• Water for future
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• v.13 no.4
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• pp.41-50
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• 1980

The prupose of this study are the theoretical examination of Gamma distribution function and its application to hydraulic engineering, that is studying the simulation of monthly streamflow by the Gamma distribtution function model(Gamma Model) based on Monte Carlo technique. In the analysis, monthly streamflow data in the Nak Dong River, the Han River, and the Keum River were used and the data were changed to modular coefficient in order to make the analysis convenient. At first, the fitness of monthly streamflow to 2-Parameter Gamma distribution was tested by Chi-square and Kolmogrov-Smironov test, by which it was found the monthly streamflow were fit well to this Gamma distribution function. Then, the Gamma Model based on the Gamma distribution and Monte Carlo Method was used in the simulation of monthly streamflow, and simulateddata showed that all their stastical characteristics were preserved well in the simulation. Consequently, it can be concluded that the Gamma Model is suitable for the simulation of monthly streamflow series directly by using the Mote Carlo technique.

• Journal of the military operations research society of Korea
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• v.22 no.2
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• pp.166-181
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• 1996

Aircraft survivability is determined by the susceptibility and the vulnerability. The aircraft susceptibility and vulnerability depend upon the hardware and software factors. Each of the hardware and software factors consisted of the qualitative and quantitative attributes varies according to the time of the mission. In order to establish the mathermatical model to analyze and evaluate the aircraft survivability, qualitative factors have to be transformed into quantitative factors. Even if many researches in the area of dynamic concept analysis and conversion of qualitative factors into the quantitative factors has been insufficient. This research enhances these insufficient area by developing a reliable aircarft survivability analysis method. The major areas of this research are as follows. First, a method for the conversion of the qualitative factors into the quantitative factors is developed by combining the Fuzzy Set Theory concept and the Delphi Technique. Second, by using the stochastic network diagram for the dynamic survivability analysis, the aircraft survivability and the probability of kill are calculated from the state probability for the situation during mission. The advantage of the analysis technique developed in this research includes ease of use and flexibility. In other words, in any given aircraft's mission execution under any variable probability density function, the developed computer program is able to analyze and evaluate the aircraft survivability.

• Journal of KIISE
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• v.44 no.7
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• pp.726-732
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• 2017

In practical distributed sensing and prediction applications over wireless sensor networks (WSN), environmental sensing activities are highly dynamic because of noisy sensory information from moving source signals. The recent distributed online convex optimization frameworks have been developed as promising approaches for solving approximately stochastic learning problems over network of sensors in a distributed manner. Negligence of mobility consequence in the original distributed saddle point algorithm (DSPA) could strongly affect the convergence rate and stability of learning results. In this paper, we propose an integrated sliding windows mechanism in order to stabilize predictions and achieve better convergence rates in cooperative detection of a moving source signal scenario.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.

• Earthquakes and Structures
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• v.18 no.2
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• pp.249-261
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• 2020

Seismic loss estimation studies require fragility curves which are usually derived using ground motion datasets. Ground motion records can be either in the form of recorded or simulated time histories compatible with regional seismicity. The main purpose of this study is to investigate the use of alternative ground motion datasets (simulated and real) on the fragility curves. Simulated dataset is prepared considering regional seismicity parameters corresponding to Erzincan using the stochastic finite-fault technique. In addition, regionally compatible records are chosen from the NGA-West2 ground motion database to form the real dataset. The paper additionally studies the effects of hazard variability and two different fragility curve derivation approaches on the generated fragility curves. As the final step for verification purposes, damage states estimated for the fragility curves derived using alternative approaches are compared with the observed damage levels from the 1992 Erzincan (Turkey) earthquake (Mw=6.6). In order to accomplish all these steps, a set of representative masonry buildings from Erzincan region are analyzed using simplified structural models. The results reveal that regionally simulated ground motions can be used alternatively in fragility analyses and damage estimation studies.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.2
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• pp.31-40
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• 1995

This study was conducted to get best fitting frequency distribution for the annual run- off and to simulate long series of annual flows by single-season first order Markov Model with comparison of statistical parameters which were derived from observed and synthetic flows at four watersheds in Seom Jin and Yeong San river systems. The results summarized through this study are as follows. 1. Hydrologic persistence of observed flows was acknowledged by the correlogram analysis. 2. A normal distribution of the annual runoff for the applied watersheds was confirmed as the best one among others by Kolmogorov-Smirnov test. 3. Statistical parameters were calculated from synthetic flows simulated by normal dis- tribution. In was confirmed that mean and standard deviation of simulated flows are much closer to those of observed data than except coefficient of skewness. 4. Hydrologic persistence between observed flows and synthetic flows simulated was also confirmed by the correlogram analysis. 5. It is to be desired that generation technique of synthetic flow in this study would be compared with other simulation techniques for the objective time series.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.2 no.3
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• pp.143-151
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• 1990

The sediment transport in shallow water regions has been studied in various ways and, accordingly, many formulas have been proposed. However, when these formulas are applied practically in the field, they are not sufficient to fully estimate the sediment transport rate yet. The primary reason is how to take into account the effect of irregularities of field waves : wave heights, periods and directions. Therefore, it is necessary to investigate stochastic and kinematic characteristics of waves in three dimensional random seas in order to more accurately estimate it. In particular, the asymmetrical properties of directional spectrum become significant and play an important role in various phenomena in a shallow water region. In this study, their effects of incident waves the joint distribution of wave heights, periods and directions are investigated through field measurements.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.193-204
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• 1995

Many studies show that the value of the warehouse is good. However, studies explicitly mention the tradeoff between costs of operating the warehouse and benefits from the warehouse. Also, it is important to know when the benefits overcome the costs. We study a one-warehouse/N-retailer(s,Q) distribution system with stochastic lead times in order to answer two questions: "What are the optimal policies of the system that minimizes total system costs\ulcorner" and given the optimal policies, "Is the value of the warehouse always good\ulcorner" We use an analytical model for answering the questions. We find that the optimal policies are different from those with deterministic lead times. In fact it is reverse. We alse find the existence of the breakeven point beyond which the benefits starts overcomming the costs. And, we show that one of the breakeven points is the mean ratio of a supplier's lead time to transportation lead time between the warehouse and the retailer. Finally, we show that the breakeven point is sensitive to the ratio of holding costs of the warehouse and the retailer and it is also sensitive to the unit backorder costs at the retailer.sts at the retailer.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1801-1806
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• 2004

Stochastic nature of subgrid-scale stress causes the predictability problem in large eddy simulation (LES) by which the LES solution field decorrelates with field from filtered directnumerical simulation (DNS). In order to evaluate the predictability limit in a priori sense, the information on the interplay between resolved scale and subgrid-scale (SGS) is required. In this study, the analysis on the inter-scale interaction is performed by applying tophat and cutoff filters to DNS database of flow over a circular cylinder at Reynolds number of 3900. The effect of filter shape is investigated on the interpretation of correlation between scales. A critique is given on the use of tophat filter for SGS analysis using DNS database. It is shown that correlations between Karman vortex and SGS kinetic energy drastically decrease when the cutoff filter is used, which implies that the small scale universality holds even in the presence of the large scale coherent structure.

• Earthquakes and Structures
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• v.8 no.4
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• pp.915-934
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• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.