• 한국연소학회:학술대회논문집
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• 2006.10a
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• pp.202-208
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• 2006

The purpose of this research is to model numerically the turbulent gas-particle flows in a rectangular chamber using Eulerian-Eulerian Method. A computer code using the ${\kappa}-{\varepsilon}-Ap$ two-phase turbulence model is developed for the numerical study. This code and the Eulerian multiphase model in FLUENT were used for the numerical simulations of the two-phase flow in a rectangular chamber. The numerical results calculated by the two different turbulent gas-particle codes have shown that the ${\kappa}-{\varepsilon}-Ap$ model results in a stronger diffusion of the flow momentum in the gas-particle turbulence interaction than the Eulerian multiphase model in FLUENT.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.1
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• pp.1-14
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• 2009

When the stagnation temperature increases, the specific heat does not remain constant and start to vary with this temperature. The gas is perfect, it's state equation remains always valid, except, it was called by gas calorically imperfect or gas at high temperatures. The purpose of this work is to develop a mathematical model for a normal shock wave normal at high temperature when the stagnation temperature is taken into account, less than the dissociation of the molecules as a generalisation model of perfect for constant heat specific. A study on the error given by the perfect gas model compared to our model is presented in order to find a limit of application of the perfect gas model. The application is for air.

• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.51-61
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• 2022

Gas separation via hollow fibre membrane modules (HFMM) is deemed to be a promising technology for natural gas sweetening, particularly for lowering the level of carbon dioxide (CO₂) in natural gas, which can cause various problems during transportation and process operation. Separation performance via HFMM is affected by membrane properties, module specifications and operating conditions. In this study, a mathematical model for HFMM is developed, which can be used to assess the effects of the aforementioned variables on separation performance. Appropriate boundary conditions are imposed to resolve steady-state values of permeate variables and incorporated in the model equations via an iterative numerical procedure. The developed model is proven to be reliable via model validation against experimental data in the literature. Also, the model is capable of capturing axial variations of process variables as well as predicting key performance indicators. It can be extended to simulate a large-scale plant and identify an optimal process design and operating conditions for improved separation efficiency and reduced cost.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.6-8
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• 2005

In this paper, we discuss model identification of nonlinear data using GAs-based Fuzzy Polynomial Neural Networks(GAs-FPNN). Fuzzy Polynomial Neural Networks(FPNN) is proposed model based Group Method Data Handling(GMDH) and Neural Networks(NNs). Each node of FPNN is expressed Fuzzy Polynomial Neuron(FPN). Network structure of nonlinear data is created using Genetic Algorithms(GAs) of optimal search method. Accordingly, GAs-FPNN have more inflexible than the existing models (in)from structure selecting. The proposed model select and identify its for optimal search of Genetic Algorithms that are no. of input variables, input variable numbers and consequence structures. The GAs-FPNN model is select tuning to input variable number, number of input variable and the last part structure through optimal search of Genetic Algorithms. It is shown that nonlinear data model design using Genetic Algorithms based FPNN is more usefulness and effectiveness than the existing models.

• Earthquakes and Structures
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• v.18 no.1
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• pp.73-82
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• 2020

With the coal mining depth increasing, both stress and gas pressure rapidly enhance, causing coal and gas outburst risk to become more complex and severe. The conventional method for prediction of coal and gas outburst adopts one prediction index and corresponding critical value to forecast and cannot reflect all the factors impacting coal and gas outburst, thus it is characteristic of false and missing forecasts and poor accuracy. For the reason, based on analyses of both the prediction indicators and the factors impacting coal and gas outburst at the test site, this work carefully selected 6 prediction indicators such as the index of gas desorption from drill cuttings Δh₂, the amount of drill cuttings S, gas content W, the gas initial diffusion velocity index ΔP, the intensity of electromagnetic radiation E and its number of pulse N, constructed the Bayes discriminant analysis (BDA) index system, studied the BDA-based multi-index comprehensive model for forecast of coal and gas outburst risk, and used the established discriminant model to conduct coal and gas outburst prediction. Results showed that the BDA - based multi-index comprehensive model for prediction of coal and gas outburst has an 100% of prediction accuracy, without wrong and omitted predictions, can also accurately forecast the outburst risk even for the low indicators outburst. The prediction method set up by this study has a broad application prospect in the prediction of coal and gas outburst risk.

• Corrosion Science and Technology
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• v.3 no.6
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• pp.257-261
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• 2004

Leaking of fuel gas in a building creates flammable atmosphere and gives rise to explosion. Observations from accidents suggest that some explosions are caused by quantity of gas significantly less than the lower explosion limit amount required to fill the whole confined space, which might be attributed to inhomogeneous mixing of the leaked gas. The minimum amount of leaked gas for explosion is highly dependent on the degree of mixing in the building. This paper proposes a method for estimating minimum amount of flammable gas for explosion assuming Gaussian distribution of flammable gas.

• Applied Chemistry for Engineering
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• v.24 no.4
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• pp.375-381
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• 2013

Kinetics data were obtained for steam reforming of methane and natural gas over the commercial nickel catalyst. Variables for the steam reforming were the reaction temperature and partial pressure of reactants. Parameters for the Power law rate model and the Langmuir-Hinshelwood model were obtained from the kinetic data. As a result of the reforming reaction using pure methane as a reactant, the reaction rate could be determined by the Power law rate model as well as the Langmuir-Hinshelwood model. In the case of methane in natural gas, however, the Langmuir-Hinshelwood model is much more suitable than the Power law rate model in terms of explaining methane reforming reaction. This behavior can be attributed to the competitive adsorption of methane, ethane, propane and butane in natural gas over the same catalyst sites.

• Membrane and Water Treatment
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• v.3 no.3
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• pp.151-168
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• 2012

Gas sparging is one of the techniques used to control the concentration polarization during ultrafiltration. In this work, the effects of gas sparging in stratified flow regime were investigated during gel layer controlling cross flow ultrafiltration in a rectangular channel. Synthetic solution of pectin was used as the gel forming solute. The liquid and gas flow rates were selected such that a stratified flow regime was prevalent in the channel. A mass transfer model was developed for this system to quantify the effects of gas flow rates on mass transfer coefficient (Sherwood number). The results were compared with the case of no gas sparging. Gas sparging led to an increase of mass transfer coefficient by about 23% in this case. The limitation of the developed model was also evaluated and it was observed that beyond a gas flow rate of 20 l/h, the model was unable to explain the experimental observation, i.e., the decrease in permeate flux with flow rate.

• Geomechanics and Engineering
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• v.30 no.1
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• pp.45-49
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• 2022

In the present study, a physical model was built for the Jintan underground gas storage cavern group according to the similarity theory. In this regard, four ellipsoid caverns were built with scaled in-situ stresses and internal pressure. Then the stability of underground caverns was analyzed. The obtained results demonstrate that loss of internal pressure adversely affects the safety of caverns and attention should be paid during the operation of gas storage.

• Journal of the Korean Institute of Gas
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• v.10 no.4 s.33
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• pp.11-16
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• 2006

The purposes of this study is to develop a domestic MARKAL(MARKet ALlocation) model with construction of database system to find the technology mix for the electricity generation market in Korea. The MARKAL model is officially used for national energy system optimization in the International Energy Agency(IEA), and the role is becoming more important in relation to analyze the greenhouse gas mitigation potential and to evaluate the technologies. Four scenarios specially emphasized on the greenhouse gas reduction and technology mix of electric generation were applied, each of them covering the analysis periods between 2004 and 2040.