• Journal of Welding and Joining
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• v.30 no.6
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• pp.113-119
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• 2012

Ultrasonic bonding is the novel packaging method for flip-chip with high yield and low-temperature bonding. The bonding module is a core part of the bonding machine, which can transfer the ultrasonic energy into the bonding spot. In this paper, we propose topology optimization technique which can make new design of boding modules due to the constraints on resonance frequency and mode shapes. The designed bonding module using topology optimization was fabricated in order to evaluate the bonding performance and reliable operation during the continuous bonding process. The actual production models based on the proposed design satisfied the target frequency range and ultrasonic power. The bonding test was performed using flip-chip with lead-free Sn-based bumps, the results confirmed that the bonding strength was sufficient with the designed bonding modules. Also the performance degradation of the bonding module was not observed after the 300-hour continuous process with bonding conditions.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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• pp.409-422
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• 2016

A parametric study based on an unsteady mathematical model of a pyrotechnically actuated device was performed for design optimization. The model simulates time histories for the chamber pressure, temperature, mass transfer and pin motion. It is validated through a comparison with experimentally measured pressure and pin displacement. Parametric analyses were conducted to observe the detailed effects of the design parameters using a validated performance analysis code. The detailed effects of the design variables on the performance were evaluated using the one-at-a-time (OAT) method, while the scatter plot method was used to evaluate relative sensitivity. Finally, the design optimization was conducted by employing a genetic algorithm (GA). Six major design parameters for the GA were chosen based on the results of the sensitivity analysis. A fitness function was suggested, which included the following targets: minimum explosive mass for the uniform ignition (small deviation), light casing weight, short operational time, allowable pyrotechnic shock force and finally the designated pin kinetic energy. The propellant mass and cross-sectional area were the first and the second most sensitive parameters, which significantly affected the pin's kinetic energy. Even though the peak chamber pressure decreased, the pin kinetic energy maintained its designated value because the widened pin cross-sectional area induced enough force at low pressure.

• The KIPS Transactions:PartB
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• v.14B no.5
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• pp.377-382
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• 2007

This paper proposes a training algorithm for global optimization of the parameters of radial basis function networks. Since conventional training algorithms usually perform only local optimization, the performance of the network is limited and the final network significantly depends on the initial network parameters. The proposed hybrid simulated annealing algorithm performs global optimization of the network parameters by combining global search capability of simulated annealing and local optimization capability of gradient-based algorithms. Via experiments for function approximation problems, we demonstrate that the proposed algorithm can find networks showing better training and test performance and reduce effects of the initial network parameters on the final results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.575-594
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• 2010

In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with "conventional" evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some "conventional" fuzzy models already encountered in the literature.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.109-117
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• 2021

In this paper, the meta-model based approximate optimization was carried out for the structure design of an ocean automatic salt collector in order to minimize the structure weight. The structural analysis was performed by using the finite element method to evaluate the strength performance of the ocean automatic salt collector in its initial design. In the structural analysis, it was evaluated the strength performance of the design load conditions. The optimum design problem was formulated so that design variables of main structure thickness would be determined by minimizing the structure weight subject to strength performance constraints. The meta-models used in the approximate optimization were the response surface method, Kriging model, and Chebyshev orthogonal polynomials. Regarding to the numerical characteristics, the solution results from approximate optimization techniques were compared to the results of non-approximate optimization. The Chebyshev orthogonal polynomials among the meta-models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the ocean automatic salt collector.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.11
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• pp.771-781
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• 2022

Sequential convex programming based performance analysis of the designed UAV is performed. The nonlinear optimization problems generated by aerodynamics are approximated to socond order program by discretization and convexification. To improve the performance of the algorithm, the solution of the relaxed problem is used as the initial trajectory. Dive trajectory optimization problem is analyzed through iterative solution procedure of approximated problem. Finally, the maximum final velocity according to the performance of the actuator model was compared.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.545-563
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• 2015

Energy harvesting (EH) and network coding (NC) have emerged as two promising technologies for future wireless networks. In this paper, we combine them together in a single system and then present a time switching-based network coding relaying (TSNCR) protocol for the two-way relay system, where an energy constrained relay harvests energy from the transmitted radio frequency (RF) signals from two sources, and then helps the two-way relay information exchange between the two sources with the consumption of the harvested energy. To evaluate the system performance, we derive an explicit expression of the outage probability for the proposed TSNCR protocol. In order to explore the system performance limit, we formulate an optimization problem to minimize the system outage probability. Since the problem is non-convex and cannot be directly solved, we design a genetic algorithm (GA)-based optimization algorithm for it. Numerical results validate our theoretical analysis and show that in such an EH two-way relay system, if NC is applied, the system outage probability can be greatly decreased. Moreover, it is shown that the relay position greatly affects the system performance of TSNCR, where relatively worse outage performance is achieved when the relay is placed in the middle of the two sources. This is the first time to observe such a phenomena in EH two-way relay systems.

• International Journal of Fluid Machinery and Systems
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• v.9 no.2
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• pp.143-149
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• 2016

In this study, a method for the multi-objective optimization of an impeller for a centrifugal compressor using fluid-structure interaction (FSI) and response surface method (RSM) was proposed. Numerical simulation was conducted using ANSYS CFX and Mechanical with various configurations of impeller geometry. Each design parameter was divided into 3 levels. A total of 15 design points were planned using Box-Behnken design, which is one of the design of experiment (DOE) techniques. Response surfaces based on the results of the DOE were used to find the optimal shape of the impeller. Two objective functions, isentropic efficiency and equivalent stress were selected. Each objective function is an important factor of aerodynamic performance and structural safety. The entire process of optimization was conducted using the ANSYS Design Xplorer (DX). The trade-off between the two objectives was analyzed in the light of Pareto-optimal solutions. Through the optimization, the structural safety and aerodynamic performance of the centrifugal compressor were increased.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.571-575
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• 2008

An engine cradle is a quite important structural assembly for supporting the engine, suspension and steering parts of vehicle and absorbing the vibrations during the drive and the shock in the car crash. Recently, the engine cradle having structural stiffness enough to support the surrounding parts and absorbing the shock of collision has been widely used. The hydroforming technology may cause many advantages to automotive applications in terms of better structural integrity of parts, reduction of production cost, weight reduction, material saving, reduction in the number of joining processes and improvement of reliability. We focus on increasing the durability and the dynamic performance of engine cradle. For realizing this objective, several optimization design techniques such as shape, size, and topology optimization are performed. This optimization scheme based on the sensitivity can provide distinguished performance improvement in using hydroforming.

• The KSFM Journal of Fluid Machinery
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• v.17 no.4
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• pp.19-29
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• 2014

In addition to the development of micro hydro turbine, the challenge in micro hydro turbine design as sustainable hydro devices is focused on the optimization of turbine runner blade which have decisive effect on the turbine performance to reach higher efficiency. A multi-objective optimization method to optimize the performance of runner blade of propeller turbine for micro turbine has been studied. For the initial design of planar blade cascade, singularity distribution method and the combination of the Bezier curve parametric technology is used. A non-dominated sorting genetic algorithm II(NSGA II) is developed based on the multi-objective optimization design method. The comparision with model test show that the blade charachteristics is optimized by NSGA-II has a good efficiency and load distribution. From model test and scale up calculation, the maximum prototype efficiency of the runner blade reaches as high as 90.87%.