• Title/Summary/Keyword: Stochastic Evolution

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Structural Dynamics Modification of Structures Having Non-Conforming Nodes Using Component Mode Synthesis and Evolution Strategies Optimization Technique (부분 구조 모드 합성법 및 유전 전략 최적화 기법을 이용한 비부합 절점을 가진 구조물의 구조변경)

  • 이준호;정의일;박윤식
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.05a
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    • pp.651-659
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    • 2002
  • Component Mode Synthesis (CMS) is a dynamic substructuring technique to get an approximate eigensolutions of large degree-of-freedom structures divisible into several components. But, In practice. most of large structures are modeled by different teams of engineers. and their respective finite element models often require different mesh resolutions. As a result, the finite element substructure models can be non-conforming and/or incompatible. In this work, A hybrid version of component mode synthesis using a localized lagrange multiplier to treat the non-conforming mesh problem was derived. Evolution Strategies (ESs) is a stochastic numerical optimization technique and has shown a robust performance for solving deterministic problems. An ESs conducts its search by processing a population of solutions for an optimization problem based on principles from natural evolution. An optimization example for raising the first natural frequency of a plate structure using beam stiffeners was presented using hybrid component mode synthesis and robust evolution strategies (RES) optimization technique. In the example. the design variables are the positions and lengths of beam stiffeners.

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Design of Steel Structures Using the Neural Networks with Improved Learning (개선된 인공신경망의 학습방법에 의한 강구조물의 설계)

  • Choi, Byoung Han;Lim, Jung Hwan
    • Journal of Korean Society of Steel Construction
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    • v.17 no.6 s.79
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    • pp.661-672
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    • 2005
  • For the efficient stochastic optimization of steel structures for which a large number of analyses is required, artificial neural networks,which have emerged as a powerful tool that could have been used to replace time-consuming procedures in many scientific or engineering applications, are applied. They are utilized for the solution of the equilibrium equations resulting from the application of the finite element method in connection with the reanalysis type of problem, for which a large number of finite element analyses are required in this study. As such, the use of artificial neural networks to predict finite element analysis outputs simplifies and facilitates the performance of the stochastic optimal design of structural systems where a trained neural network is used to replace the structural reanalysis phase. Moreover, to improve efficiency of used artificial neural networks, genetic algorithm is utilized. The stochastic optimizer used in this study is an algorithm based on the evolution theory. The efficiency of the proposed procedure is examined in problems with both volume (weight) functions and real-world cost functions

A Development of Hourly Rainfall Simulation Technique Based on Bayesian MBLRP Model (Bayesian MBLRP 모형을 이용한 시간강수량 모의 기법 개발)

  • Kim, Jang Gyeong;Kwon, Hyun Han;Kim, Dong Kyun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.3
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    • pp.821-831
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    • 2014
  • Stochastic rainfall generators or stochastic simulation have been widely employed to generate synthetic rainfall sequences which can be used in hydrologic models as inputs. The calibration of Poisson cluster stochastic rainfall generator (e.g. Modified Bartlett-Lewis Rectangular Pulse, MBLRP) is seriously affected by local minima that is usually estimated from the local optimization algorithm. In this regard, global optimization techniques such as particle swarm optimization and shuffled complex evolution algorithm have been proposed to better estimate the parameters. Although the global search algorithm is designed to avoid the local minima, reliable parameter estimation of MBLRP model is not always feasible especially in a limited parameter space. In addition, uncertainty associated with parameters in the MBLRP rainfall generator has not been properly addressed yet. In this sense, this study aims to develop and test a Bayesian model based parameter estimation method for the MBLRP rainfall generator that allow us to derive the posterior distribution of the model parameters. It was found that the HBM based MBLRP model showed better performance in terms of reproducing rainfall statistic and underlying distribution of hourly rainfall series.

Decision of Optimal Magnetic Field Shielding Location around Power System Using Evolution Strategy Algorithm (Evolution Strategy 알고리즘을 이용한 송진선로 주변에서의 최적 자계차폐 위치선정)

  • Choe, Se-Yong;Na, Wan-Su;Kim, Dong-Hun;Kim, Dong-Su;Lee, Jun-Ho;Park, Il-Han;Sin, Myeong-Cheol;Kim, Byeong-Seong
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.51 no.1
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    • pp.5-14
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    • 2002
  • In this paper, we analyze inductive interference in conductive material around 345 kV power transmission line, and evaluate the effects of mitigation wires. Finite element method (FEM) is used to numerically compute induced eddy currents as well as magnetic fields around powder transmission lines. In the analysis model, geometries and electrical properties of various elements such as power transmission line, buried pipe lines, overhead ground wire, and conducting earth are taken into accounts. The calculation shows that mitigation wire reduces fairly good amount of eddy currents in buried pipe line. To find the optimum magnetic field shielding location of mitigation wire, we applied evolution strategy algorithm, a kind of stochastic approach, to the analysis model. Finally, it was shown that we can find more effective shielding effects with optimum location of one mitigation wire than with arbitrary location of multi-mitigation wires around the buried pipe lines.

Seismic Behaviors of a Bridge System in the Stochastic Perspectives (추계론적 이론을 이용한 교량내진거동분석)

  • Mha, Ho-Seong
    • Journal of the Earthquake Engineering Society of Korea
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    • v.9 no.6 s.46
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    • pp.53-58
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    • 2005
  • Semi-analytical methodology to examine the dynamic responses of a bridge is developed via the joint probability density function. The evolution of joint probability density function is evaluated by the semi-analytical procedure developed. The joint probability function of the bridge responses can be obtained by solving the path-integral solution of the Fokker-Planet equation corresponding to the stochastic differential equations of the system. The response characteristics are observed from the joint probability density function and the boundary of the envelope of the probability density function can provide the maxima ol the bridge responses.

DEELOPMENTS IN ROBUST STOCHASTIC CONTROL;RISK-SENSITIVE AND MINIMAL COST VARIANCE CONTROL

  • Won, Chang-Hee
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.107-110
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    • 1996
  • Continuing advances in the formulation and solution of risk-sensitive control problems have reached a point at which this topic is becoming one of the more intriguing modern paradigms of feedback thought. Despite a prevailing atmosphere of close scrutiny of theoretical studies, the risk-sensitive body of knowledge is growing. Moreover, from the point of view of applications, the detailed properties of risk-sensitive design are only now beginning to be worked out. Accordingly, the time seems to be right for a survey of the historical underpinnings of the subject. This paper addresses the beginnings and the evolution, over the first quarter-century or so, and points out the close relationship of the topic with the notion of optimal cost cumulates, in particular the cost variance. It is to be expected that, in due course, some duality will appear between these notions and those in estimation and filtering. The purpose of this document is to help to lay a framework for that eventuality.

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The Development of Robot System for Assessing Slip Resistance (미끄럼 저항 측정을 위한 로봇 시스템 개발)

  • Kim, Jung Soo
    • Journal of the Korean Society of Safety
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    • v.28 no.5
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    • pp.1-4
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    • 2013
  • The main objective was to design and develop a prototype robot system for assessing slip resistance. The developed robot system will be able to be used for stochastic nature of friction in the whole workplace. The second objective was to evaluate its operating condition in the laboratory, using a dreg sled type slipmeter(BOT-3000) as reference device. It was found that COF(Coefficient of Friction) measured with robot system was similar to that of BOT-3000 when sliding velocity was reached at 0.2m/s. The robot system might be the more promising one than any traditional measurement devices. A further evolution of prototype devices, as well as the development of test methods for that's various applications, is to be started in forthcoming studies.

Effect of cover cracking on reliability of corroded reinforced concrete structures

  • Chen, Hua-Peng;Nepal, Jaya
    • Computers and Concrete
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    • v.20 no.5
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    • pp.511-519
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    • 2017
  • The reliability of reinforced concrete structures is frequently compromised by the deterioration caused by reinforcement corrosion. Evaluating the effect caused by reinforcement corrosion on structural behaviour of corrosion damaged concrete structures is essential for effective and reliable infrastructure management. In lifecycle management of corrosion affected reinforced concrete structures, it is difficult to correctly assess the lifecycle performance due to the uncertainties associated with structural resistance deterioration. This paper presents a stochastic deterioration modelling approach to evaluate the performance deterioration of corroded concrete structures during their service life. The flexural strength deterioration is analytically predicted on the basis of bond strength evolution caused by reinforcement corrosion, which is examined by the experimental and field data available. An assessment criterion is defined to evaluate the flexural strength deterioration for the time-dependent reliability analysis. The results from the worked examples show that the proposed approach is capable of evaluating the structural reliability of corrosion damaged concrete structures.

A Study on the Optimum Structural Design for Oil Tankers Using Multi-Objective Optimization

  • Jang, Chang-Doo;Shin, Sang-Hun
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1998.04a
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    • pp.245-253
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    • 1998
  • Recently, the importance of multi-objective optimization techniques and stochastic search methods is increasing. The stochastic search methods have the concepts of the survival of the fittest and natural selection such as genetic algorithms(GA), simulated annealing(SA) and evolution strategies (ES). As many accidents of oil tankers cause marine pollution, oil tankers of double hull or mid deck structure are being built to minimize the marine pollution. For the improvement of oil tanker design technique, an efficient optimization technique is proposed in this study. Multi-objective optimization problem of weight and cost of double hull and mid deck tanker is formulated. Discrete design variables are used considering real manufacturing, and the concept of relative production cost is also introduced. The ES method is used as an optimization technique, and the ES algorithm was developed to generate a more efficient Pareto optimal set.

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Risk-based optimum repair planning of corroded reinforced concrete structures

  • Nepal, Jaya;Chen, Hua-Peng
    • 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.