• Journal of computational fluids engineering
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• v.21 no.3
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• pp.39-47
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• 2016

We conducted a multi-stage optimization to secure the desired performance of a centrifugal fan for home appliance in an early stage of product development. In optimization, the static pressure at the outlet of the fan is chosen as an objective function that is to be maximized, providing the required flow rate at the operating point of the fan. The optimization procedure begins with parameters for an initial baseline fan design. The baseline design is optimized by using a commercial optimization package. Accordingly, the corresponding blade models with a set of geometrical parameters are generated. Flow through a fan is simulated by solving the Reynolds-averaged Navier-Stokes equations. A multi-stage optimization scheme is employed to determine the family of optimum values for the parameters, leading to the pressure increase at the outlet of the fan. To validate the numerically obtained optimal design parameters, we fabricated the three types of fans using rapid prototyping and assessed the performance using a fan tester. Experimental results show that the design parameters at each stage satisfy the goal of optimization. The multi-stage optimization process turned out to be a useful tool in the development of a centrifugal fan.

• 한국항공운항학회:학술대회논문집
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• 2016.05a
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• pp.269-275
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• 2016

This paper considers the arrival, airport and departure capacity as a whole, through which, the network effect between airports is fully emphasized, the flight action is coordinated, and the flight demand pattern is reasonably assigned. The optimization problem of flight queues in multi-airport is studied in detail; the mathematical model of multi-airport opening non-real time flow management in terminal area is established, and related problems such as the parameters, the simplification and the solving of the model are discussed in detail to some extent. Appropriate decision making variables are taken to make the multi-airport network system linear 0-1 integer programming model, thus, the solving of the model is available and the central flow management is realized. The heuristic implicit enumeration presented in this paper can effectively solve this kind of problems. Through the simulation of some airports network system, we not only validate the algorithm presented in this paper, but also give a deep analysis of the results, which would produce reference for later practicable use. The simulation proves that this algorithm offers a good way to settle the problem of multi-airport flight queue optimization in air traffic management automation system in terminal area.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.199-206
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• 2014

The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integrates multi-population strategy, collaborative strategy, genetic strategy, and ant colony strategy, to avoid the premature phenomenon, dynamically balance the global search ability and local search ability, and accelerate the convergence speed. We select the traveling salesman problem to demonstrate the validity and feasibility of the NHGAO algorithm for solving complex optimization problems. The simulation experiment results show that the proposed NHGAO algorithm can obtain the global optimal solution, achieve self-adaptive control parameters, and avoid the phenomena of stagnation and prematurity.

• Bulletin of the Korean Mathematical Society
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• v.50 no.6
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• pp.2035-2051
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• 2013

In this paper, we study numerical schemes for solving multi-dimensional option pricing problem. We compare the direct solving method and the Operator Splitting Method(OSM) by using finite difference approximations. By varying parameters of the Black-Scholes equations for the maximum on the call option problem, we observed that there is no significant difference between the two methods on the convergence criterion except a huge difference in computation cost. Therefore, the two methods are compatible in practice and one can improve the time efficiency by combining the OSM with parallel computation technique. We show numerical examples including the Equity-Linked Security(ELS) pricing based on either two assets or three assets by using the OSM with the Monte-Carlo Simulation as the benchmark.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.1898-1909
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• 1993

In this paper, a convenient scheme for solving multi-objective optimization problems including fuzzy information in both objective functions and constraints is presented. At first, a multi-objective problem is converted into single objective problem based on the norm method, and a merbership function is constructed by selecting its type and providing the parameters defined by the norm method. Finally, this fuzzy programming problem is converted into an ordinary optimization problem which can be solved by usual nonlinear programming techniques. With this scheme, a designer can conveniently obtain pareto optimal solutions of a fuzzy system only by providing some parameters corresponding to the importance of the objectiv functions. Proposed scheme is simple and efficient in treating multi-objective fuzzy systems compared with and method by with membership function value is provided interactively. To show the validity of the scheme, a simple 3-bar truss example and optimal cutting problem are solved, and the results show that the scheme is very useful and easy to treat multi-objective fuzzy systems.

• Journal of Power Electronics
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• v.19 no.2
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• pp.431-442
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• 2019

This paper proposes a unified high-frequency bipolar buck-boost (UHFBB) control strategy for a dual-active-bridge (DAB), which is derived from the classical buck and boost DC/DC converter. It can achieve optimized current stress of the switches and soft switching in wider range. The UHFBB control strategy includes multi-control-variables, which can be achieved according to an algorithm derived from an accurate mathematical model. The design method for the parameters, such as the transformer turns ratio and the inductance, are shown. The current stress of the switches is analyzed for selecting an optimal inductor. The analysis is verified by the experimental results within a 500W prototype.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.744-749
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• 2007

Kinematic and kinetic analysis has been performed for Soft Golf swings utilizing realistic three dimensional computer simulations based on three dimensional motion tracking data. Soft Golf is a newly developed recreational sport in South Korea aimed to become a safe and easy-to-learn sport for all ages. The advantage of Soft Golf stems from lighter weight of the club and much larger area of the sweet spot. This paper tries to look into kinematic and kinetic aspects of soft golf swings compared to regular golf swing and find the advantages of lighter Soft Golf clubs. For this purpose, swing motions of older aged participants were captured and kinematic analysis was performed for various kinematic parameters such as club head velocity, joint angular velocity, and joint range of motions as a pilot study. Kinetic analysis was performed by applying kinematic data to computer simulation models constructed from anthropometric database and the measurements from the participants. The simulations were solved using multi-body dynamics solver. Firstly, the kinematic parameters such as joint angles were obtained by solving inverse dynamics problem based on motion tracking data. Secondly, the kinetic parameters such as joint torques were obtained by solving control dynamics problem of making joint torque to follow pre-defined joint angle data. The results showed that mechanical loadings to major joints were reduced with lighter Soft Golf club.

• Structural Engineering and Mechanics
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• v.12 no.3
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• pp.267-281
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• 2001

Transient and quasi-steady-state vertical vibrations of a multi-span beam steel bridge located on a single-track railway line are considered, induced by a superfast passenger train, moving at speed 120-360 km/h. Matrix dynamic equations of motion of a simplified model of the system are formulated partly in the implicit form. A recurrent-iterative algorithm for solving these equations is presented. Excessive vibrations of the system in the resonant zones are reduced effectively with passive dynamic absorbers, tuned to the first mode of a single bridge span. The dynamic analysis has been performed for a series of types of bridges with span lengths of 10 to 30 m, and with parameters closed to multi-span beam railway bridges erected in the second half of the $20^{th}$ century.

• Journal of applied mathematics & informatics
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• v.34 no.5_6
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• pp.383-395
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• 2016

The convergence rate of a numerical procedure based on Schwarz Alternating Method (SAM) for solving elliptic boundary value problems depends on the selection of the interface conditions applied on the interior boundaries of the overlapping subdomains. It has been observed that the Robin condition (mixed interface condition), controlled by a parameter, can optimize SAM's convergence rate. In [8], one formulated the twolayer multi-parameterized SAM and determined the optimal values of the multi-parameters to produce the best convergence rate for one-dimensional elliptic boundary value problems. Two-dimensional implementation was presented in [10]. In this paper, we present an implementation for threedimensional problem.

• Industrial Engineering and Management Systems
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• v.7 no.3
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• pp.204-213
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• 2008

Companies that produce capital goods need to schedule the production of products that have complex product structures with components that require many operations on different machines. A feasible schedule must satisfy operation and assembly precedence constraints. It is also important to avoid deadlock situations. In this paper a Genetic Algorithm (GA) has been developed that includes a new repair process that rectifies infeasible schedules that are produced during the evolution process. The algorithm was designed to minimise the combination of earliness and tardiness penalties and took into account finite capacity constraints. Three different sized problems were obtained from a collaborating capital goods company. A design of experimental approach was used to systematically identify that the best genetic operators and GA parameters for each size of problem.