• International Journal of Precision Engineering and Manufacturing
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• v.3 no.1
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• pp.13-19
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• 2002

Although the design of magnetic bearing needs a systematic optimization due to several design variables, constraints, geometric limitations, nonlinearities, and so on, the present designs for magnetic bearings have been conducted in the linear region of the characteristics for magnetic materials by trial and error considering design constraints. This article, therefore, provides the possibility of a genetic algorithm(GA) based optimization with two dimensional nonlinear finite element magnetic field analysis for the design of a radial heteropolar magnetic bearing. The magnetic bearing design by GA based optimization makes good agreements with that by a commercial optimization software DOT using the sensitivity analysis.

• Smart Structures and Systems
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• v.21 no.3
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• pp.263-278
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• 2018

Thermal Exchange Optimization (TEO) is a newly developed algorithm which mimics the thermal exchange between a solid object and its surrounding fluid. In this paper, an improved version of the TEO is developed to fix the shortcomings of the standard version. To demonstrate the viability of the new algorithm, the CEC 2016's single objective problems are considered along with the discrete size optimization of benchmark skeletal structures. Problem specific constraints are handled using a fly-back mechanism. The results show the validity of the improved TEO method compared to its standard version and a number of well-known algorithms.

• Computers and Concrete
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• v.24 no.2
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• pp.117-123
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• 2019

Optimization is an important subject which is widely used in engineering problems. In this paper, an analytical method is developed for optimum design of reinforced concrete beams considering both flexural and shear effects. A closed-form formulation is derived for optimal height and rebar of beams. The total material cost of steel and concrete is considered as the objective function which is minimized during the optimization process. The ultimate flexural and shear capacities of the beam are considered as the main constraints. The ultimate limit state is considered for deriving the relations for flexural capacity of the beam. The design requirements are considered according to the item 9 of the Iranian National Building. Analytical formulas and some curves are proposed to be used for optimum design of RC beams. The proposed method can be used to perform the optimization of RC beams without the need of any prior knowledge in optimization. Also, the results of the studied numerical example show that the proposed method results in a better design comparing with the other methods.

• Steel and Composite Structures
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• v.44 no.2
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• pp.211-224
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• 2022

Multi-objective optimization was conducted to obtain the optimal configuration of a composite sandwich structure with honeycomb-foam hybrid core subjected to underwater shock waves, which can fulfill the demand for light weight and energy efficient design of structures against underwater blast. Effects of structural parameters on the dynamic response of the sandwich structures subjected to underwater shock waves were analyzed numerically, from which the correlations of different parameters to the dynamic response were determined. Multi-objective optimization of the structure subjected to underwater shock waves of which the initial pressure is 30 MPa was conducted based on surrogate modelling method and genetic algorithm. Moreover, optimization results of the sandwich structure subjected to underwater shock waves with different initial pressures were compared. The research can guide the optimal design of composite sandwich structures subjected to underwater shock waves.

• Wind and Structures
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• v.34 no.3
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• pp.259-274
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• 2022

The present paper is focused on analyzing a set of Computational Fluid Dynamics (CFD) simulation data on reducing orthogonal peak base moment coefficients on a high-rise rectangular building with wings. The study adopts an aerodynamic optimization procedure (AOP) composed of CFD, artificial neural network (ANN), and genetic algorithm (G.A.). A parametric study is primarily accomplished by altering the wing positions with 3D transient CFD analysis using k - ε turbulence models. The CFD technique is validated by taking up a wind tunnel test. The required design parameters are obtained at each design point and used for training ANN. The trained ANN models are used as surrogates to conduct optimization studies using G.A. Two single-objective optimizations are performed to minimize the peak base moment coefficients in the individual directions. An additional multiobjective optimization is implemented with the motivation of diminishing the two orthogonal peak base moments concurrently. Pareto-optimal solutions specifying the preferred building shapes are offered.

• Structural Engineering and Mechanics
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• v.7 no.4
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• pp.401-412
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• 1999

The purpose of this paper is to show how the Evolutionary Structural Optimization (ESO) algorithm developed by Xie and Steven can be extended to optimal design problems of thin shells subjected to thermal loading. This extension simply incorporates an evolutionary iterative process of thermoelastic thin shell finite element analysis. During the evolution process, lowly stressed material is gradually eliminated from the structure. This paper presents a number of examples to demonstrate the capabilities of the ESO algorithm for solving topology optimization and thickness distribution problems of thermoelastic thin shells.

• Structural Engineering and Mechanics
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• v.47 no.5
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• pp.729-740
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• 2013

This paper addresses the structural design of the front end of Siemens ER24 locomotive body. The steel structure of the frontend is replaced with composite. Optimization of the composite lay-up is performed using Genetic Algorithms. Initially an optimized single design for the entire structure is presented. Then a more refined optimum is developed by considering the separate optimization of 7 separate regions of the structure. Significant savings in the weight of the structure are achieved.

• Structural Engineering and Mechanics
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• v.44 no.4
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• pp.501-519
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• 2012

Truss weight is one of the most important factors in the cost of construction that should be reduced. Different methods have been proposed to optimize the weight of trusses. The artificial bee colony algorithm has been proposed recently. This algorithm selects the lightest section from a list of available profiles that satisfy the existing provisions in the design codes and specifications. An important issue in optimization algorithms is how to impose constraints. In this paper, the artificial bee colony algorithm is used for the discrete optimization of trusses. The fly-back mechanism is chosen to impose constraints. Finally, with some basic examples that have been introduced in similar articles, the performance of this algorithm is tested using the fly-back mechanism. The results indicate that the rate of convergence and the accuracy are optimized in comparison with other methods.

• East Asian mathematical journal
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• v.31 no.3
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• pp.371-377
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• 2015

We consider a nondifferentiable robust optimization problem, which has a maximum function of continuously differentiable functions and support functions as its objective function, continuously differentiable functions as its constraint functions. We prove optimality conditions for the nondifferentiable robust optimization problem. We formulate a Wolfe type dual problem for the nondifferentiable robust optimization problem and prove duality theorems.

• CDE review
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• v.3 no.2
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• pp.89-92
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• 1997

이 글에서 소개하는 topology optimization은 structural optimization의 한 분야로서 최근 10여년 동안 급격하게 발전되어 온 분야이다. Structural optimization은 오랜 역사(일반적으로 최초의 structural optimization은 17세기 Galileo에 의하여 되어졌다고 받아들임)를 가지고 발달되어 왔음에도 불구하고 아직도 최적화 방법론과 응용 관점에서 빠르게 발전되고 있다. 이 분야는 사회적인 요구(한정된 자원과 에너지, 안전도, 환경문제)와 컴퓨터 관련 학문(고성능 컴퓨터, computational geometry, finite element method)의 발달에 힘입어 최근 30년간 많은 진전이 있었다.