• Smart Structures and Systems
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• v.26 no.3
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• pp.311-318
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• 2020

The goal of this study is to analytically and non-stochastically generate structural uncertainty behaviors of isotropic beams and laminated composite plates under plane stress conditions by using an interval finite element method. Uncertainty parameters of structural properties considering resistance and load effect are formulated by interval arithmetic and then linked to the finite element method. Under plane stress state, the isotropic cantilever beam is modeled and the laminated composite plate is cross-ply lay-up [0/90]. Triangular shape with a clamped-free boundary condition is given as geometry. Through uncertainties of both Young's modulus for resistance and applied forces for load effect, the change of structural maximum deflection and maximum von-Mises stress are analyzed. Numerical applications verify the effective generation of structural behavior uncertainties through the non-stochastic approach using interval arithmetic and immediately the feasibility of the present method.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.435-439
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• 1998

A control strategy for flexible structure under irregular disturbance by using of$\boxDr$random gain$\boxUl$is developed and implemented. System equation is transformed to stochastic domain by F-P-K approach from physical domain. A controller is designed in the stochastic domain, accordingly system is controlled by$\boxDr$random gain$\boxUl$in time domain. In the paper, a new control technique is successfully employed for flexible system under white noise, and the result is verified by Monte-Carlo simulation and compared with the performance via LQR controller.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.9
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• pp.37-49
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• 1992

The standard definition of computational vision is a set of inverse problems of recovering surfaces from images. Thus the common characteristics of the most early vision problems are ill-posed. The main idea for solving ill-posed problems is to restrict the class of admissible solutions by introducing suitable a priori knowledge. Standard regurarization methods lead to satisfactory solutions of early vision problems but cannot deal effectively and directly with a few general problems, such as discontinuity and fusion of information from multiple modules. In this paper, we discuss limitations of standard regularization theory and present new stochastic method. We will outline a rigorous approach to overcome part of ill-posedness of image restoration, edge detection, and stereo vision problems, based on Bayes estimation and MRF(Markov random field) model, that effectively deals with the problems. This result makes one hope that this framework could be useful in the solution of other vision problems.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1346-1349
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• 2010

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.485-492
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• 1998

Most forecasting models often fail to produce appropriate forecasts because we build a model based on the assumption of the data being generated from the only one stochastic process. However, in many real problems, the time series data are generated from one stochastic process for a while and then abruptly undergo certain structural changes. In this paper, we assume the basic underlying process is the simple state-space model with random level and deterministic drift but interrupted by three types of exogenous shocks: level shift, drift change, outlier. A Bayesian procedure to detect, estimate and adapt to the structural changes is developed and compared with simple, double and adaptive exponential smoothing using simulated data and the U.S. leading composite index.

• Nuclear Engineering and Technology
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• v.29 no.1
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• pp.68-77
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• 1997

The reactor power control system is described in the fashion of the order increased LQR system. To obtain the optimal state feedback gain vectors, the weighting matrix of the performance function should be determined. Since the contentional method has some limitations, stochastic searching methods are investigated to optimize the LQR weighting matrix using the modified genetic algorithm combined with the simulated annealing, a new optimizing tool named the hybrid MGA-SA is developed to determine the weighting parameters of the LQR system. This optimizing tool provides a more systematic approach in designing the LQR system. Since it can be easily incorporated with any forms of the cost function, it also provides the great flexibility in the optimization problems.

• Journal of the military operations research society of Korea
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• v.27 no.2
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• pp.76-87
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• 2001

The effect of variable hit probabilities in the stochastic duel are examined. The objective of this study is to evaluate the outcomes of combat under the situations which we assume either round dependent hit probabilities or time dependent hit probabilities. Due to the complexity of an analytic approach to large-sized battles, a simulation modeling technique has been introduced. several specific examples are demonstrated fire allocation strategies. Output measures are compared among cases each with its own type of hit probability fashion such as constant, round to round, or time dependent manners. For these specific cases, the advantages of round to round improvement or increasing function of time for the hit probability are displayed.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.445-450
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• 2007

본 논문에서는 "확률적 배낭(stochastic knapsack)" 문제에 대하여 잘 알려진 Complete Sharing(CS), Complete Partitioning(CP)이 트래픽 특성에 따라 성능의 차이가 나타난다는 약점과 각 정책(policy)들의 평균 성능에 대한 최적 파라미터들을 트래픽 특성에 따라 결정하여야 한다는 약점을 보완하는 모델에 근거한 "Parallel Rollout(PR)"에 기초한 적응적인 정책(adaptive policy)을 제안한다. 주어진 트래픽 모델을 병합한 확률적 배낭 문제를 마코프 결정 과정(Markov Decision Process, MDP)으로 모델링하고, 마코프 결정 과정상에서 기존의 주어진 정책들을 PR 기법을 적용, 하나의 정책으로 융합하고 그 정책이 기존의 주어진 어떤 정책보다도 성능이 같거나 더 뛰어나다는 이론적 근거를 실험을 통하여 확인한다.

• Structural Monitoring and Maintenance
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• v.2 no.2
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• pp.133-143
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• 2015

Civil engineering infrastructure is aging and requires cost-effective maintenance strategies to enable infrastructure systems operate reliably and sustainably. This paper presents an approach for determining risk-cost balanced repair strategy of corrosion damaged reinforced concrete structures with consideration of uncertainty in structural resistance deterioration. On the basis of analytical models of cover concrete cracking evolution and bond strength degradation due to reinforcement corrosion, the effect of reinforcement corrosion on residual load carrying capacity of corroded reinforced concrete structures is investigated. A stochastic deterioration model based on gamma process is adopted to evaluate the probability of failure of structural bearing capacity over the lifetime. Optimal repair planning and maintenance strategies during the service life are determined by balancing the cost for maintenance and the risk of structural failure. The method proposed in this study is then demonstrated by numerical investigations for a concrete structure subjected to reinforcement corrosion. The obtained results show that the proposed method can provide a risk cost optimised repair schedule during the service life of corroded concrete structures.

• Ocean Systems Engineering
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• v.2 no.4
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• pp.257-269
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• 2012

This paper provides a practical stochastic method by which the maximum equilibrium scour depth around spherical bodies exposed to long-crested (2D) and short-crested (3D) nonlinear random waves can be derived. The approach is based on assuming the waves to be a stationary narrow-band random process, adopting the Forristall (2000) wave crest height distribution representing both 2D and 3D nonlinear random waves, and using the regular wave formulas for scour and self-burial depths by Truelsen et al. (2005). An example calculation is provided.