• Structural Engineering and Mechanics
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• 제63권6호
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• pp.837-846
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• 2017

An accurate calculation of the stochastic wind field is the foundation for analyzing wind-induced structure response and reliability. In this research, the spatial correlation of structural wind field was considered based on the time domain method. A method for calculating the stochastic wind field based on cross stochastic Fourier spectrum was proposed. A flowchart of the proposed methodology is also presented in this study to represent the algorithm and workflow. Along with the analysis of regional wind speed distribution, the wind speed time history sample was calculated, and the efficiency can therefore be verified. Results show that the proposed method and programs could provide an efficient simulation for the wind-induced structure response analysis, and help determine the related parameters easily.

• Wind and Structures
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• 제10권1호
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• pp.45-60
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• 2007

Transmission tower is a vital component in electrical system. In order to accurately compute the dynamic response and reliability of transmission tower under the excitation of wind loading, a new method termed as probability density evolution method (PDEM) is introduced in the paper. The PDEM had been proved to be of high accuracy and efficiency in most kinds of stochastic structural analysis. Consequently, it is very hopeful for the above needs to apply the PDEM in dynamic response of wind-excited transmission towers. Meanwhile, this paper explores the wind stochastic field from stochastic Fourier spectrum. Based on this new viewpoint, the basic random parameters of the wind stochastic field, the roughness length $z_0$ and the mean wind velocity at 10 m heigh $U_{10}$, as well as their probability density functions, are investigated. A latticed steel transmission tower subject to wind loading is studied in detail. It is shown that not only the statistic quantities of the dynamic response, but also the instantaneous PDF of the response and the time varying reliability can be worked out by the proposed method. The results demonstrate that the PDEM is feasible and efficient in the dynamic response and reliability analysis of wind-excited transmission towers.

• Wind and Structures
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• 제16권5호
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• pp.433-455
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• 2013

A phase delay spectrum model towards the representation of spatial coherence of stochastic wind fields is proposed. Different from the classical coherence functions used in the spectral representation methods, the model is derived from the comprehensive description of coherence of fluctuating wind speeds and from the thorough analysis of physical accounts of random factors affecting phase delay, building up a consistent mapping between the simulated fluctuating wind speeds and the basic random variables. It thus includes complete probabilistic information of spatial stochastic wind fields. This treatment prompts a ready and succinct scheme for the simulation of fluctuating wind speeds, and provides a new perspective to the accurate assessment of dynamic reliability of wind-induced structures. Numerical investigations and comparative studies indicate that the developed model is of rationality and of applicability which matches well with the measured data at spatial points of wind fields, whereby the phase spectra at defined datum mark and objective point are feasibly obtained using the numerical scheme associated with the starting-time of phase evolution. In conjunction with the stochastic Fourier amplitude spectrum that we developed previously, the time history of fluctuating wind speeds at any spatial points of wind fields can be readily simulated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.495-513
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• 2020

The correlation identification of the subsurface is a novel electrical prospecting method which could suppress stochastic noise. This method is increasingly being utilized by geophysicists. It achieves the frequency response of the underground media through division of the cross spectrum of the input & output signal and the auto spectrum of the input signal. This is subject to the spectral leakage when the cross spectrum and the auto spectrum are computed from cross correlation and autocorrelation function by Discrete Fourier Transformation (DFT, "To obtain an accurate frequency response of the earth system, we propose an improved correlation identification method which uses all phase Fast Fourier Transform (APFFT) to acquire the cross spectrum and the auto spectrum. Simulation and engineering application results show that compared to existing correlation identification algorithm the new approach demonstrates more precise frequency response, especially the phase response of the system under identification.

• Structural Engineering and Mechanics
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• 제39권6호
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• pp.877-893
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• 2011

Response spectra of earthquake ground motions are important in the earthquake-resistant design and reliability analysis of structures. The formulation of the response spectrum in the frequency domain efficiently computes and evaluates the stochastic response spectrum. The frequency information of the excitation can be described using different functional forms. The shapes of the calculated response spectra of the excitation show strong magnitude and site dependency, but weak distance dependency. In this paper, to compare the effect of the earthquake ground motion variables, the contribution of these sources of variability to the response spectrum's uncertainty is calculated by using a stochastic analysis. The analytical results show that earthquake source factors and soil condition variables are the main sources of uncertainty in the response spectra, while path variables, such as distance, anelastic attenuation and upper crust attenuation, have relatively little effect. The presented formulation of dynamic structural response in frequency domain based only on the frequency information of the excitation can provide an important basis for the structural analysis in some location that lacks strong motion records.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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• pp.439-446
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• 1998

One of the most important roles in the nonlinear dynamic structural analysis is to select a proper ground excitation, which dominates the response of a structure. Because of the lack of recorded accelerograms in Korea, a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms is necessarily required. If all information is not available at site, the information from other sites with similar features can be used by the procedure of seismic hazard analysis. Eliopoulos and Wen identified the parameters of the ground motion model by the empirical relations or expressions developed by Trifunac and Lee. Because the relations used in the parameter identification are largely empirical, it is required to apply the artificial neural networks instead of the empirical model. Additionally, neural networks have the advantage of the empirical model that it can continuously re-train the new recorded data, so that it can adapt to the change of the enormous data. Based on the redefined traditional processes, three neural-networks-based models (FAS_NN, PSD_NN and INT_NN) are proposed to individually substitute the Fourier amplitude spectrum, the parameter identification of power spectral density function and intensity function. The paper describes the first half of the research for the development of Neural-Networks-based model for the generation of an Artificial earthquake and a Response Spectrum(NNARS).

• Structural Engineering and Mechanics
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• 제5권6호
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• pp.839-851
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• 1997

Closed-form solutions are analytically derived for stochastic properties of earthquake ground motion fields, which are conditioned by an observed time series at certain observation sites and are characterized by spectra with uncertainties. The theoretical framework presented here can estimate not only the expectations of such simulated earthquake ground motions, but also the prediction errors which offer important information for the field of engineering. Before these derivations are made, the theory of conditional random fields is summarized for convenience in this study. Furthermore, a method for stochastic interpolation of power spectra is explained.

• 정보처리학회논문지B
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• 제17B권1호
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• pp.69-78
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• 2010

스펙트럴 모델링 합성 (Spectral Modeling Synthesis, SMS)은 뮤지컬 사운드 모델링을 위한 강력한 툴로써 사용되어 왔다. 이 기술은 사운드를 결정적 (deterministic) 성분과 통계적 (stochastic) 성분의 조합으로 간주한다. Deterministic 성분은 크기 (amplitude), 주파수 (frequency), 위상 (phase) 함수에 따른 사인파의 연속으로 표현되는 반면, stochastic 성분은 백색 잡음 (white noise)으로 자극된 시간 변화 필터로서 동작하는 크기 스펙트럼 엔블로프 (spectrum envelop)의 연속으로 표현된다. 이러한 표현들은 원음의 모든 지각적인 특징들을 활용해 합성된 사운드를 구현 가능케 한다. 하지만, 고래 소리와 같은 복잡한 사운드에 대해 기존의 SMS를 사용할 때 연속적인 프로임에 있는 부분 주파수가 다른 경우 결정적 성분에서 상당한 위상 변화가 발생한다. 왜냐하면 기존의 SMS는 사운드의 결정적 성분을 합성하기 위해서 계산된 위상을 이용하기 때문이다. 그 결과 기존의 SMS는 높은 주파수 영역에서 원래 스펙트럼과 합성된 스펙트럼 사이에서 좋은 스펙트럼 매칭을 제공하지 못한다. 이러한 문제를 해결하기 위해 본 논문은 수정된 SMS를 제안한다. 제안하는 SMS는 결정적 성분을 합성하기 위해 원래 주파수 정보를 이용할 뿐만 아니라 주파수 영역에서 복잡한 잔재 (residual) 스펙트럼을 계산함으로써 원음과 합성음 사이에서 좋은 스펙트럼 매칭을 제공한다. 다양한 고래 소리 합성을 모의 실험한 결과, 제안된 방법은 시간 및 주파수 영역에서 기존의 SMS와 유사한 성능을 보였다. 하지만, 제안된 방법은 기존의 SMS보다 스펙트럼 매칭에서 더 좋은 성능을 보였다.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2000년도 춘계 학술발표회 논문집 Proceedings of EESK Conference-Spring
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• pp.44-48
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• 2000

Several parameters to represent the characteristics of the observed at the domestic networks from several earthquakes occurred in the Korean Peninsula. Parameters to fit most the multiple Fourier amplitude spectra of the observed accelerations are estimated. This study adopts the stochastic ground motion model referred to the BLWN mode in which the energy is distributed randomly over the duration of the source and which has proven to be very effective in modeling a wide range of ground motion observations. The stochastic ground motion model employed here uses an omega-squared ({{{{ omega ^2 }}) Brune source model with a single corner frequency and a constant stress drop,. The {{{{ omega ^2 }} source model has become a seismological standard because of its simplicity an ability to predict spectral amplitudes and shapes over an extremely broad ranges of magnitudes distances and from the inversion show very unstable based on the fact of high values of mean/median. These results may imply that more observed data and more precise site classification including accurate preparation analysis of data such as more accurate scaling from counts to kine are needed for more stable are effective inversion of Fourier amplitude spectrum of the observed ground motions.

• 한국환경보건학회지
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• 제17권2호
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• pp.1-8
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• 1991

The stochastic variance and structures of time series data on air quality were examined by employing the techniques of autocorrelation function, variance spectrum, fourier series, ARIMA model. Among the air quality properties of atmosphere, SO$_{2}$ is one of the most siginificant and widely measured parameters. In the study, the air quality data were included hourly observations on SO$_{2}$ TSP and O$_{3}$. The data were measured by automatic recording instrument installed in Kwanghwamoon during February and March in 1991. The results of study were as follows 1. Hourly air quality series varied with the domiant 24 hour periodicity and the 12 hour periodic variation was also observed. 2. The correlation coefficients between SO$_{2}$ and O$_{3}$ is -0.4735. 3. In simulating or forecasting variation in SO$_{2}$ ARIMA models are on a useful tools. The multiplicative seasonal ARIMA (1, 1, 0) (0, 2, 1)$_{24}$ model provided satisfactory results for hourly SO$_{2}$ time series.