• 제목/요약/키워드: Prediction Control

검색결과 2,211건 처리시간 0.03초

재생냉각시스템의 성능예측기법에 관한 실험적 연구 (An Experimental Study on the Performance Prediction Logic for a Regenerative Cooling System)

  • 정세용;이양석
    • 한국군사과학기술학회지
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    • 제12권3호
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    • pp.396-405
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    • 2009
  • The experimental research was conducted to setup a performance prediction logic for the regenerative cooling system on a small scale liquid rocket engine using kerosene and LOX. Total heat flux of the combustion gas side was determined for the flow rate of the coolant, combustion pressure using the calorimeter thrust chamber. Based on the experimental investigation, a performance prediction scheme for the regenerative cooling system is setup in our own way. A performance prediction logic for the regenerative cooling system has been developed by the correction scheme of the combustion gas side. The key parameters determining the temperature limitation of the coolant are the mass flow rate of the coolant and the length of the combustion chamber and the nozzle. And the parameters to control the limitation of the usable wall temperature are the number of channels and wall thickness.

초음속 유도탄 기저항력 예측의 불확실성 (Uncertainties In Base Drag Prediction of A Supersonic Missile)

  • 안효근;홍승규;이복직;안창수
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2004년도 추계 학술대회논문집
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    • pp.47-51
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    • 2004
  • Accurate Prediction of a supersonic missile base drag continues to defy even well-rounded CFD codes. In an effort to address the accuracy and predictability of the base drags, the influence of grid system and competitive turbulence models on the base drag is analyzed. Characteristics of some turbulence models is reviewed through incompressible turbulent flow over a flat plate, and performance for the base drag prediction of several turbulence models such as Baldwin-Lomax(B-L), Spalart-Allmaras(S-A), $\kappa-\epsilon$, $\kappa-\omega$ model is assessed. When compressibility correction is injected into the S-A model, prediction accuracy of the base drag is enhanced. The NSWC wind tunnel test data are utilized for comparison of CFD and semi-empirical codes on the accuracy of base drag predictability: they are about equal, but CFD tends to perform better. It is also found that, as angle of attack of a missile with control (ins increases, even the best CFD analysis tool we have lacks the accuracy needed for the base drag prediction.

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A Study on the Emission Characteristics and Prediction of Volatile Organic Compounds from Floor and Furniture

  • Pang, Seung-Ki;Sohn, Jang-Yeul;Chung, Kwang-Seop
    • International Journal of Air-Conditioning and Refrigeration
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    • 제13권2호
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    • pp.89-98
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    • 2005
  • In this study, indoor VOCs concentration emitted from floor and furniture was measured after the installation of floor and furniture in a real residence. With the measured data, prediction method and predication equations for indoor concentration of each VOCs and BTEX were developed. The following conclusions were drawn from this study. First, according to the predicted results of concentration decrease of BTEX (benzene, toluene, ethylbenzene, m,p,o-xylene) after the installation of floor in a real residence, prediction equation can be expressed using exponential function. Second, in case of floor, more reliable prediction equation can be obtained by using cumulative value of indoor concentration than by using just hourly measured value directly. Indoor concentration of benzene can be expressed as $y=408.52(1­e^{-00031{\times}time})$ with $R^2$ of 0.94 which is significantly high value. Third, toluene showed the highest concentration in case of furniture installation indoors, and it needed the longest time for concentration decrease. However, other substances except toluene showed constant concentration throughout the measurement period. Fourth, in case of furniture installation indoors, prediction equation of toluene concentration decrease is estimated to be $y= 3616.3{\times}e^{(-0.1091{\times}time)}+513.96{\times}e^{(-0.0006{\times}time)}\;with\; R^2$ of 0.95 which is significantly high value.

Prediction model of surface subsidence for salt rock storage based on logistic function

  • Wang, Jun-Bao;Liu, Xin-Rong;Huang, Yao-Xian;Zhang, Xi-Cheng
    • Geomechanics and Engineering
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    • 제9권1호
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    • pp.25-37
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    • 2015
  • To predict the surface subsidence of salt rock storage, a new surface subsidence basin model is proposed based on the Logistic function from the phenomenological perspective. Analysis shows that the subsidence curve on the main section of the model is S-shaped, similar to that of the actual surface subsidence basin; the control parameter of the subsidence curve shape can be changed to allow for flexible adjustment of the curve shape. By using this model in combination with the MMF time function that reflects the single point subsidence-time relationship of the surface, a new dynamic prediction model of full section surface subsidence for salt rock storage is established, and the numerical simulation calculation results are used to verify the availability of the new model. The prediction results agree well with the numerical simulation results, and the model reflects the continued development of surface subsidence basin over time, which is expected to provide some insight into the prediction and visualization research on surface subsidence of salt rock storage.

기상 예보 데이터와 일사 예측 모델식을 활용한 실시간 에너지 수요예측 (Real-time Energy Demand Prediction Method Using Weather Forecasting Data and Solar Model)

  • 곽영훈;천세환;장철용;허정호
    • 설비공학논문집
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    • 제25권6호
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    • pp.310-316
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    • 2013
  • This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.

HILS 시스템을 통한 IPMSM의 철손저항 추정 (Prediction of Iron Loss Resistance by Using HILS System)

  • 정기윤;강래청;이형철
    • 한국자동차공학회논문집
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    • 제23권1호
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    • pp.25-33
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    • 2015
  • This paper presents the d-q axis equivalent circuit model of an interior permanent magnet (IPM) which includes the iron loss resistance. The model is implemented to be able to run in real-time on the FPGA-based HIL simulator. Power electronic devices are removed from the motor control unit (MCU) and a separated controller is interfaced with the real-time simulated motor drive through a set of proper inputs and outputs. The inputs signals of the HIL simulation are the gate driver signals generated from the controller, and the outputs are the winding currents and resolver signals. This paper especially presents iron loss prediction which is introduced by means of comparing the torque calculated from d-q axis currents and the desired torque; and minimizing the torque difference. This prediction method has stable prediction algorithm to reduce torque difference at specific speed and load. Simulation results demonstrate the feasibility and effectiveness of the proposed methods.

Prediction of short-term algal bloom using the M5P model-tree and extreme learning machine

  • Yi, Hye-Suk;Lee, Bomi;Park, Sangyoung;Kwak, Keun-Chang;An, Kwang-Guk
    • Environmental Engineering Research
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    • 제24권3호
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    • pp.404-411
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    • 2019
  • In this study, we designed a data-driven model to predict chlorophyll-a using M5P model tree and extreme learning machine (ELM). The Juksan weir in the Youngsan River has high chlorophyll-a, which is the primary indicator of algal bloom every year. Short-term algal bloom prediction is important for environmental management and ecological assessment. Two models were developed and evaluated for short-term algal bloom prediction. M5P is a classification and regression-analysis-based method, and ELM is a feed-forward neural network with fast learning using the least square estimate for regression. The dataset used in this study includes water temperature, rainfall, solar radiation, total nitrogen, total phosphorus, N/P ratio, and chlorophyll-a, which were collected on a daily basis from January 2013 to December 2016. The M5P model showed that the prediction model after one day had the highest performance power and dropped off rapidly starting with predictions after three days. Comparing the performance power of the ELM model with the M5P model, it was found that the performance power of the 1-7 d chlorophyll-a prediction model was higher. Moreover, in a period of rapidly increasing algal blooms, the ELM model showed higher accuracy than the M5P model.

Prediction of total sediment load: A case study of Wadi Arbaat in eastern Sudan

  • Aldrees, Ali;Bakheit, Abubakr Taha;Assilzadeh, Hamid
    • Smart Structures and Systems
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    • 제26권6호
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    • pp.781-796
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    • 2020
  • Prediction of total sediment load is essential in an extensive range of problems such as the design of the dead volume of dams, design of stable channels, sediment transport in the rivers, calculation of bridge piers degradation, prediction of sand and gravel mining effects on river-bed equilibrium, determination of the environmental impacts and dredging necessities. This paper is aimed to investigate and predict the total sediment load of the Wadi Arbaat in Eastern Sudan. The study was estimated the sediment load by separate total sediment load into bedload and Suspended Load (SL), independently. Although the sediment records are not sufficient to construct the discharge-sediment yield relationship and Sediment Rating Curve (SRC), the total sediment loads were predicted based on the discharge and Suspended Sediment Concentration (SSC). The turbidity data NTU in water quality has been used for prediction of the SSC in the estimation of suspended Sediment Yield (SY) transport of Wadi Arbaat. The sediment curves can be used for the estimation of the suspended SYs from the watershed area. The amount of information available for Khor Arbaat case study on sediment is poor data. However, the total sediment load is essential for the optimal control of the sediment transport on Khor Arbaat sediment and the protection of the dams on the upper gate area. The results show that the proposed model is found to be considered adequate to predict the total sediment load.

L샘츨의 제어늦음을 갖는 다지탈 최적 선형 Regulator의 Robust 안전성 (On the Robust Stability of the Optimal Digital Linear Regulator Having L Sample Controlling Delays.)

  • 이동철;정형환
    • 대한전기학회논문지
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    • 제36권6호
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    • pp.437-443
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    • 1987
  • Due to the recent development of microprocessor, the digital control is now in use for the practical structure of the control systems, but it leaves the problem of controlling delays caused by computation time when it is applied to the realization problems, such as application method of the control law and controlling effect of continuous control, etc. This paper deals with robust stability of the digital regulator which compensates for the controlling delays by applying prediction values of state.

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Closed-loop predictive control using periodic gain

  • Lee, Young-Il
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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    • pp.173-176
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    • 1994
  • In this paper a closed-form predictive control which takes the intervalwise receding horizon strategy is presented and its stability properties are investigated. A slate-space form output predictor is derived which is composed of the one-step ahead optimal output prediction, input and output data of the system. A set of feedback gains are obtained using the dynamic programming algorithm so that they minimize a multi-stage quadratic cost function and they are used periodically.

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