• Title/Summary/Keyword: Monte Carlo simulation

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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.

Characterization of a CLYC Detector and Validation of the Monte Carlo Simulation by Measurement Experiments

  • Kim, Hyun Suk;Smith, Martin B.;Koslowsky, Martin R.;Kwak, Sung-Woo;Ye, Sung-Joon;Kim, Geehyun
    • Journal of Radiation Protection and Research
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    • v.42 no.1
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    • pp.48-55
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    • 2017
  • Background: Simultaneous detection of neutrons and gamma rays have become much more practicable, by taking advantage of good gamma-ray discrimination properties using pulse shape discrimination (PSD) technique. Recently, we introduced a commercial CLYC system in Korea, and performed an initial characterization and simulation studies for the CLYC detector system to provide references for the future implementation of the dual-mode scintillator system in various studies and applications. Materials and Methods: We evaluated a CLYC detector with 95% $^6Li$ enrichment using various gamma-ray sources and a $^{252}Cf$ neutron source, with validation of our Monte Carlo simulation results via measurement experiments. Absolute full-energy peak efficiency values were calculated for gamma-ray sources and neutron source using MCNP6 and compared with measurement experiments of the calibration sources. In addition, behavioral characteristics of neutrons were validated by comparing simulations and experiments on neutron moderation with various polyethylene (PE) moderator thicknesses. Results and Discussion: Both results showed good agreements in overall characteristics of the gamma and neutron detection efficiencies, with consistent ~20% discrepancy. Furthermore, moderation of neutrons emitted from $^{252}Cf$ showed similarities between the simulation and the experiment, in terms of their relative ratios depending on the thickness of the PE moderator. Conclusion: A CLYC detector system was characterized for its energy resolution and detection efficiency, and Monte Carlo simulations on the detector system was validated experimentally. Validation of the simulation results in overall trend of the CLYC detector behavior will provide the fundamental basis and validity of follow-up Monte Carlo simulation studies for the development of our dual-particle imager using a rotational modulation collimator.

Nodal Probabilistic Production Cost Evaluation using Monte Carlo Simulation Methods (Monte Carlo Simulation을 이용한 각 부하지점별 확률론적 발전비산정)

  • Mun, Seung-Pil;Kim, Hong-Sik;Choe, Jae-Seok
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.51 no.9
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    • pp.425-432
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    • 2002
  • This Paper illustrates a method for evaluating nodal probabilistic production cost using the CMELDC. A new method for constructing CMELDC(CoMposite Power System Equivalent Load Duration Curve) has been developed by authors. The CMELDC can be obtained by convolution integral processing between the probability distribution functions of the fictitious generators outage capacity and the load duration curves at each load point. In general, if complex operating conditions are involved and/or the number of severe events is relatively large, Monte Carlo methods are more efficient. Because of that reason, Monte Carlo Methods are applied for the construction of CMELDC in this study. And IEEE-RTS 24 buses model is used as our case study with satisfactory results.

Statistical comparison analysis based on Monte Carlo simulation between PSD random analysis and it's equivalent static analysis for avionics equipment (Monte Carlo모의에 의한 항공전자장비의 PSD랜덤진동해석과 등가정적해석의 통계적 비교분석)

  • Park, Hee-Beom;Lee, Seok-Kyu;Yang, Sung-Cheol;Kim, Jin-Cheon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2008.04a
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    • pp.119-126
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    • 2008
  • 방위산업분야의 항공기용 전자장비는 신뢰성 설계를 위하여 MIL규격이나 실측된 PSD데이터를 이용하여 보수적으로 설계하는 것이 일반적이다. 하나의 프로젝트에서 개발되는 PCB는 수십 종에 이르고 그 장착위치나 설계변경이 병행되므로 PSD랜덤 진동해석의 대안으로 등가정적해석을 수행하게 된다. 등가정적해석결과의 보수성을 확인하기 위하여 PSD랜덤진동해석으로부터 추출된 정규분포를 갖는 각 방향 응력에 대해 Monte Carlo모의를 수행하여 결과를 비교분석하였다. 결론적으로 PSD랜덤진동 해석의 대안으로 등가정적해석결과의 유용성과 보수성을 통계적으로 비교하였고 실험을 통하여 결과의 타당성을 보였다.

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A Study on Uncertainty Analyses of Monte Carlo Techniques Using Sets of Double Uniform Random Numbers

  • Lee, Dong Kyu;Sin, Soo Mi
    • Architectural research
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    • v.8 no.2
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    • pp.27-36
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    • 2006
  • Structural uncertainties are generally modeled using probabilistic approaches in order to quantify uncertainties in behaviors of structures. This uncertainty results from the uncertainties of structural parameters. Monte Carlo methods have been usually carried out for analyses of uncertainty problems where no analytical expression is available for the forward relationship between data and model parameters. In such cases any direct mathematical treatment is impossible, however the forward relation materializes itself as an algorithm allowing data to be calculated for any given model. This study addresses a new method which is utilized as a basis for the uncertainty estimates of structural responses. It applies double uniform random numbers (i.e. DURN technique) to conventional Monte Carlo algorithm. In DURN method, the scenarios of uncertainties are sequentially selected and executed in its simulation. Numerical examples demonstrate the beneficial effect that the technique can increase uncertainty degree of structural properties with maintaining structural stability and safety up to the limit point of a breakdown of structural systems.

A PRICING METHOD OF HYBRID DLS WITH GPGPU

  • YOON, YEOCHANG;KIM, YONSIK;BAE, HYEONG-OHK
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.20 no.4
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    • pp.277-293
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    • 2016
  • We develop an efficient numerical method for pricing the Derivative Linked Securities (DLS). The payoff structure of the hybrid DLS consists with a standard 2-Star step-down type ELS and the range accrual product which depends on the number of days in the coupon period that the index stay within the pre-determined range. We assume that the 2-dimensional Geometric Brownian Motion (GBM) as the model of two equities and a no-arbitrage interest model (One-factor Hull and White interest rate model) as a model for the interest rate. In this study, we employ the Monte Carlo simulation method with the Compute Unified Device Architecture (CUDA) parallel computing as the General Purpose computing on Graphic Processing Unit (GPGPU) technology for fast and efficient numerical valuation of DLS. Comparing the Monte Carlo method with single CPU computation or MPI implementation, the result of Monte Carlo simulation with CUDA parallel computing produces higher performance.

Design of Occupant Protection Systems Using Global Optimization (전역 최적화기법을 이용한 승객보호장치의 설계)

  • Jeon, Sang-Ki;Park, Gyung-Jin
    • Transactions of the Korean Society of Automotive Engineers
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    • v.12 no.6
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    • pp.135-142
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    • 2004
  • The severe frontal crash tests are NCAP with belted occupant at 35mph and FMVSS 208 with unbelted occupant at 25mph, This paper describes the design process of occupant protection systems, airbag and seat belt, under the two tests. In this study, NCAP simulations are performed by Monte Carlo search method and cluster analysis. The Monte Carlo search method is a global optimization technique and requires execution of a series of deterministic analyses, The procedure is as follows. 1) Define the region of interest 2) Perform Monte Carlo simulation with uniform distribution 3) Transform output to obtain points grouped around the local minima 4) Perform cluster analysis to obtain groups that are close to each other 5) Define the several feasible design ranges. The several feasible designs are acquired and checked under FMVSS 208 simulation with unbelted occupant at 25mph.