• 제목/요약/키워드: Rate Sensitive Model

검색결과 219건 처리시간 0.029초

하천 수질모형 시스템의 안정성 및 민감도 분석 (Stability and Sensitivity Analysis of Stream Water Quality System Model)

  • 심순보;한재석
    • 물과 미래
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    • 제21권4호
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    • pp.407-414
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    • 1988
  • 본 논문의 목적은 하천 수질모형 시스템이 안정성 및 해감도이론에 의해 이론적으로 어떻게 분석되며, 그 결과 모형화를 위한 수치분석의 신뢰성과 수질 매개변수의 변화에 따른 모형의 민감성을 입증하는 것이다. 무한 Fourier 급수를 이용하여 전개한 안정성이론은 유한차분법을 사용한 모형의 수치해법을 분석하는데 있고, 1부 선형상태벡터식으로 표현되는 민감도이론은 BOD 부하, 유량, 온도와 같은 수질배개변수의 변동효과를 이론적으로 분석하는데 사용되었고, 그 연구 결과는 하천 수질모형시스템의 신뢰성을 파악할 수 있음이 입증되었다.

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불포화대에서 오염물질 이동현상에 대한 다중구획 모델의 단순 근사방법 (Simplified Approximation Method of the Multi-Compartments Model on the Migration of Contaminant through Unsaturated Zone)

  • 정재학
    • 방사성폐기물학회지
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    • 제5권1호
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    • pp.29-37
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    • 2007
  • 특정 구획으로 유입된 오염물질이 해당 구획 내부에 순간적으로 균일하게 분포한다는 구획모델에 대한 기본가정의 한계로 인해, 전통적인 단일구획모델로는 불포화대에서 오염물질의 이동현상을 적절하게 예측할 수 없다. 한편 물리적으로 동일한 불포화대를 여러 개의 구획으로 구분한 다중구획모델링 기법은 실제 불포화대에서의 오염물질 이동 지연효과를 적절하게 설명할 수 있으나, 지금까지 일반적인 해석해가 보고된 바 없으며 고려하는 구획의 개수가 증가할수록 모델링에 많은 시간이 소요되는 등의 한계가 있다. 이러한 문제점을 해결하기 위하여, 이류가 지배적인 조건 하에서 불포화대의 오염물질 이동현상에 대한 다중구획모델을 수립하고 이를 해석적인 방법으로 계산할 수 있는 일반해를 유도한 후, 다중구획모델을 단일구획모델로 근사할 수 있는 수학적 제약조건을 도출하였다. 단순화된 근사방법론의 유효성은 가상적인 조건 하에서 간단한 수치해석적 방법을 통해 검증하였다. 물리적으로 동일한 특성을 갖는 불포화대를 단일 구획으로 가정할 경우, 불포화대로부터 포화대로 유입되는 오염물질의 전이율은 상수가 아닌 시간 종속적인 명목전이율로 표현할 수 있음을 증명하였다. 또한 명목전이율은 불포화대 구획간 전이율에 민감하며 오염층으로부터의 전이율에 대한 민감도는 미미한 것으로 나타났다. 이 연구에서 개발된 단순화된 근사방법론은 많은 시간이 요구되는 다중구획 모델링을 통하지 않고 불포화대 오염물질 이동현상을 신속하고 합리적으로 예측하기 위한 목적으로 활용될 수 있을 것으로 기대된다.

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혈중 목표 농도 자동 조절기(TCI) 개발 PART2: 시스템 구현 및 평가 (Development of Target-Controlled Infusion system in Plasma Concentration. PART2: Design and Evaluation)

  • 안재목
    • 대한의용생체공학회:의공학회지
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    • 제24권1호
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    • pp.45-53
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    • 2003
  • Based on the 4-compartmental pharmacokinetic model developed in PART1, target-controlled infusion(TCI) pump system was designed and evaluated. The TCI system consists of digital board including microcontroller and digital signal process(DSP), analog board, motor-driven actuator, user friendly interface, power management and controller. It provides two modes according to the drugs: plasma target concentration and effect target concentration. Anaesthetist controls the depth of anaesthesia for patients by adjusting the required concentration to maintain both plasma and effect site in drug concentration. The data estimated in DSP include infusion rate, initial load dose, and rotation number of motor encoder. During TCI operation, plasma concentration. effect site concentration, awaken concentration, context-sensitive decrement time and system error information are displayed in real time. Li-ion battery guarantees above 2 hours without power line failure. For high reliability of the system, two microprocessors were used to perform independent functions for both pharmacokinetic algorithm and motor control strategy.

강건 실험계획법을 이용한 열화자료의 분석 (Analysis of Degradation Data Using Robust Experimental Design)

  • 서순근;하천수
    • 품질경영학회지
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    • 제32권1호
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    • pp.113-129
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    • 2004
  • The reliability of the product can be improved by making the product less sensitive to noises. Especially, it Is important to make products robust against various noise factors encountered in production and field environments. In this paper, the phenomenon of degradation assumes a simple random coefficient degradation model to present analysis procedures of degradation data for robust experimental design. To alleviate weak points of previous studies, such as Taguchi's, Wasserman's, and pseudo failure time methods, novel techniques for analysis of degradation data using the cross array that regards amount of degradation as a dynamic characteristic for time are proposed. Analysis approach for degradation data using robust experimental design are classified by assumptions on parametric or nonparametric degradation rate(or slope). Also, a simulation study demonstrates the superiority of proposed methods over some previous works.

확률론적 지진재해도 분석을 위한 지진원 모델의 민감도 분석 (Sensitivity Analysis of Seismic Source Models for Probabilistic Seismic Hazard Analysis)

  • 김연중;전정윤;김태균
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 2003년도 추계 학술발표회논문집
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    • pp.36-45
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    • 2003
  • Sensitivity analyses for several seismic source models were studied. For the area sources, the hazard is steeply decreasing with the source-to-site distance. Hazard is decreasing when the area of the source is increasing with fixed annual rate. For the fault sources, the fault length, distance from a site and dip angle of near fault show very sensitive effect to seismic hazard. But the various magnitude-rupture length relationships show effect to seismic hazard slightly. For the fault source with small magnitude, the exponential model is preferred rather than the characteristic model to the magnitude-recurrence law.

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Effectiveness of Sensitivity Analysis for Parameter Selection in CLIMEX Modeling of Metcalfa pruinosa Distribution

  • Byeon, Dae-hyeon;Jung, Sunghoon;Mo, Changyeun;Lee, Wang-Hee
    • Journal of Biosystems Engineering
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    • 제43권4호
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    • pp.410-419
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    • 2018
  • Purpose: CLIMEX, a species distribution modeling tool, includes various types of parameters representing climatic conditions; the estimation of these parameters directly determines the model accuracy. In this study, we investigated the sensitivity of parameters for the climatic suitability calculated by CLIMEX for Metcalfa pruinosa in South Korea. Methods: We first changed 12 parameters and identified the three significant parameters that considerably affected the CLIMEX simulation response. Results: The result indicated that the simulation was highly sensitive to changes in lower optimal temperatures, lower soil moisture thresholds, and cold stress accumulation rate based on the sensitivity index, suggesting that these were the fundamental parameters to be used for fitting the simulation into the actual distribution. Conclusion: Sensitivity analysis is effective for estimating parameter values, and selecting the most important parameters for improving model accuracy.

Life cycle reliability analyses of deteriorated RC Bridge under corrosion effects

  • Mehmet Fatih Yilmaz
    • Earthquakes and Structures
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    • 제25권1호
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    • pp.69-78
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    • 2023
  • Life-cycle performance analysis of a reinforced concrete box section bridge was generated. Moreover, Monte Carlo simulation with important sampling (IS) was used to simulate the bridge material and load uncertainties. The bridge deterioration model was generated with the basic probabilistic principles and updated according to the measurement data. A genetic algorithm (GA) with the response surface model (RSM) was used to determine the deterioration rate. The importance of health monitoring systems to sustain the bridge to give services economically and reliably and the advantages of fiber-optic sensors for SHM applications were discussed in detail. This study showed that the most effective loss of strength in reinforced concrete box section bridges is corrosion of the reinforcements. Due to reinforcement corrosion, the use of the bridge, which was examined, could not meet the desired strength performance in 25 years, and the need for reinforcement. In addition, it has been determined that long-term health monitoring systems are an essential approach for bridges to provide safe and economical service. Moreover the use of fiber optic sensors has many advantages because of the ability of the sensors to be resistant to environmental conditions and to make sensitive measurements.

가중계수법을 이용한 5회선 초음파 유량계의 유속적분방법의 불확도 평가 (Uncertainty Evaluation of Velocity Integration Method for 5-Chord Ultrasonic Flow Meter Using Weighting Factor Method)

  • 이호준;이권희;노석홍;황상윤;노영아
    • 유체기계공업학회:학술대회논문집
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    • 유체기계공업학회 2005년도 연구개발 발표회 논문집
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    • pp.287-294
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    • 2005
  • Flow rate measurement uncertainties of the ultrasonic flow meter are generally influenced by many different factors, such as Reynolds number, flow distortion, turbulence intensity, wall surface roughness, velocity integration method along the acoustic paths, and transducer installation method, etc. Of these influencing factors, one of the most important uncertainties comes from the velocity integration method. In the present study, a optimization weighting factor method for 5-chord, which is given by a function of the chord locations of acoustic paths, is employed to obtain the mean velocity in the flow through a pipe. The power law profile is assumed to model the axi-symmetric pipe flow and its results are compared with the present weighting factor concept. For an asymmetric pipe flow, the Salami flow model is applied to obtain the velocity profiles. These theoretical methods are also compared with the previous Gaussian, Chebyshev, and Tailor methods. The results obtained show that for the fully developed turbulent pipe flows with surface roughness effects, the present weighting factor method is much less sensitive than Chebyshev and Tailor methods, leading to a better reliability in flow rate measurement using the ultrasonic flow meters.

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반응로 형상에 따른 주기적으로 배열된 패턴위의 GaN 성장 특성 (Characteristic of GaN Growth on the Periodically Patterned Substrate for Several Reactor Configurations)

  • 강성주;김진택;박복춘;이철로;백병준
    • 대한기계학회논문집B
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    • 제31권3호
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    • pp.225-233
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    • 2007
  • The growth of GaN on the patterned substances has proven favorable to achieve thick, crack-free GaN layers. In this paper, numerical modeling of transport and reaction of species is performed to estimate the growth rate of GaN from tile reaction of TMG(trimethly-gallium) and ammonia. GaN growth rate was estimated through the model analysis including the effect of species velocity, thermal convection and chemical reaction, and thermal condition for the uniform deposition was to be presented. The effect of shape and construction of microscopic pattern was also investigated using a simulator to perform surface analysis, and a review was done on the quantitative thickness and shape in making GaN layer on the pattern. Quantitative analysis was especially performed about the shape of reactor geometry, periodicity of pattern and flow conditions which decisively affect the quality of crystal growth. It was found that the conformal deposition could be obtained with the inclination of trench ${\Theta}>125^{\circ}$. The aspect ratio was sensitive to the void formation inside trench and the void located deep in trench with increased aspect ratio.

Prediction Model of Real Estate ROI with the LSTM Model based on AI and Bigdata

  • Lee, Jeong-hyun;Kim, Hoo-bin;Shim, Gyo-eon
    • International journal of advanced smart convergence
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    • 제11권1호
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    • pp.19-27
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    • 2022
  • Across the world, 'housing' comprises a significant portion of wealth and assets. For this reason, fluctuations in real estate prices are highly sensitive issues to individual households. In Korea, housing prices have steadily increased over the years, and thus many Koreans view the real estate market as an effective channel for their investments. However, if one purchases a real estate property for the purpose of investing, then there are several risks involved when prices begin to fluctuate. The purpose of this study is to design a real estate price 'return rate' prediction model to help mitigate the risks involved with real estate investments and promote reasonable real estate purchases. Various approaches are explored to develop a model capable of predicting real estate prices based on an understanding of the immovability of the real estate market. This study employs the LSTM method, which is based on artificial intelligence and deep learning, to predict real estate prices and validate the model. LSTM networks are based on recurrent neural networks (RNN) but add cell states (which act as a type of conveyer belt) to the hidden states. LSTM networks are able to obtain cell states and hidden states in a recursive manner. Data on the actual trading prices of apartments in autonomous districts between January 2006 and December 2019 are collected from the Actual Trading Price Disclosure System of the Ministry of Land, Infrastructure and Transport (MOLIT). Additionally, basic data on apartments and commercial buildings are collected from the Public Data Portal and Seoul Metropolitan Government's data portal. The collected actual trading price data are scaled to monthly average trading amounts, and each data entry is pre-processed according to address to produce 168 data entries. An LSTM model for return rate prediction is prepared based on a time series dataset where the training period is set as April 2015~August 2017 (29 months), the validation period is set as September 2017~September 2018 (13 months), and the test period is set as December 2018~December 2019 (13 months). The results of the return rate prediction study are as follows. First, the model achieved a prediction similarity level of almost 76%. After collecting time series data and preparing the final prediction model, it was confirmed that 76% of models could be achieved. All in all, the results demonstrate the reliability of the LSTM-based model for return rate prediction.