Mehmet Polat Saka - Academia.edu (original) (raw)

Papers by Mehmet Polat Saka

Proceedings of the Twelfth International Conference on Civil, Structural and Environmental Engineering Computing

Journal of the Structural Division, 1981

Computational Technology Reviews, 2014

Advances in Engineering Software, 2016

Optimum design of real world steel space frames under design code provisions is a complicated opt... more Optimum design of real world steel space frames under design code provisions is a complicated optimization problem due to the presence of large numbers of highly nonlinear constraints and discrete design variables. The use of gradient based optimization techniques in finding the optimum solution of such large design problems is cumbersome due to the selection of initial design points and convergence difficulties while metaheuristic algorithms do not suffer such problems. Artificial bee colony (ABC) algorithm is one of the recent additions to the swarm intelligence based meta-heuristic search techniques that mimic natural foraging behavior of honey bees. In this study optimum design problem of steel space frames is formulated according to the provisions of LRFD-AISC and its solution is obtained by using enhanced artificial bee colony algorithm. The performance of artificial bee colony algorithm is improved by adding Levy flight distribution in the search of scout bees. Real world steel space frames are designed with the new algorithm developed in this study to demonstrate its robustness and efficiency. © 2015 Elsevier Ltd. All rights reserved.

Structural Engineering and Mechanics, 1999

A structural optimization process is presented for arches with varying cross-section. The optimal... more A structural optimization process is presented for arches with varying cross-section. The optimality criteria method is used to develop a recursive relationship for the design variables considering displacement, stresses and minimum depth constraints. The depth at the crown and at the support are taken as design variables first. Then the approach is extended by taking the depth values of each joint as design variable. The curved beam element of constant cross section is used to model the parabolic and circular arches with varying cross section. A number of design examples are presented to demonstrate the application of the method.

The Cuckoo search algorithm is a recent addition to metaheuristic techniques. It simulates the br... more The Cuckoo search algorithm is a recent addition to metaheuristic techniques. It simulates the breeding behaviour of certain cuckoo species into a numerical optimization technique. Cuckoo birds lay their eggs in the nests of other host birds so that their chicks when hatched can be nurtured by the host birds. The optimum design algorithm presented for moment resisting steel frames is based on the cuckoo search algorithm. The design algorithm selects the appropriate W sections for the beams and column of a steel frame out of 272 W sections listed in the LRFD-AISC (Load and Resistance Factor Design, American Institute of Steel Construction) [52] such that the code requirements are satisfied and the weight of steel frame is the minimum. Code specifications necessitate the consideration of a combined strength constraint with lateral torsional buckling for beam-column members. Furthermore displacement constraints as well as inter-storey drift restrictions of multi-storey frames are also included in the design formulation. Further constraints related with the constructability of a steel frame are also considered. The number of steel frames are designed by the algorithm presented to demonstrate its efficiency. The same steel frames are also designed by using the big bang-big crunch algorithm as well as the particle swarm optimizer for comparison.

Swarm Intelligence and Bio-Inspired Computation, 2013

Swarm intelligence refers to collective intelligence. Biologists and natural scientist have been ... more Swarm intelligence refers to collective intelligence. Biologists and natural scientist have been studying the behavior of social insects due to their efficiency of solving complex problems such as finding the shortest path between their nest and food source or organizing their nests. In spite of the fact that these insects are unsophisticated individually, they make wonders as a swarm by interaction with each other and their environment. In last two decades, the behaviors of various swarms that are used in finding preys or mating are simulated into a numerical optimization technique. In this chapter, eight different swarm intelligence–based algorithms are summarized and their working steps are listed. These techniques are ant colony optimizer, particle swarm optimizer, artificial bee colony algorithm, glowworm algorithm, firefly algorithm, cuckoo search algorithm, bat algorithm, and hunting search algorithm. Two optimization problems taken from the literature are solved by all these eight algorithms and their performance are compared. It is noticed that most of the swarm intelligence–based algorithms are simple and robust techniques that determine the optimum solution of optimization problems efficiently without requiring much of a mathematical struggling.

ijeas.akdeniz.edu.tr

Abstract: Member grouping of a steel grillage system has an important effect in the minimum weigh... more Abstract: Member grouping of a steel grillage system has an important effect in the minimum weight design of these systems. In the present study, this effect is investigated using an optimum design algorithm which is based on a recently developed particle swarm ...

Journal of Structural Engineering, 2002

Journal of Structural Engineering, 1993

Timber‐concrete floors are widely used in the Persian Gulf region because of their resistance to ... more Timber‐concrete floors are widely used in the Persian Gulf region because of their resistance to the hot and aggressive environment of the area. Because no shear connector is provided, the timber joists and concrete slab work independently. In this study, it is suggested that ...

Computers & Structures, 1988

Abstrnct-The structural optimization algorithms developed in recent years mainly consider the ela... more Abstrnct-The structural optimization algorithms developed in recent years mainly consider the elastic behaviour of structures. The reserve of resisting loads in nonlinear regions is totally ignored. The optimum design algorithm presented in this study takes into account the response of the structure beyond the elastic limit. This is achieved by coupling a nonlinear analysis technique with an optimality criteria approach. The first is used to provide the nonlinear behaviour of the structure as the design variables are changed. The latter is employed to obtain a recursive relationship to be utilized to update these design variables. The design algorithm iricludes the displacement limitations. Consideration of the post buckling and post yielding behaviour of the truss members makes the necessity of stress and buckling constraints irrelevant. Minimum size constraints are imposed on the design variables. A number of design examples are presented to demonstrate the application of the method.

Computers & Structures, 2014

This study presents a design-driven heuristic approach named guided stochastic search (GSS) techn... more This study presents a design-driven heuristic approach named guided stochastic search (GSS) technique for discrete sizing optimization of steel trusses. The method works on the basis of guiding the optimization process using the well-known principle of virtual work as well as the information collected during the structural analysis and design stages. The performance of the proposed technique is investigated through a benchmark truss instance as well as four real-size trusses sized for minimum weight according to AISC-LRFD specifications. A comparison of the numerical results obtained using the GSS with those of other available algorithms indicates that the proposed technique is capable of locating promising solutions using lesser computational effort.

Computer-Aided Design, 1981

ABSTRACT

Advances in Engineering Software, 2012

Particle Swarm method based optimum design algorithm for unbraced steel frames is presented. The ... more Particle Swarm method based optimum design algorithm for unbraced steel frames is presented. The Particle Swarm method is a numerical optimization technique that simulates the social behavior of birds, fishes and bugs. In nature fish school, birds flock and bugs swarm not only for reproduction but for other reasons such as finding food and escaping predators. Similar to birds seek to find food, the optimum design process seeks to find the optimum solution. In the particle swarm optimization each particle in the swarm represents a candidate solution of the optimum design problem. In the optimum design algorithm presented the design constraints are imposed in accordance with LRFD-AISC (Load and Resistance Factor Design, American Institute of Steel Construction). In the design of beam-column members the combined strength constraints are considered that take into account the lateral torsional buckling of the member. The algorithm developed selects optimum W sections for beams and columns of unbraced frame from the list of 272 W-sections list. This selection is carried out such that design constraints imposed by the LRFD are satisfied and the minimum frame weight is obtained. The efficiency of the algorithm is demonstrated considering a number of design examples.

Computers & Structures, 2011

The present study addresses a parallel solution algorithm for optimum design of large steel space... more The present study addresses a parallel solution algorithm for optimum design of large steel space frame structures, in particular high-rise steel buildings. The algorithm implements a novel discrete evolution strategy optimization method to effectively size these systems for minimum weight according to the provisions of ASD-AISC specification and various practical aspects of design process. The multitasking environment in the algorithm rests on a master-slave model based parallelization of the optimization procedure, which provides an ideal platform for attaining optimal solutions in a timely manner without losing accuracy in computations. Three design examples from the category of high-rise steel buildings are studied extensively to demonstrate cost-efficiency of the algorithm in conjunction with a cluster of computers with 32 processors. The variation in performance of the parallel computing system with respect to the number of processors employed is also scrutinized in each design example.

Grup Numarası İlk kolon oryantasyonuyla bulunan en iyi tasarım Değişen kolon oryantasyonuyla bulu... more Grup Numarası İlk kolon oryantasyonuyla bulunan en iyi tasarım Değişen kolon oryantasyonuyla bulunan en iyi tasarım Hazır kesit Alan (in 2) (cm 2) Hazır kesit Alan (in 2) (cm 2)

Advances in Engineering Software, 2019

In this study, optimum design algorithm is presented for tied-arch bridges under AASHTO-LRFD Brid... more In this study, optimum design algorithm is presented for tied-arch bridges under AASHTO-LRFD Bridge Design Specifications provisions. It is decided that in tied-arch bridges ties, arch ribs, and bottom and top bracings are made of built-up box sections, whereas built-up I sections are utilized for floor beams and stringers. Bars are adopted for hangers. In the formulation of the optimization problem, design variables are selected as the cross sectional dimensions of steel plates not that of I and box sections. Design pools are prepared for steel plate sections in addition to the hanger bars so that the optimization algorithm can select appropriate steel plates, construct I and box built-up sections for members of 3-D tied-arch such that the weight of the bridge is minimized. In addition to design code requirements, geometrical constraints among its elements that are required for manufacturability of the bridge are also considered. The design process of tied-arch bridges differs from that of steel framed structures. It necessitates consideration of moving vehicle loads. Design optimization algorithms require the response of bridges under several design load arrangements and in the construction of influence lines. This is achieved by using open application programming interface (OAPI) facility of SAP2000. The solution of discrete nonlinear programming problem is obtained by using the proposed Enhanced Artificial Bee Colony algorithm (eABC). The proposed algorithm is compared with Standard Artificial Bee Colony (ABC) and Exponential Big Bang-Big Crunch (eBB-BC) algorithms to evaluate its performance.

Journal of Constructional Steel Research, 2003

A genetic algorithm based optimum design method is presented for nonlinear multistorey steel fram... more A genetic algorithm based optimum design method is presented for nonlinear multistorey steel frames with semi-rigid connections. The design algorithm obtains optimum frame by selecting appropriate sections from standard steel section tables while satisfying the serviceability and strength limitations specified in BS5950. The algorithm accounts for the effect of the flexibility of the connections and the geometric non-linearity of the

Computers & Structures, 2000

... Meanwhile, plastic hinges may form at some member ends and the frame may lose its ... design ... more ... Meanwhile, plastic hinges may form at some member ends and the frame may lose its ... design variables are decoded and the sequence numbers in the available steel section list ... order to make comparison with the optimum designs obtained for non-linear elasticplastic frames. ...

Computers & Structures, 1991

A structural optimization algorithm is developed for geometrically nonlinear three-dimensional tr... more A structural optimization algorithm is developed for geometrically nonlinear three-dimensional trusses subject to displacement, stress and cross-sectional area constraints. The method is obtained by coupling the nonlinear analysis technique with the optimality criteria approach. The ...