• Journal of Mechanical Science and Technology
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• 제17권5호
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• pp.726-739
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• 2003

A multi-dimensioanl model is being increasingly used to predict the thermo-flow field in the gas turbine combustor. This article addresses an integrated survey of modeling of the liquid spray formation and fuel distribution in gas turbine with high-shear nozzle/swirler assembly. The processes of concern include breakup of a liquid jet injected through a hole type orifice into air stream, spray-wall interaction and spray-film interaction, breakup of liquid sheet into ligaments and droplet,5, and secondary droplet breakup. Atomization of liquid through hole nozzle is described using a liquid blobs model and hybrid model of Kelvin-Helmholtz wave and Rayleigh-Taylor wave. The high-speed viscous liquid sheet atomization on the pre-filmer is modeled by a linear stability analysis. Spray-wall interaction model and liquid film model over the wall surface are also considered.

• 한국가스학회지
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• 제7권1호
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• pp.41-46
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• 2003

14atm, 233K의 아세틸렌 기체를 자유팽창 시켜서 생성한 아세틸렌 cluster의 상과 온도 변화를 실험적으로 측정하였으며, cluster를 여러 겹의 shell로 나누어 취급하고 각 shell 마다 증발과 열전도 현상에 근거한 온도계산을 하는 모델링을 적용하여 이론적인 온도를 구하고 실험값과 비교함으로써, 생성된 cluster의 크기를 4.88$\mu$으로 결정하였다.

• 터널과지하공간
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• 제16권6호
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• pp.476-485
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• 2006

발파에 의한 암반의 손상이나 파쇄는 폭약의 폭굉 과정에서 발생하는 충격파와 가스팽창의 영향에 의해 야기된다. 발파에 의한 파괴 메커니즘을 완전히 이해하기 위해서는 두 메커니즘을 같이 연구해야한다. 본 연구에서는 개별 요소법에 기초한 수치해석 프로그램인 PFC2D를 이용하여 발파공 벽면에 작용하는 폭굉압과 가스압을 동시에 모델링 할 수 있고 이에 따른 암반 내 균열 발생을 확인할 수 있는 알고리즘을 개발하였다. 또한 시멘트-모르타르 블록에서의 모형 발파시험을 수치해석을 수행함으로써, 개발된 알고리즘을 검증하였다.

• Journal of Mechanical Science and Technology
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• 제15권9호
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• pp.1302-1310
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• 2001

This paper introduces modeling and simulation results for pipeline inspection gauge (PIG) with bypass flow control in natural gas pipeline. The dynamic behaviour of the PIG depends on the different pressure across its body and the bypass flow through it. The system dynamics includes: dynamics of driving gas flow behind the PIG, dynamics of expelled gas in front of the PIG, dynamics of bypass flow, and dynamics of the PIG. The bypass flow across the PIG is treated as incompressible flow with the assumption of its Mach number smaller than 0.45. The governing nonlinear hyperbolic partial differential equations for unsteady gas flows are solved by method of characteristics (MOC) with the regular rectangular grid under appropriate initial and boundary conditions. The Runge-Kuta method is used for solving the steady flow equations to get initial flow values and the dynamic equation of the PIG. The sampling time and distance are chosen under Courant-Friedrich-Lewy (CFL) restriction. The simulation is performed with a pipeline segment in the Korea Gas Corporation (KOGAS) low pressure system, Ueijungboo-Sangye line. Simulation results show us that the derived mathematical model and the proposed computational scheme are effective for estimating the position and velocity of the PIG with bypass flow under given operational conditions of pipeline.

• 대한기계학회논문집
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• 제11권6호
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• pp.982-990
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• 1987

본 연구에서는 참고문헌(12)에서 배제된 머플러와 플래퍼밸브의 운동을 추가 시킴으로써 앞의 모델보다 실제장치에 근접시켜 보다 정확한 열적 및 동적거동을 예측 하고, 또한 컴퓨터 시뮬레이션의 수행시 계산시간을 줄여 정상운전상태의 결과를 얻고 자 한다.

• Journal of information and communication convergence engineering
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• 제6권4호
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• pp.448-453
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• 2008

This study describes design and development techniques of estimation models for process modeling. One case study is undertaken to design a model using standard gas furnace data. Neural networks (NN) and genetic programming (GP) are each employed to model the crucial relationships between input factors and output responses. In the case study, two models were generated by using 70% training data and evaluated by using 30% testing data for genetic programming and neural network modeling. The model performance was compared by using RMSE values, which were calculated based on the model outputs. The average RMSE for training and testing were 0.8925 (training) and 0.9951 (testing) for the NN model, and 0.707227 (training) and 0.673150 (testing) for the GP model, respectively. As concern the results, the NN model has a strong advantage in model training (using the all data for training), and the GP model appears to have an advantage in model testing (using the separated data for training and testing). The performance reproducibility of the GP model is good, so this approach appears suitable for modeling physical fabrication processes.

• Geomechanics and Engineering
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• 제13권1호
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• pp.99-117
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• 2017

Rock physics modeling of sandstone reservoir from gas fields of Krishna-Godavari basin represents the link between reservoir parameters and seismic properties. The rock physics diagnostic models such as contact cement, constant cement and friable sand are chosen to characterize reservoir sands of two wells in this basin. Cementation is affected by the grain sorting and cement coating on the surface of the grain. The models show that the reservoir sands in two wells under examination have varying cementation from 2 to more than 6%. Distinct and separate velocity-porosity and elastic moduli-porosity trends are observed for reservoir zones of two wells. A methodology is adopted for generation of Rock Physics Template (RPT) based on fluid replacement modeling for Raghavapuram Shale and Gollapalli Sandstones of Early Cretaceous. The ratio of P-wave velocity to S-wave velocity (Vp/Vs) and P-impedance template, generated for this above formations is able to detect shale, brine sand and gas sand with varying water saturation and porosity from wells in the Endamuru and Suryaraopeta gas fields having same shallow marine depositional characters. This RPT predicted detection of water and gas sands are matched well with conventional neutron-density cross plot analysis.

• 한국가스학회지
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• 제1권1호
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• pp.73-80
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• 1997

본 연구는 화학장치설비중 저장탱크에서 누출된 유해독성가스인 염소의 풍하거리에 따른 10분 평균, 30분 평균 및 1시간 평균 최대 지표면 농도를 산출하여 염소가스의 법적 규제농도인 IDLH 및 ERPG-3 농도들과 비교함으로써 유해위험거리 (hazard distance) 또는 독성완충거리 (toxic buffer distance)를 정량적으로 예측하는 분산모델링 방법론을 개발하고자 수행되었다. 본 분산모델링을 위하여 누출원모델, 분산모델, 기상 및 지형자료들 이 SuperChems 모델에 입력자료로 사용되었으며, 대기의 안정도, 풍속, 표면거칠기 길이의 변화에 따른 지표면 농도의 영향이 평가되었다.

• 지능정보연구
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• 제7권2호
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• pp.83-93
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• 2001

기업부실예측은 과거로부터 많은 연구가 이루어진 분야로, 주로 통계기법에 의한 분류예측문제로 다루어져 왔다. 최근에는 인공신경망, 의사결정나무 등 비선형성을 반영할 수 있는 인공지능 기법을 적용한 연구가 많이 수행되고 있다. 본 연구에서는 최적화에 주로 활용하는 인공지능 기법인 유전자 알고리즘을 규칙추출을 통한 기업부실예측 모형의 개발에 적용하고, 활용가능성을 검증하였다.

• 상하수도학회지
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• 제25권4호
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• pp.503-510
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• 2011

Ammonia in water which is toxic to human, its concentration is regulated below 0.5 mg/L in drinking water. Current study aimed to develop appropriate models for ammonia stripping using hollow fiber membrane contactor. Two different models were developed during the study. Model 1 was assumed only free ammonia ($NH_3$) transfer in stripping process, whereas the Model 2 was assumed with total ammonia ($NH_3+{NH_4}^+$) transfer. Ammonium chloride ($NH_4CI$), sodium hydroxide(NaOH) were used to make ammonia solution, which was concentration of 25 mg as N/L at a pH of 10.5. The experimental conditions were such that, the liquid flow was in tube-side in upward direction and t he gas flow was on shell-side in downward direction a t room temperature. The experimental and modeling results showed that marginal difference were observed at low gas flux. However the difference between the both models and experimental value were increased when the gas flux was increased. The study concludes that the Model 1 with free ammonia is more appropriate when both models were compared and useful in ammonia stripping process at low gas flux.