• Title/Summary/Keyword: Monte Carlo model

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Trip Assignment for Transport Card Based Seoul Metropolitan Subway Using Monte Carlo Method (Monte Carlo 기법을 이용한 교통카드기반 수도권 지하철 통행배정)

  • Meeyoung Lee;Doohee Nam
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.2
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    • pp.64-79
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    • 2023
  • This study reviewed the process of applying the Monte Carlo simulation technique to the traffic allocation problem of metropolitan subways. The analysis applied the assumption of a normal distribution in which the travel time information of the inter-station sample is the basis of the probit model. From this, the average and standard deviation are calculated by separating the traffic between stations. A plan was proposed to apply the simulation with the weights of the in-vehicle time of individual links and the walking and dispatch interval of transfer. Long-distance traffic with a low number of samples of 50 or fewer was evaluated as a way to analyze the characteristics of similar traffic. The research results were reviewed in two directions by applying them to the Seoul Metropolitan Subway Network. The travel time between single stations on the Seolleung-Seongsu route was verified by applying random sampling to the in-vehicle time and transfer time. The assumption of a normal distribution was accepted for sample sizes of more than 50 stations according to the inter-station traffic sample of the entire Seoul Metropolitan Subway. For long-distance traffic with samples numbering less than 50, the minimum distance between stations was 122Km. Therefore, it was judged that the sample deviation equality was achieved and the inter-station mean and standard deviation of the transport card data for stations at this distance could be applied.

Evaluation of Levee Reliability by Applying Monte Carlo Simulation (Monte Carlo 기법에 의한 하천제방의 안정성 평가)

  • Jeon, Min Woo;Kim, Ji Sung;Han, Kun Yeun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.5B
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    • pp.501-509
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    • 2006
  • The safety of levee that depends on the river flood elevation has been regarded as very important keys to build up various flood prevention systems. However, deterministic methods for computation of water surface profile cannot reflect the effect of possible inaccuracies in the input parameters. The purpose of this study is to develop a methodology of uncertainty computation of design flood level based on steady flow analysis and Monte Carlo simulation. This study addresses the uncertainty of water surface elevation by Manning's coefficients, design discharges, river cross sections and boundary condition. Monte Carlo simulation with the variations of these parameters is performed to quantify the variations of water surface elevations in a river. The proposed model has been applied to the Kumho-river. The reliability analysis was performed within 38.5 km (95 sections) reach considered the variations of the above-mentioned parameters. Overtopping risks were evaluated by comparing the elevations of the flood condition with the those of the levees. The results show that there is a necessity which will raise the levee elevation between 1 cm and 56 cm at 7 sections. The model can be used for preparing flood risk maps, flood forecasting systems and establishing flood disaster mitigation plans as well as complement of conventional levee design.

Visual Tracking Using Monte Carlo Sampling and Background Subtraction (확률적 표본화와 배경 차분을 이용한 비디오 객체 추적)

  • Kim, Hyun-Cheol;Paik, Joon-Ki
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.5
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    • pp.16-22
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    • 2011
  • This paper presents the multi-object tracking approach using the background difference and particle filtering by monte carlo sampling. We apply particle filters based on probabilistic importance sampling to multi-object independently. We formulate the object observation model by the histogram distribution using color information and the object dynaminc model for the object motion information. Our approach does not increase computational complexity and derive stable performance. We implement the whole Bayesian maximum likelihood framework and describes robust methods coping with the real-world object tracking situation by the observation and transition model.

Monte Carlo Simulation of MR Damper Landing Gear Taxiing Mode under Nonstationary Random Excitation

  • Lee, Hyo-Sang;Jang, Dae-Sung;Hwang, Jai-Hyuk
    • Journal of Aerospace System Engineering
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    • v.14 no.4
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    • pp.10-17
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    • 2020
  • When an aircraft is taxiing, excitation force is applied according to the shape of the road surface. The sprung mass acceleration caused by the excitation of the road surface negatively affects the feeling of boarding. This paper addresses the verification process of the semi-active control method applied to improve the feeling of boarding. The Magneto-Rheological damper landing gear model is employed alongside the control method. It is a Oleo-Pneumatic damper filled with a fluid having the characteristics of increasing yield stress when subjected to a magnetic field. The control method involves verifying Skyhook Control Type2 developed by Skyhook control. The Sinozuka white noise model that considers runway characteristics was employed for the road surface in the simulation. The runway road surface obtained through this model has stochastic characteristics, so the dynamic characteristics were analyzed by applying Monte-Carlo simulation. A dynamic analysis was conducted by co-simulating the landing gear model made by RecurDyn and the control method designed by Simulink. Simulation results show that the Skyhook Control Type2 method has the best control effect in the low speed range compared to the passive type (without control) and skyhook control.

Monte Carlo Simulations and DFT Studies of the Structural Properties of Silicon Oxide Clusters Reacting with a Water Molecule

  • Jisu Lee;Gyun-Tack Bae
    • Journal of the Korean Chemical Society
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    • v.67 no.5
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    • pp.333-338
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    • 2023
  • In this study, the H2O reaction with SiO clusters was investigated using ab initio Monte Carlo simulations and density functional theory calculations. Three chemistry models, PBE1/DGDZVP (Model 1), PBE1/DGDZVP (Si atom), and aug-cc-pVDZ (O and H atoms), (Model 2) and PBE1/aug-cc-pVDZ (Model 3), were used. The average bond lengths, as well as the relative and reaction energies, were calculated using Models 1, 2, and 3. The average bond lengths of Si-O and O-H are 1.67-1.75 Å and 0.96-0.97 Å, respectively, using Models 1, 2, and 3. The most stable structures were formed by the H transfer from an H2O molecule except for Si3O3-H2O-1 cluster. The Si3O3 cluster with H2O exhibited the lowest reaction energy. In addition, the Bader charge distributions of the SinOn and (SiO)n-H2O clusters with n = 1-7 were calculated using Model 1. We determined that the reaction sites between H2O and the SiO clusters possessed the highest fraction of electrons.

Risk Model for the Safety Evaluation of Dam and Levee: II. Application (댐 및 하천제방에 대한 위험도 해석기법의 개발 : II. 적용 예)

  • Han, Geon-Yeon;Lee, Jong-Seok
    • Journal of Korea Water Resources Association
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    • v.30 no.6
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    • pp.691-698
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    • 1997
  • The risk assessment model for dam and levee is applied to a river where two adjacent dams are located in the upstream of the watershed. "A" dam is proven to be safe with 200-year precipitation and unsafe with PMP condition, whereas "B" dam to be safe with 200-year precipitation and PMP condition. The computed risk considering the uncertainties of the runoff coefficient. initial water depth and relevant data of the dam and spillway turn out to be equivalent results in Monte-Carlo and AFOSM method. In levee risk model, this study addresses the uncertainty of water surface elevation by Manning's equation. Monte-Carlo simulation with the variations of Manning's roughness coefficient is calculated by assuming that it follows atriangular distribution. The model can be used for preparing flood risk maps, flood warning systems, and establishing nation's flood disaster protection plan.

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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.

The Monte Carlo Simulation and Algorithm on the Relationship Interest Rate Models for the Pricing of Bond Options (채권 옵션의 가격결정을 위한 이자율 모형의 관계에 대한 알고리즘과 몬테 카르로 시뮬레이션)

  • Lee, Gwangyeon;Park, Kisoeb
    • Journal of the Korea Society for Simulation
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    • v.28 no.3
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    • pp.49-56
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    • 2019
  • In this paper, we deal with two pricing of bond options using the relationship between the forward rate model and the Libor rate model. First, we derive a formula for obtaining discounted bond prices using the restrictive condition of the Ritchken and Sankarasubramanian (RS), and then use the volatility function relationship of the forward rate and the Libor rate models to find the analytic solution (AS) of bond options pricing. Second, the price of the bond options is calculated by simulating several scenarios from the presented condition using Monte Carlo Simulation (MCS). Comparing the results of the implementation of the above two pricing methods, the relative error (RE) is obtained, which means the ratio of AS and MCS. From the results, we can confirm that the RE is around 3.9%, which means that the price of the bond options can be predicted very accurately using the MCS as well as AS.

Time-dependent analysis of cable trusses -Part II. Simulation-based reliability assessment

  • Kmet, S.;Tomko, M.;J., Brda
    • Structural Engineering and Mechanics
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    • v.38 no.2
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    • pp.171-193
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    • 2011
  • One of the possible alternatives of simulation-based time-dependent reliability assessment of pre-stressed biconcave and biconvex cable trusses, the Monte Carlo method, is applied in this paper. The influence of an excessive deflection of cable truss (caused by creep of cables and rheologic changes) on its time-dependent serviceability is investigated. Attention is given to the definition of the basic random variables and their statistical functions (basic, mutually dependent random variables such as the pre-stressing forces of the bottom and top cable, structural geometry, the Young's modulus of elasticity of the cables, and the independent variables, such as permanent load, wind, snow and thermal actions). Then, the determination of the response of the cable truss to the loading effects, and the definition of the limiting values considering serviceability of the structure are performed. The potential of the method, using direct Monte Carlo technique for simulation-based time-dependent reliability assessment as a powerful tool, is emphasized. Results obtained by the First order reliability method (FORM) are compared with those obtained by the Monte Carlo simulation technique.

A cross-entropy algorithm based on Quasi-Monte Carlo estimation and its application in hull form optimization

  • Liu, Xin;Zhang, Heng;Liu, Qiang;Dong, Suzhen;Xiao, Changshi
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.13 no.1
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    • pp.115-125
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    • 2021
  • Simulation-based hull form optimization is a typical HEB (high-dimensional, expensive computationally, black-box) problem. Conventional optimization algorithms easily fall into the "curse of dimensionality" when dealing with HEB problems. A recently proposed Cross-Entropy (CE) optimization algorithm is an advanced stochastic optimization algorithm based on a probability model, which has the potential to deal with high-dimensional optimization problems. Currently, the CE algorithm is still in the theoretical research stage and rarely applied to actual engineering optimization. One reason is that the Monte Carlo (MC) method is used to estimate the high-dimensional integrals in parameter update, leading to a large sample size. This paper proposes an improved CE algorithm based on quasi-Monte Carlo (QMC) estimation using high-dimensional truncated Sobol subsequence, referred to as the QMC-CE algorithm. The optimization performance of the proposed algorithm is better than that of the original CE algorithm. With a set of identical control parameters, the tests on six standard test functions and a hull form optimization problem show that the proposed algorithm not only has faster convergence but can also apply to complex simulation optimization problems.