• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.5
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• pp.1244-1253
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• 1990

Time-Marching methods solving Euler equations are used for calculation of two-dimensional, steady, inviscid flow through a stationary compressor cascade. Calculation method is based on the Denton`s opposed difference scheme. A smoothing in the axial direction is used to increase the stability of solution. The computational grid consists of quadrilateral elements, one of which has four nodes at each corner and the grid points on the upper periodic boundaries are located one pitch away from those on the lower boundaries to satisfy the periodicity condition. Results of calculation show good agreement with other computational and experimental results, proving that the present method of calculation should be applied with confidence for the cascade flow with shock wave.

• Journal of the Korean Society of Propulsion Engineers
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• v.6 no.2
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• pp.75-84
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• 2002

A numerical analysis of unsteady motion in solid rocket motors with a nozzle has been conducted. The numerical formulation including modified $\kappa$-$\varepsilon$ turbulence model treats the complete conservation equation for the gas phase and the one-dimensional equations in the radial direction for the condensed phase. A fully coupled implicit scheme based on a dual time-stepping integration algorithm has been adopted to solve the governing equations. After obtaining a steady state solution, pulse and periodic oscillations of pressure are imposed at the head-end to simulate acoustic oscillations of a travelling-wave motion in the combustion chamber. Various steady and unsteady state features in the combustion chamber of a rocket motor has been analyzed as results of numerical calculations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.117-126
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• 2015

This paper is to analyze an integrated production and inventory model in a single-vendor multi-buyer supply chain. The vendor is defined as the manufacturer and the buyers as the retailers. The product that the manufacturer produces is supplied to the retailers with constant periodic time interval. The production rate of the manufacturer is constant for the time. The demand of the retailers is constant for the time. The cycle time of the vendor is defined as the elapsed time from the start of the production to the start of the next production, while the cycle times of the buyer as the elapsed time between the adjacent supply times from the vendor to the buyer. The cycle times of the vendor and the buyers that minimizes the total cost in a supply chain are analyzed. The cost factors are the production setup cost and the inventory holding cost of the manufacturer, the ordering cost and the inventory holding cost of the retailers. The cycle time of the vendor is investigated through the cycle time that satisfies economic production quantity with the production setup cost and the inventory holding cost of the manufacturer. An integrated production and inventory model is formulated, and an algorithm is developed. An numerical example is presented to explain the algorithm. The solution of the algorithm for the numerical examples is compared with that of genetic algorithm. Numerical example shows that the vendor and the buyers can save cost by integrated decision making.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.586-591
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• 2012

The solution of maintenance decision support system for the gas turbine engine, which is currently operating in GUNSAN combined cycle power plant, was developed and is consist of online monitoring module, periodic performance trending module, optimal compressor washing interval analysis module and hot component management module. Also, GUI platform was applied to this solution for the user to monitoring the analyzed result of engine performance condition and then to make a decision of the consequent maintenance action. In online condition monitoring module, the performance degradation of engine is provided by the analysis of difference between the real time measurement data compared to exist engine performance. The optimal compressor washing interval module produced the washing interval of maximum net profit value by researching the maintenance expense and the loss profit value corresponds to the performance degradation with economic assessment algorithm. Thus, this solution support the user to enable the optimal maintenance and operation of gas turbine engine with overall analysis of engine condition and main information.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.1
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• pp.61-67
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• 2000

Digital controllers found in many industrial real-time systems consist of a number of interacting periodic tasks. To sustain the required control quality, these tasks possess the maximum activation periods as performance constraints. An essential step in developing a real-time system is thus to assign each of these tasks a constant period such that the maximum activation requirements are met while the system utilization is minimized [1]. Given a task graph design allowing producer/consumer relationships among tasks [2], resource demands of tasks, and range constraints on periods, the period assignment problem falls into a class of nonlinear optimization problems. This paper proposes a ploynomial time approximation algorithm which produces a solution whose utilization does not exceed twice the optimal utilization. Our experimental analysis shows that the proposed algorithm finds solutions which are very close to the optimal ones in most cases of practical interest.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.305-312
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• 2010

The aim of this study is to find an analytic solution to the problem of determining the optimal capacity of a batch-storage network to meet demand for finished products in a system undergoing joint random variations of operating time and batch material loss. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to joint random variations in the cycle time and batch size. The production processes have also joint random variations in cycle time and product quantity. The spoiled materials are treated through regeneration or waste disposal processes. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced. The proposed method has the potential to rapidly provide very useful data on which to base investment decisions during the early plant design stage. It should be of particular use when these decisions must be made in a highly uncertain business environment.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.454-454
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• 2014

Silicon microwire array is one of the promising platforms as a means for developing highly efficient solar cells thanks to the enhanced light trapping efficiency. Among the various fabrication methods of microstructures, deep reactive ion etching (DRIE) process has been extensively used in fabrication of high aspect ratio microwire arrays. In this presentation, we show precisely controlled Si microwire arrays by tuning the DRIE process conditions. A periodic microdisk arrays were patterned on 4-inch Si wafer (p-type, $1{\sim}10{\Omega}cm$) using photolithography. After developing the pattern, 150-nm-thick Al was deposited and lifted-off to leave Al microdisk arrays on the starting Si wafer. Periodic Al microdisk arrays (diameter of $2{\mu}m$ and periodic distance of $2{\mu}m$) were used as an etch mask. A DRIE process (Tegal 200) is used for anisotropic deep silicon etching at room temperature. During the process, $SF_6$ and $C_4F_8$ gases were used for the etching and surface passivation, respectively. The length and shape of microwire arrays were controlled by etching time and $SF_6/C_4F_8$ ratio. By adjusting $SF_6/C_4F_8$ gas ratio, the shape of Si microwire can be controlled, resulting in the formation of tapered or vertical microwires. After DRIE process, the residual polymer and etching damage on the surface of the microwires were removed using piranha solution ($H_2SO_4:H_2O_2=4:1$) followed by thermal oxidation ($900^{\circ}C$, 40 min). The oxide layer formed through the thermal oxidation was etched by diluted hydrofluoric acid (1 wt% HF). The surface morphology of a Si microwire arrays was characterized by field-emission scanning electron microscopy (FE-SEM, Hitachi S-4800). Optical reflection measurements were performed over 300~1100 nm wavelengths using a UV-Vis/NIR spectrophotometer (Cary 5000, Agilent) in which a 60 mm integrating sphere (Labsphere) is equipped to account for total light (diffuse and specular) reflected from the samples. The total reflection by the microwire arrays sample was reduced from 20 % to 10 % of the incident light over the visible region when the length of the microwire was increased from $10{\mu}m$ to $30{\mu}m$.

• Korean Chemical Engineering Research
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• v.46 no.3
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• pp.585-597
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• 2008

The aim of this study was to find an analytic solution to the problem of determining the optimal capacity (lot-size) of a batch-storage network to meet demand for a finished product in a system undergoing random failures of operating time and/or batch material. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to short-term random variations in the cycle time and batch size as well as long-term variations in the average trend. Some of the production processes have random variations in product quantity. The spoiled materials are treated through regeneration or waste disposal processes. All other processes have random variations only in the cycle time. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis, the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced.

• Journal of computational fluids engineering
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• v.6 no.2
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• pp.22-31
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• 2001

The two-dimensional unsteady incompressible viscous flow behind rectangular bluff bodies between two parallel plates was analyzed numerically. The steady state flow and the vortex flow behind rectangular bluff bodies in the channel were investigated for two regimes i.e., the laminar(Re = 100, 300, 500) and the turbulent flows(Re = 10⁴∼10/sup 6/). The vortex shedding was generated by a physical disturbance(6%) numerically imposed at the rear of the bluff bodies for a short time. It was observed that the perturbed flow became periodic after a transient period. And in the case of unsteady inflow, the sinusoidal pulsatile flow was applied as the inlet condition in the turbulent flow of Reynolds number of 1.0×10/sup 5/. FLUENT code was employed to solve the problems. The power-law scheme was used to get stable linearized equations and the PISO algorithm was applied to finding the solution of them.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.116-125
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• 2019

The Dynamic Vehicle Routing Problem (DVRP) involves a combinatorial optimization problem where new customer demands become known over time, and old routes must be reconfigured to generate new routes while executing the current solution. We consider the high level of dynamism problem. An application of highly dynamic DVRP is the ambulance service where a patient contacts the service center, followed by an evaluation of case severity, and a visit by a practitioner/ ambulance is scheduled accordingly. This paper considers a variant of the DVRP and proposes a decentralized algorithm in which collaborators (Depot and Vehicle), both have only partial information about the entire system. The DVRP is modeled as a periodic re optimization of VRP using the proposed decentralized algorithm where collaborators exchange local information to achieve the best global objective for the current state of the system. We assume the existence of a dispatcher e.g., headquarter of the company who can communicate to vehicles in order to gather information and assigns the new visits to them. The effectiveness of the proposed decentralized coordination algorithm is further evaluated using benchmark data given in literature. The results show that the proposed method performed better than the compared algorithms which utilize the centralized coordination in 12 out of 21 benchmark problems.