• Wind and Structures
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• 제6권2호
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• pp.107-126
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• 2003

This paper describes a simple and practical approach through the application of Linear Stochastic Estimation (LSE) to reconstruct wind-induced pressure time series from the covariance matrix for structural load analyses on a low building roof. The main application of this work would be the reduction of the data storage requirements for the NIST aerodynamic database. The approach is based on the assumption that a random pressure field can be estimated as a linear combination of some other known pressure time series by truncating nonlinear terms of a Taylor series expansion. Covariances between pressure time series to be simulated and reference time series are used to calculate the estimation coefficients. The performance using different LSE schemes with selected reference time series is demonstrated by the reconstruction of structural load time series in a corner bay for three typical wind directions. It is shown that LSE can simulate structural load time series accurately, given a handful of reference pressure taps (or even a single tap). The performance of LSE depends on the choice of the reference time series, which should be determined by considering the balance between the accuracy, data-storage requirements and the complexity of the approach. The approach should only be used for the determination of structural loads, since individual reconstructed pressure time series (for local load analyses) will have larger errors associated with them.

• Wind and Structures
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• 제7권6호
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• pp.373-392
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• 2004

This paper presents a methodology for spatial extrapolation of wind-induced pressure time series from a corner bay to roof locations on a low building away from the corner through the application of proper orthogonal decomposition (POD). The approach is based on the concept that pressure time series in the far field can be approximated as a linear combination of a series of modes and principal coordinates, where the modes are extracted from the full roof pressure field of an aerodynamically similar building and the principal coordinates are calculated from data at the leading corner bay only. The reliability of the extrapolation for uplift time series in nine bays for a cornering wind direction was examined. It is shown that POD can extrapolate reasonably accurately to bays near the leading corner, given the first three modes, but the extrapolation degrades further from the corner bay as the spatial correlations decrease.

• 한국전산구조공학회논문집
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• 제13권4호
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• pp.405-415
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• 2000

한 구조물에 작용하는 풍압력 시계열이 자기회귀 이동평균(ARMA) 모델을 사용하여 모델화 된다. AR 과정에서 시계열의 현재 값은 유한한 수의 이전 값들의 선형적 결합과 한 백색잡음에 의해 나타난다. MA 과정에서 시계열의 현재값은 유한한 수의 이전 백색잡음들에 선형적이다. ARMA 과정은 AR과 MA 과정의 결합이다. 본 논문에서, AR, MA와 ARMA 모델이 풍압력 시계열에 적용되고, 데이터를 나타내기에 가장 적합한 ARMA 모델을 선정하는 과정이 소개된다. 모델의 변수들은 최대 가능도법을 사용하여 산정되고, 압력 시계열의 시간적 복잡성의 척도인 모델 차수를 최적화하기 위해 AICC 모델 선정 기준이 사용된다. 또한, 모델의 유효성을 조사하기 위해 LBP 검사가 사용된다. 본 연구로부터, AR 과정이 풍압력 시계열을 나타내기에 가장 적합하다는 결론이 얻어진다.

• Wind and Structures
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• 제3권3호
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• pp.159-175
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• 2000

Many practical time series, including pressure signals measured on roof-corners of low-rise buildings in quartering winds, consist of relatively quiescent periods interrupted by intermittent transients. The dyadic wavelet transform is used to detect these transients in pressure time series and a relatively simple pattern classification scheme is used to detect underlying structure in these transients. Statistical analysis of the resulting pattern classes yields a library of signal "building blocks", which are useful for detailed characterization of transients inherent to the signals being analyzed.

• Journal of Korean Neurosurgical Society
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• 제65권1호
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• pp.151-160
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• 2022

Continuous monitoring of intracranial pressure is a well established medical procedure. Still, little is known about long-term behavior of intracranial pressure in normal pressure hydrocephalus. The present study is designed to evaluate periodicity of intracranial pressure over long-time scales using intraventricular pressure monitoring in patients with normal pressure hydrocephalus. In addition, the circadian and diurnal patterns of blood pressure and body temperature in those patients are studied. Four patients, selected with "probable" normal pressure hydrocephalus, were monitored for several dozen hours. Intracranial pressure, blood pressure, and body temperature were recorded hourly. Autocorrelation functions were calculated and cross-correlation analysis were carried out to study all the time-series data. Autocorrelation results show that intracranial pressure, blood pressure, and body temperature values follow bimodal (positive and negative) curves over a day. The cross-correlation functions demonstrate causal relationships between intracranial pressure, blood pressure, and body temperature. The results show that long-term fluctuations in intracranial pressure exhibit cyclical patterns with periods of about 24 hours. Continuous intracranial pressure recording in "probable" normal pressure hydrocephalus patients reveals circadian fluctuations not related to the day and night cycle. These fluctuations are causally related to changes in blood pressure and body temperature. The present study reveals the complete loss of the diurnal blood pressure and body temperature rhythmicities in patients with "probable" normal pressure hydrocephalus.

• Journal of Mechanical Science and Technology
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• 제18권7호
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• pp.1246-1257
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• 2004

The objective of this paper is to characterize dynamic pressure traces measured at self-excited combustion instabilities occurring in two combustion systems of different hardware. One system is a model lean premixed gas turbine combustor and the other a fullscale bipropellant liquid rocket thrust chamber. It is commonly observed in both systems that low frequency waves at around 300㎐ are first excited at the onset of combustion instabilities and after a short duration, the instability mode becomes coupled to the resonant acoustic modes of the combustion chamber, the first longitudinal mode for the lean premixed combustor and the first tangential mode for the rocket thrust chamber. Low frequency waves seem to get excited at first since flame shows the higher heat release response on the lower frequency perturbations with the smaller phase differences between heat release and pressure fluctuations. Nonlinear time series analysis of pressure traces reveals that even stable combustion might have chaotic behavior with the positive maximum Lyapunov exponent. Also, pressure fluctuations under combustion instabilities reach a limit cycle or quasi-periodic oscillations at the very similar run conditions, which manifest that a self-excited high frequency instability has strong nonlinear characteristics.

• 반도체디스플레이기술학회지
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• 제22권4호
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• pp.131-135
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• 2023

Neural network-based time series models called time series neural networks (TSNNs) are trained by the error backpropagation algorithm and used to predict process shifts of parameters such as gas flow, RF power, and chamber pressure in reactive ion etching (RIE). The training data consists of process conditions, as well as principal components (PCs) of optical emission spectroscopy (OES) data collected in-situ. Data are generated during the etching of benzocyclobutene (BCB) in a SF₆/O₂ plasma. Combinations of baseline and faulty responses for each process parameter are simulated, and a moving average of TSNN predictions successfully identifies process shifts in the recipe parameters for various degrees of faults.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2011년도 제37회 추계학술대회논문집
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• pp.241-245
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• 2011

엔진 시험과정에서 데이터는 시계열 형태로 수집된다. 보통 그러한 시계열들의 섭동보다는 시간평균에 더 관심을 가진다. 본 논문에서는 공기 흡입식 엔진의 시험에서 측정된 압력과 유량 데이터의 섭동에 시계열의 복잡성의 척도로 제안된 개념인 multiscale sample entropy라는 분석법을 적용해본다. 분석 결과, 서로 다른 물리량은 각각의 시간척도에서 다른 복잡성을 가진다는 것을 보였고, 이를 잘 이용하면 엔진 시험의 성패 여부를 즉각적으로 알려주는 도구를 만들 수 있을 것이다.

• Wind and Structures
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• 제26권1호
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• pp.11-24
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• 2018

Full-scale measurements of wind action on the open roof structure of the WuXi grand theater, which is composed of eight large-span free-form leaf-shaped space trusses with the largest span of 76.79 m, were conducted during the passage of Typhoons HaiKui and SuLi. The wind pressure field data were continuously and simultaneously monitored using a wind pressure monitoring system installed on the roof structure during the typhoons. A detailed analysis of the field data was performed to investigate the characteristics of the fluctuating wind pressure on the open roof, such as the wind pressure spectrum, spatial correlation coefficients, peak wind pressures and non-Gaussian wind pressure characteristics, under typhoon conditions. Three classical methods were used to calculate the peak factors of the wind pressure on the open roof, and the suggested design method and peak factors were given. The non-Gaussianity of the wind pressure was discussed in terms of the third and fourth statistical moments of the measured wind pressure, and the corresponding indication of the non-Gaussianity on the open roof was proposed. The result shows that there were large pulses in the time-histories of the measured wind pressure on Roof A2 in the field. The spatial correlation of the wind pressures on roof A2 between the upper surface and lower surface is very weak. When the skewness is larger than 0.3 and the kurtosis is larger than 3.7, the wind pressure time series on roof A2 can be taken as a non-Gaussian distribution, and the other series can be taken as a Gaussian distribution.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2004년도 임시총회 및 추계학술발표회
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• pp.113-114
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• 2004

In order to classify the groundwater recharge characteristics in an urban area, a time series analysis of groundwater level data was performed. For this study, the daily groundwater level data from 35 monitoring wells were collected for 3 years (Fig. 1). The use of the cross-correlation function (CCF), one of the time series analysis, showed both the close relationship between rainfall and groundwater level change and the lag time (delay time) of groundwater level fluctuation after a rainfall event. Based on the result of CCF, monitored wells were classified into two major groups. Group I wells (n=10) showed a fast response of groundwater level change to rainfall event, with a delay time of maximum correlation between rainfall and groundwater level near 1 to 7 days. On the other hand, the delay time of 17-68 days was observed from Group II wells (n=25) (Fig. 1). The fast response in Group I wells is possibly caused by the change of hydraulic pressure of bedrock aquifer due to the rainfall recharge, rather than the direct response to rainfall recharge.