• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.240-245
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• 2008

컴퓨터 그래픽스에서 많은 광원들을 포함하는 장면을 사실적으로 렌더링하기 위해서는, 많은 양의 조명 계산을 수행해야 한다. 다수의 광원들로부터 빠르게 조명 계산을 하기 위해 많이 사용되는 기법 중에 몬테 카를로(Monte Carlo) 기법이 있다. 본 논문은 이러한 몬테 카를로(Monte Carlo) 기법을 기반으로, 다수의 광원들을 효과적으로 샘플링 할 수 있는 새로운 중요도 샘플링 기법을 제안한다. 제안된 기법의 두 가지 핵심 아이디어는 첫째, 장면 내에 다수의 광원이 존재하여도 어떤 특정 지역에 많은 영향을 주는 광원은 일부인 경우가 많다는 점이고 두 번째는 공간 일관성(spatial coherence)이 낮거나 그림자 경계 지역에 위치한 픽셀들은 영향을 받는 주요 광원이 서로 다르다는 점이다. 제안된 기법은 이러한 관찰에 착안하여 특정 지역에 광원이 기여하는 정도를 평가하고 이에 비례하게 확률 밀도 함수(PDF: Probability Density Function)를 결정하는 방법을 제안한다. 이를 위하여 이미지 공간상에서 픽셀들을 클러스터링(clustering)하고 클러스터 구조를 기반으로 대표 샘플을 선정한다. 선정된 대표 샘플들로부터 광원들의 기여도를 평가하고 이를 바탕으로 클러스터 단위의 확률 밀도 함수를 결정하여 최종 렌더링을 수행한다. 본 논문이 제안하는 샘플링 기법을 적용했을 때 전통적인 샘플링 방식과 비교하여 같은 샘플링 개수에서 노이즈(noise)가 적게 발생하는 좋은 화질을 얻을 수 있었다. 제안된 기법은 다수의 조명과 다양한 재질, 복잡한 가려짐이 존재하는 장면을 효과적으로 표현할 수 있다.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.4
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• pp.44-50
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• 2010

Structural vibration is a significant problem in many multi-part or multi-component assemblies. In aircraft industry, structures are composed of various fasteners, such as bolts, snap, hinge, weld or other fastener or connector (collectively "fasteners"). Due to these, prediction and design involving dynamic characteristics is quite complicated. However, the current state of the art does not provide an analytical tool to effectively predict structure's dynamic characteristics, because consideration of structural uncertainties (i.e. material properties, geometric tolerance, dimensional tolerance, environment and so on) is difficult and very small fasteners in the structure cause a huge amount of analysis time to predict dynamic characteristics using the FEM (finite element method). In this study, to resolve the current state of the art, a new approach is proposed using the FEM and probabilistic analysis. Firstly, equivalent elements are developed using simple element (e.g. bar, beam, mass) to replace fasteners' finite element model. Developed equivalent elements enable to explain static behavior and dynamic behavior of the structure. Secondly, probabilistic analysis is applied to evaluate the PDF (probability density function) of dynamic characteristics due to tolerance, material properties and so on. MCS (Monte-Carlo simulation) is employed for this. Proposed methodology offers efficiency of dynamic analysis and reality of the field as well. Simple plates joined by fasteners are taken as an example to illustrate the proposed method.

• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.3 s.234
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• pp.314-321
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• 2005

Discrete Wavelet Transform (DWT) has been applied to the Direct Numerical Simulation (DNS) data of turbulent channel flow. DWT splits the turbulent flow into two orthogonal parts, one corresponding to coherent structures and the other to incoherent background flow. The coherent structure is extracted from not vorticity field but velocity's since the channel flow is not isoropic. By comparing DWT's result of channel flow with that of isotropic flow, it is shown that coherent structure maintains the properties of original channel flow. The velocity field of coherent structures can be represented by few wavelet modes and that these modes are sufficient to reproduce the velocity probability density function (PDF) and the energy spectrum over the entire inertial range. The remaining incoherent background flow is homogeneous, has small amplitude, and is uncorrelated. These results are compared with those obtained for the same compression rate using large eddy simulation (LES) filtering. In contrast to the incoherent background flow of DWT, the LES subgrid scales have a much larger amplitude and are correlated, which makes their statistical modeling more difficult.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.7
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• pp.552-559
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• 2013

In this paper, the multiple-input multiple-output (MIMO) system with a precoder is considered in the transmit-correlated Rayleigh channels. We specifically target the MIMO system employing the minimum mean square error receivers. Based on random matrix theory, we first present a direct and generalized formulation for deriving a probability density function (PDF) of the signal-to-interference-plus-noise ratio (SINR). Then, we derive the accurate closed-form SINR PDFs for a small number of transmit and receive antennas. Based on the SINR PDFs, tight closed-form approximations of the symbol error rate (SER) are derived. Our analysis suggests that the SER approximations can be used to accurately estimate the error probabilities or as a useful tool for the system design.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.277-286
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• 2010

In this paper amplitude and phase distortion of the received signal through a fading channel results in a severe performance degradation of the communication system, Therefore we consider the variance of the maximum a posteriori phase estimate of sinusoidal signal by the Cramer-Rao bound in wireless fading channel. To find the Cramer-Rao lower bound for the variance of the phase, We use the derived probability density function(pdf) of the phase in Nakagami fading channel. We analyze the error performance of modulation signals using order statistics on generalized combining reception and find adequate diversity branch number.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.709-720
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• 2010

This paper describes the modeling of climate change impact on drought using a conceptual soil moisture model and presents the results of the modeling approach. The future climate series is obtained by scaling the historical series, informed by CCCma CGCM3-T63 with A2 green house emission scenario, using a daily scaling method that considers changes in the future monthly precipitation and potential evapotranspiration as well as in the daily precipitation distribution. The majority of the modeling results indicate that there will be more frequent drought in Korea in the future.

• Wind and Structures
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• v.36 no.2
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• pp.133-147
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• 2023

The random vibration of saddle membrane structures under wind load is studied theoretically and experimentally. First, the nonlinear random vibration differential equations of saddle membrane structures under wind loads are established based on von Karman's large deflection theory, thin shell theory and potential flow theory. The probabilistic density function (PDF) and its corresponding statistical parameters of the displacement response of membrane structure are obtained by using the diffusion process theory and the Fokker Planck Kolmogorov equation method (FPK) to solve the equation. Furthermore, a wind tunnel test is carried out to obtain the displacement time history data of the test model under wind load, and the statistical characteristics of the displacement time history of the prototype model are obtained by similarity theory and probability statistics method. Finally, the rationality of the theoretical model is verified by comparing the experimental model with the theoretical model. The results show that the theoretical model agrees with the experimental model, and the random vibration response can be effectively reduced by increasing the initial pretension force and the rise-span ratio within a certain range. The research methods can provide a theoretical reference for the random vibration of the membrane structure, and also be the foundation of structural reliability of membrane structure based on wind-induced response.

• Structural Engineering and Mechanics
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• v.87 no.1
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• pp.1-18
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• 2023

The paper presents a Bayesian Finite element (FE) model updating methodology by utilizing modal data. The dynamic condensation technique is adopted in this work to reduce the full system model to a smaller model version such that the degrees of freedom (DOFs) in the reduced model correspond to the observed DOFs, which facilitates the model updating procedure without any mode-matching. The present work considers both the MPV and the covariance matrix of the modal parameters as the modal data. Besides, the modal data identified from multiple setups is considered for the model updating procedure, keeping in view of the realistic scenario of inability of limited number of sensors to measure the response of all the interested DOFs of a large structure. A relationship is established between the modal data and structural parameters based on the eigensystem equation through the introduction of additional uncertain parameters in the form of modal frequencies and partial mode shapes. A novel sampling strategy known as the Metropolis-within-Gibbs (MWG) sampler is proposed to sample from the posterior Probability Density Function (PDF). The effectiveness of the proposed approach is demonstrated by considering both simulated and experimental examples.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.201-201
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• 2022

본 연구에서는 강우량이 여름에 집중되어있는 우리나라의 강우 특성을 잘 나타낼 수 있는 최적의 확률분포형을 선정하고 해석적 확률모델 (Analytical Probabilistic Model, APM)을 개발하여 유출량을 예측하고자 하였다. 국내 10개 지역인 부산, 춘천, 대구, 대전, 전주, 진주, 서울, 속초, 태백, 원주를 연구 지역으로 설정하였고, 30년 시 단위 강우자료를 지역별 interevent time definition(IETD)을 적용하여 강우 사상으로 그룹화하였다. APM 연구에 일반적으로 사용되는 일변수 지수 분포 이외의 이변수 지수, 감마, 이변수 로그정규 확률밀도함수 (Probability Density Function, PDF)를 강우사상의 특성인 강우량, 강우 지속시간, 무강우 시간의 히스토그램에 적용한 결과, 이 변수 로그정규분포가 우리나라의 강우 특성을 가장 잘 대표하였다. 로그정규분포를 이용하여 APM을 유도하고 유출량을 예측하였다. 예측한 유출량에 대한 빈도분석을 수행하여 Storm Water Management Model (SWMM)의 결과와 비교함으로써 유도한 APM의 적합성을 확인하였다. SWMM의 입력 매개변수 보정을 위해서는 서울 군자 지역에서 관측한 실제 강우량 및 유출량 자료를 사용하였다. 로그정규분포로 유도한 APM과 SWMM의 빈도분석 결과를 비교하였을 때 초과 확률과 재현주기 모두 매우 유사한 결과를 나타내었음을 확인하였다.