• 제목/요약/키워드: potential-flow models

검색결과 115건 처리시간 0.031초

수계별 소수력자원의 수문학적 성능특성 (Hydrologic Performance Characteristics of Small Hydro Power Resources for River Systems)

  • 박완순;이철형
    • 한국태양에너지학회 논문집
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    • 제30권2호
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    • pp.65-71
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    • 2010
  • The hydrologic performance characteristics of small hydro power(SHP) sites located in four major river systems have been studied. The model, which can predict flow duration characteristic of stream, was developed to analyze the variation of inflow caused from rainfall condition. And another model to predict hydrologic performance for SHP plants is established. Monthly inflow data measured at Andong dam for 32 years were analyzed. The predicted results from the developed models in this study showed that the data were in good agreement with measured results of long term inflow at Andong dam. The results from hydrologic performance analysis for SHP sites located on five major river systems based on the models developed in this study show that the specific design flowrate and specific output of SHP site have large difference between the river systems.

의사스펙트로법에 의한 대기확산현상의 수치모델(2): 실규모의 복잡지형에서의 스펙트로모델 (Numerical Models for Atmospheric Diffusion Phenomena by Pseudospectral Method(2) : Spectral Model for a Hilly Terrain of Real Scale)

  • 김선태
    • 한국대기환경학회지
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    • 제9권3호
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    • pp.242-246
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    • 1993
  • Theoretically, spectral method has the highest accuracy among present numerical methods, but it is generally difficult to apply to complex terrains because of complex boundary conditions. Recently, spectral-element method, basically divide the domain into a set of rectangular subdomain and solve the equation at each subdomain, has been introduced. However, boundary conditions become more complex and requires more computing time, thus spectral-element method is not powerful for all complex terrain problems. In this paper, potential flow theory was intorduced to solve the air flows and diffusion phenomenon in the presence of terrain obstacles. Using the velocity potential-stream line orthogonal coordinate space, the diffusion problems of hilly terrain by pseudospectral method were solved and compared those with no terrain real scale solutions.

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전난류에서의 파마찰계수 (Wave Friction Factor far Rough Turbulent Flow)

  • 유동훈
    • 한국해안해양공학회지
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    • 제5권2호
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    • pp.51-57
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    • 1993
  • 포텐셜 이론으로 구해지는 해저면 유속은 일반적으로 난류경계층에서의 파유속과 같다고 가정한다. 해저면 가까이에서 파운동에 의한 유속분포를 해석하기 위한 최근의 이론과 수치모형에서 발견되는 실험결과와의 오차는 주로 이 가정의 문제점으로부터 연유하는 것으로 사료된다. 경계층 최상점에서의 유속에 대한 이론치와 실유속치와의 관계식을 본고에서 제의하였다. 이 관계식을 이용하여 Jonsson(1967)과 Fredsoe(1984)가 각각 개발한 기존 이론식을 수정하였으며, 수정된 이론을 이용하여 파마찰계수를 산정한 결과, 발표된 실험치들과 비교하여 상당한 향상을 얻을 수 있었다.

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낙동강 유역 환경유량에 대한 기후변화의 영향 분석 (An Analysis of the Effect of Climate Change on Nakdong River Environmental Flow)

  • 이아연;김상단
    • 한국물환경학회지
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    • 제27권3호
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    • pp.273-285
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    • 2011
  • This study describes the modeling of climate change impact on runoff across southeast Korea using a conceptual rainfall-runoff model TANK and assesses the results using the concept of environmental flows developed by International Water Management Institute. The future climate time series is obtained by scaling the historical series, informed by 4 global climate models and 3 greenhouse gas emission scenarios, to reflect a $4.0^{\circ}C$ increase at most in average surface air temperature and 31.7% increase at most in annual precipitation, using the spatio-temporal changing factor method that considers changes in the future mean seasonal rainfall and potential evapotranspiration as well as in the daily rainfall distribution. Although the simulation results from different global circulation models and greenhouse emission scenarios indicate different responses in flows to the climate change, the majority of the modeling results show that there will be more runoff in southeast Korea in the future. However, there is substantial uncertainty, with the results ranging from a 5.82% decrease to a 48.15% increase in the mean annual runoff averaged across the study area according to the corresponding climate change scenarios. We then assess the hydrologic perturbations based on the comparison between present and future flow duration curves suggested by IMWI. As a result, the effect of hydrologic perturbation on aquatic ecosystems may be significant at several locations of the Nakdong river main stream in dry season.

기록치 오차와 유역모형의 검정(I) - 기록치 내의 측정 오차 분석 - (Errors in Recorded Information and Calibration of a Catchment Modelling System(I) - Analysis of Measurement Errors in Recorded Information -)

  • Kyung Sook Choi;James E. Ball
    • 한국농공학회지
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    • 제45권5호
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    • pp.110-116
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    • 2003
  • A catchment modelling system is the summation of the numerous hydrologic, hydraulic and other process models necessary to simulate the response of a catchment to a storm event. Differences between the recorded catchment response and that predicted by a catchment modelling system can arise from structural errors within the catchment modelling system, evaluation errors in the control parameters, or measurement errors in the recorded data being used to assess the reliability of the evaluation of the control parameters. Presented herein is an investigation of the potential measurement errors within the recorded information, which was considered to occur from instrument error in the ultra sonic flow monitor. This investigation was undertaken using three available rating curves at the Musgrave Avenue Stormwater System in Centennial Park, Sydney, developed by Abustan (1997), Water Board (1994), and using Manning's equation.

인공신경망 기반 VRF 시스템 제어 (ANN-Based VRF (variable refrigerant flow) system control)

  • 문진우
    • 토지주택연구
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    • 제10권3호
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    • pp.9-16
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    • 2019
  • This study aimed at developing control algorithms for operating a variable refrigerant flow (VRF) heating and cooling system with optimal system parameter set-points. Two artificial neural network (ANN) models, which were respectively designed to predict the heating energy cost and cooling energy amount for upcoming next control cycle, was developed and embedded into the control algorithms. Performance of the algorithms were tested using the computer simulation programs - EnergyPlus, BCVTB, MATLAB in an incorporative manner. The results revealed that the proposed control algorithms remarkably saved the heating energy cost by as much as 7.93% and cooling energy consumption by as much as 28.44%, compared to a conventional control strategy. These findings support that the ANN-based predictive control algorithms showed potential for cost- and energy-effectiveness of VRF heating and cooling systems.

자바 스레드와 네트워크 자원을 이용한 병렬처리 (Thread-Level Parallelism using Java Thread and Network Resources)

  • 김태용
    • 한국항행학회논문지
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    • 제14권6호
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    • pp.984-989
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    • 2010
  • 본 논문에서는 초소형 정밀 마이크로 흐름센서를 설계하기 위해 Java 멀티스레드를 이용한 병렬 프로그래밍 기법을 도입하여 센서 모듈의 성능 분석과 개선이 가능한 병렬처리형 설계 툴을 개발하였다. 연산에 따른 기본 성능을 측정하기 위하여 열운송 방정식에 지배되는 포텐셜 문제를 두 개의 실험모델로 나누어 실험을 수행하였다. 시뮬레이션 결과 네트워크 PC의 수를 증가시키면 이와 비례하는 속도향상 특성이 나타났다. 따라서 본 연구에서 제안하는 병렬화 방안은 대규모 연산모델에도 적용 가능함을 확인하였다.

Prediction of the remaining time and time interval of pebbles in pebble bed HTGRs aided by CNN via DEM datasets

  • Mengqi Wu;Xu Liu;Nan Gui;Xingtuan Yang;Jiyuan Tu;Shengyao Jiang;Qian Zhao
    • Nuclear Engineering and Technology
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    • 제55권1호
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    • pp.339-352
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    • 2023
  • Prediction of the time-related traits of pebble flow inside pebble-bed HTGRs is of great significance for reactor operation and design. In this work, an image-driven approach with the aid of a convolutional neural network (CNN) is proposed to predict the remaining time of initially loaded pebbles and the time interval of paired flow images of the pebble bed. Two types of strategies are put forward: one is adding FC layers to the classic classification CNN models and using regression training, and the other is CNN-based deep expectation (DEX) by regarding the time prediction as a deep classification task followed by softmax expected value refinements. The current dataset is obtained from the discrete element method (DEM) simulations. Results show that the CNN-aided models generally make satisfactory predictions on the remaining time with the determination coefficient larger than 0.99. Among these models, the VGG19+DEX performs the best and its CumScore (proportion of test set with prediction error within 0.5s) can reach 0.939. Besides, the remaining time of additional test sets and new cases can also be well predicted, indicating good generalization ability of the model. In the task of predicting the time interval of image pairs, the VGG19+DEX model has also generated satisfactory results. Particularly, the trained model, with promising generalization ability, has demonstrated great potential in accurately and instantaneously predicting the traits of interest, without the need for additional computational intensive DEM simulations. Nevertheless, the issues of data diversity and model optimization need to be improved to achieve the full potential of the CNN-aided prediction tool.

뉴런 활성화 경사 최적화를 이용한 개선된 플라즈마 모델 (An improved plasma model by optimizing neuron activation gradient)

  • 김병환;박성진
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.20-20
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    • 2000
  • Back-propagation neural network (BPNN) is the most prevalently used paradigm in modeling semiconductor manufacturing processes, which as a neuron activation function typically employs a bipolar or unipolar sigmoid function in either hidden and output layers. In this study, applicability of another linear function as a neuron activation function is investigated. The linear function was operated in combination with other sigmoid functions. Comparison revealed that a particular combination, the bipolar sigmoid function in hidden layer and the linear function in output layer, is found to be the best combination that yields the highest prediction accuracy. For BPNN with this combination, predictive performance once again optimized by incrementally adjusting the gradients respective to each function. A total of 121 combinations of gradients were examined and out of them one optimal set was determined. Predictive performance of the corresponding model were compared to non-optimized, revealing that optimized models are more accurate over non-optimized counterparts by an improvement of more than 30%. This demonstrates that the proposed gradient-optimized teaming for BPNN with a linear function in output layer is an effective means to construct plasma models. The plasma modeled is a hemispherical inductively coupled plasma, which was characterized by a 24 full factorial design. To validate models, another eight experiments were conducted. process variables that were varied in the design include source polver, pressure, position of chuck holder and chroline flow rate. Plasma attributes measured using Langmuir probe are electron density, electron temperature, and plasma potential.

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Functional Recovery Following the Transplantation of Olfactory Ensheathing Cells in Rat Spinal Cord Injury Model

  • Muniswami, Durai Murugan;Tharion, George
    • Asian Spine Journal
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    • 제12권6호
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    • pp.998-1009
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    • 2018
  • Study Design: Olfactory ensheathing cells (OECs) from rat olfactory mucosa were cultured, characterized, and transplanted into a rat model of spinal cord injury (SCI). Purpose: To evaluate different doses of OECs in a rat model of SCI. Overview of Literature: SCI causes permanent functional deficit because the central nervous system lacks the ability to perform spontaneous repair. Cell therapy strategies are being explored globally. The clinical use of human embryonic stem cell is hampered by ethical controversies. Alternatively, OECs are a promising cell source for neurotransplantation. This study aimed to evaluate the efficacy of different doses of allogenic OEC transplantation in a rat model of SCI. Methods: OECs were cultured from the olfactory mucosa of Albino Wistar rats; these cells were characterized using immunohistochemistry and flow cytometry. Rats were divided into five groups (n=6 rats each). In each group, different dosage ($2{\times}10^5$, $5{\times}10^5$, $10{\times}10^5$, and >$10{\times}10^5$) of cultured cells were transplanted into experimentally injured spinal cords of rat models. However, in the SCI group, only DMEM (Dulbecco's modified Eagle's medium) was injected. Rats were followed up upto 8 weeks post-transplantation. The outcome of transplantation was assessed using the Basso, Beattie, Bresnahan (BBB) scale; motor-evoked potential studies; and histological examination. Results: Cultured cells expressed 41% of p75NTR, a marker for OEC, and 35% of anti-fibronectin, a marker for olfactory nerve fibroblast. These cells also expressed $S100{\beta}$ and glial fibrillary acid protein of approximately 75% and 83%, respectively. All the transplanted groups showed promising BBB scores for hind-limb motor recovery compared with the SCI group (p<0.05). A motor-evoked potential study showed increased amplitude in all the treated groups compared with the SCI. Green fluorescent protein-labeled cells survived in the injured cord, suggesting their role in the transplantation-mediated repair. Transplantation of $5{\times}10^5$ cells showed the best motor outcomes among all the doses. Conclusions: OECs demonstrated a therapeutic effect in rat models with the potential for future clinical applications.