• Title/Summary/Keyword: 몬테카를로 모사기법

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Assessment of Extreme Wind Risk for Window Systems in Apartment Buildings Based on Probabilistic Model (확률 모형 기반의 아파트 창호 시스템 강풍 위험도 평가)

  • Ham, Hee Jung;Yun, Woo-Seok;Choi, Seung Hun;Lee, Sungsu;Kim, Ho-Jeong
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.28 no.6
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    • pp.625-633
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    • 2015
  • In this study, a coupled probabilistic framework is developed to assess wind risk on apartment buildings by using the convolution of wind hazard and fragility functions. In this framework, typhoon induced extreme wind is estimated by applying the developed Monte Carlo simulation model to the climatological data of typhoons affecting Korean peninsular from 1951 to 2013. The Monte Carlo simulation technique is also used to assess wind fragility function for 4 different damage states by comparing the probability distributions of the window system's resistance performance and wind load. Wind hazard and fragility functions are modeled by the Weibull and lognormal probability distributions based on simulated wind speeds and failure probabilities. The modeled functions are convoluted to obtain the wind risk for the different damage levels. The developed probabilistic framework clearly shows that wind risk are influenced by various important characteristics of terrain and apartment building such as location of building, exposure category, topographic condition, roof angle, height of building, etc. The risk model presented in this paper can be used as tools to predict economic loss estimation and to establish wind risk mitigation plan for the existing building inventory.

Markov Chain Monte Carlo Simulation to Estimate Material Properties of a Layered Half-space (층상 반무한 지반의 물성치 추정을 위한 마르코프 연쇄 몬테카를로 모사 기법)

  • Jin Ho Lee;Hieu Van Nguyen;Se Hyeok Lee
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.36 no.3
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    • pp.203-211
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    • 2023
  • A Markov chain Monte Carlo (MCMC) simulation is proposed for probabilistic full waveform inversion (FWI) in a layered half-space. Dynamic responses on the half-space surface are estimated using the thin-layer method when a harmonic vertical force is applied. Subsequently, a posterior probability distribution function and the corresponding objective function are formulated to minimize the difference between estimations and observed data as well as that of model parameters from prior information. Based on the gradient of the objective function, a proposal distribution and an acceptance probability for MCMC samples are proposed. The proposed MCMC simulation is applied to several layered half-space examples. It is demonstrated that the proposed MCMC simulation for probabilistic FWI can estimate probabilistic material properties such as the shear-wave velocities of a layered half-space.

Inverse Heat Transfer Analysis Using Monte Carlo Method in Gas-Filled Micro-Domains Enclosed by Parallel Plates (몬테카를로 방법을 이용한 기체로 채워진 평판 사이의 마이크로 역열전달 해석)

  • Kim, Sun-Kyoung
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.35 no.7
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    • pp.657-664
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    • 2011
  • This study proposes an inverse method for estimating the boundary temperature in a gas-filled, onedimensional parallel domain enclosed by parallel plates. The distance between the plates is considered submicron to one mm. In the current method, it is assumed that the conditions of both heat flux and temperature are simultaneously applicable to one boundary, while no conditions are applicable to the other boundary The temperature on one of the boundaries should be inversely determined from the known temperature and heat flux on the other boundary. This study proposes a procedure for estimating the unknown boundary temperature through Monte Carlo simulation. Both the forward and inverse problems employ the Monte Carlo approach. The forward (direct) problem is solved by using the direct simulation Monte Carlo while the inverse solution is obtained by the simulated annealing.

Prediction of Failure Probability of Breakwater using Neural Network (신경망을 활용한 사석식 방파제의 파괴확률예측)

  • Kim, Dong-Hyawn;Park, Woo-Sun;Han, Sang-Hun
    • Ocean and Polar Research
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    • v.25 no.spc3
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    • pp.347-351
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    • 2003
  • A new approach to reliability analysis of rubble mound breakwater using neural network is proposed. At first, a neural network model which can estimate the stability number of any breakwaters for some design conditions is trained. Then, the neural network model is integrated with Monte Carlo simulation technique in order to calculate probability of failure for the breakwater. The proposed technique is compared with conventional approach using empirical formula.

Performance Moment Integration (PMI) for Prediction Performance Changes of a Loudspeaker Model Due to the Uncertainty of Design Variables (성능 모멘트 적분법을 이용한 설계 변수의 불확실성에 기인한 스피커 모델의 성능 변동 예측)

  • Kang, Byung-Su;Lee, Sang-kyun;Kim, Dong-Wook;Kim, Dong-Hun
    • Proceedings of the KIEE Conference
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    • 2015.07a
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    • pp.766-767
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    • 2015
  • 전자기 관련 제품에서 제작공차에 의한 성능변동의 확률론적 분포특성을 효율적으로 예측하기 위해 성능 모멘트 적분법을 도입하였다. 제안된 기법을 검증하기 위해 간단한 수학예제와 스피커 모델의 폴피스 사이 공극의 평균자속 밀도에 대한 확률론적 분포특성 예측을 수행하고, 이를 기존 확률론적 분포특성 예측 기법과 비교하였다. 또한 몬테카를로 수치모사법을 이용하여 도출된 성능의 확률론적 분포특성 예측 값을 재계산 후 비교함으로써 제안된 기법의 정밀도를 검증하였다.

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Stress Analysis of Single-Lap Adhesive Joints Considering Uncertain Material Properties (물성치의 불확실성을 고려한 단일 겹치기 이음의 응력해석)

  • 김태욱
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.16 no.4
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    • pp.401-406
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    • 2003
  • This paper deals with stress analysis of single-lap adhesive joints which have uncertain material properties. Basically, material properties have a certain amount of scatter and such uncertainties can affect the performance of joints. In this paper, the convex modeling is introduced to consider such uncertainties in calculating peel and shear stress of adhesive joints and the results are compared with those from the Monte Carlo simulation. Numerical results show that stresses increase when uncertainties considered, which indicates that such uncertainties should not be ignored for estimation of structural safety. Also, the results obtained by the convex modeling and the Monte Carlo simulation show good agreement, which demonstrates the effectiveness of convex modeling.

Monte Carlo Simulation of Transmission-Type X-ray Tube with Dual-Structured Target (이중 적층 구조 표적을 갖는 투과형 엑스선관의 몬테카를로 전산모사)

  • Kwon Su, Chon
    • Journal of the Korean Society of Radiology
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    • v.17 no.1
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    • pp.107-114
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    • 2023
  • X-ray fluorescence analysis has been widely used in the field of science and industry because it gives information about elements and their concentrations without destruction of samples. To increase analysis accuracy of fluorescence generated by photons of the transmission-type X-ray tube for mixture and compound samples would be recommend to have strong energy near 10 keV and 20 keV simultaneously. Tungsten of 9.65 keV and molybdenum of 17.48 keV were considered as targets with dual deposition structure for obtaining two strong characteristic X-rays, and the transmission-type X-ray tube was analyzed using Geant4 Monte Carlo simulation. The W-Mo structure resulted in strong characteristic X-ray near 10 keV and 20 keV simultaneously. A structure with Mo-W multilayers of 5 ㎛ thick also gave optimal spectrum. Various material combination and thickness optimization for the dual-structured target can give X-ray spectrum with strong characteristic X-ray of specific energies.

Reliability-Based Design Optimization of Electromagnetic Devices by Evaluating Probabilistic Constraints Based on Performance Measure Approach (목표 성능치 기반의 확률구속조건 평가 기법을 이용한 전자기 장치의 신뢰도 기반 최적설계)

  • Kim, Dong-Wook;Kim, Dong-Hun
    • Journal of the Korean Magnetics Society
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    • v.23 no.2
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    • pp.62-67
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    • 2013
  • This paper introduces an effective methodology for reliability-based design optimization of electromagnetic products, where a performance measure approach is adopted to accurately assess probabilistic constrains. Two design problems consisting of a loudspeaker and a superconducting magnetic energy storage system are considered. The efficiency of the proposed method in evaluating the failure probability of performances during the optimization process are compared with the existing method based on the reliability index approach. Moreover, in term of the accuracy of probability failure values, optimized design results are examined with reference values obtained from the Monte Carlo simulation.

Probabilistic Evaluation Methodology for Nuclear Components (원전 주요기기의 확률론적 평가 기법)

  • Lee, Joon-Seong;Kwak, Sang-Log;Kim, Young-Jin;Park, Youn-Won
    • Proceedings of the KSME Conference
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    • 2001.06a
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    • pp.459-464
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    • 2001
  • For major nuclear power plant components periodic inspections and integrity assessments are needed for the safety. But many flaws are undetectable due to sampling inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties, applied load and undetectable flaws. This paper describes a Probabilistic Fracture Mechanics(PFM) analysis based on Monte Carlo(MC) algorithms. Taking important parameters as probabilistic variables such as fracture toughness, crack growth rate and flaw shape, failure probability of major nuclear power plant components is archived as a results of MC simulation. For the verification of these analysis, a comparison study of the PFM analysis using other commercial code, mathematical method is carried out and a good agreement was observed between those results.

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Application of Probabilistic Technique for the Development of Fire Accident Scenarios in Railway Tunnel (확률론적 기법을 활용한 철도터널의 화재사고 시나리오의 구성)

  • 곽상록;홍선호;왕종배;조연옥
    • Journal of the Korean Society for Railway
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    • v.7 no.4
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    • pp.302-306
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    • 2004
  • Many long railway tunnels without emergency evacuation system or ventilation system are under construction or in-use in Korea. In the case of tunnel-fire, many fatalities are occur in current condition. Current safety level is estimated in this study, for the efficient investment on safety. But so many uncertainties in major input parameters make the safety estimation difficult. In this study, probabilistic techniques are applied for the consideration of uncertainties in major input parameters. As results of this study, accident scenarios and survival ratio under tunnel fire accident are determined for various conditions.