• 제목/요약/키워드: ensemble mean

검색결과 200건 처리시간 0.118초

Sea Surface statistical Properties as Measured by Laser Beam Reflections

  • Lee, Kwi-Joo;Park, Young-Sik;Voliak, K.I.
    • International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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    • 제4권1호
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    • pp.10-21
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    • 2001
  • A new method of laser remote sensing is proposed, based on sensing the sea surface by a narrow laser beam (2-3cm) and analyzing statistically specular reflections. Construction of the angular dependency of the average density of specks versus the aircraft flight horizontal azimuth allows calculation of both intensity and azimuthal properties of the sea surface spectrum. The paper contains the experimental setup and technique, the field measurement data taken onboard an aircraft and the examples of calculated main statistical parameters of sea waves. Their energy-carrying component velocity is found by the mean velocity of an ensemble of specular points at the random sea surface. The surface wave nonlinearity is shown to affect substantially the statistical characteristics measured: mean numbers of specular areas with th given elevation and given slope, arranged along the line of crossing the sea surface by the scanning laser beam. Experimental measurement of a variance in the number of these areas yields a principal possibility to calculate the correlation function of the sea surface without its preliminary modeling.

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PIV 기법을 이용한 모형철도터널 직관덕트에서 유동 분포 계측 및 수치해석 결과와의 비교분석 (MEASUREMENT OF FLOW DISTRIBUTION IN A STRAIGHT DUCT OF RAILWAY TUNNEL MOCK-UP USING PIV AND COMPARISON WITH NUMERICAL SIMULATION)

  • 장용준;정우성;박일순
    • 한국전산유체공학회지
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    • 제15권3호
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    • pp.39-45
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    • 2010
  • The turbulent flows in a tunnel mock-up($10L{\times}0.5W{\times}0.25H$ m3 : scale reduction 1/20) with rectangular cross section were investigated. The instantaneous velocity fields of Re = 49,029, 89,571 were measured by the 2-D PIV system which is consisted of double pulsed Nd:Yag laser and the tracer particles in the straight-duct mock-up where the flows were fully developed. The mean velocity profiles were taken from the ensemble averages of 1,000 instantaneous velocity fields. Simultaneously, numerical simulations(RANS) were performed to compare with experimental data using STREAM code. Non-linear eddy viscosity model (NLEVM : Abe-Jang-Leschziner Eddy Viscosity Model) was employed to resolve the turbulent flows in the duct. The calculated mean velocity profiles were well compared with PIV results. In the log-law profiles, the experimental data were in good agreement with numerical simulations all the way to the wake region except the viscous sub-layer (near wall region).

Effects of Individual Sweating Response on Changes in Skin Blood Flow and Temperature Induced by Heat of Sorption Wearing Cotton Ensemble

  • Tanaka, Kaori;Hirata, Kozo
    • 한국의류산업학회지
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    • 제2권5호
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    • pp.398-404
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    • 2000
  • We examined the effect of individual sweating responses on thermoregulatory responses induced by heat of sorption, immediately after the onset of sweating. The present study consists of two experiments. In experiment 1, made of 100% cotton (C) and 100% polyester (P) clothing were exposed in the chamber at ambient temperature (Ta) of $27.2^{\circ}C$ and relative humidity (rh) raised from 50% to 95% at five different increase rates of environmental vapor pressure (VP). The increase rate of clothing surface temperature (Tcs), peak Tcs and peak time showed significant correlation with the increase rate of environmental VP in C-clothing (p<0.05). In experiment 2, seven female subjects were studied during leg water immersion ($35-41^{\circ}C$) for 70min in Ta of 27.2 and 50%rh. There were significant positive correlations in the increase rate of clothing microclimate VP vs. changes in Tcs, skin blood flow, mean skin temperature and mean body temperature (p<0.05). The present results showed that individual clothing microclimate VP had significant effects on thermoregulatory responses induced by heat of sorption wearing C ensembles.

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회전하는 선박 프로펠러 전방 유입류에 대한 PIV 속도장 해석 (PIV Velocity Field Analysis of Inflow ahead of a Rotating Marine Propeller)

  • 이상준;백부근
    • 대한조선학회논문집
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    • 제41권4호
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    • pp.30-37
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    • 2004
  • Flow characteristics of the inflow ahead of a rotating propeller attached to a container ship model were investigated using a two-frame PIV (Particle Image Velocimetry) technique. Ensemble-averaged mean velocity fields were measured at four different blade phases. The mean velocity fields show the acceleration of inflow due to the rotating propeller and the velocity deficit in the near-wake region. The axial velocity distribution of inflow in the upper plane of propeller is quite different from that in the lower plane due to the thick hull boundary layer. The propeller inflow also shows asymmetric axial velocity distribution in the port and starboard side. As the inflow moves toward the propeller, the effect of phase angle variation of propeller blade on the inflow becomes dominant. In the upper plane above the propeller axis the inflow has very low axial velocity and large turbulent kinetic energy, compared with the lower plane. The boundary layer developed along the bottom surface of stern hull forms a strong shear layer affecting vortex structure of the propeller near-wake.

IN-CYLINDER FLOW ANALYSIS USING WAVELET ANALYSIS

  • Park, D.;Sullivan, P.E.;Wallace, J.S.
    • International Journal of Automotive Technology
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    • 제7권3호
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    • pp.289-294
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    • 2006
  • Better fundamental understanding of the interactions between the in-cylinder flows and combustion process is an important requirement for further improvement in the fuel economy and emissions of internal combustion(IC) engines. Flow near a spark plug at the time of ignition plays an important role for early flame kernel development(EFKD). Velocity data measurements in this study were made with a two-component laser Doppler velocimetry(LDV) near a spark plug in a single cylinder optical spark ignition(SI) engine with a heart-shaped combustion chamber. LDV velocity data were collected on an individual cycle basis under wide-open motored conditions with an engine speed of 1,000rpm. This study examines and compares the flow fields as interpreted through ensemble, cyclic and discrete wavelet transformation(DWT) analysis. The energy distributions in the non-stationary engine flows are also investigated over crank angle phase and frequency through continuous wavelet transformation(CWT) for a position near a spark plug. Wavelet analysis is appropriate for analyzing the flow fields in engines because it gives information about the transient events in a time and frequency plane. The results of CWT analysis are provided and compared with the mean flows of DWT first decomposition level for all cycles at a position. Low frequency high energy found with CWT corresponds well with the peak locations of the mean velocity. The high frequency flows caused by the intake jet gradually decay as the piston approaches the bottom dead center(BDC).

Machine Learning Methodology for Management of Shipbuilding Master Data

  • Jeong, Ju Hyeon;Woo, Jong Hun;Park, JungGoo
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제12권1호
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    • pp.428-439
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    • 2020
  • The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

전지구 해양 재분석 자료 비교 분석 (Intercomparison of the Global Ocean Reanalysis Data)

  • 장유순
    • 한국해양학회지:바다
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    • 제20권2호
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    • pp.102-118
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    • 2015
  • 본 연구에서는 국제 공동 해양 재분석 자료 비교 프로젝트 결과를 요약하였다. 다양한 재분석 자료 생산 시스템의 종류 및 특성을 소개하였으며, 대표적인 8가지 해양 변수(열용량, 열염분 높이, 해수면 높이, 표층 열속, 혼합층 깊이, 아표층염분, $20^{\circ}C$ 등온선 깊이, 해빙)에 대한 전지구 해양 자료 동화 모델 성능을 비교 분석하였다. 일반적으로 단일 재분석 자료 결과보다 앙상블 평균 값이 비교적 높은 성능을 나타내었으나, 검증 변수와 해역에 따라 서로 다른 특징을 보였다. 해양 변수 중에는 염분 및 해빙 변동이 모델간 가장 큰 편차를 보였다. 심층 해역, 남극해, 서안 경계 해역을 포함한 연안역에서는 공통적으로 객관 분석장과 동화 모델간의 편차가 크게 나타났다. 국내에서도 독립적으로 운영되고 있는 해양 자료 동화 모델간의 비교 분석 프로그램이 추진되어, 향후 관련된 국제 공동 연구에 활발히 참여할 수 있는 기회가 확대되기를 기대한다.

낙동강유역 하천유량 예측모형 구축 (Streamflow Forecast Model on Nakdong River Basin)

  • 이병주;배덕효
    • 한국수자원학회논문집
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    • 제44권11호
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    • pp.853-861
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    • 2011
  • 본 연구는 연속형 강우-유출모형과 관측유량 자료동화기법으로 앙상블 칼만필터 기법을 연계한 SURF 모형을 낙동강유역에 적용하여 하천유량예측의 적용성을 평가하고자 하는데 그 목적이 있다. 낙동강유역을 43개 소유역으로 구분하고 2006년과 2007년의 홍수기간 동안 12개 평가지점에 대해 유출모의를 수행하였다. 관측유량 자료동화 효과로 인해 예측유량의 정확도가 향상되며 1~5시간의 예측선행시간별 유효성지수를 분석한 결과 자료동화로 인해 46.2~30.1%의 모의유량의 정확도가 개선되는 것으로 나타났다. 또한 관측강우의 50%를 적용하여 자료동화 전 후의 모의 첨두유량에 대한 평균정상절대오차를 비교하였으며 자료동화로 인해 40% 이상의 정확도가 향상됨을 확인하였다. 이상의 결과로부터 SURF 모형은 낙동강유역의 실시간 하천유량예측에 활용될 수 있을 것으로 판단된다.

CMIP5 MME와 Best 모델의 비교를 통해 살펴본 미래전망: I. 동아시아 기온과 강수의 단기 및 장기 미래전망 (Future Change Using the CMIP5 MME and Best Models: I. Near and Long Term Future Change of Temperature and Precipitation over East Asia)

  • 문혜진;김병희;오효은;이준이;하경자
    • 대기
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    • 제24권3호
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    • pp.403-417
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    • 2014
  • Future changes in seasonal mean temperature and precipitation over East Asia under anthropogenic global warming are investigated by comparing the historical run for 1979~2005 and the Representative Concentration Pathway (RCP) 4.5 run for 2006~2100 with 20 coupled models which participated in the phase five of Coupled Model Inter-comparison Project (CMIP5). Although an increase in future temperature over the East Asian monsoon region has been commonly accepted, the prediction of future precipitation under global warming still has considerable uncertainties with a large inter-model spread. Thus, we select best five models, based on the evaluation of models' performance in present climate for boreal summer and winter seasons, to reduce uncertainties in future projection. Overall, the CMIP5 models better simulate climatological temperature and precipitation over East Asia than the phase 3 of CMIP and the five best models' multi-model ensemble (B5MME) has better performance than all 20 models' multi-model ensemble (MME). Under anthropogenic global warming, significant increases are expected in both temperature and land-ocean thermal contrast over the entire East Asia region during both seasons for near and long term future. The contrast of future precipitation in winter between land and ocean will decrease over East Asia whereas that in summer particularly over the Korean Peninsula, associated with the Changma, will increase. Taking into account model validation and uncertainty estimation, this study has made an effort on providing a more reliable range of future change for temperature and precipitation particularly over the Korean Peninsula than previous studies.

가중치 기반 Bag-of-Feature와 앙상블 결정 트리를 이용한 정지 영상에서의 인간 행동 인식 (Human Action Recognition in Still Image Using Weighted Bag-of-Features and Ensemble Decision Trees)

  • 홍준혁;고병철;남재열
    • 한국통신학회논문지
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    • 제38A권1호
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    • pp.1-9
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    • 2013
  • 본 논문에서는 CS-LBP (Center-Symmetric Local Binary Pattern) 특징과 공간 피라미드를 이용한 BoF (Bag of Features)를 생성하고 이를 랜덤 포레스트(Random Forest) 분류기에 적용하여 인간의 행동을 인식하는 알고리즘을 제안한다. BoF를 생성하기 위해 영상을 균일한 패치로 나누고, 각 패치 마다 CS-LBP 특징을 추출한다. 행동 분류 성능을 향상시키기 위해 패치들마다 추출한 특징벡터들에 대해 K-mean 클러스터링을 적용하여 코드 북을 생성한다. 본 논문에서는 영상의 지역적인 특성을 고려하기 위해 공간 피라미드 방법을 적용하고 각 공간 레벨에서 추출된 BoF에 대해 가중치를 적용하여 최종적으로 하나의 특징 벡터로 결합한다. 행동 분류를 위해 결정트리의 앙상블로 이루어진 랜덤 포레스트는 학습 단계에서 각 행동 클래스를 위한 분류 모델을 만든다. 가중 BoF가 적용된 랜덤 포레스트는 다양한 인간 행동 영상을 포함하고 있는 Standford Actions 40 데이터를 성공적으로 분류하였다. 또한 기존 방법에 비해 분류 성능이 유사하거나 우수하며, 한 장의 영상에 대해 빠른 인식속도를 보였다.