• Title/Summary/Keyword: Statistical energy analysis

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Statistical model for forecasting uranium prices to estimate the nuclear fuel cycle cost

  • Kim, Sungki;Ko, Wonil;Nam, Hyoon;Kim, Chulmin;Chung, Yanghon;Bang, Sungsig
    • Nuclear Engineering and Technology
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    • v.49 no.5
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    • pp.1063-1070
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    • 2017
  • This paper presents a method for forecasting future uranium prices that is used as input data to calculate the uranium cost, which is a rational key cost driver of the nuclear fuel cycle cost. In other words, the statistical autoregressive integrated moving average (ARIMA) model and existing engineering cost estimation method, the so-called escalation rate model, were subjected to a comparative analysis. When the uranium price was forecasted in 2015, the margin of error of the ARIMA model forecasting was calculated and found to be 5.4%, whereas the escalation rate model was found to have a margin of error of 7.32%. Thus, it was verified that the ARIMA model is more suitable than the escalation rate model at decreasing uncertainty in nuclear fuel cycle cost calculation.

Selecting of the Energy Performance Diagnosis Items through the Sensitivity Analysis of Existing Buildings (민감도 분석을 통한 기존건축물의 에너지성능 진단항목 선별)

  • Kong, Dong-Seok;Chang, Yong-Sung;Huh, Jung-Ho
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.27 no.7
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    • pp.354-361
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    • 2015
  • The building energy audit is an important process when collecting basic information for improving the energy performance of existing buildings. Audit parameters should be associated with the energy performance of the building. Such audit parameters will vary according to an individual building's characteristics and energy consumption patterns, but most building energy audits are performed in the same way. The sensitivity analysis (SA) is a statistical method to quantify the correlation between inputs and outputs that can determine which input is influential to which output. Therefore, an SA can identify influential parameters when applied to building energy analysis. In this paper, we adopted the Morris method to identify building energy audit parameters and performed a Monte Carlo simulation for uncertainty analysis. As a result, this method was able to identify an influential parameter for building energy audits and reduce uncertainty in energy consumption in buildings.

Determination of Shock Response Spectrum Using FRF of Statistical Energy Analysis Method (통계적 에너지 분석법의 FRF를 이용한 충격 응답 스텍트럼(SRS)의 결정)

  • 구성완;황철규;김인성
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.14 no.7
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    • pp.551-560
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    • 2004
  • A method how to determine the shock response spectrum from the FRF of the statistical energy analysis( SEA ) is presented here. The system of 3 different Plates connected by bolt joints is selected simulating missile structural sections Joined together. First, the SEA model was rendered by SEA parameters which were determined from experimental SEA method. Then, the mobility power was input to the SEA model and we can verify the validity of the model in the medium to high frequency range checking the reproduction of output average velocity. And, the shock induced shock response spectrum(SRS) was obtained using SEA FRF and arbitrarily chosen experimental FRF. We have compared the thus obtained SRS with actually measured SRS and they were relatively in good agreement. In this paper, we used the measured SEA FRF and therefore we have got the SRS well agreed with actually measured SHS even in the low frequency range. If the SEA FRF of well verified SEA model is used, the good result will come out in SEA effective frequency range which is more important at SRS.

A simplified normalized cumulative hysteretic energy spectrum

  • Sun, Guohua;Gu, Qiang;Fang, Youzhen
    • Earthquakes and Structures
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    • v.12 no.2
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    • pp.177-189
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    • 2017
  • For energy-based seismic design, a simplified normalized cumulative hysteretic energy spectrum proposed for obtaining hysteretic energy as energy demand is the main objective in this paper. The dimensionless parameter, ${\beta}_{Eh}$, is presented to express hysteretic energy indirectly. The ${\beta}_{Eh}$ spectrum is constructed directly through subtracting the hysteretic energy of single degree-of-freedom (SDOF) system energy equation. The simplified ${\beta}_{Eh}$ spectral formulation as well as pseudo-acceleration spectrum of modern seismic provisions is developed based on the regression analysis of the large number of seismic responses of SDOF system subjected to earthquake excitations, which considers the influence of earthquake event, soil type, damping ratio, and ductility factor. The relationship between PGV and PGA is established according to the statistical analysis relied on a total of 422 ground motion records. The combination of ${\beta}_{Eh}$ spectrum and PGV/PGA equation allows determining the cumulative hysteretic energy as a main aseismic design indicator.

Statistical Analysis on Residuals from No-Fault Reference Models of a Residential Heat Pump System in Normal Cooling Operation (가정용 열펌프 시스템의 정상냉방 운전조건에서 기준모델에 의한 잔차의 통계적 분석)

  • Kim, Min-Sung;Yoon, Seok-Ho;Baik, Young-Jin
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.35 no.12
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    • pp.1351-1358
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    • 2011
  • To approximate the threshold of the fault detection and diagnosis (FDD) system, validation of the measurements is mandatory. Naturally, the system shows uncertainties due to measuring sensors - mostly thermocouples or RTDs - and due to repeatability. The uncertainty of a thermocouple comes from natural variation or a drift of the thermocouple measurement. Considering the natural variation behaves like zero-mean white noise, its natural variation can be characterized closely by the steady-state standard deviation. However, residuals between measurements and no-fault references in FDD systems show a statistical distribution with various uncertainties. In this paper, steady-state variations of measurement residuals were investigated by utilizing built-in temperature sensors in a heat pump for the model development and the final application.

Establishment of The Wind Resource Database of Jejudo by Meteo-Statistical Analysis (기상통계분석에 의한 제주도 풍력자원 데이터베이스 구축)

  • Kim, Hyun-Goo;Jang, Mun-Seok;Kyong, Nam-Ho
    • 한국신재생에너지학회:학술대회논문집
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    • 2006.06a
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    • pp.296-297
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    • 2006
  • In order to support wind power development, the wind resource database of Jejudo has been established by meteo-statistical analysis on meteorological-mast measurements of KIER. Analysis processes contain correlation of monthly wind speed and power-law exponent among neighboring sites, Measure-Correlated-Predict for long-term correlation, classification of exposure category using satellite image and so forth. It is found that the monthly variations of wind speed and power-law exponent depend on seasonal winds and characterize wind system of Jejudo.

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A Review of the Progress with Statistical Models of Passive Component Reliability

  • Lydell, Bengt O.Y.
    • Nuclear Engineering and Technology
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    • v.49 no.2
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    • pp.349-359
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    • 2017
  • During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records) and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models.

Analysis of Vehicle Noise/Vibration Characteristics Using SEA (SEA를 이용한 승용차 소음/진동 특성 해석)

  • 김태환;채장범;임진수;고병식;안지훈
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1998.04a
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    • pp.75-80
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    • 1998
  • Statistical Energy Analysis(SEA) has been considered as a possible method for predicting responses of complex structures, especially at higher frequencies. In this paper, an SEA model of vehicle was built using 138 energy storing subsystems connected together using 1019 junctions. SEAM software program was used to build and calculate the model. To demonstrate the accuracy of the SEA model, predicted response levels were compared with measured levels. The source input levels were measured at the engine mounting parts. For the vibration levels, the agreement between the calculation results and the experimental ones was found to be good. The energy flow between connected subsystems can be presented, because the analysis method is based on the estimation of the power flow between subsystems. This paper also identifies some dominant energy flow paths from sources. It is finally presented that the SEA model can optimize the design parameters of vehicles using model parameters and energy flow paths.

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The Characteristic of Enterprise Groups and the Demand-Supply Relation Analysis in the Korea Solar Energy Industry (국내 태양광산업에서의 기업집단별 특성과 기업간 수요공급관계의 이해)

  • Park, Chang-Kirl
    • Journal of the Korean Solar Energy Society
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    • v.34 no.4
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    • pp.83-90
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    • 2014
  • South Korea's solar energy industry has been made vertical integration and specialization as part of the restructuring in the downturn of the world economy and the oversupply situation of raw materials. This study is to understand the characteristics of the solar energy industry, using data to systematic approach. In this study, it was defined the major business of firms as 22 business types and classified into 5 enterprise groups as technology and business strategy. After that, It was deduced features of Enterprise group by the statistical analysis and looked to draw a map of the industrial structure by social network analysis using the information on companies' demand and supply.

Prediction of Vibrational Responses of Automotive Door System Using Energy Flow Analysis in Medium-to-high Frequencies (에너지흐름해석법을 이용한 중고주파수 대역 자동차 도어 진동예측)

  • Park, Young-Ho;Hong, Suk-Yoon;Kil, Hyun-Gwon
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.20 no.11
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    • pp.1097-1102
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    • 2010
  • In this paper, the energy flow analysis(EFA) of the body-in-white door of a real automotive was performed using the energy flow finite element method(EFFEM) to effectively predict the vibrational responses of built-up structures in the medium to high frequency range. To increase the validity of EFA results, the structural hysteresis damping loss factor was measured by the experiment using the concept of statistical energy analysis(SEA). As the excitation frequency increases, the predicted results simulated with EFFEM generally agree with the experimental results.