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Showing 4 results for Fadaee

M. Mashayekhi, M.j. Fadaee, J. Salajegheh , E. Salajegheh,
Volume 1, Issue 2 (6-2011)
Abstract

A two-stage optimization method is presented by employing the evolutionary structural optimization (ESO) and ant colony optimization (ACO), which is called ESO-ACO method. To implement ESO-ACO, size optimization is performed using ESO, first. Then, the outcomes of ESO are employed to enhance ACO. In optimization process, the weight of double layer grid is minimized under various constraints which artificial ground motion is used to calculate the structural responses. The presence or absence of elements in bottom and web grids and also cross-sectional areas are selected as design variables. The numerical results reveal the computational advantages and effectiveness of the proposed method.
M. Mashayekhi, J. Salajegheh, M.j. Fadaee , E. Salajegheh,
Volume 1, Issue 4 (12-2011)
Abstract

For reliability-based topology optimization (RBTO) of double layer grids, a two-stage optimization method is presented by applying “Solid Isotropic Material with Penalization” and “Ant Colony Optimization” (SIMP-ACO method). To achieve this aim, first, the structural stiffness is maximized using SIMP. Then, the characteristics of the obtained topology are used to enhance ACO through six modifications. As numerical examples, reliability-based topology designs of typical double layer grids are obtained by ACO and SIMP-ACO methods. Their numerical results reveal the effectiveness of the proposed SIMPACO method for the RBTO of double layer grids.
S. Gharehbaghi, M. J. Fadaee,
Volume 2, Issue 4 (10-2012)
Abstract

This paper deals with the optimization of reinforced concrete (RC) structures under earthquake loads by introducing a simple methodology. One of the most important problems in the design of RC structures is the existing of various design scenarios that all of them satisfy design constraints. Despite of the steel structures, a large number of design candidates due to a large number of design variables can be utilized. Doubtless, the economical and practical aspects are two effective parameters on accepting a design candidate. As such, in this paper the conventional design process that uses a trial and error process is replaced with an automated process using optimization technique. Also, the cost of construction is selected as an objective function in the automated process. A real valued model of particle swarm optimization (PSO) algorithm is utilized to perform the optimization process. Design constraints conform to the ACI318-08 code and standard 2800-code recommendations. Three ground motion records modified based on Iranian Design Spectrum is considered as earthquake excitations. Moreover, to reveal the effectiveness and robustness of the presented methodology, for example, a three-bay eighteen-story RC frame is optimized against the combination of gravity and earthquake loads. The entire process is summarized in a computer programming using a link between MATLAB platform and OpenSEES as open source object-oriented software.
H. Dehghani , M. J. Fadaee,
Volume 5, Issue 2 (3-2015)
Abstract

The use of fiber reinforced polymer (FRP) U-wrap to rehabilitate concrete beams has increased in popularity over the past few years. As such, many design codes and guidelines have been developed to enable designers to use of FRP for retrofitting reinforced concrete beams. FIB is the only guideline for design which presents a formula for torsional capacity of concrete beams strengthened with FRP. The Rackwitz-Fiessler method was applied to make a reliability assessment on the torsional capacity design of concrete beams retrofitted with U-wrap FRP laminate by this guideline. In this paper, the average of reliability index obtained is 2.92, reflecting reliability of the design procedures. This value is somehow low in comparison to target reliability level of 3.5 used in the guideline calibration and so, optimum resistance factor may be needed in future guideline revisions. From the study on the relation between average reliability index and optimum resistance factor, a value of 0.723 for the optimum resistance factor is suggested.

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