• Title/Summary/Keyword: Monte Carlo (MC) simulation

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Real-Time Estimation of Missile Debris Predicted Impact Point and Dispersion Using Deep Neural Network (심층 신경망을 이용한 실시간 유도탄 파편 탄착점 및 분산 추정)

  • Kang, Tae Young;Park, Kuk-Kwon;Kim, Jeong-Hun;Ryoo, Chang-Kyung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.49 no.3
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    • pp.197-204
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    • 2021
  • If a failure or an abnormal maneuver occurs during the flight test of a missile, the missile is deliberately self-destructed so as not to continue the flight. At this time, debris are produced and it is important to estimate the impact area in real-time whether it is out of the safety area. In this paper, we propose a method to estimate the debris dispersion area and falling time in real-time using a Fully-Connected Neural Network (FCNN). We applied the Unscented Transform (UT) to generate a large amount of training data. UT parameters were selected by comparing with Monte-Carlo (MC) simulation to secure reliability. Also, we analyzed the performance of the proposed method by comparing the estimation result of MC.

Performance Evaluation of Direct Broadcasting Satellite Channel using a MC and QA Method (MC기법과 QA기법을 이용한 직접위성방송채널 성능평가)

  • 정지원;조형래;고성찬
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.4
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    • pp.839-847
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    • 1999
  • This paper presents the performance evaluation of direct broadcasting satellite by monte-carlo(MC) and quasi-analytic(QA) simulation method in the existence of uplink/downlink adjacent channel interference(ACI), co-channel interference(CCI), and gaussian noise. Korea's satellite system parameters and link design are used at the simulation. MC and QA simulation methods are a valuable adjunct to analytical performance.

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Monte Carlo simulation of interacting liquid crystal and substrate using rigid model molecules

  • Hyodo, Yosuke;Koda, Tomonori;Momoi, Yuichi;Kim, Woo-Yeol;Nishioka, Akihiro;Miyata, Ken;Murasawa, Go
    • 한국정보디스플레이학회:학술대회논문집
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    • 2007.08a
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    • pp.952-953
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    • 2007
  • In the present study, we propose MC simulation that takes interface phenomena between liquid crystal and substrate into consideration. We use rigid model molecules of liquid crystal and substrate. Interface is generated using potential field that induces decomposition of molecules.

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Modeling and Simulation of Line Edge Roughness for EUV Resists

  • Kim, Sang-Kon
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.14 no.1
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    • pp.61-69
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    • 2014
  • With the extreme ultraviolet (EUV) lithography, the performance limit of chemically amplified resists has recently been extended to 16- and 11-nm nodes. However, the line edge roughness (LER) and the line width roughness (LWR) are not reduced automatically with this performance extension. In this paper, to investigate the impacts of the EUVL mask and the EUVL exposure process on LER, EUVL is modeled using multilayer-thin-film theory for the mask structure and the Monte Carlo (MC) method for the exposure process. Simulation results demonstrate how LERs of the mask transfer to the resist and the exposure process develops the resist LERs.

Probabilistic seismic assessment of structures considering soil uncertainties

  • Hamidpour, Sara;Soltani, Masoud;Shabdin, Mojtaba
    • Earthquakes and Structures
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    • v.12 no.2
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    • pp.165-175
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    • 2017
  • This paper studies soil properties uncertainty and its implementation in the seismic response evaluation of structures. For this, response sensitivity of two 4- and 12-story RC shear walls to the soil properties uncertainty by considering soil structure interaction (SSI) effects is investigated. Beam on Nonlinear Winkler Foundation (BNWF) model is used for shallow foundation modeling and the uncertainty of soil properties is expanded to the foundation stiffness and strength parameters variability. Monte Carlo (MC) simulation technique is employed for probabilistic evaluations. By investigating the probabilistic evaluation results it's observed that as the soil and foundation become stiffer, the soil uncertainty is found to be less important in influencing the response variability. On the other hand, the soil uncertainty becomes more important as the foundation-structure system is expected to experience nonlinear behavior to more sever degree. Since full This paper studies soil properties uncertainty and its implementation in the seismic response evaluation of structures. For this, response sensitivity of two 4- and 12-story RC shear walls to the soil properties uncertainty by considering soil structure interaction (SSI) effects is investigated. Beam on Nonlinear Winkler Foundation (BNWF) model is used for shallow foundation modeling and the uncertainty of soil properties is expanded to the foundation stiffness and strength parameters variability. Monte Carlo (MC) simulation technique is employed for probabilistic evaluations. By investigating the probabilistic evaluation results it's observed that as the soil and foundation become stiffer, the soil uncertainty is found to be less important in influencing the response variability. On the other hand, the soil uncertainty becomes more important as the foundation-structure system is expected to experience nonlinear behavior to more sever degree. Since full probabilistic analysis methods like MC commonly are very time consuming, the feasibility of simple approximate methods' application including First Order Second Moment (FOSM) method and ASCE41 proposed approach for the soil uncertainty considerations is investigated. By comparing the results of the approximate methods with the results obtained from MC, it's observed that the results of both FOSM and ASCE41 methods are in good agreement with the results of MC simulation technique and they show acceptable accuracy in predicting the response variability.

Development of Seismic Fragility Curves for Slopes Using ANN-based Response Surface (인공신경망 기반의 응답면 기법을 이용한 사면의 지진에 대한 취약도 곡선 작성)

  • Park, Noh-Seok;Cho, Sung-Eun
    • Journal of the Korean Geotechnical Society
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    • v.32 no.11
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    • pp.31-42
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    • 2016
  • Usually the seismic stability analysis of slope uses the pseudostatic analysis considering the inertial force by the earthquake as a static load. Geostructures such as slope include the uncertainty of soil properties. Therefore, it is necessary to consider probabilistic method for stability analysis. In this study, the probabilistic stability analysis of slope considering the uncertainty of soil properties has been performed. The fragility curve that represents the probability of exceeding limit state of slope as a function of the ground motion has been established. The Monte Carlo Simulation (MCS) has been implemented to perform the probabilistic stability analysis of slope with pseudostatic analysis. A procedure to develop the fragility curve by the pseudostatic horizontal acceleration has been presented by calculating the probability of failure based on the Artificial Neural Network (ANN) based response surface technique that reduces the required time of MCS. The results showed that the proposed method can get the fragility curve that is similar to the direct MCS-based fragility curve, and can be efficiently used to reduce the analysis time.

Determination of dosimetric dependence for effective atomic number of LDR brachytherapy seed capsule by Monte Carlo simulation

  • Berkay Camgoz;Dilara Tarim
    • Nuclear Engineering and Technology
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    • v.55 no.8
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    • pp.2734-2741
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    • 2023
  • Brachytherapy is a special case of radiotherapy. It should be arranged according to some principles in medical radiation applications and radiation physics. The primary principle is to use as low as reasonably achievable dose in all ionizing radiation applications for diagnostic and therapeutic treatments. Dosimetric distributions are dependent on radioactive source properties and radiation-matter interactions in an absorber medium such as phantom or tissue. In this consideration, the geometrical structure and material of the seed capsule, which surrounds a radioactive material, are directly responsible for isodose profiles and dosimetric functions. In this study, the radiometric properties of capsule material were investigated on dose distribution in a water phantom by changing its nuclear properties using the EGSnrc Monte Carlo (MC) simulation code. Effective atomic numbers of hypothetic mixtures were calculated by using different elements with several fractions for capsule material. Model 6711 brachytherapy seed was modeled by EGSnrc/Dosrcnrc Code and dosimetric functions were calculated. As a result, dosimetric parameters of hypothetic sources have been acquired in large-scale atomic number. Dosimetric deviations between the data of hypothetic seeds and the original one were analyzed. Unit dose (Gy/Particle) distributions belonging to different types of material in seed capsule have remarkably differed from the original capsule's data. Capsule type is major variable to manage the expected dose profile and isodose distribution around a seed. This study shows us systematically varied scale of material type (cross section or effective atomic number dependent) offers selective material usage in production of seed capsules for the expected isodose profile of a specific source.

Stochastic cost optimization of ground improvement with prefabricated vertical drains and surcharge preloading

  • Kim, Hyeong-Joo;Lee, Kwang-Hyung;Jamin, Jay C.;Mission, Jose Leo C.
    • Geomechanics and Engineering
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    • v.7 no.5
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    • pp.525-537
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    • 2014
  • The typical design of ground improvement with prefabricated vertical drains (PVD) and surcharge preloading involves a series of deterministic analyses using averaged or mean soil properties for the various combination of the PVD spacing and surcharge preloading height that would meet the criteria for minimum consolidation time and required degree of consolidation. The optimum design combination is then selected in which the total cost of ground improvement is a minimum. Considering the variability and uncertainties of the soil consolidation parameters, as well as considering the effects of soil disturbance (smear zone) and drain resistance in the analysis, this study presents a stochastic cost optimization of ground improvement with PVD and surcharge preloading. Direct Monte Carlo (MC) simulation and importance sampling (IS) technique is used in the stochastic analysis by limiting the sampled random soil parameters within the range from a minimum to maximum value while considering their statistical distribution. The method has been verified in a case study of PVD improved ground with preloading, in which average results of the stochastic analysis showed a good agreement with field monitoring data.

The Reliability Analysis for Homogeneous Slope Stability Using Stochastic Finite Element Method (확율유한요소법을 이용한 균질 사면의 신뢰성 해석)

  • 조래청;도덕현
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.38 no.5
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    • pp.125-139
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    • 1996
  • This study was performed to provide the design method for soil structure which guarantees proper safety with uncertainty of soil parameters. For this purpose, the effect of uncertainty of soil parameters for slope stability was analyzed by Bishop's simplified method and Monte Carlo simulation(MC). And reliability analysis program, RESFEM, was developed by combining elastic theory, MC, FEM, SFEM, and reliability, which can consider uncertainty of soil parameters. For factor of safety(FS) 1.0 and 1.2 by Bishop's simplified method, the probability of failure(Pf) was analyzed with varying coefficient of variation(c.o.v.) of soil parameters. The Pf increased as c.o.v. of soil parameters increased. This implies that FS is not the absolute index of slope safety, and even if FS is same, it has different Pf according to c.o.v. of soil parameters. The RESFEM was able to express the Pf at each element in slope quantitatively according to uncertainty of soil parameters. The variation of Pf with uncertainty of soil parameters was analyzed by RESFEM, and it was shown that the Pf increased as the c.o.v. of soil parameters increased.

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Robust optimization of a hybrid control system for wind-exposed tall buildings with uncertain mass distribution

  • Venanzi, Ilaria;Materazzi, Annibale Luigi
    • Smart Structures and Systems
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    • v.12 no.6
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    • pp.641-659
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    • 2013
  • In this paper is studied the influence of the uncertain mass distribution over the floors on the choice of the optimal parameters of a hybrid control system for tall buildings subjected to wind load. In particular, an optimization procedure is developed for the robust design of a hybrid control system that is based on an enhanced Monte Carlo simulation technique and the genetic algorithm. The large computational effort inherent in the use of a MC-based procedure is reduced by the employment of the Latin Hypercube Sampling. With reference to a tall building modeled as a multi degrees of freedom system, several numerical analyses are carried out varying the parameters influencing the floors' masses, like the coefficient of variation of the distribution and the correlation between the floors' masses. The procedure allows to obtain optimal designs of the control system that are robust with respect to the uncertainties on the distribution of the dead and live loads.