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

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Massive Parallel Processing Algorithm for Semiconductor Process Simulation (반도체 공정 시뮬레이션을 위한 초고속 병렬 연산 알고리즘)

  • 이제희;반용찬;원태영
    • Journal of the Korean Institute of Telematics and Electronics D
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    • v.36D no.3
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    • pp.48-58
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    • 1999
  • In this paper, a new parallel computation method, which fully utilize the parallel processors both in mesh generation and FEM calculation for 2D/3D process simulation, is presented. High performance parallel FEM and parallel linear algebra solving technique was showed that excessive computational requirement of memory size and CPU time for the three-dimensional simulation could be treated successively. Our parallelized numerical solver successfully interpreted the transient enhanced diffusion (TED) phenomena of dopant diffusion and irregular shape of R-LOCOS within 15 minutes. Monte Carlo technique requires excessive computational requirement of CPU time. Therefore high performance parallel solving technique were employed to our cascade sputter simulation. The simulation results of Our sputter simulator allowed the calculation time of 520 sec and speedup of 25 using 30 processors. We found the optimized number of ion injection of our MC sputter simulation is 30,000.

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A Markov-based prediction model of tunnel geology, construction time, and construction costs

  • Mahmoodzadeh, Arsalan;Mohammadi, Mokhtar;Ali, Hunar Farid Hama;Salim, Sirwan Ghafoor;Abdulhamid, Sazan Nariman;Ibrahim, Hawkar Hashim;Rashidi, Shima
    • Geomechanics and Engineering
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    • v.28 no.4
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    • pp.421-435
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    • 2022
  • The necessity of estimating the time and cost required for tunnel construction has led to extensive research in this regard. Since geological conditions are significant factors in terms of time and cost of road tunnels, considering these conditions is crucial. Uncertainties about the geological conditions of a tunnel alignment cause difficulties in planning ahead of the required construction time and costs. In this paper, the continuous-space, discrete-state Markov process has been used to predict geological conditions. The Monte-Carlo (MC) simulation (MCS) method is employed to estimate the construction time and costs of a road tunnel project using the input data obtained from six tunneling expert questionnaires. In the first case, the input data obtained from each expert are individually considered and in the second case, they are simultaneously considered. Finally, a comparison of these two modes based on the technique presented in this article suggests considering views of several experts simultaneously to reduce uncertainties and ensure the results obtained for geological conditions and the construction time and costs.

Search for Dark Photon in e+e- → A'A' Using Future Collider Experiments

  • Kihong Park;Kyungho Kim;Alexei Sytov;Kihyeon Cho
    • Journal of Astronomy and Space Sciences
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    • v.40 no.4
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    • pp.259-266
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    • 2023
  • The Standard Model (SM) does not provide an information for 26% of dark matter of the universe. In the dark sector, dark matter is supposed to be linked with the hypothetical particles called dark photons that have similar role to photons in electromagnetic interaction in the SM. Besides astronomical observation, there are studies to find dark matter candidates using accelerators. In this paper, we searched for dark photons using future electron-positron colliders, including Circular Electron Positron Collider (CEPC)/CEPC, Future Circular Collider (FCC-ee)/Innovative Detector for Electron-positron Accelerator (IDEA), and International Linear Collider (ILC)/International Large Detector (ILD). Using the parameterized response of the detector simulation of Delphes, we studied the sensitivity of a double dark photon mode at each accelerator/detector. The signal mode is double dark photon decay channel, e+e- → A'A', where A' (dark photon with spin 1) decaying into a muon pair. We used MadGraph5 to generate Monte Carlo (MC) events by means of a Simplified Model. We found the dark photon mass at which the cross-sections were the highest for each accelerator to obtain the maximum number of events. In this paper we show the expected number of dark photon signal events and the detector efficiency of each accelerator. The results of this study can facilitate in the dark photon search by future electron-positron accelerators.

An Application of Dirichlet Mixture Model for Failure Time Density Estimation to Components of Naval Combat System (디리슈레 혼합모형을 이용한 함정 전투체계 부품의 고장시간 분포 추정)

  • Lee, Jinwhan;Kim, Jung Hun;Jung, BongJoo;Kim, Kyeongtaek
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.4
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    • pp.194-202
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    • 2019
  • Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters' posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

Analysis of Interference Impact of UWB System on WiBro System (UWB 시스템에 의한 WiBro 시스템에서의 간섭영향에 관한 연구)

  • Yoon Young-Keun;Hong Heon-Jin;Lee Il-Kyoo;Choi Ik-Guen;Kwak Kyung-Sub
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.8A
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    • pp.814-819
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    • 2006
  • This paper presents the impacts of Ultra Wide-Band(UWB) system applied in Indoor and Handhold communications using frequency band from 3.1 GHz to 10.6 GHz on Wireless Broad-band(WiBro) system based on Orthogonal Frequency Division Multiplexing(OFDM) using frequency of 2.3 GHz. The Minimum Coupling Loss(MCL) method for the case of single interference and Monte Carlo(MC) simulation for multiple interference considering practical scenario were used to evaluate the interference effects of UWB system on WiBro system. As a result, the minimum separation distance between single interferer and the victim receiver required 34.4 m and above to guarantee the co-existence. Also, the UWB transmitting PSD of around - 81 dBm / MHz below should be required to meet the minimum throughput loss of WiBro mobile station in case of multiple UWB interference.

Reliability-based combined high and low cycle fatigue analysis of turbine blade using adaptive least squares support vector machines

  • Ma, Juan;Yue, Peng;Du, Wenyi;Dai, Changping;Wriggers, Peter
    • Structural Engineering and Mechanics
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    • v.83 no.3
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    • pp.293-304
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    • 2022
  • In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

Reliability Assessment Based on an Improved Response Surface Method (개선된 응답면기법에 의한 신뢰성 평가)

  • Cho, Tae Jun;Kim, Lee Hyeon;Cho, Hyo Nam
    • Journal of Korean Society of Steel Construction
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    • v.20 no.1
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    • pp.21-31
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    • 2008
  • response surface method (RSM) is widely used to evaluate th e extremely smal probability of ocurence or toanalyze the reliability of very complicated structures. Althoug h Monte-Carlo Simulation (MCS) technique can evaluate any system, the procesing time of MCS dependson the reciprocal num ber of the probability of failure. The stochastic finite element method could solve thislimitation. However, it is limit ed to the specific program, in which the mean and coeficient o f random variables are programed by a perturbation or by a weigh ted integral method. Therefore, it is not aplicable when erequisite programing. In a few number of stage analyses, RSM can construct a regresion model from the response of the c omplicated structural system, thus, saving time and efort significantly. However, the acuracy of RSM depends on the dist ance of the axial points and on the linearity of the limit stat e functions. To improve the convergence in exact solution regardl es of the linearity limit of state functions, an improved adaptive response surface method is developed. The analyzed res ults have ben verified using linear and quadratic forms of response surface functions in two examples. As a result, the be st combination of the improved RSM techniques is determined and programed in a numerical code. The developed linear adapti ve weighted response surface method (LAW-RSM) shows the closest converged reliability indices, compared with quadratic form or non-adaptive or non-weighted RSMs.

A Study on the properties of the Multiensemble Sampling method (Multiensemble Sampling 방법의 속성에 대한 연구)

  • Han, Kyu-Kwang
    • The Journal of Natural Sciences
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    • v.15 no.1
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    • pp.11-34
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    • 2005
  • It is no exaggeration to say that the productivity of a research using computer simulations on complex molecular systems like biomolecules depends on the ability of the sampling algorithm to explore the relevant parts of configuration space. In this study, we investigate the properties on the mutiensemble sampling (MES) which is one of the solutions that surmount limitations of conventional sampling algorithms. Works for finding out practical systematic ways of using the MES efficiently to explore distantly separated regions in configuration space are performed. In this work, the more generalized form of weighting function for MES is used and 'cavity formation in water' is simulated using Monte Carlo. investigating the correlation of simulation parameters and the efficiency of the method, we propose a practical way of maximizing the power of the MES. We applied the way to 'cavity formation in water' and were able to explore the parts of configuration space relevant to cavities of radius from 0 to 5.6A in a single simulation.

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Probabilistic Risk Assessment of Coastal Structures using LHS-based Reliability Analysis Method (LHS기반 신뢰성해석 기법을 이용한 해안구조물의 확률론적 위험도평가)

  • Huh, Jung-Won;Jung, Hong-Woo;Ahn, Jin-Hee;An, Sung-Wook
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.19 no.6
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    • pp.72-79
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    • 2015
  • An efficient and practical reliability evaluation method is proposed for the coastal structures in this paper. It is capable of evaluating reliability of real complicated coastal structures considering uncertainties in various sources of design parameters, such as wave and current loads, resistance-related design variables including Young's modulus and compressive strength of the reinforced concrete, soil parameters, and boundary conditions. It is developed by intelligently integrating the Latin Hypercube sampling (LHS), Monte Carlo simulation (MCS) and the finite element method (FEM). The LHS-based MCS is used to significantly reduce the computational effort by limiting the number of simulation cycles required for the reliability evaluation. The applicability and efficiency of the proposed method were verified using a caisson-type breakwater structure in the numerical example.

Evaluation of the Radiochromic Film Dosimetry for a Small Curved Interface (휘어진 경계에서의 좁은 영역에 대한 Radiochromic 필름 도시메트리 평가)

  • Kang, Sei-Kwon;Park, Soah;Hwang, Taejin;Cheong, Kwang-Ho;Han, Taejin;Kim, Haeyoung;Lee, Me-Yeon;Kim, Kyoung Ju;Bae, Hoonsik
    • Progress in Medical Physics
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    • v.23 no.4
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    • pp.234-238
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    • 2012
  • A tumor on the eyelid is often treated using a high-energy electron beam, with a metallic eye shield inserted between the eyelid and the eyeball to preserve the patient's sight. Pretreatment quality assurance of the inner eyelid dose on the metallic shield requires a very small dosimetry tool. For enhanced accuracy, a flexible device fitting the curved interface between the eyelid and the shield is also required. The radiochromic film is the best candidate for this device. To measure the doses along the curved interface and small area, a 3-mm-wide strip of EBT2 film was inserted between the phantom eyelid and the shield. After irradiation with 6 MeV electron beams, the film was evaluated for the dose profile. An acrylic eye shield of the same size as the real eye shield was machined, and CT images free from metal artifacts were obtained. Monte Carlo simulation was performed on the CT images, taking into account eye shield material, such as tungsten, aluminum, and steel. The film-based interface dose distribution agreed with the MC calculation within 2.1%. In the small (millimeter scale) and curved region, radiochromic film dosimetry promises a satisfactory result with easy handling.