• 물과 미래
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• 제22권2호
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• pp.201-211
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• 1989

인접계측지점의 상관성을 이용하여 결측지점의 자료를 보완한 다음, 다중상관 기법에 의하여 총강우량의 호우곡면을 구성한다. 구성된 호우 곡면에서 주기성분을 분리하여 호우잔차를 발생시키는데, 이중 프리에 해석을 이용했다. 각 강우에 잔차성분들은 균질등방성이라고 가정하여 이에 대응하는 자기 상관 함수를 조사하엿다. 실용성을 보완하기 위해서 경험치와 비교하였다. 모든 강우에 대한 정규상관 함수의 계수는 비슷한 양상을 보였다. 위의 결과를 사용하여 한강유역에 내린 강우의 공간분포를 나타내는 환상스펙트럼 분포함수를 추정하였다.

• Geomechanics and Engineering
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• 제17권6호
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• pp.565-572
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• 2019

Spatial variability is an inherent characteristic of soil, and auto-correlation length (ACL) is a very important parameter in the reliability or probabilistic analyses of geotechnical engineering that consider the spatial variability of soils. Current methods for estimating the ACL need a large amount of laboratory or in-situ experiments, which is a great obstacle to the application of random field theory to geotechnical reliability analysis and design. To estimate the ACL reasonably and efficiently, we propose a micro-structure based numerical simulation method. The quartet structure generation set algorithm is used to generate stochastic numerical micro-structure of soils, and scanning electron microscope test of soil samples combined with digital image processing technique is adopted to obtain parameters needed in the QSGS algorithm. Then, 2-point correlation function is adopted to calculate the ACL based on the generated numerical micro-structure of soils. Results of a case study shows that the ACL can be estimated efficiently using the proposed method. Sensitivity analysis demonstrates that the ACL will become stable with the increase of mesh density and model size. A model size of $300{\times}300$ with a grid size of $1{\times}1$ is suitable for the calculation of the ACL of clayey soils.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권8호
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• pp.442-450
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• 2000

Active noise control is an approach to noise reduction in which a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and a time-adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Opppenheim model assumed that transfer function characteristics from the canceling source to the error sensor is only propagation delay. But this paper proposes a modified Oppenheim model by considering transfer characteristics of acoustic device and noise path. This transfer characteristics is adaptively cancelled by adaptive model. This is proved by computer simulation with artifically generated random noise and sine wave noise. The details of the proposed architecture, and theoretical simulation and experimental results of the noise cancellation system for three dimension enclosure are presented in the paper.

• 대한기계학회논문집
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• 제16권9호
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• pp.1788-1795
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• 1992

본 연구에서는 상술한 특성을 갖는 유동자에 대하여 신뢰성이 보장된 스펙트 럼 추정법의 모색과 화립을 위해 의사 난류신호(turbulent-like signal)를 자기회기 모형(autoregressive model:AR model)으로 생성하고 추출간격이 유동장에 영향을 받는 비주기적 확률과정을 수치적으로 모사한다. 이 비주기적 실현 신호로 부터 현재 가 장 많이 사용되고 있는 Roberts와 Gaster의 직접 변화법과 추출 및 유지신호의 피리오 도그램(periodogram)법에 대해 데이터 밀도와 난류강도의 다양한 변화에 따른 속도편 의의 영향 등을 살펴보는데 목적을 둔다.

• Geomechanics and Engineering
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• 제30권6호
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• pp.503-515
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• 2022

The permeability coefficient is an essential parameter for the study of seepage flow in fractured rock mass. This paper discusses the feasibility and application value of using readily available RQD (rock quality index) data to estimate mine water inflow and grouting quantity. Firstly, the influence of different fracture frequencies on permeability in a unit area was explored by combining numerical simulation and experiment, and the relationship between fracture frequencies and pressure and flow velocity at the monitoring point in fractured rock mass was obtained. Then, the stochastic function generation program was used to establish the flow analysis model in fractured rock mass to explore the relationship between flow velocity, pressure and analyze the universal law between fracture frequency and permeability. The concepts of fracture width and connectivity are introduced to modify the permeability calculation formula and grouting formula. Finally, based on the on-site grouting water control example, the rock mass quality index is used to estimate the mine water inflow and the grouting quantity. The results show that it is feasible to estimate the fracture frequency and then calculate the permeability coefficient by RQD. The relationship between fracture frequency and RQD is in accordance with exponential function, and the relationship between structure surface frequency and permeability is also in accordance with exponential function. The calculation results are in good agreement with the field monitoring results, which verifies the rationality of the calculation method. The relationship between the rock mass RQD index and the rock mass permeability established in this paper can be used to invert the mechanical parameters of the rock mass or to judge the permeability and safety of the rock mass by using the mechanical parameters of the rock mass, which is of great significance to the prediction of mine water inflow and the safety evaluation of water inrush disaster management.

• 대한토목학회논문집
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• 제26권6A호
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• pp.1001-1011
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• 2006

재료인수, 기하인수 또는 작용하중 등에 불확실성을 가지는 구조에 대한 추계론적 해석의 정확해는, 일반적인 관점에서, 불확실성을 표현하는 추계장의 수치생성과 이에 대한 몬테카를로 해석을 통하여 얻을 수 있다. 그러나 불확실 인수의 공간적 분포를 나타내는 추계장은 그 특성을 표현해주는 두 가지의 함수를 동시에 만족시켜야 한다. 하나는 확률변수의 공간적 분포 상황을 표현해주는 스펙트럼밀도함수이며, 다른 하나는 통계적 특성을 나타내는 확률밀도함수이다. 일반적으로 이들 두 함수를 동시에 만족시키는 추계장의 정확한 수치생성은 여러 이유에서 어려운 일로 여겨지고 있다. 그러나 상관관계거리가 무한대인 확률변수상태의 경우 추계장은 상수추계장이 되며, 이 경우 스펙트럼밀도함수에 의하여 부과되는 제한조건은 사라지게 되어, 단순히 확률밀도함수에 대한 조건만이 남게 된다. 이 경우, 구조인수의 불확실성에 의한 구조응답은 확률밀도함수만을 고려하여 얻을 수 있게 된다. 이렇게 산정되는 응답변화도는 기존의 급수전개 및 섭동법 등의 수치해법은 물론 몬테카를로 해석에서도 얻을 수 없었던 정확해에 대한 준이론해를 제공해 줄 수 있다.

• International Journal of Contents
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• 제12권4호
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• pp.31-44
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• 2016

Knowledge creation and management are regarded as critical success factors for an organization's survival in the knowledge era. As a process of knowledge acquisition and sharing, organizational learning mechanisms (OLMs) guide the learning function of organizations represented by its different learning activities. We examined a variety of learning processes that constitute OLMs. In this study, we aimed to capture the process and framework of OLMs and knowledge sharing and acquisition. Factors facilitating OLMs were investigated at three levels: individual, group, and organizational. The concept of an OLM has received some attention in the field of organizational learning, however, the relationship among the factors generating OLMs has not been empirically tested. As part of the ongoing discussion, we attempted a systemic approach for OLMs. OLMs can be represented by factors that are inherent to the organization's system; therefore, prior to empirically testing the OLM generating factor(s), evaluation of its organizational integration is required to determine effective treatment of each factor. Thus, we developed a framework to manage knowledge and proposed a method to numerically evaluate factors influencing the OLMs. Specifically, composite importance (CI) of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was applied to explore the interaction effect of these factors based on systemic approach. The augmented matrix thus generated is expected to serve as a stochastic matrix of an absorbing Markov chain.

• 자원환경지질
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• 제29권6호
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• pp.713-724
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• 1996

현장에서의 주요 운송 메카니즘을 연구하기 위하여 시간별 잔존수 농도분포곡선 자료를 이용하였다. 운송개념을 대표하는 모델로서 2개의 상반된 가설에 근기한 모델, 즉 CDE와 CLT모델을 사용하였으며 파라미터 추정을 위하여 깊이별 평균농도자료에 최적화기법을 적용하였으며 잔존수 농도의 도달시간을 나타내는 확율밀도함수를 이용하여 모멘트해석도 시행되었다. 모멘트 해석결과 잔존수농도의 1차 및 2차 시간 모멘트는 침출수농도의 것들보다 크게 나타났다. 또한 시간 모멘트를 이용하여 오염물질 운송시간의 변이도와 확산 파라미터도 도출되었다. 변이도 및 확산계수와 운송거리간의 상관관계는 침출수농도 및 잔존수농도에 대해서 동일하게 나타났다. 이러한 관계를 이용하여 2가지 모델을 검정하였으나 운송거리에 따른 운송파라미터의 불규칙한 변화로 확정적 결론을 얻을 수 없었다. 따라서 첫 번째 깊이에서 얻은 파라미터를 이용하여 다른 깊이에서의 오염물질 운송 방식을 예측하여 실측자료와 비교하여 각 모델을 검정하였다. 그 결과 CLT 모델이 CDE 모델보다 현장실측자료에 근접하였다. 이는 오염물질이 이동함에 따라 완전한 혼합이 발생하는 것이 아니라 상관흐름 즉, "오염물질이 각 층을 통과할 때 빠른 물질은 빠르게 느린 물질은 지속적으로 느리게 움직인다"는 사실을 뒷받침한다고 볼 수 있다. 특히 첨두농도에 대한 CDE 모델의 과대예측은 오염물질 확산의 과소평가에 기인하는 것으로 나타났다.

• Smart Structures and Systems
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• 제17권6호
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.809-824
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• 2017

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.