• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 A
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• pp.241-243
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• 1998

This paper describes a new method for the faster shape optimization of the electromagnetic devices. In a conventional iterative method of shape design optimization using design sensitivity based on a finite element method, meshes for a new shape of the model are generated and a discretized system equation is solved using the meshes in each iteration. They cause much design time. To save this time, a polynomial approximation of the finite element solution with respect to the geometric design parameters using Taylor expansion is constructed. This approximate state variable expressed explicitly in terms of design parameters is employed in a gradient-based optimization method. The proposed method is applied to the shape design of quadrupole magnet.

• 한국전산유체공학회지
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• 제6권3호
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• pp.10-18
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• 2001

Genetic Algorithm(GA) is applied to aerodynamic shape optimization and demonstrated its merits in global searching ability and the independency of differentiability. However, applications of GA are limited due to slow convergence rate, premature termination, and high computing costs. The present aerodynamic designs such as wing shape optimizations using GA have seldom been applied because of high computing costs. This paper has two objects; improvement of the efficiency of GA and application of GA into aerodynamic shape optimization for 2D and 3D wings. The study indicates that GA can be applied to aerodynamic design and its performance is comparable to traditional design methods.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.531-536
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• 2001

The structural shape optimization is a useful tool for engineers to determine the shape of a structure. During the optimization process, relocations of nodes happen successively. However, excessive movement of nodes often results in the mesh distortion and eventually deteriorates the accuracy of the optimum solution. To overcome this problem, an efficient method for the shape optimization has been developed. The method starts from the design domain which is large enough to hold the possible shape of the structure. The design domain has pre-defined uniform fine meshes. At every cycle, the method judges whether all the elements are inside of the structure or not. Elements inside of the structure are assigned with real material properties, however elements outside of the structure are assigned with nearly zero values. The performance of the method is evaluated through various examples.

• Advances in aircraft and spacecraft science
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• 제4권4호
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• pp.467-486
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• 2017

A method for decoupling reliability based design optimization problem into a set of deterministic optimization and performing a reliability analysis is described. The inner reliability analysis and the outer optimization are performed separately in a sequential manner. Since the outer optimizer must perform a large number of iterations to find the optimized shape and size of structure, the computational cost is very high. Therefore, during the course of this research, new multilevel reliability optimization methods are developed that divide the design domain into two sub-spaces to be employed in an iterative procedure: one of the shape design variables, and the other of the size design variables. In each iteration, the probability constraints are converted into equivalent deterministic constraints using reliability analysis and then implemented in the deterministic optimization problem. The framework is first tested on a short column with cross-sectional properties as design variables, the applied loads and the yield stress as random variables. In addition, two cases of curvilinearly stiffened panels subjected to uniform shear and compression in-plane loads, and two cases of curvilinearly stiffened panels subjected to shear and compression loads that vary in linear and quadratic manner are presented.

• 한국유체기계학회 논문집
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• 제12권3호
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• pp.7-12
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• 2009

In this paper, shape optimization based on three-dimensional flow analysis has been performed for impeller design of centrifugal compressor. To evaluate the objective function of an isentropic efficiency, Reynolds-averaged Navier-Stokes equations are solved with SST (Shear Stress Transport) turbulence model. The governing equations are discretized by finite volume approximations. The optimization techniques based on the radial basis neural network method are used for the optimization. Latin hypercube sampling as design of experiments is used to generate thirty design points within design space. Sequential quadratic programming is used to search the optimal point based on the radial basis neural network model. Four geometrical variables concerning impeller shape are selected as design variables. The results show that the isentropic efficiency is enhanced effectively from the shape optimization by the radial basis neural network method.

• 전기학회논문지
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• 제62권2호
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• pp.177-183
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• 2013

We describe a new method for selecting design variables for shape optimization of high-voltage gas circuit breaker using a Kriging meta-model and a genetic algorithm. Firstly we sample balance design variables using the Latin Hypercube Sampling. Secondly, we build meta-model using the Kriging. Thirdly, we search the optimal design variables using a genetic algorithm. To obtain the more exact design variable, we adopt the boundary shifting method. With the proposed optimization frame, we can get the improved interruption design and reduce the design time by 80%. We applied the proposed method to the optimization of multivariate optimization problems as well as shape optimization of a high - voltage gas circuit breaker.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 봄 학술발표회 논문집
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• pp.335-342
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• 2002

A continuum-based design sensitivity analysis (DSA) method fur non-shape problems is developed for geometrically nonlinear elastic structures. The non-shape problem is characterized by the design variables that are not associated with the domain of system like sizing, material property, loading, and so on. Total Lagrangian formulation with the Green-Lagrange strain and the second Piola-Kirchhoff stress is employed to describe the geometrically nonlinear structures. The spatial domain is discretized using the 4-node isoparametric plane stress/strain elements. The resulting nonlinear system is solved using the Newton-Raphson iterative method. To take advantage of the derived analytical sensitivity In topology optimization, a fast and efficient design sensitivity analysis method, adjoint variable method, is employed and the material property of each element is selected as non-shape design variable. Combining the design sensitivity analysis method and a gradient-based design optimization algorithm, an automated design optimization method is developed. The comparison of the analytical sensitivity with the finite difference results shows excellent agreement. Also application to the topology design optimization problem suggests a very good insight for the layout design.

• 대한기계학회논문집A
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• 제38권4호
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• pp.363-370
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• 2014

본 연구에서는 NURBS(Non-Uniform Rational B-spline)를 이용한 형상최적화 방법을 제안한다. 대부분 NURBS 기반 형상 최적화 방법은 NURBS의 제어점 위치 좌표 값만을 설계변수로 택하고 있다. 이러한 경우, 형상최적화 과정에서 종종 제어점들이 서로 가까워져 메쉬 품질을 악화시키고 수렴이 되지 않는 등의 문제를 야기시킨다. 본 연구에서는 형상최적화에서 NURBS 제어점의 좌표뿐 아니라 가중치를 추가적으로 설계 변수로 고려하여 세밀한 형상 변화를 가능하게 하고, 제어점 위치 좌표 최적화 과정과 제어점 가중치 최적화 과정을 분리하여 단계적으로 효율적인 형상 최적화를 수행하였다. 제안한 형상최적화 방법을 예제에 적용하여 제안된 방법의 효율성을 검증하였다.

• 한국공간구조학회논문집
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• 제2권3호
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• pp.93-102
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• 2002

The objective of this study is the development of size, shape and topology discrete optimum design algorithm which is based on the genetic algorithms. The algorithm can perform both shape and topology optimum designs of trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of trusses and the constraints are stress and displacement. The basic search method for the optimum design is the genetic algorithms. The algorithm is known to be very efficient for the discrete optimization. The genetic algorithm consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. The efficiency and validity of the developed size, shape and topology discrete optimum design algorithms were verified by applying the algorithm to optimum design examples

• 한국생산제조학회지
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• 제19권5호
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• pp.637-644
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the growth-strain method. An actual design involves uncertain conditions such as material property, operational load, Poisson's ratio and dimensional variation. The purpose of the RBSO is to consider the variations of probabilistic constraint and performances caused by uncertainties. In this study, the growth-strain method was applied to shape optimization of reliability analysis. Even though many papers for reliability-based shape optimization in mathematical programming method and ESO (Evolutionary Structural Optimization) were published, the paper for the reliability-based shape optimization using the growth-strain method has not been applied yet. Growth-strain method is applied to performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints in the change of average mises stress. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization. It was verified that the reliability-based shape optimization using growth-strain method are very effective for general structure. The purpose of this study is to improve structure's safety considering probabilistic variable.