• JSTS:Journal of Semiconductor Technology and Science
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• v.5 no.4
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• pp.229-236
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• 2005

This paper presents a system level architecture evaluation technique that leverages transaction level modeling but also significantly extends it to the realm of system level performance evaluation. A major issue lies with the modeling effort. To reduce the modeling effort the proposed technique develops the concept of worst case scenarios. Since the memory controller is often found to be an important component that critically affects the system performance and thus needs optimization, the paper further addresses how to evaluate and optimize the memory controllers, focusing on the test environment and the methodology. The paper also presents an industrial case study using a real state-of-the-art design. In the case study, it is reported that the proposed technique has helped successfully find the performance bottleneck and provide appropriate feedback on time.

• International Journal of Fluid Machinery and Systems
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• v.2 no.2
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• pp.179-188
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• 2009

Recent development of high speed computers and use of optimization techniques have given a big momentum of turbomachinery design replacing expensive experimental cost as well as trial and error approaches. The surrogate based optimization techniques being used for aerodynamic turbomachinery designs coupled with Reynolds-averaged Navier-Stokes equations analysis involve single- and multi-objective optimization methods. The objectives commonly tried to improve were adiabatic efficiency, pressure ratio, weight etc. Presently coupling the fluid flow and structural analysis is being tried to find better design in terms of weight, flutter and vibration, and turbine life. The present article reviews the surrogate based optimization techniques used recently in turbomachinery shape optimizations.

• Korean Journal of Computational Design and Engineering
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• v.16 no.6
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• pp.397-406
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• 2011

Since tolerance allocation in a mobile phone camera manufacturing process greatly affects production cost and reliability of optical performance, a systematic design methodology for allocating optimal tolerances is required. In this study, we proposed the tolerance optimization procedure for determining tolerances that minimize production cost while satisfying the reliability constraints on important optical performance indices. We employed Latin hypercube sampling for evaluating the reliabilities of optical performance and a function-based sequential approximate optimization technique that can reduce computational burden and well handle numerical noise in the tolerance optimization process. Using the suggested tolerance optimization approach, the optimal production cost was decreased by 30.3 % compared to the initial cost while satisfying the two constraints on the reliabilities of optical performance.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.55-62
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• 2005

In this paper, a CAB/CAE integrated optimal design system is developed, in which design and analysis process is automated using CAD/CAE softwares, for a complicated model for which parametric modeling provided by CAD software is not possible. CAD modeling process is automated by using UG/OPEN API function and UG/Knowledge Fusion provided by Unigraphics. The generated model is transferred to the analysis code ANSYS in parasolid format. Visual DOC software is used for optimization. The system is developed for PLS(Plasma Lighting System), which is a next generation illumination system that is used to illuminate stadium or outdoor advertizing panel. The PLS system consists of more then 20 components, which requires a lot of human efforts in modeling and analysis. The analysis for PLS includes static load, wind load and impact load analysis. As a result of analysis, it is found that the most critical component is a tilt assembly, which links lower & upper body assembly. For more reliable analysis, experiment is conducted using MTS and compared with the Finite element analysis result. The objective in the optimization is to minimize the material volume under allowable stresses. The design variables are three parameters in the tilt assembly that are chosen to be the most sensitive in stress values of twelve parameters. Gradient based method and RSM(Response Surface Method) are used for the algorithm and the results are compared. As a result of optimization, the maximum stress is reduced by 57%.

• Smart Structures and Systems
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• v.15 no.3
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• pp.897-911
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• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.2
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• pp.81-87
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• 2004

This paper deals with a new approach to tolerance optimization problems. Optimal tolerance allotment problems can be formulated as stochastic optimization problems. Most schemes to solve the stochastic optimization problems have been found to exhibit difficulties in multivariate integration of the probability density function. As a typical example of stochastic optimization the optimal tolerance allotment problem has the same difficulties. In this stochastic model, manufacturing system is represented by Gauss-Markov stochastic process and the manufacturing unit availability is characterized for realistic optimization modeling. The new algorithm performed robustly for a large deviation approximation. A significant reduction in computation time was observed compared to the results obtained in previous studies.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.6
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• pp.635-644
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• 2003

To ensure the reliability of ultrasonic nondestructive testing techniques for modern structural materials, the effects of anisotropy and inhomogeneity and the influence of non-planar component geometries on ultrasonic wave propagation have to be taken into account. In this article, fundamentals and applications of two analytical approaches to three-dimensional elastic beam field calculation are presented. Results for both isotropic materials including curved interfaces and for anisotropic media like composites are presented, covering field profiles for various types of transducers and the modeling of time-dependent rf-signals.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.275-280
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• 2004

Shape optimization was performed to obtain the precise shape of cutouts including the internal shape of cutouts in laminated composite plates by three dimensional modeling using solid element. The volume control of the growth-strain method was implemented and the distributed parameter chosen as Tsai-Hill fracture index for shape optimization. The volume control of the growth-strain method makes Tsai-Hill failure index at each element uniform in laminated composites under the initial volume. Then shapes optimized by Tsai-Hill failure index were compared with those of the initial shapes for the various load conditions and cutouts. The following conclusions were obtained in this study. (1) It was found that growth-strain method was applied efficiently to shape optimization of three dimensional cutouts in a laminate composite, (2) The optimal shapes of the various load conditions and cutouts were obtained, (3) The maximum Tsal-Hill failure index was reduced up to 67% when shape optimization was peformed under the initial volume by volume control of growth-strain method.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.44-51
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• 2011

Polymer Electrolyte Fuel Cells (PEFCs) operate in wide-range changes in temperature, humidity, and electric current for automotive applications. In order to operate automotive PEFC efficiently, optimal air supply is required to adjust to these changes. This paper presents an air-supply optimization process that consists of experiments, modeling of the PEFC system, and optimization. The objective is to establish an air supply suitable for the required power for PEFC system and optimized with a Lagrange multiplier. Our simplified PEFC system model is used as a constraint for optimization problem. The result of this paper presents that efficient operation of PEFC system can be achieved by air-supply optimization.

• Structural Engineering and Mechanics
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• v.86 no.1
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• pp.119-137
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• 2023

The purpose of this research is to assess the performance of CBN and ceramic tools during the dry turning of gray cast iron EN GJL-350. During the turning operation, the variable machining parameters are cutting speed, feed rate, depth of cut and type of the cutting material. This contribution consists of two sections, the first one deals with the performance evaluation of four materials in terms of evolution of flank wear, surface roughness (2D and 3D) and cutting forces. The focus of the second section is on statistical analysis, followed by modeling and optimization. The experiments are conducted according to the Taguchi design L₃₂ and based on ANOVA approach to quantify the impact of input factors on the output parameters, namely, the surface roughness (Ra), the cutting force (Fz), the cutting power (Pc), specific cutting energy (Ecs). The RSM method was used to create prediction models of several technical factors (Ra, Fz, Pc, Ecs and MRR). Subsequently, the desirability function approach was used to achieve a multi-objective optimization that encompasses the output parameters simultaneously. The aim is to obtain optimal cutting regimes, following several cases of optimization often encountered in industry. The results found show that the CBN tool is the most efficient cutting material compared to the three ceramics. The optimal combination for the first case where the importance is the same for the different outputs is Vc=660 m/min, f=0.116 mm/rev, ap=0.232 mm and the material CBN. The optimization results have been verified by carrying out confirmation tests.