• Membrane Journal
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• v.12 no.2
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• pp.90-96
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• 2002

A novel methodology on the calculations of osmotic pressure and gradient diffusion coefficient has been provided ill the present study, by applying a succinct numerical analysis on the experimental results. Although both the osmotic pressure and the gradient diffusion coefficient represent a fundamental characteristic in related membrane filtrations such as microfiltration and ultrafiltration, neither theoretical analysis nor experiments can readily determine them. The osmotic pressure of colloidal suspension has been successfully determined from a relationship between the data of the time-dependent permeate flux, their numerical accumulations, and their numerical derivatives. It is obvious that the osmotic pressure is gradually increased, as the particle concentration increases. The thermodynamic coefficient was calculated from the numerical differentiation of the correlation equation of osmotic pressure, and the hydrodynamic coefficient was evaluated from the previously developed relation for an ordered system. Finally, the estimated gradient diffusion coefficient, which entirely depends on the particle concentration, was compared to the previous results obtained from the statistical mechanical simulations.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1605-1609
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• 2010

CGCM3.1 SRES B1 시나리오의 2D 변수들을 입력값으로 인공신경망 모형을 이용한 스케일 상세화기법으로 강부식(2009)은 소양강댐 유역의 월 누적강수 경향분석을 실시하였다. 원시 GCM 시나리오를 스케일 상세화 시키기 위한 기법의 하나로 인공신경망 모형을 사용할 수 있는데, 이 경우 GCM에서 모의되는 강수플럭스, 해면기압, 지표면 근처에서의 일 평균온도, 지표면 근처에서의 일평균온도, 지표면으로부터 발생하는 잠열플럭스 등과 같은 22개의 변수를 잠재적인 예측인자로 사용하여 신경망을 구성하게 된다. 입력변수세트의 구성은 인공신경망의 계산 효율을 좌우하는 중요한 요소라 할 수 있다. 본 연구에서는 변수의 물리적 특성을 고려하여 순차적인 변수선택을 통한 신경망 입력변수 세트를 구성하고 입력세트 간의 학습성과 비교를 통하여, 최적 입력변수 선정 및 신경망의 학습효과를 높일 수 있는 방법에 대해 연구하였다. 물리적 상관성이 높다고 판단되는 GCM_Prec, huss, ps를 입력변수로 하여 순차적인 케이스를 학습해본 결과 huss와 ps를 입력변수로 하는 케이스에 대해서 적은 오차와 높은 상관성을 보였다, 또한, 신경망의 학습 효과를 높이기 위해 홍수기와 비홍수기로 구분하여 학습한 결과 홍수기와 비홍수기로 구분하여 신경망을 구성하였을 경우가 향상된 모의값을 나타내었다. 기후변화모의자료는 CCCma(Canadian Center for Climate Modeling and Analysis)에서 제공되는 CGCM3.1/T63 20C3M 시나리오를 사용하였으며, 관측값으로는 AWS에서 제공된 일 누적강수를 사용하였다. 인공신경망의 학습기간은 1997년부터 2000년이며, 검증기간은 2001년부터 2004년으로 구성하였다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.134-134
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• 2011

3차원 난류 부력젵의 혼합을 큰 와 모의(large-eddy simulation) 기법을 이용하여 수치모의 한다. 개발된 수치모형은 3차원 열동수역학 모형을 이용하여 부력젵의 퍼짐, 자기 보존 그리고 주변류의 연행 등을 포함하는 난류젵의 동적 특성을 분석할 수 있다. 수치해석에서 하부격자규모 (subgrid scale, SGS) 난류 응력은 부력항을 수정한 Smagorinsky 모형을 이용한다. 여과된 엔탈피 수송방정식에서 하부격자규모의 스칼라 플럭스는 상수의 SGS Prandtl 수를 가지는 단순 경사수송 가설에 근거하여 모의한다. 계산된 결과를 실험결과와 비교하며, 결과는 양호하게 일치함을 보여준다. 계산결과에 따르면 부력항의 수정이나 SGS 난류 Prandtl 수는 결과에 큰 영향을 미치지 않지만 SGS 모형 상수인 Cs 값은 부력젵 확산 예측에 중요한 영향을 미치는 것으로 나타났다.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 1999.04a
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• pp.8-8
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• 1999

2-유체 인젝터의 분무연소에 대한 통찰 및 구조에 대한 이해와 연료-공기 혼합과 연소반응의 물리적 이해에 필요한 수치적 모델의 개발 및 검증을 위해서는 2유체 시스템에서 액체 및 기체 각각의 기본적 특성인 액적크기, 액적속도, 액적의 질량플럭스(flux), 가스상의 속도측정 등이 필요하다. 특히, 액체분무에서는 액적의 크기를 예측하는 것이 매우 중요한 과제이며, 액적의 크기에 영향을 주는 인자들로는 노즐의 형태, 분사액체의 물성치(점도, 표면장력, 밀도), 주위기체의 조건(온도, 압력, 응축과 증발현상), 분사압력 등이 있다. 그러나, 실제 분무액적의 크기는 분포를 가지므로 같은 SMD를 가지더라도 그 분포의 정도는 크게 다를 수 있어 결과적으로 분무액적의 크기를 평균값만으로 표현하는 것은 불충분할 뿐만 아니라 그 적용에도 한계를 가지게 된다. 따라서 분무액적의 평균크기와 함께 그 분포의 정도 등을 함께 나타내려는 시도가 많은 과학자들에 의하여 연구되었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.207-207
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• 2020

하천으로 유입된 오염물질의 거동을 정확하게 예측하는 것은 하천 시스템의 수질 유지관리에 매우 중요하다. 본 연구에서는 1차 감쇠율(decay rate)을 가진 비보존성 오염물의 비정상 이송해석 방정식의 해를 위해 유한체적기법이 개발되어졌다. 하천 흐름 해석을 위해 자연형 단면에서의 마름-젖음 해석이 가능한 기법이 도입되었다. 이 기법은 2차-정도의 정확성와 Courant 수가 1 까지 안정함을 보장한다. 도입된 기법은 Godnov 형의 유한체적기법을 이용하여 St. Venant 방정식들을 해석하였고 질량 및 운동량 플럭스는 Roe 형의 Riemann Solver 를 사용하여 연산하였다. 오염물의 이송 해석은 추가적인 이송-확산 방정식을 도입을 통해 기존의 St. Venant 방정식과 함께 풀려질 수 있다. 추가된 방정식과 St. Venant 식은 3×3 eigenstructure를 구성하였고 이는 2차원 흐름해석 기법과 유사하게 해석될 수 있었다. 본 연구 모형의 검증을 위해 오염물의 계속적 주입을 가정한 가상 및 실제 하천에 적용되었다. 연구된 기법은 모든 적용에서 합리적 정확도를 가지고 오염물질의 연속적인 특성을 잘 모의하고 있었다.

• Membrane Journal
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• v.5 no.1
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• pp.35-43
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• 1995

For several years lots of attempts have been made to establish the liquid membrane-based techniques for separations of gas mixtures especially containing carbon dioxide. A more effective system to separate $CO_{2}$ from flue gases, a circulatory hollow-fiber membrane absorber(HFMA) consisting of absorption and desorption modules with vacuum mode, has been considered in this study. Gas-liquid mass transfer has been modeled on a membrane module with non-wetted hollow-fibers in the laminar flow regime. The influence of an absorbent flow rate on the separation performance of the circulatory HFMA can be predicted quantitatively by obtaining the $CO_{2}$ concentration profile in a tube side. The system of $CO_{2}/N_{2}$ binary gas mixture has been studied using pure water as an(inert) absorbent. As the absorbent flow rate is increased, the permeation flux(i.e., defined as permeation rate/membrane contact area) also increases. The enhanced selectivity compared to the previous results, on the other hand, shows the decreasing behavior. It has been found obviously that the permeation flux depends on the variations of pressure in gas phase of desorption module. From an accurate comparison with the results of conventional flat sheet membrane module, the advantageous permeability of this circulatory HFMA can be clearly ascertained as expected. Our efforts to the theoretical model will provide the basic analysis on the circulatory HFMA technique for a better design and process.

• Membrane Journal
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• v.33 no.1
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• pp.34-45
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• 2023

Two computational intelligence techniques namely artificial neural networks (ANN) and support vector machine (SVM) are employed to model the permeate flux based on seven input variables including time, transmembrane pressure, rotating velocity, the pore diameter of the membrane, dynamic viscosity, concentration and density of the feed fluid. The best-fit model was selected through the trial-error method and the two statistical parameters including the coefficient of determination (R²) and the average absolute relative deviation (AARD) between the experimental and predicted data. The obtained results reveal that the optimized ANN model can predict the permeate flux with R² = 0.999 and AARD% = 2.245 versus the SVM model with R² = 0.996 and AARD% = 4.09. Thus, the ANN model is found to predict the permeate flux with high accuracy in comparison to the SVM approach.

• Clean Technology
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• v.13 no.2
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• pp.143-150
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• 2007

The objective of this study is to develop hydrocarbon-based cleaning agents by blending paraffins, glycol ethers and siloxanes in oder to effectively clean contaminants such as flux, solder and grease. And the effect of cleaning ability by wetting index, aniline points and solubility parameter of the formulated hydrocarbon-based cleaning agents were studied in this work. The formulated hydrocarbon-based cleaning agents were prepared on the base of physical properties of their individual components. Wetting indexes and aniline points of their were measured through experiments and solubility parameters of their were calculated based on the Hansen's equation. In this study, evaluation of cleaning ability by cleaning agents were carried out using contaminants such as flux, solder, and grease. The experimental results showed that the cleaning ability of the formulated cleaning agents was excellent in cleaning contaminants such as flux, solder and grease and that the influencing parameters on their cleaning efficiency were found to be different according to contaminant types. MC($20.3MPa^{1/2}$), DF-1 ($24.2MPa^{1/2}$) and DF-2($21.5MPa^{1/2}$) with similar solubility parameter as flux ($21.3MPa^{1/2}$) showed 100% cleaning efficiency within 3 minutes in flux cleaning. And CFC-113, MC and 1,1,1-TCE with low aniline point less than $-20^{\circ}C$ showed excellent cleaning efficiency in solder cleaning. DG-1($16.2\;MPa^{1/2}$) and DG-2($15.5\;MPa^{1/2}$) with similar solubility parameter as grease($15.0{\sim}17.0\;MPa^{1/2}$) showed relatively low cleaning efficiency of grease, but CFC-113 and MC with high wetting index and low aniline point showed good cleaning efficiency in grease cleaning. As a result of this study, the hydrocarbon-based cleaning agents alternative to regulated cleaning agents such as CFC-113, 1,1,1-TCE and MC were able to be developed through properly blending paraffins, glycol ethers and siloxanes for cleaning flux, solder and grease. And it can be shown that various influencing parameters of cleaning efficiency such as wetting index, aniline point, solubility parameter and etc. of the non-aqueous cleaning agent should be reviewed for prediction of their cleaning ability and can be applied to formulation of cleaning agents.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.6
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• pp.617-623
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• 2001

To predict the seasonal variation of dissolved oxygen (DO) in Hakata bay, Japan, possible 20 time-series of different hourly-solar-radiation intensities were generated based on stochastically changing solar radiation intensity, and a numerical simulation on dissolved oxygen (DO) was carried out for each time series by using the Sediment-Water Ecological Model (SWEM). The model, consisting of two sub-models with hydrodynamic and biological models, simulates the circulation process of nutrient between water column and sediment, such as nutrient regeneration from sediments as well as ecological structures on the growth of phytoplankton and zooplankton, The results of the model calibration followed the seasonal variation of observed water quality well, and generated cumulative-frequency-distribution (CFD) curves of daily solar radiation agreed well with observed ones, The simulation results indicated that the exchange of sea water would have a great influence on the DO concentration, and that the concentration could change more than 1 mg/L in a day. This prediction method seems to be an effective way to examine a solution to minimize fishery damage when DO is depleted.