• Title/Summary/Keyword: Monte carlo analysis

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OCT Signal Analysis and Optimization in Dental Medium using Monte-Carlo Simulation (몬테카를로 시뮬레이션을 이용한 치아 조직내 OCT 신호 해석 및 최적화)

  • 황대석;이승용;김신자;류광렬;이호근;이영우
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2004.05b
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    • pp.321-323
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    • 2004
  • We developed the monte-carlo simulation code for analysis of the On signal in dental medium. In calculation, we obtain the two different propagation signals as a function of the probing depth. Signal 2 begins to exceed the signal 1 at a very small probing depth(=60${\mu}{\textrm}{m}$). For reduce the signal, detection area is limited to radius and detection angle. As numerical result, probing depth becomes appoximately 500${\mu}{\textrm}{m}$.

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Foreign Detection Based on Wavelet Transform Algorithm with Image Analysis Mechanism in the Inner Wall of the Tube

  • Zhu, Jinlong;Yu, Fanhua;Sun, Mingyu;Zhao, Dong;Geng, Qingtian
    • Journal of Information Processing Systems
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    • v.15 no.1
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    • pp.34-46
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    • 2019
  • A method for detecting foreign substances in mould based on scatter grams was presented to protect moulds automatically during moulding production. This paper proposes a wavelet transform foreign detection method based on Monte Carlo analysis mechanism to identify foreign objects in the tube. We use the Monte Carlo method to evaluate the image, and obtain the width of the confidence interval by the deviation statistical gray histogram to divide the image type. In order to stabilize the performance of the algorithm, the high-frequency image and the low-frequency image are respectively drawn. By analyzing the position distribution of the pixel gray in the two images, the suspected foreign object region is obtained. The experiments demonstrate the effectiveness of our approach by evaluating the labeled data.

Uncertainty Analysis for Speed and Power Performance in Sea Trial using Monte Carlo Simulation (몬테카를로 시뮬레이션을 이용한 시운전 선속-동력 성능에 대한 불확실성 해석)

  • Seo, Dae-Won;Kim, Min-Su;Kim, Sang-Yeob
    • Journal of the Society of Naval Architects of Korea
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    • v.56 no.3
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    • pp.242-250
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    • 2019
  • The speed and power performance of a ship is not only a guarantee issue between the ship owner and the ship-yard, but also is related with the Energy Efficiency Design Index (EEDI) regulation. Recently, International Organization for Standardization (ISO) published the procedure of the measurement and assessment for ship speed and power at sea trial. The results of speed and power performance measured in actual sea condition must inevitably include various uncertainty factors. In this study, the influence for systematic error of shaft power measurement system was examined using the Monte Carlo simulation. It is found that the expanded uncertainty of speed and power performance is approximately ${\pm}1.2%$ at the 95% confidence level(k=2) and most of the uncertainty factor is attributed to shaft torque measurement system.

Hierarchical Bayes Analysis of Smoking and Lung Cancer Data

  • Oh, Man-Suk;Park, Hyun-Jin
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.115-128
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    • 2002
  • Hierarchical models are widely used for inference on correlated parameters as a compromise between underfitting and overfilling problems. In this paper, we take a Bayesian approach to analyzing hierarchical models and suggest a Markov chain Monte Carlo methods to get around computational difficulties in Bayesian analysis of the hierarchical models. We apply the method to a real data on smoking and lung cancer which are collected from cities in China.

Reliability Analysis of Open Cell Caisson Breakwater Against Circular Slip Failure (무공케이슨 방파제의 원호활동에 대한 신뢰성 분석)

  • Kim, Sunghwan;Huh, Jungwon;Kim, Dongwook
    • Journal of the Korean Geosynthetics Society
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    • v.18 no.4
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    • pp.193-204
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    • 2019
  • Reliability analyses of sixteen domestic design cases of open cell caisson breakwaters against circular sliding failure were conducted in this study. For the reliability analyses, uncertainties of parameters of soils, mound, and concrete cap were assessed. Bishop simplified method was used to obtain load and resistance of open cell caisson breakwater for randomly generated open cell caisson breakwater. Sufficient number of Monte Carlo simulations were conducted for randomly generated open cell caisson breakwaters, and statistical analysis was conducted on loads and resistances collected from the large number of Monte Carlo simulations. Probability of failure produced from Monte Carlo simulation has a nonconvergence issue for very low probability of failure; therefore, First-Order Reliability Method (FORM) was conducted using the statistical characteristics of loads and resistances of open cell caisson breakwaters. In addition, effects of safety factor, uncertainties of load and resistance, and correlation between load and resistance on reliability of open cell caisson breakwaters against circular sliding failure were examined.

A Ship-Valuation Model Based on Monte Carlo Simulation (몬테카를로 시뮬레이션방법을 이용한 선박가치 평가)

  • Choi, Jung-Suk;Lee, Ki-Hwan;Nam, Jong-Sik
    • Journal of Korea Port Economic Association
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    • v.31 no.3
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    • pp.1-14
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    • 2015
  • This study utilizes Monte Carlo simulation to forecast the time charter rate of vessels, the three-month Libor interest rate, and the ship demolition price, to mitigate future uncertainties involving these factors. The simulation was performed 10,000 times to obtain an exact result. For the empirical analysis - based on considerations in ordering ships in 2010-a comparison between the Monte Carlo simulation-based stochastic discounted cash flow (DCF) method and traditional DCF methods was made. The analysis revealed that the net present value obtained through Monte Carlo simulation was lower than that obtained via regular DCF methods, alerting the owners to risks and preventing them from placing injudicious orders for ships. This research has implications in reducing the uncertainties that future shipping markets face, through the use of a stochastic DCF approach with relevant variables and probability methods.

Structural Safety Analysis of Launching System Through Monte-Carlo Simulation (몬테 카를로 시뮬레이션을 통한 발사관 구조 안전성 분석)

  • Park, Chul-Woo;Lee, Onsoo;Shin, Hyo-Sub;Park, Jin-Yong;Lee, Dong-Ju
    • Journal of the Korea Society for Simulation
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    • v.27 no.4
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    • pp.69-77
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    • 2018
  • Launching system is designed to store the payload, withstand the rigors, and prevent it from rusting and damaging. The behavior during initial deployment of the missile is determined by production, assembly and insertion condition of a launching tube and a missile. The purpose of this research is to confirm the safety of a launching tube by statistically analyzing behavior of the missile, during initial deployment stage. Error parameters which effect initial behavior of the missile are selected and analyzed through Monte-Carlo Simulation. Based on the result of simulation, tip-off and stress distribution between rail and shoe is predicted by using the commercial analysis program called Recurdyn. Lastly, the safety factor is calculated based on yield strength of the material and maximum stress of the rail during the process of launching. The safety of the launching system is verified from the result of the safety factors.

Stochastic analysis for Real Rate Interest of Building Life Cycle Cost(LCC) with Monte-Carlo Simulation (몬테카를로 시뮬레이션을 이용한 건축물 생애주기비용(LCC)의 실질할인율에 대한 확률론적 분석)

  • Kim, Bum-Sic;Jung, Young-Han
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2012.05a
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    • pp.161-163
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    • 2012
  • Recently on Value Engineering(VE) and Life Cycle Cost(LCC) social interests is increasing. The government Turn Key, BTL projects and public works projects, such as VE and LCC Analysis on the value and economic analysis is mandatory. And accordingly the VE and LCC analysis is underway for the various studies. However, there is a problem existing in the LCC analysis. Worth the cost varies according to the flow of time. However, the real interest rate during the LCC analysis of buildings in calculation time for interest rates and inflation are not considering the value of the flow. In other words, a few years using the average value of the deterministic analysis method has been adopted. These costs for the definitive analysis of the cost of an uncertain future, unforeseen changes resulting hazardous value. In this study of the last 15 years interest rates and inflation targeting by using Monte-Carlo Simulation is to perform probabilistic analysis. This potential to overcome uncertainties of the cost of building a more scientific and LCC Estimation of the probability value of the real interest rate is presented.

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Development of 2-D Water Quality Management Model by Using Reliability Analysis (신뢰도 해석기법을 이용한 2차원 수질관리모형의 개발)

  • Kim, Sang-Ho;Han, Kun-Yeun;Kim, Won;Choi, Hung-Sik
    • Journal of Korea Water Resources Association
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    • v.35 no.5
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    • pp.463-474
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    • 2002
  • A two-dimensional water quality management model, Unsteady/Uncertainty Water Quality Model(UUWQM), is developed for a hydrodynamic analysis, an advection-diffusion analysis, and a reliability analysis by using uncertainty technique. The model is applied to the 35 km reach of Sungju to Hyunpoong in the midstream of Nakdong River. 2-D hydrodynamic and water quality analyses are peformed in this reach. Important input variables are decided by sensitivity analysis and verified by Monte Carlo method. Frequency distributions of water quality concentrations are computed from MFOSM method and Monte Carlo method at several locations in this study area. A water quality management system is constructed by calculating the violation probabilities of existing water quality standards.

Deterministic and Stochastic Water Quality Analysis in the Nakdong River (낙동강 유역에서의 확정론적 및 추계학적 수질해석)

  • Han, Kun-Yeun;Choi, Hyun-Sang;Kim, Sang-Ho
    • Journal of Korea Water Resources Association
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    • v.35 no.4 s.129
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    • pp.385-395
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    • 2002
  • A stochastic model using FOEA(First-Order Error-Analysis) and Monte Carlo Method is developed to predict water quality variation in a river. A sensitivity analysis using influential matrix is performed to determine the significant reaction coefficients. Also the BFGS (Broyden-Fletcher-Goldfarb-Shanno) optimization method is applied to estimate the optimal values of the major reaction coefficients. The developed stochastic model is applied to the real study reach and the results are agreed well with those of deterministic analysis. The process for analyzing the uncertainties of the discharge, water quality and reaction coefficients of headwater and tributaries is included in the model to estimate the influence on the water quality variation at downstream. The extents of contribution of the uncertainties influencing on the total uncertainty can be evaluated from the results of the model.