvilinear stiffeners using an artificial neural network (ANN) residual kriging based surrogate modeling approach. The ANN residual kriging based surrogate modeling involves two steps. In the first step, we approximate the objective function
using ANN. In the next step we use kriging to model the residue. We optimize the panel in an iterative way. Each iteration involves two steps-shape optimization and size optimization. For both shape and size optimization, we use ANN residual kriging based surrogate model. At each optimization step, we do an initial sampling and fit an ANN residual kriging model for the objective function. Then we keep updating
this surrogate model using an adaptive sampling algorithm until the minimum value of the objective function converges. The comparison of the design obtained using our optimization scheme with that obtained using a traditional genetic algorithm (GA) based optimization scheme shows satisfactory agreement. However, with this surrogate model based approach we reach optimum design with less computation effort as compared to the GA based approach which does not use any surrogate model.
surrogate model; optimization; artificial neural network; kriging; stiffened panel
Rakesh K. Kapania: Department of Aerospace and Ocean Engineering, Virginia Polytechnic Institute and State University, Blacksburg, USA
Mohammed R. Sunny: Department of Aerospace Engineering, Indian Institute of Technology, Kharagpur 721302, India
Sameer B. Mulani: Department of Aerospace Engineering and Mechanics, The University of Alabama, Tuscaloosa,AL 35487, USA
Subrata Sanyal: Measurement Science and Engineering Department, Naval Surface Warfare Center (NSWC), Corona Division, P.O. Box 5000, Corona, CA 92878, USA
Based on the variation of strain along the cross section, any region in a structural member can be classified into two regions namely, Bernoulli´s region (B-region) and Disturbed region (D-region). Since the variation of strain along the cross section for a B-region is linear, well-developed theories are available for their analysis and design. On the other hand, the design of D-region is carried out based on thumb rules and past experience due to the presence of nonlinear strain distribution. Strut-and-Tie method is a novel
approach that can be used for the analysis and design of both B-region as well as D-region with equal importance. The strut efficiency factor (βs) is needed for the design and analysis of concrete members using Strut and Tie method. In this paper, equations for finding βs for bottle shaped struts in concrete deep beams (a D-region) with and without steel fibres are developed. The effects of transverse reinforcement on βs are also considered. Numerical studies using commercially available finite element software along with limited amount of experimental studies were used to find βs.
strut; efficiency factor; strut-and-tie; STM; fibre reinforced concrete; SFRC; ANSYS; nonlinear analysis of concrete; nonlinear finite element analysis of reinforced concrete
Sandeep M.S., Praveen Nagarajan, A.P. Shashikala and Shehin A. Habeeb: Department of Civil Engineering, NIT Calicut
The present paper describes the results of numerical modeling of a dam founded on loose liquefiable deposit using PLAXIS-3D finite element software. Effect of a different dam water level on parameters like displacements, Excess Pore water pressures, Liquefaction potential and Accelerations is studied. El- Centro earthquake motion is applied as input earthquake motion. The results of this study show that different upstream dam water level greatly affects the displacements, excess pore pressure and displacement tendency of the underlying foundation soils and the dam.
seismic analysis; earthen dam; excess pore pressure; acceleration; displacements
Shashank Bhatnagar, A Kranthikumar and V A Sawant: Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India
This article presents an adaptive directional differential evolution (ADDE) algorithm and its application in solving discrete sizing truss optimization problems. The algorithm is featured by a new selfadaptation approach and a simple directional strategy. In the adaptation approach, the mutation operator is adjusted in accordance with the change of population diversity, which can well balance between global
exploration and local exploitation as well as locate the promising solutions. The directional strategy is based on the order relation between two difference solutions chosen for mutation and can bias the search direction for increasing the possibility of finding improved solutions. In addition, a new scaling factor is introduced as a vector of uniform random variables to maintain the diversity without crossover operation. Numerical results show that the optimal solutions of ADDE are as good as or better than those from some modern
metaheuristics in the literature, while ADDE often uses fewer structural analyses.
adaptive directional differential evolution; population diversity; truss sizing optimization; discrete variables
Department of Structural Mechanics, National University of Civil Engineering, 55 Giai Phong Road, Hanoi, Vietnam