• Structural Engineering and Mechanics
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• 제8권1호
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• pp.53-72
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• 1999

The most important features of linear soil-foundation-structure interaction are reviewed, using stochastic modeling and considering kinematic interaction, inertial interaction, and structural distortion as three separate stages of the dynamic response to the free-field motion. The way in which each of the three dynamic stages modifies the spectral density of the motion is studied, with the emphasis being on interpretation of these results, rather than on the development of new analysis techniques. Structural distortion and inertial interaction analysis are shown to be precisely modeled as linear filtering operations. Kinematic interaction, though, is more complicated, even though it has a filter-like effect on the frequency content of the motion.

• Wind and Structures
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• 제22권5호
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• pp.525-541
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• 2016

An offshore wind turbine supported by a spar buoy floating platform is the subject of this study on tower and rotor extreme loads. The platform, with a 120-meter draft and assumed to be sited in 320 meters of water, supports a 5 MW wind turbine. A baseline model for this turbine developed at the National Renewable Energy Laboratory (NREL) is employed in stochastic response simulations. The support platform, along with the mooring system consisting of three catenary lines, chosen for loads modeling, is based on the "Hywind" floating wind turbine concept. Our interest lies in gaining an understanding of the dynamic coupling between the support platform motion and the turbine loads. We first investigate short-term response statistics using stochastic simulation for a range of different environmental wind and wave conditions. From this study, we identify a few "controlling" environmental conditions for which long-term turbine load statistics and probability distributions are established.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.488-488
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• 2015

Intermittent streamflow is common phenomenon in arid and semi-arid regions. To manage water resources of intermittent streamflows, stochactic simulation data is essential; however the seasonally stochastic modeling for intermittent streamflow is a difficult task. In this study, using the periodic Markov chain model, we simulate intermittent monthly streamflow for occurrence and the periodic gamma autoregressive and copula models for amount. The copula models were tested in a previous study for the simulation of yearly streamflow, resulting in successful replication of the key and operational statistics of historical data; however, the copula models have never been tested on a monthly time scale. The intermittent models were applied to the Colorado River system in the present study. A few drawbacks of the PGAR model were identified, such as significant underestimation of minimum values on an aggregated yearly time scale and restrictions of the parameter boundaries. Conversely, the copula models do not present such drawbacks but show feasible reproduction of key and operational statistics. We concluded that the periodic Markov chain based the copula models is a practicable method to simulate intermittent monthly streamflow time series.

• Journal of applied mathematics & informatics
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• 제41권1호
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• pp.11-31
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• 2023

The paper presents a critical analysis of selected topics related to the modeling of interacting species in which prey has nonlinear reproduction, which is in competition with predator. The mathematical model's stochastic stability is investigated. The method of designing appropriate Lyapunov functions is used to identify permanence conditions among the parameters of the model and conditions for the structure to no longer be extinct. The system's two-dimensional diffusive stability is regarded and studied. The system experiences the process of saddle-node bifurcation by varying the death rate of predator parameter. Further effects of parameters that undergo inherent oscillations are numerically investigated, revealing that as the intensity of predation parameter b is increased, the device encounters non-periodic and damped oscillations.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2023년도 춘계학술대회
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• pp.252-253
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• 2023

Container terminal automation might offer many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A robust lane detection method is proposed using score-based generative modeling through stochastic differential equations for image-to-image translation. Image processing techniques are combined with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithm (GA) to ensure lane positioning robustness. The proposed method is validated by a dataset collected from the port terminals under different environmental conditions and tested the robustness of the lane detection method with stochastic noise.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제20권10호
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• pp.534-542
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• 2014

멀티스케일 모델링은 시공간적으로 서로 다른 규모의 시스템을 다룰 수 있는 시뮬레이션 기법이다. 본 연구에서는 멀티스케일 모델링 연구의 일환으로 서로 다른 시뮬레이션 기법인 분자동역학과 확률회전동역학을 결합할 수 있는 방법을 제안한다. 분자동역학 프로그램 중 잘 알려진 오픈 소스인 LAMMPS를 기반으로 멀티스케일링 모델링을 구현하였으며 LAMMPS에서 정의한 제3자를 위한 표준 확장 방법을 따랐다. 제안된 방법에서는 확률회전동역학 모델을 기본으로 경계 영역은 분자동역학으로 해석 가능하게 하였고 심리스한 해석을 보장하기 위하여 중첩 영역과 정보 교환 영역을 함께 구현하였다. 예비실험을 수행한 결과, 제안된 멀티스케일 방법론이 기존 분자동역학 시뮬레이션 결과와 일치된 해석 결과를 보여주었으며 실행 시간 또한 단축시킬 수 있음을 확인하였다.

• 한국항만경제학회지
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• 제38권4호
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• pp.13-23
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• 2022

본 연구는 2015년 1월부터 2020년 4월까지 건화물선 시장의 일별 운임수익률에 대한 레버리지 효과를 포착하기 위한 확률 변동성(stochastic volatility) 모형을 제안하고 운임수익률을 분석한다. 확률 변동성 분석에서 수익률과 변동성 간에 존재하는 음의 상관관계에 기초한 레버리지 효과에 대한 Bayesian Markov Chain Monte Carlo 방법을 포함하는 추정은 건화물선 운임수익률은 레버리지 효과를 포함하는 추정이 일반적인 SV 모형에 기초한 분석보다 유사한 추정치를 나타내지만 레버리지 효과에 대한 상관성 추정에서 통계적으로 유의미함을 나타낸다. 즉, 실증분석 결과는 수익률과 변동성의 상관도, 변동의 크기와 부호에 따라 상이함을 나타내며, 이는 SV 모델이 레버리지 효과를 고려하는 것이 추정치의 적합도를 향상시킴을 나타낸다. 추정모형의 레버리지 효과에 대한 통계적 유의성에 추가적으로 로그 예측력 점수를 통한 분석은 레버리지 효과를 고려하는 모형의 예측력이 향상된 추정 결과를 제시한다. 이러한 실증분석 결과는 레버리지 효과를 포함하는 확률 변동성 모형이 해양 산업의 운임 리스크 모델링에 중요함을 통계적으로 제시하는 유의미한 실증분석 결과다.

• Industrial Engineering and Management Systems
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• 제4권2호
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• pp.184-191
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• 2005

In this article we study the feasibility of the Ant Colony Optimisation (ACO) algorithm for finding optimal Kanban allocations in Kanban systems represented by Stochastic Petri Net (SPN) models. Like other optimisation algorithms inspired by nature, such as Simulated Annealing/Genetic Algorithms, the ACO algorithm contains a large number of adjustable parameters. Thus we study the influence of the parameters on performance of ACO on the Kanban allocation problem, and identify the most important parameters.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.821-826
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• 2003

The Purpose of this paper is to automate the representation of manufacturing line using Petri net model. In the manufacturing cell, the line can be represented using workflow which is composed of Bill of Material (BOM) and Bill of Processes (BOP). BOP shows the precedence of processes and the relationship between assembly and disassembly. As a modeling scheme, generalized stochastic Petri net is adopted. For a problem domain with flexible manufacturing cell, Petri net model is made and behavioral properties are analyzed.

• 전기학회논문지
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• 제61권7호
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• pp.1007-1013
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• 2012

Modeling of photovoltaic power systems is significant to analytically predict its dynamics in practical applications. This paper presents a novel modeling algorithm of such system by using probability and statistic theories. We first establish a linear model basically composed of Fourier parameter sets for mapping the input/output variable of photovoltaic systems. The proposed model includes solar irradiation and ambient temperature of photovoltaic modules as an input vector and the inverter power output is estimated sequentially. We deal with these measurements as random variables and derive a parameter learning algorithm of the model in terms of statistics. Our learning algorithm requires computation of an expectation and joint expectation against solar irradiation and ambient temperature, which are analytically solved from the integral calculus. For testing the proposed modeling algorithm, we utilize realistic measurement data sets obtained from the Seokwang Solar power plant in Youngcheon, Korea. We demonstrate reliability and superiority of the proposed photovoltaic system model by observing error signals between a practical system output and its estimation.