• Wind and Structures
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• 제35권6호
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• pp.419-430
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• 2022

In wind-resistant designs, wind velocity is assumed to be a Gaussian process; however, local complex topography may result in strong non-Gaussian wind features. This study investigates the non-Gaussian wind features over complex terrain under atmospheric turbulent boundary layers by the large eddy simulation (LES) model, and the turbulent inlet of LES is generated by the consistent discretizing random flow generation (CDRFG) method. The performance of LES is validated by two different complex terrains in Changsha and Mianyang, China, and the results are compared with wind tunnel tests and onsite measurements, respectively. Furthermore, the non-Gaussian parameters, such as skewness, kurtosis, probability curves, and gust factors, are analyzed in-depth. The results show that the LES method is in good agreement with both mean and turbulent wind fields from wind tunnel tests and onsite measurements. Wind fields in complex terrain mostly exhibit a left-skewed Gaussian process, and it changes from a softening Gaussian process to a hardening Gaussian process as the height increases. A reduction in the gust factors of about 2.0%-15.0% can be found by taking into account the non-Gaussian features, except for a 4.4% increase near the ground in steep terrain. This study can provide a reference for the assessment of extreme wind loads on structures in complex terrain.

• Wind and Structures
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• 제28권5호
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• pp.315-329
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• 2019

Non-synoptic winds have distinctive statistical properties compared to synoptic winds and can produce different wind loads on buildings and structures. The current study uses the new capabilities of the WindEEE Dome at Western University to replicate a stationary non-Gaussian wind event recorded at the Port of La Spezia in Italy. These stationary non-Gaussian wind events are also known as intermediate wind events as they differ from non-stationary non-Gaussian events (e.g., downbursts) as well as stationary Gaussian events (e.g., atmospheric boundary layer (ABL) flows). In the present study, the wind loads on a typical low-rise building are investigated for an intermediate wind event reproduced using a continuous radial impinging jet (IJ) at the WindEEE Dome. For the same building model, differences in wind loads between ABL and IJ are also examined. Wind loads on different surface zones on the building, as defined in the ASCE code for design loads, are also calculated and compared with the code.

• 한국통신학회논문지
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• 제38C권4호
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• pp.365-370
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• 2013

본 논문에서는 비정규 잡음에 강인한 직교 주파수 분할 다중화 (orthogonal frequency division multiplexing: OFDM) 블라인드 주파수 옵셋 추정기들을 제안한다. 먼저 복소 등방성 코시 과정으로 모델링 된 비정규 잡음 환경에서 최대 우도 (maximum likelihood: ML) 추정기를 제안한다. 또한, ML 기반의 보다 간단한 추정기를 제안한다. 모의실험을 통해 제안한 추정기들이 비정규 잡음에 강인하며 기존 추정기보다 우수한 주파수 옵셋 추정 성능을 가짐을 보인다.

• 전자공학회논문지
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• 제50권1호
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• pp.232-238
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• 2013

본 논문은 노이즈가 비 정규 분포를 따르는 수중 환경에서 비 선형 필터 기법에 따른 Mass-Damper-Spring (MBK) 시스템 위치추정에 관한 연구 내용이다. 최근 위치 추정에 사용되는 필터는 확장 칼만 필터 (EKF: Extended Kalman Filter) 와 파티클 필터(Particle Filter)가 주목 받고 있다. EKF는 가우시안 잡음 (Gaussian Noise) 이 존재하는 비선형 시스템에서 정확도가 높은 알고리즘으로 널리 사용되고 있지만, 수중 환경과 같이 비 가우시안 잡음이 존재하는 경우 사용에 많은 제약이 따른다. 이에 본 논문에서는 상태예측을 기반으로 둔 EKF와 비교하여, 통계적 발생 가능성 인자 (Maximum Likelihood) 에 기반한 분포 재해석 기법을 이용한 개선된 ODPF (One-Dimension Particle Filter)를 제안한다. 모의 실험을 통하여 non-Gaussian noise가 존재하는 수중 환경에서 EKF와 제안한 Particle filter를 사용한 위치 추정 결과를 비교 분석하였으며, 계산 용량 및 통계 샘플이 충분한 경우 ODPF가 EKF 대비 정확한 위치 추정 결과를 제공하는 것을 확인하였다.

• 대한수학회지
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• 제37권1호
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• pp.1-19
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• 2000

We formulate a non-central limit theorem for non-linear functionals of stationary Gaussian vector processes with dependence.

• 응용통계연구
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• 제28권2호
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• pp.353-360
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• 2015

공간적으로 관측되는 연속형 자료를 분석하는 모형으로 공간적 상관관계를 고려한 다양한 정규모형이 지난 수십 년간 제안되었다. 그 중에서 공간효과를 랜덤효과로 모형화하는 공간선형모형(Spatial Linear Mixed Model; SLMM)이 가장 널리 활용되는 모형 중 하나일 것이다. 연결함수(link function)을 사용하면 SLMM을 비정규 데이터도 적용할 수 있는 일반화된 공간선형모형(Spatial Generalized Linear Mixed Model; SGLMM)으로 자연스럽게 확장할 수 있다. 이 논문에서는 가장 널리 활용되는 SGLMM을 알아보고 실제 데이터 적용사례를 R 패키지를 활용하여 제시하고자 한다.

• Wind and Structures
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• 제36권1호
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• pp.15-29
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• 2023

To better estimate the non-Gaussian extreme wind pressures for high-rise buildings, a data-driven revised Hermitetype peak factor estimation model is proposed in this papar. Subsequently, a comparative study on three types of methods, such as Hermite-type models, short-time estimate Gumbel method (STE), and new translated-peak-process method (TPP) is carried out. The investigations show that the proposed Hermite-type peak factor has better accuracy and applicability than the other Hermite-type models, and its absolute accuracy is slightly inferior to the STE and new TPP methods for non-Gaussian wind pressures by comparing with the observed values. Moreover, these methods generally overestimate the Gaussian wind pressures especially the STE.

• Wind and Structures
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• 제3권1호
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• pp.1-10
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• 2000

Recently, an efficient and practical method has been developed for the generation of univariate non-Gaussian wind pressure time histories on low building roofs; this methodology requires intermittent exponential random numbers for the simulation. On the other hand, the conventional spectral representation scheme with random phase is found suitable for the generation of univariate Gaussian wind pressure time histories on low building roofs; this simulation scheme requires uniform random numbers. The dependency of these simulation methodologies on the random number generator is one of the items affecting the accuracy of the simultion result; therefore, an attempt has been made to investigate the issue. This note presents the observed sensitivity of random number sets in repetitive simulations of Gaussian and non-Gaussian wind pressures.

• 천문학회보
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• 제39권1호
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• pp.78.2-78.2
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• 2014

Many techniques for data analysis also based on gaussian noise assumption which is often valid in various situations. However, the sensitivity of gravitational wave searches are limited by their non-gaussian and non-stationary noise. We introduce various on-going efforts to overcome this limitation in Korean Gravitational Wave Group. First, artificial neural networks are applied to discriminate non-gaussian noise artefacts and gravitational-wave signals using auxiliary channels of a gravitational wave detector. Second, viability of applying Hilbert-Huang transform is investigated to deal with non-stationary data of gravitational wave detectors. We also report progress in acceleration of low-latency gravitational search using GPGPU.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.55-58
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• 2005

This paper discusses the asymptotic efficiency of estimators for optimal portfolios when returns are vector-valued non-Gaussian stationary processes. We give the asymptotic distribution of portfolio estimators ${\hat{g}}$ for non-Gaussian dependent return processes. Next we address the problem of asymptotic efficiency for the class of estimators ${\hat{g}}$ First, it is shown that there are some cases when the asymptotic variance of ${\hat{g}}$ under non-Gaussianity can be smaller than that under Gaussianity. The result shows that non-Gaussianity of X(t) does not always affect worse. Second, we give a necessary and sufficient condition for ${\hat{g}}$ to be asymptotically efficient when the return process is Gaussian, which shows that ${\hat{g}}$ is not asymptotically efficient generally. From this point of view we propose to use maximum likelihood type estimators for g, which are asymptotically efficient. We examine our approach numerically.