Azad, Saeıd Kazemzadeh

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Azad, Saeıd Kazemzadeh

Name Variants

Azad, S. Kazemzadeh
Saeid Kazemzadeh, Azad
S.K.Azad
Azad, Saeid Kazemzadeh
S., Azad
Azad, Saeıd Kazemzadeh
A., Saeid Kazemzadeh
S.,Azad
Azad,S.K.
A.,Saeid Kazemzadeh
Saeıd Kazemzadeh, Azad
A.,Saeıd Kazemzadeh

Job Title

Doçent Doktor

Email Address

saeid.azad@atilim.edu.tr

Main Affiliation

Department of Civil Engineering

Status

Former Staff

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Scholarly Output

21

Articles

19

Citation Count

390

Supervised Theses

2 Scholarly Output Search Results

Now showing 1 - 10 of 21

Citation - WoS: 1
Citation - Scopus: 1
Metaheuristic Optimization of Rotating Multilayer Composite Tubes Under Internal Heating and Pressure
(Springer, 2022) Azad, Saeid Kazemzadeh; Akis, Tolga; Civil Engineering; Department of Civil Engineering
Although analysis/design of multilayer assemblies has been always an active field of research, works on the optimal design of rotating multilayer composite tubes are very limited. This paper addresses the design optimization of rotating multilayer composite tubes under internal heating and pressure. For determining the structural responses, analytical solutions are provided based on different boundary conditions. The automated selection of optimal material as well as thickness optimization of pressurized multilayer assemblies is carried out under different angular speed and internal heating conditions using a metaheuristic algorithm. The corresponding optimum design for each angular speed as well as internal heating condition is sought, and the numerical results are discussed. The study provides general guidelines for conceptual design of rotating multilayer composite tubes subjected to internal heating and pressure.
Citation - WoS: 27
Citation - Scopus: 29
Monitored Convergence Curve: a New Framework for Metaheuristic Structural Optimization Algorithms
(Springer, 2019) Azad, Saeid Kazemzadeh; Department of Civil Engineering
Metaheuristic optimization algorithms, by nature, depend on random processes, and therefore, performing numerous algorithm runs is inevitable to locate a reasonably good solution. Although executing the algorithms for small-size or trivial structural optimization problems could be computationally affordable, when dealing with challenging optimization problems, there is almost no chance of performing numerous independent runs of metaheuristics in a timely manner. This difficulty is basically due to the limitations in computational technologies as well as the excessive computational cost of such problems. In such cases that the number of independent runs is limited to a small number, each optimization run becomes highly valuable and, therefore, the stability of results becomes much more significant. In the present study, it is attempted to monitor the convergence curve of each succeeding run of the algorithm with respect to the information obtained in the previous runs. An easy-to-implement yet efficient framework is proposed for metaheuristic structural optimization algorithms where every succeeding run is monitored at certain intervals named as solution monitoring period. The solution monitoring period is selected such that, at each run, on the one hand, the algorithm could explore the search space to improve the solution quality, and on the other hand, the algorithm is occasionally forced to return to the previously visited more promising solutions if it is not able to improve the solution after a certain number of iterations. The numerical experiments using challenging test instances with up to 354 design variables indicate that, in general, the proposed approach helps to improve the solution quality as well as the robustness or stability of results in metaheuristic structural optimization.
Citation - WoS: 23
Citation - Scopus: 27
Optimum Design of Steel Braced Frames Considering Dynamic Soil-Structure Interaction
(Springer, 2019) Bybordiani, Milad; Azad, Saeid Kazemzadeh; Department of Civil Engineering
Recent studies on design optimization of steel frames considering soil-structure interaction have focused on static loading scenarios, and limited work has been conducted to address the design optimization under dynamic soil-structure interaction. In the present work, first, a platform is developed to perform optimization of steel frames under seismic loading considering dynamic soil-structure interaction (SSI) in order to quantify the effects of earthquake records on the optimum design. Next, verification of the adopted modeling technique is conducted using comparison of the results with the reference solution counterparts in frequency domain. For time history analyses, records from past events are selected and scaled to a target spectrum using simple scaling approach as well as spectrum matching technique. For sizing of the steel frames, a recently developed metaheuristic optimization algorithm, namely exponential big bang-big crunch optimization method, is employed. To alleviate the computational burden of the optimization process, the metaheuristic algorithm is integrated with the so-called upper bound strategy. Effects of factors such as the building height, presence of soil domain, and the utilized ground motion scaling technique are investigated and discussed. The numerical results obtained based on 5- and 10-story steel braced frame dual systems reveal that, although dynamic SSI reduced the seismic demands to some extent, given the final design pertains to different load combinations, the optimum weight difference is not considerable.
Citation - WoS: 11
Citation - Scopus: 10
Multi-Stage Guided Stochastic Search for Optimization and Standardization of Free-Form Steel Double-Layer Grids
(Elsevier Science inc, 2021) Azad, Saeid Kazemzadeh; Aminbakhsh, Saman; Shaban, Samer S. S.; Civil Engineering; Department of Civil Engineering
There has been a growing interest in the use of free-form structures with irregularly curved yet aesthetically pleasing configurations in the recent decades. Although design optimization of regular steel grids has been well addressed in the literature of structural optimization, still limited work has been devoted to optimum design of real-size free-form grid structures. On the one hand, a main obstacle when dealing with real-size free-form steel grids is the excessive computational effort associated with contemporary evolutionary optimization algorithms. On the other hand, it is generally perceived that the obtained final designs using conventional optimization algorithms may not necessarily be favored in practice if certain provisions are not stipulated by the algorithm to preclude an abundance of distinct steel section sizes in the final design. Hence, instead of offering a single optimum or near optimum design, it would be more desirable to provide the designer or decision maker with a Pareto front set of non-dominated design alternatives taking into account both the minimum weight as well as the assortment of available steel section sizes in the final design. Accordingly, in this paper, a computationally efficient multi-stage guided stochastic search algorithm is proposed for optimization and standardization of realsize free-form steel double-layer grids. A gradual design-oriented section elimination approach is followed where in the first optimization stage, a complete set of commercially available steel sections is introduced to the algorithm and in the succeeding stages, the size of section list is reduced by eliminating the redundant sizes. Two variants of the algorithm are employed to demonstrate the usefulness of the proposed technique in challenging test examples of free-form steel double-layer grids, and the obtained Pareto fronts are plotted to illustrate the trade-off between minimum weight and assortment of steel section sizes in the final design.
Citation - WoS: 31
Citation - Scopus: 35
Discrete Sizing Optimization of Steel Trusses Under Multiple Displacement Constraints and Load Cases Using Guided Stochastic Search Technique
(Springer, 2015) Azad, S. Kazemzadeh; Hasancebi, O.; Department of Civil Engineering
The guided stochastic search (GSS) is a computationally efficient design optimization technique, which is originally developed for discrete sizing optimization problems of steel trusses with a single displacement constraint under a single load case. The present study aims to investigate the GSS in a more general class of truss sizing optimization problems subject to multiple displacement constraints and load cases. To this end, enhancements of the GSS are proposed in the form of two alternative approaches that enable the technique to deal with multiple displacement/load cases. The first approach implements a methodology in which the most critical displacement direction is considered only when guiding the search process. The second approach, however, takes into account the cumulative effect of all the critical displacement directions in the course of optimization. Advantage of the integrated force method of structural analysis is also utilized for further reduction of the computational effort in these approaches. The proposed enhancements of GSS are investigated and compared with some selected techniques of design optimization through six truss structures that are sized for minimum weight. The numerical results reveal that both enhancements generally provide promising solutions with an insignificant computational effort.
Citation - WoS: 2
Citation - Scopus: 2
Structural Design Optimization of Multi-Layer Spherical Pressure Vessels: a Metaheuristic Approach
(Springer, 2019) Akis, Tolga; Azad, Saeid Kazemzadeh; Civil Engineering; Department of Civil Engineering
This study addresses the optimum design problem of multi-layer spherical pressure vessels based on von Mises yield criterion. In order to compute the structural responses under internal pressure, analytical solutions for one-, two-, and three-layer spherical pressure vessels are provided. A population-based metaheuristic algorithm is reformulated for optimum material selection as well as thickness optimization of multi-layer spherical pressure vessels. Furthermore, in order to enhance the computational efficiency of the optimization algorithm, upper bound strategy is also integrated with the algorithm for reducing the total number of structural response evaluations during the optimization iterations. The performance of the algorithm is investigated through weight and cost minimization of one-, two- and three-layer spherical pressure vessels and the results are presented in detail. The obtained numerical results, based on different internal pressures as well as vessel sizes, indicate the usefulness and efficiency of the employed methodology in optimum design of multi-layer spherical pressure vessels.
Citation - WoS: 7
Citation - Scopus: 9
E-Constraint Guided Stochastic Search With Successive Seeding for Multi-Objective Optimization of Large-Scale Steel Double-Layer Grids
(Elsevier, 2022) Azad, Saeid Kazemzadeh; Aminbakhsh, Saman; Civil Engineering; Department of Civil Engineering
This paper proposes a design-driven structural optimization algorithm named e-constraint guided stochastic search (e-GSS) for multi-objective design optimization of large-scale steel double-layer grids having numerous discrete design variables. Based on the well-known e-constraint method, first, the multi-objective optimization problem is transformed into a set of single-objective optimization problems. Next, each single-objective optimization problem is tackled using an enhanced reformulation of the standard guided stochastic search algorithm proposed based on a stochastic maximum incremental/decremental step size approach. Moreover, a successive seeding strategy is employed in conjunction with the proposed e-GSS algorithm to improve its performance in multi-objective optimization of large-scale steel double-layer grids. The numerical results obtained through multi-objective optimization of three challenging test examples, namely a 1728-member double-layer compound barrel vault, a 2304-member double-layer scallop dome, and a 2400-member double-layer multi-radial dome, demonstrate the usefulness of the proposed e-GSS algorithm in generating Pareto fronts of the foregoing multi-objective structural optimization problems with up to 2400 distinct sizing variables.
Citation - WoS: 41
Citation - Scopus: 47
Computationally Efficient Discrete Sizing of Steel Frames Via Guided Stochastic Search Heuristic
(Pergamon-elsevier Science Ltd, 2015) Azad, S. Kazemzadeh; Hasancebi, O.; Department of Civil Engineering
Recently a design-driven heuristic approach named guided stochastic search (GSS) technique has been developed by the authors as a computationally efficient method for discrete sizing optimization of steel trusses. In this study, an extension and reformulation of the GSS technique are proposed for its application to problems from discrete sizing optimization of steel frames. In the GSS, the well-known principle of virtual work as well as the information attained in the structural analysis and design stages are used together to guide the optimization process. A design wise strategy is employed in the technique where resizing of members is performed with respect to their role in satisfying strength and displacement constraints. The performance of the GSS is investigated through optimum design of four steel frame structures according to AISC-LRFD specifications. The numerical results obtained demonstrate that the GSS can be employed as a computationally efficient design optimization tool for practical sizing optimization of steel frames. (C) 2015 Elsevier Ltd. All rights reserved.
Citation - WoS: 44
Citation - Scopus: 41
Enhanced Hybrid Metaheuristic Algorithms for Optimal Sizing of Steel Truss Structures With Numerous Discrete Variables
(Springer, 2017) Azad, Saeid Kazemzadeh; Department of Civil Engineering
The advent of modern computing technologies paved the way for development of numerous efficient structural design optimization tools in the recent decades. In the present study sizing optimization problem of steel truss structures having numerous discrete variables is tackled using combined forms of recently proposed metaheuristic techniques. Three guided, and three guided hybrid metaheuristic algorithms are developed by integrating a design oriented strategy to the stochastic search properties of three recently proposed metaheuristic optimization techniques, namely adaptive dimensional search, modified big bang-big crunch, and exponential big bang-big crunch algorithms. The performances of the proposed guided, and guided hybrid metaheuristic algorithms are compared to those of standard variants through optimum design of real-size steel truss structures with up to 728 design variables according to AISC-LRFD specification. The numerical results reveal that the hybrid form of adaptive dimensional search and exponential big bang-big crunch algorithm is the most promising algorithm amongst the other investigated techniques.
Serbest Biçimli Çelık Çift Katmanlı Uzay Kafeslerin Optimizasyonu ve Standardizasyonu
(2021) Shaban, Samer S S; Azad, Saeıd Kazemzadeh; Department of Civil Engineering
Son yıllarda düzensiz eğrili ancak estetik açıdan hoş görünen konfigürasyonlara sahip serbest biçimli yapıların kullanımına artan bir ilgi olmuştur. Normal çelik uzay kafeslerin tasarım optimizasyonu, yapısal optimizasyon literatüründe detaylı bir şekilde ele alınsa da, gerçek boyutlu serbest biçimli uzay kafes yapıların optimum tasarımında yapılan çalışmalar hala sınırlı düzeyde kalmıştır. Bir yandan, gerçek boyutlu serbest biçimli çelik kafeslerin optimizasyonunun önündeki ana engel, güncel evrimsel optimizasyon algoritmalarıyla ortaya çıkan aşırı hesaplama yüküdür. Öte yandan, algoritma tarafından nihai tasarımda farklı çelik kesit boyutlarının sayıca fazlalığını önlemek için gerekli kısıtlamalar uygulanmamışsa, geleneksel optimizasyon algoritmaları kullanılarak elde edilen nihai tasarımların uygulamada tercih edilmemesi muhtemeldir. Bu nedenle, tek bir optimum veya optimuma yakın tasarım sunmak yerine, tasarımcıya veya karar vericiye, hem minimum ağırlığı hem de mevcut ürün çeşitliliğini hesaba katan ve etkin tasarım alternatifleri setinden oluşan bir Pareto eğrisi sunmak daha arzu edilir olacaktır. Buna göre, bu çalışmada, gerçek boyutlu serbest biçimli çelik çift katmanlı uzay kafeslerin optimizasyonu ve standardizasyonu için hesaplama açısından verimli çok aşamalı rehberli stokastik arama algoritması önerilmiştir. İlk optimizasyon aşamasında, algoritmaya ticari olarak mevcut çelik profillerin eksiksiz bir setinin sunulduğu ve sonraki aşamalarda, kullanılmayan veya daha az kullanılan kesitleri eleyerek kesit listesinin kademeli olarak küçültüldüğü, bir tasarım odaklı kesit eleme yaklaşımı izlenmiştir. Serbest biçimli çelik çift katmanlı uzay kafeslerin sıra dışı kolay olmayan test örnekleri üzerinde önerilen tekniğin kullanışlılığını göstermek için algoritmanın iki farklı versiyonu kullanılmış ve elde edilen Pareto eğrisi, minimum ağırlık ve çelik kesit çeşitleri arasındaki dengeyi göstermek için çizilmiştir.

Azad, Saeıd Kazemzadeh

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Scholarly Output

21

Articles

19

Citation Count

390

Supervised Theses

2

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