• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.218-225
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• 2008

When the heat release and acoustic pressure fluctuations are generated in the combustor by irregular combustion, these fluctuations affect the mass flow rate of the propellants injected through the injectors. Also, the variations of the mass flow rate by these fluctuations again bring about irregular combustion and furthermore that is related with combustion instability. Therefore, it is very important to identify the mass variation for the pressure fluctuation on the injector and to investigate its transfer function. So, we first have studied quantifying the variation of mass flow rate generated in simplex swirl injector by injection pressure fluctuation. To acquire the transient mass flow rate in orifice with time, we have tried to measure of the flow axial velocity and liquid film thickness in orifice. The axial velocity is acquired through theoretical approach after measuring the pressure in orifice and the flow area in the orifice is measured by electric conductance method. As results, mass flow rate calculated by axial velocity and liquid film thickness measuring in orifice accorded with mass flow rate acquired by direct measuring method in the small error range within 1 percents in steady state and within 6 percents as average mass flow rate in pulsated state. Hence this method can be used to measure the mass flow rate not only in steady state but also in unsteady state because the mass flow rate in the orifice can acquire with time and this method shows very high accuracy based on the experimental results.

• The Journal of Information Systems
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• v.5
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• pp.21-41
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• 1996

Linear programming has become an important tool in decision-making of modern business management. This remarkable growth can be traced to the pioneering efforts of many individuals and research organizations. The popular using of personal computers make it very easy to process those complicated linear programming models. Furthermore advanced linear programming software packages assist us to solve L.P. models without any difficult process. Even though the advanced L.P. professional packages, the needs of more detailed deterministic elements for business decisions have forced us to apply dynamic approaches for more resonable solutions. For the purpose of these problems applying to the "Mathematica" packages which is composed of mathematic tools, the simplex processes show us the flexible and dynamic decision elements included to any other professional linear programming tools. Especially we need proper dynamic variables to analyze the shadow prices step by step. And applying SAS(Statistical Analysis System) packages to the L.P. problems, it is also one of the best way to get good solution. On the way trying to the other L.P. packages which are prepared for Spreadsheets i.e., MS-Excel, Lotus-123, Quatro etc. can be applied to linear programming models. But they are not so much useful for the problems. Calculating simplex tableau is an important method to interpret L.P. format for the optimal solution. In this paper we find out that the more detailed and efficient techniques to interpret useful software of mathematica and SAS for business decision making of linear programming. So it needs to apply more dynamic technique of using of Mathematica and SAS multiple software to get more efficient deterministic factors for the sophiscated L.P. solutions.

• Korean Management Science Review
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• v.15 no.1
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• pp.1-12
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• 1998

This paper discusses a new algorithm, the PAPANET (Pivot And Probe Algorithm for NETwork optimization), for solving linear, capacitated linear network flow problem (NPs), PAPANET is a variation and specialization of the Pivot And Probe Algorithm (PAPA) developed by Sethi and Thompson, published in 1983-1984. PAPANET first solves an initial relaxed NP (RNP) with all the nodes from the original problem and a limited set of arcs (possibly all the artificial and slack arcs). From the arcs not considered in the current relaxation, we PROBE to identify candidate arcs that violate the current solution's dual constraints maximally. Candidate arcs are added to the RNP, and this new RNP is solved to optimality. This candidate pricing procedure and pivoting continue until all the candidate arcs price unfavorably and all of the dual constraints corresponding to the other, so-called noncandidate arcs, are satisfied. The implementation of PAPANET requires significantly fewer arcs and less solution CPU time than is required by the standard network simplex method implementation upon which it is based. Computational tests on randomly generated NPs indicate that our PAPANET implementation requires up to 40-50% fewer pivots and 30-40% less solution CPU time than is required by the comparable standard network simplex implementation from which it is derived.

• Journal of Environmental Science International
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• v.29 no.8
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• pp.793-800
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• 2020

The conventional development of multi-component electrodes is based on the researcher's experience and is based on trial and error. Therefore, there is a need for a scientific method to reduce the time and economic losses thereof and systematize the mixing of electrode components. In this study, we use design of mixture experiments (DOME)- in particular a simplex lattice design with Design Expert^Ⓡ program- to attempt to find an optimum mixing ratio for a three-component electrode for the high RNO degradation; RNO is an indictor of OH radical formation. The experiment included 12 experimental points with 2 center replicates for 3 different independent variables (with the molar ratio of Ru, Ti, Ir). As the Prob > F value of the 'Quadratic' model is 0.0026, the secondary model was found to be suitable. Applying the molar ratio of the electrode components to the corrected response model results is an RNO removal efficiency (%) = 59.89 × [Ru] + 9.78 × [Ti] + 67.03 × [Ir] + 66.38 × [Ru] × [Ir] + 132.86 × [Ti] × [Ir]. The R² value of the equation is 0.9374 after the error term is excluded. The optimized formulation of the ternary electrode for an high RNO degradation was acquired when the molar ratio of Ru 0.100, Ti 0.200, Ir 0.700 (desirability d value, 1).

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.87-94
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• 2001

Silicon nitride films grown by plasma-enhanced chemical vapor deposition (PECVD) are useful for a variety of applications, including anti-reflecting coatings in solar cells, passivation layers, dielectric layers in metal/insulator structures, and diffusion masks. PECVD systems are controlled by many operating variables, including RF power, pressure, gas flow rate, reactant composition, and substrate temperature. The wide variety of processing conditions, as well as the complex nature of particle dynamics within a plasma, makes tailoring SiN film properties very challenging, since it is difficult to determine the exact relationship between desired film properties and controllable deposition conditions. In this study, SiN PECVD modeling using optimized neural networks has been investigated. The deposition of SiN was characterized via a central composite experimental design, and data from this experiment was used to train and optimize feed-forward neural networks using the back-propagation algorithm. From these neural process models, the effect of deposition conditions on film properties has been studied. A recipe synthesis (optimization) procedure was then performed using the optimized neural network models to generate the necessary deposition conditions to obtain several novel film qualities including high charge density and long lifetime. This optimization procedure utilized genetic algorithms, hybrid combinations of genetic algorithm and Powells algorithm, and hybrid combinations of genetic algorithm and simplex algorithm. Recipes predicted by these techniques were verified by experiment, and the performance of each optimization method are compared. It was found that the hybrid combinations of genetic algorithm and simplex algorithm generated recipes produced films of superior quality.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1
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• pp.78-85
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• 1999

In this paper we propose a method to improve the performance of the mel-cepstrum that is widely used in speech recognition. Typically, the met-cepstrum is obtained by critical band filters that have fixed center spacing and bandwidth. However different filter characteristics produce a different mel-cepstrum, resulting in a different performance. In this paper we analyze triangular-shaped and rectangular-shaped filters. By changing the characteristics of filters such as center frequency and bandwidth, we analyze the performance of the met-cepstrum. Then utilizing the simplex method, we propose a method to optimize the critical band filters. Using the dynamic time warping, we performed speaker independent recognition experiments with Korean digit words pronounced by 10 males and 10 females. Experiments show that the rectangular-shaped filters show good performance and the mel-cepstrum obtained by the optimized filters shows better performance than filters that have fixed center spacing and bandwidth.

• Environmental Engineering Research
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• v.24 no.4
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• pp.662-669
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• 2019

Anaerobic digestion is a popular sewage sludge (Ss) treatment method as it provides significant pollution control and energy recovery. However, the low C/N ratio and poor biodegradability of Ss necessitate pretreatment methods that improve solubilization under anaerobic conditions in addition to anaerobic co-digestion with other substrates to improve the process efficiency. In this study, three pretreatment methods, namely microwave irradiation, ultrasonication, and heat treatment, were investigated, and the corresponding improvement in methane production was assessed. Additionally, the simplex centroid design method was utilized to determine the optimum mixture ratio of food waste (Fw), livestock manure (Lm), and Ss for maximum methane yield. Microwave irradiation at 700 W for 6 min yielded the highest biodegradability (62.0%), solubilization efficiency (59.7%), and methane production (329 mL/g VS). The optimum mixture ratio following pretreatment was 61.3% pretreated Ss, 28.6% Fw, and 10.1% Lm. The optimum mixture ratio without pretreatment was 33.6% un-pretreated Ss, 46.0% Fw, and 20.4% Lm. These results indicate that the choice of pretreatment method plays an important role in efficient anaerobic digestion and can be applied in operational plants to enhance methane production. Co-digestion of Ss with Fw and Lm was also beneficial.

• Journal of Environmental Science International
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• v.25 no.5
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• pp.737-744
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• 2016

For electrolysis process using an insoluble electrode, electrochemical performance was greatly affected by the manufacturing method and procedure, such as the firing temperature, pre-treatment, type of precursor solution, coating method, electrode material, etc. Components of the electrode therein is one of the most important factors in electrochemical reaction. To achieve such characteristics, a appropriate ratio of the electrode material should be carefully chosen. The aim of this research was to apply experimental design method in the optimization of electrode component for the maximum generation of oxidants in electrochemical oxidation process. Mixture design, especially expanded simplex lattice design, in DOME (design of mixture experiments) with Design Expert - commercial software - was used to analyze the data. Analysis of variance (ANOVA) showed a high coefficient of determination ($R^2$) value of 0.9470, thus ensuring a satisfactory adjustment of the $3^{rd}$ order special cubic regression model with the experimental data. The application of response surface methodology (RSM) yielded the following regression equation, which is an empirical relationship between the TRO generation concentration and independent variables(mol ratio of 3 electrode components) in a real unit: TRO generation concentration $(mg/L)=TRO\;conc.=98.25{\times}[Ir]+49.71{\times}[Sn]+95.29{\times}[Sb]-16.91{\times}[Ir]{\times}[Sn]-29.47{\times}[Ir]{\times}[Sb]-22.65{\times}[Sn]{\times}[Sb]+703.19{\times}[Ir]{\times}[Sn]{\times}[Sb]$. The optimized formulation of the 3 component electrode for an high TRO (total residual oxidants) generation was acquired at mol ratio of Ir 0.406, Sn 0.210, Sb 0.384 (desirability d value, 1).

• 전기의세계
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• v.30 no.6
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• pp.375-385
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• 1981

New algorithms are derived for nonlinear programming problems which are characterized by their large variables and equality and inequality constraints. The algorithms are based upon the introduction of the Dependent-Variable-Elimination method, Independent-Variable-Reduction method, Optimally-Ordered-Triangular-Factorization method, Equality-Inequality-Sequential-Satisfaction method, etc. For a case study problem relating to the optimal determination of load flow in a 10-bus, 13-line sample power system, several approaches are undertaken, such as SUMT, Lagrange's Multiplier method, sequential applications of linear and quadratic programming method. For applying the linear programming method, the conventional simplex algorithm is modified to the large-system-oriented one by the introduction of the Two-Phase method and Variable-Upper-Bounding method, thus resulting in remarkable savings in memory requirements and computing time. The case study shows the validity and effectivity of the algorithms presented herein.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.2
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• pp.43-51
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• 1993

This paper describes the flow path design of unidirectional automated guided vehicle systems. The objective is to find the flow path which will minimize total travel time of unloaded as well as loaded vehicles. The allocation of unloaded vehicles is determined by applying the transportation simplex method. The problem is solved using a branch-and-bound technique. A simple illustrative example is discussed to demonstrate the procedure.