Thematische Bibliographien / Monte Carlo Simulation Technique

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Auswahl der wissenschaftlichen Literatur zum Thema „Monte Carlo Simulation Technique“

Autor: Grafiati
Veröffentlicht am 4. Juni 2021
Zuletzt aktualisiert am 9. Juni 2025

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Zeitschriftenartikel zum Thema "Monte Carlo Simulation Technique"

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JAKUMEIT, JÜRGEN. "COMPUTATIONAL ASPECTS OF THE LOCAL ITERATIVE MONTE CARLO TECHNIQUE." International Journal of Modern Physics C 11, no. 04 (June 2000): 665–73. http://dx.doi.org/10.1142/s0129183100000584.

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Lately, the Local Iterative Monte Carlo technique was introduced for an efficient simulation of effects connected to sparsely populated regions in semiconductor devices like hot electron effects in silicon MOSFETs. This paper focuses on computational aspects of this new Monte Carlo technique, namely the reduction of the computation time by parallel computation and the reuse of drift information. The Local Iterative Monte Carlo technique combines short Monte Carlo particle flight simulations with an iteration process to a complete device simulation. The separation between short Monte Carlo simulations and the iteration process makes a simple parallelization strategy possible. The necessary data transfer is small and can be performed via the Network File System. An almost linear speed up could be achieved. Besides by parallelization, the computational expenses can be significantly reduced, when the results of the short Monte Carlo simulations are memorized in a drift table and used several times. A comparison between a bulk, a one-dimensional and the two-dimensional Local Iterative Monte Carlo simulation reveals that by using the drift information more than once, becomes increasingly efficient with increasing dimension of the simulation.
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SWENDSEN, ROBERT H., BRIAN DIGGS, JIAN-SHENG WANG, SHING-TE LI, CHRISTOPHER GENOVESE, and JOSEPH B. KADANE. "TRANSITION MATRIX MONTE CARLO." International Journal of Modern Physics C 10, no. 08 (December 1999): 1563–69. http://dx.doi.org/10.1142/s0129183199001340.

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Although histogram methods have been extremely effective for analyzing data from Monte Carlo simulations, they do have certain limitations, including the range over which they are valid and the difficulties of combining data from independent simulations. In this paper, we describe a complementary approach to extracting information from Monte Carlo simulations that uses the matrix of transition probabilities. Combining the Transition Matrix with an N-fold way simulation technique produces an extremely flexible and efficient approach to rather general Monte Carlo simulations.
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Dou, Mingze. "Principle and Applications of Monte-Carlo Simulation in Forecasting, Algorithm and Health Risk Assessment." Highlights in Science, Engineering and Technology 88 (March 29, 2024): 406–14. http://dx.doi.org/10.54097/jjw5by20.

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Monte Carlo simulation, as a technique to reverse parameters by random sampling in known data, is widely used in many fields such as finance, computer and engineering. While introducing the basic concepts and related principles of Monte Carlo simulation, this paper will focus on three new applications of Monte Carlo simulation in electricity price prediction, algorithm and health risk assessment. The limitations and future development of the Monte Carlo simulation are discussed later. Future research should solve the defects of Monte Carlo simulation with long computing consumption time, lack of evaluation method and strict sampling requirements, and enhance the adaptability of this method by combining the problems worth research in various fields. This paper hopes to provide the reader with the relevant background knowledge of Monte Carlo simulations to facilitate the application of Monte Carlo simulation to complex problems in more domains. Overall, these results shed light on guiding further exploration of applications based on Monte Carlo Simulations.
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Huang, Xiangyuan. "Consumer and Marketing Research Using the Monte Carlo Simulation." Advances in Economics, Management and Political Sciences 32, no. 1 (November 10, 2023): 35–41. http://dx.doi.org/10.54254/2754-1169/32/20231561.

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In order to conduct consumer-related research and develop marketing strategies to outperform rival businesses, Monte Carlo simulation, a technique that was first employed in nuclear weapons and has subsequently been used in other physics-related domains, is described in this study. The literature on using Monte Carlo simulation for market and customer-related research and suggestions is summarized in two parts in this paper. The first section discusses the role of Monte Carlo simulations in customer research, outlining the various factors that affect consumers' decisions to purchase goods and services, and the second section discusses the specific help that Monte Carlo simulations can offer businesses, particularly in terms of measuring markets and creating effective marketing strategies. The paper also offers several applicable examples to describe certain elements in the middle of the text. Eventually, it is argued that Monte Carlo simulation, when used in conjunction with other techniques, can assist businesses in comprehending the market's costs and unpredictability and in developing effective marketing strategies.
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Sheet, Abd Al Kareem I., and Nadia Adeel Saeed. "Monte Carlo Simulation and Applications." Journal of Kufa for Mathematics and Computer 1, no. 6 (December 30, 2012): 75–78. https://doi.org/10.31642/jokmc/2018/010608.

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The Monte Carlo simulation technique is one of the common computational tools used to imitate and follow up complex real life systems and their development with time. Variables of a disease problem were defined and the mathematical model for this problem was constructed. The numerical solution of this model was compared with the computational simulation of  Markov Renewal Process of the type '' Birth and Death ''. We obvious from the results we obtained the efficiency of the Monte Carlo simulation technique and through out extended time periods episodes.Â
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Suzuki, SHO, NAOKI Takano, and MITSUTERU ASAI. "F406 Monte Carlo Simulation of dynamic problem using Model Order Reduction Technique." Proceedings of The Computational Mechanics Conference 2011.24 (2011): _F—58_—_F—59_. http://dx.doi.org/10.1299/jsmecmd.2011.24._f-58_.

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Chen, Jiming. "Monte Carlo Simulations in Complex Systems: Challenges and New Approaches." Theoretical and Natural Science 86, no. 1 (January 15, 2025): 114–19. https://doi.org/10.54254/2753-8818/2025.20172.

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Monte Carlo simulations are crucial for examining the Ising model, especially when it's tough to find analytical solutions. However, traditional Monte Carlo methods, like the Metropolis algorithm, encounter significant hurdles, such as slowing down near phase transitions and issues related to finite sizes. This paper looks into both the advantages and limitations of these traditional Monte Carlo techniques. It also covers recent developments like Tensor Network Monte Carlo and Quantum Monte Carlo methods, which have shown promise in overcoming these challenges. Furthermore, the paper explores how machine learning techniques are being incorporated into Monte Carlo simulations to enhance their efficiency and accuracy. These advancements represent a major leap forward in simulating complex systems and have expanded the use of Monte Carlo methods into new areas, including quantum systems and models with disorder. This paper finds that traditional Monte Carlo methods, like the Metropolis algorithm, face issues such as critical slowing down and finite-size effects. New methods, such as Tensor Network Monte Carlo (TNMC) and Quantum Monte Carlo (QMC), effectively address these challenges, enhancing simulation accuracy and efficiency in complex systems. Additionally, integrating machine learning optimizes parameters and accelerates convergence, expanding Monte Carlos applicability to large-scale, high-dimensional systems across various scientific fields.
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Nur, Nabihah Rusyda Roslan, Farhanie Mohd Fauzi NoorFatin, and Ikhwan Muhammad Ridzuan Mohd. "Variance reduction technique in reliability evaluation for distribution system by using sequential Monte Carlo simulation." Bulletin of Electrical Engineering and Informatics 11, no. 6 (December 1, 2022): 3061~3068. https://doi.org/10.11591/eei.v11i6.3950.

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This paper discusses the need for variance reduction in simulations in order to reduce the time required to compute a simulation. The large and complex network is commonly evaluated using a large-scale Monte Carlo simulation. Unfortunately, due to the different sizes of the network, it takes some time to complete a simulation. However, variance reduction techniques (VRT) can help to solve the issues. The effect of VRT changes the behaviors of a simulation, particularly the time required to run the simulation. To evaluate the reliability indices, two sequential Monte Carlo (SMC) methods are used. SMC with VRT and SMC without VRT are the two options. The presence of VRT in the simulation distinguishes the two simulations. Finally, reliability indices: system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and customer average interruption duration index (CAIDI) will be calculated at the end of the simulation to determine the efficiency for the SMC with and without VRT. Overall, the SMC with VRT is more efficient because it is more convenient and saves time than the SMC without VRT.
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Mo, Zihan, Boxu He, and Tian Qin. "Option Pricing Based on Several Monte Carlo Techniques." Theoretical and Natural Science 107, no. 1 (May 6, 2025): 227–34. https://doi.org/10.54254/2753-8818/2025.22650.

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The Monte Carlo method is broadly used in financial technology and engineering for pricing complex derivatives and managing risk due to its flexibility and adaptability. However, Monte Carlo simulation may suffer from high variance problems, impacting accuracy and effectiveness. Control and antithetic variates are two main variance-reduction techniques to optimize the simulation. This paper compares the performance of normal Monte Carlo, and Monte Carlo optimized with control variates or antithetic variates in four different European options. In the work, the Monte Carlo optimization based on antithetic variates generally performs well, but in power options, the control variable method has a better effect on Monte Carlo optimization. By leveraging these variance reduction techniques, the accuracy and effectiveness of Monte Carlo simulations can be significantly enhanced, leading to more reliable option pricing. The results not only demonstrate the important role of variance-reduction techniques in the Monte Carlo method but also offer practical methods to improve option pricing strategy.
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Tamošiūnienė, Rima. "The Use of Monte Carlo Simulation Technique to Support Investment Decisions." Business: Theory and Practice 7, no. (2) (June 27, 2006): 73–80. https://doi.org/10.3846/btp.2006.09.

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In this paper the methodology and uses of Monte Carlo simulation technique in the evaluation of investment projects are presented to analyse and assess the risk. The first part presents the theoretical background of Monte Carlo analysis in various process stages. The second part examines the interpretation of the results generated by the application of project formulation, financial and risk analysis including investment decision criteria and measures of risk based on the expected NPV value concept. The final part draws some conclusions regarding the usefulness and limitations of Monte Carlo analysis in investment appraisal.
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Dissertationen zum Thema "Monte Carlo Simulation Technique"

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Rangaraj, Dharanipathy. "Multicomponent aerosol dynamics : exploration of direct simulation Monte Carlo technique /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p3144452.

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Jackson, Andrew N. "Structural phase behaviour via Monte Carlo techniques." Thesis, University of Edinburgh, 2001. http://hdl.handle.net/1842/4850.

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There are few reliable computational techniques applicable to the problem of structural phase behaviour. This is starkly emphasised by the fact that there are still a number of unanswered questions concerning the solid state of some of the simplest models of matter. To determine the phase behaviour of a given system we invoke the machinery of statistical physics, which identifies the equilibrium phase as that which minimises the free-energy. This type of problem can only be dealt with fully via numerical simulation, as any less direct approach will involve making some uncontrolled approximation. In particular, a numerical simulation can be used to evaluate the free-energy difference between two phases if the simulation is free to visit them both. However, it has proven very difficult to find an algorithm which is capable of efficiently exploring two different phases, particularly when one or both of them is a crystalline solid. This thesis builds on previous work (Physical Review Letters 79 p.3002), exploring a new Monte Carlo approach to this class of problem. This new simulation technique uses a global coordinate transformation to switch between two different crystalline structures. Generally, this `lattice switch' is found to be extremely unlikely to succeed in a normal Monte Carlo simulation. To overcome this, extended-sampling techniques are used to encourage the simulation to visit `gateway' microstates where the switch will be successful. After compensating for this bias in the sampling, the free-energy difference between the two structures can be evaluated directly from their relative probabilities. As concrete examples on which to base the research, the lattice-switch Monte Carlo method is used to determine the free-energy difference between the face-centred cubic (fcc) and hexagonal close-packed (hcp) phases of two generic model systems --- the hard-sphere and Lennard-Jones potentials. The structural phase behaviour of the hard-sphere solid is determined at densities near melting and in the close-packed limit. The factors controlling the efficiency of the lattice-switch approach are explored, as is the character of the `gateway' microstates. The face-centred cubic structure is identified as the thermodynamically stable phase, and the free-energy difference between the two structures is determined with high precision. These results are shown to be in complete agreement with the results of other authors in the field (published during the course of this work), some of whom adopted the lattice-switch method for their calculations. Also, the results are favourably compared against the experimentally observed structural phase behaviour of sterically-stabilised colloidal dispersions, which are believed to behave like systems of hard spheres. The logical extension of the hard sphere work is to generalise the lattice-switch technique to deal with `softer' systems, such as the Lennard-Jones solid. The results in the literature for the structural phase behaviour of this relatively simple system are found to be completely inconsistent. A number of different approaches to this problem are explored, leading to the conclusion that these inconsistencies arise from the way in which the potential is truncated. Using results for the ground-state energies and from the harmonic approximation, we develop a new truncation scheme which allows this system to be simulated accurately and efficiently. Lattice-switch Monte Carlo is then used to determine the fcc-hcp phase boundary of the Lennard-Jones solid in its entirety. These results are compared against the experimental results for the Lennard-Jones potential's closest physical analogue, the rare-gas solids. While some of the published rare-gas observations are in approximate agreement with the lattice-switch results, these findings contradict the widely held belief that fcc is the equilibrium structure of the heavier rare-gas solids for all pressures and temperatures. The possible reasons for this disagreement are discussed. Finally, we examine the pros and cons of the lattice-switch technique, and explore ways in which it can be extended to cover an even wider range of structures and interactions.
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Can, Mutan Oya. "Comparison Of Regression Techniques Via Monte Carlo Simulation." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12605175/index.pdf.

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The ordinary least squares (OLS) is one of the most widely used methods for modelling the functional relationship between variables. However, this estimation procedure counts on some assumptions and the violation of these assumptions may lead to nonrobust estimates. In this study, the simple linear regression model is investigated for conditions in which the distribution of the error terms is Generalised Logistic. Some robust and nonparametric methods such as modified maximum likelihood (MML), least absolute deviations (LAD), Winsorized least squares, least trimmed squares (LTS), Theil and weighted Theil are compared via computer simulation. In order to evaluate the estimator performance, mean, variance, bias, mean square error (MSE) and relative mean square error (RMSE) are computed.
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Louvin, Henri. "Development of an adaptive variance reduction technique for Monte Carlo particle transport." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS351/document.

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L’algorithme Adaptive Multilevel Splitting (AMS) a récemment fait son apparition dans la littérature de mathématiques appliquées, en tant que méthode de réduction de variance pour la simulation Monte Carlo de chaı̂nes de Markov. Ce travail de thèse se propose d’implémenter cette méthode de réduction de variance adaptative dans le code Monte-Carlo de transport de particules TRIPOLI-4,dédié entre autres aux études de radioprotection et d’instrumentation nucléaire. Caractérisées par de fortes atténuations des rayonnements dans la matière, ces études entrent dans la problématique du traitement d’évènements rares. Outre son implémentation inédite dans ce domaine d’application, deux nouvelles fonctionnalités ont été développées pour l’AMS, testées puis validées. La première est une procédure d’encaissement au vol permettant d’optimiser plusieurs scores en une seule simulation AMS. La seconde est une extension de l’AMS aux processus branchants, courants dans les simulations de radioprotection, par exemple lors du transport couplé de neutrons et des photons induits par ces derniers. L’efficacité et la robustesse de l’AMS dans ce nouveau cadre applicatif ont été démontrées dans des configurations physiquement très sévères (atténuations du flux de particules de plus de 10 ordres de grandeur), mettant ainsi en évidence les avantages prometteurs de l’AMS par rapport aux méthodes de réduction de variance existantes<br>The Adaptive Multilevel Splitting algorithm (AMS) has recently been introduced to the field of applied mathematics as a variance reduction scheme for Monte Carlo Markov chains simulation. This Ph.D. work intends to implement this adaptative variance reduction method in the particle transport Monte Carlo code TRIPOLI-4, dedicated among others to radiation shielding and nuclear instrumentation studies. Those studies are characterized by strong radiation attenuation in matter, so that they fall within the scope of rare events analysis. In addition to its unprecedented implementation in the field of particle transport, two new features were developed for the AMS. The first is an on-the-fly scoring procedure, designed to optimize the estimation of multiple scores in a single AMS simulation. The second is an extension of the AMS to branching processes, which are common in radiation shielding simulations. For example, in coupled neutron-photon simulations, the neutrons have to be transported alongside the photons they produce. The efficiency and robustness of AMS in this new framework have been demonstrated in physically challenging configurations (particle flux attenuations larger than 10 orders of magnitude), which highlights the promising advantages of the AMS algorithm over existing variance reduction techniques
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Nilsson, Emma. "Monte Carlo simulation techniques : The development of a general framework." Thesis, Linköping University, Department of Management and Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-18327.

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<p>Algorithmica Research AB develops software application for the financial markets. One of their products is Quantlab that is a tool for quantitative analyses. An effective method to value several financial instruments is Monte Carlo simulation. Since it is a common method Algorithmica is interesting in investigating if it is possible to create a Monte Carlo framework.</p><p>A requirement from Algorithmica is that the framework is general and this is the main problem to solve. It is difficult to generate a generalized framework because financial derivatives have very different appearances. To simplify the framework the thesis will be delimitated to European style derivatives where the underlying asset is following a Geometric Brownian Motion.</p><p>The definition of the problem and delimitation were defined gradually, in parallel with the review of literature, this to be able to decide what purpose, and delimitations that is reasonable to treat. Standard Monte Carlo requires a large number of trials and is therefore slow. To speed up the process there exist different variance reduction techniques and also Quasi Monte Carlo simulation, where deterministic numbers (low discrepancy sequences) is used instead of random. The thesis investigated the variance reduction techniques; control variate technique, antithetic variate technique, and the low discrepancy sequences; Sobol, Faure and Halton.</p><p>Three test instruments were chosen to test the framework, an Asian option and a Barrier option where the purpose is to conclude which Monte Carle method that performs best, and also a structured product; Smart Start, that is more complex and the purpose is to test that the framework can handle it.</p><p>To increase the understanding of the theory the Halton, Faure and Sobol sequence were implemented in Quantlab in parallel with the review of literature. The Halton and Faure sequences also seemed to perform worse than Sobol so they were not further analyzed.</p><p>The developing of the framework was an iterative process. The chosen solution is to design a general framework by using five function pointers; the path generator, the payoff function, the stop criterion function and the volatility and interest rates. The user specifies these functions by him/her given some obligatory input and output values. It is not a problem-free solution to use function pointers and several conflicts and issues are defined, therefore it is not recommended to implement the framework as it is designed today.</p><p>In parallel with the developing of the framework several experiments on the Asian and Barrier options were performed with varying result and it is not possible to draw a conclusion on which method that is best. Often Sobol seems to converge better and fluctuates less than standard Monte Carlo. The literature indicates that it is important that the user has an understanding of the instrument that should be valued, the stochastic process it follows and the advantages and disadvantages of different Monte Carlo methods. It is recommended to evaluate the different method with experiments, before deciding which method to use when valuing a new derivative.</p>
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FOIS, GIOVANNA ROSA. "Monte Carlo simulation studies for spatially fractionated radiation therapy techniques." Doctoral thesis, Università degli Studi di Cagliari, 2013. http://hdl.handle.net/11584/266224.

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The purpose of this work was to evaluate the possible gain in tissue sparing in hadrontherapy when a spatial fractionation of the dose is used. Monte Carlo simulations (GATE v.6) have been used as a method to assess the dose distributions in a cylindrical water phantom (16 cm height and 16 cm of diameter). The phantom was irradiated with carbon and oxygen minibeams of 0.7 mm of beam width, and with protons in a grid geometry configuration. Several centre-to-centre distances, covering a 2 x 2 cm2 area, have been taken into account. The ratio of the peak-to-valley doses (PVDR) and the penumbrae was used as evaluation parameter, since PVDR is considered to be a very relevant dosimetric parameter for tissue sparing. Extremely high PVDRs values and very narrow penumbrae were obtained in all depths. This means that this new way of dose delivery might allow the use of higher and potentially curative doses in clinical cases where tissue tolerances are a limit to achieve a curative treatment. The high PVDR obtained and the small penumbrae in comparison with existing radiosurgery techniques, suggest a potential gain in healthy tissue sparing in those new techniques.
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Ahmad, Abdul Ossman. "Advances in an open-source direct simulation Monte Carlo technique for hypersonic rarefied gas flows." Thesis, University of Strathclyde, 2013. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=26579.

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Hypersonic vehicles that travel through rarefied gas environments are very expensive to design through experimental methods. In the last few decades major work has been carried out in developing numerical methods to capture these types of flows to a certain degree of accuracy. This accuracy is increased using particle based numerical techniques as opposed to continuum computational fluid dynamics. However, one of the modern problems of particle based techniques is the high computational cost associated with it. This thesis presents an enhanced open-source particle based technique to capture high speed rarefied gas flows. This particle based technique is called dsmcFoam and is based on the direct simulation Monte Carlo technique. As a result of the author's work dsmcFoam has become more efficient and accurate. Benchmark studies of the standard dsmcFoam solver will be presented before introducing the main advances. The results of the benchmark investigations are compared with analytical solutions, other DSMC codes and experimental data available in the literature. And excellent agreement is found when good DSMC practice has been followed. The main advances of dsmcFoam discussed are a routine for selecting collision pairs called the transient adaptive sub-cell (TASC) method and a dynamic wall temperature model (DWTM). The DWTM relates the wall temperature to the heat flux. In addition, verification and validation studies are undertaken of the DWTM. Furthermore, the widely used conventional 8 sub-cell method used to select possible collision pairs becomes very cumbersome to employ properly. This is because many mesh refinement stages are required in order to obtain accurate data. Instead of mesh refinement the TASC technique automatically employs more sub-cells, and these sub-cells are based on the number of particles in a cell. Finally, parallel efficiency tests of dsmcFoam are presented in this thesis along with a new domain decomposition technique for parallel processing. This technique splits up the computational domain based on the number of particles, such that each processor has the same number of particles to work with.
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Lester, Christopher. "Efficient simulation techniques for biochemical reaction networks." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:bb804e01-b1de-409f-b843-4806c2c990c2.

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Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemical processes. The mathematical formulations that such models lead to are opaque, and, due to their complexity, are often considered analytically intractable. As such, a variety of Monte Carlo simulation algorithms have been developed to explore model dynamics empirically. Whilst well-known methods, such as the Gillespie Algorithm, can be implemented to investigate a given model, the computational demands of traditional simulation techniques remain a significant barrier to modern research. In order to further develop and explore biologically relevant stochastic models, new and efficient computational methods are required. In this thesis, high-performance simulation algorithms are developed to estimate summary statistics that characterise a chosen reaction network. The algorithms make use of variance reduction techniques, which exploit statistical properties of the model dynamics, so that the statistics can be computed efficiently. The multi-level method is an example of a variance reduction technique. The method estimates summary statistics of well-mixed, spatially homogeneous models by using estimates from multiple ensembles of sample paths of different accuracies. In this thesis, the multi-level method is developed in three directions: firstly, a nuanced implementation framework is described; secondly, a reformulated method is applied to stiff reaction systems; and, finally, different approaches to variance reduction are implemented and compared. The variance reduction methods that underpin the multi-level method are then re-purposed to understand how the dynamics of a spatially-extended Markov model are affected by changes in its input parameters. By exploiting the inherent dynamics of spatially-extended models, an efficient finite difference scheme is used to estimate parametric sensitivities robustly. The new simulation methods are tested for functionality and efficiency with a range of illustrative examples. The thesis concludes with a discussion of our findings, and a number of future research directions are proposed.
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Baker, Adam Richard Ernest. "The use of the Monte Carlo technique in the simulation of small-scale dosimeters and microdosimeters." Thesis, University of Birmingham, 2011. http://etheses.bham.ac.uk//id/eprint/2897/.

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In order to understand the effects of low keV radiation upon small scales, a number of detector designs have been developed to investigate the ways energy is deposited. This research was conducted in order to investigate a number of different detector designs, looking in particular at their properties as small scale dosimeters exposed to photon radiation with an energy of 5-50 keV. In addition to this, Monte Carlo models were constructed of the different detector designs in order to ascertain the trends in energy absorption within the detectors. An important part of the research was investigating the dose enhancement effects produced when the low Z elements present in human tissues are in proximity to higher Z metallic elements within this energy range. This included looking at dose enhancement due to the photoelectric effect, with a photon energy of 5-50 keV and through the absorption of thermal neutrons. The reason for studying the dose enhancement was twofold - looking at the increase in energy absorption for elements that are currently being investigated for medical applications as well as elements that are present in dosemeters alongside the tissue equivalent elements. By comparing the results produced using the Monte Carlo codes MCNP4C and EGSnrc, simulations were produced for a variety of different detector designs, both solid state and gasfilled. These models were then compared with experimental results and were found to be able to predict trends in the behaviour of some of the detector designs.
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Mastail, Cédric. "Modélisation et simulation du dépôt des oxydes à forte permittivité par la technique du Monte-Carlo cinétique." Toulouse 3, 2009. http://thesesups.ups-tlse.fr/989/.

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Miniaturiser les composants impose des changements radicaux pour l'élaboration des dispositifs micro électroniques du futur. Dans ce cadre, les oxydes de grille MOS atteignent des épaisseurs limites qui les rendent perméables aux courants de fuite. Une solution est de remplacer le SiO2 par un matériau de permittivité plus élevée permettant l'utilisation de couches plus épaisses pour des performances comparables. Dans ce travail nous présentons une modélisation multi-échelle de la croissance par couche atomique (ALD) d'HfO2 sur Si permettant de relier la nano-structuration d'une interface au procédé d'élaboration. Nous montrons que la connaissance de processus chimiques élémentaires, via des calculs DFT, permet d'envisager une simulation procédé qui repose sur le développement d'un logiciel de type Monte Carlo Cinétique nommé "HIKAD". Au delà des mécanismes les plus évidents, adsorption, désorption, décomposition et hydrolyse des précurseurs sur la surface, nous introduirons la notion de mécanismes de densification des couches d'oxyde déposées. Ces mécanismes sont l'élément clé permettant de comprendre comment s'effectue la croissance de la couche en termes de couverture. Mais au delà de cet aspect ils nous permettent d'appréhender comment, à partir de réactions de type moléculaire le système évolue vers un matériau massif. Nous discuterons ces divers éléments à la lumière de résultats de caractérisations obtenus récemment sur le plan expérimental du dépôt d'oxydes d'hafnium<br>Miniaturizing components requires radical changes in the development of future micro electronic devices. In this perspective, the gate dielectric of MOS devices can become so thin as to be made permeable to leakage currents. One solution is to replace SiO2 by a material with a higher permittivity which would allow the use of thicker layers with similar results. My work presents a multi-scale modelling of the growth of HfO2 on Si by atomic layer (ALD), which allows me to link the nano-structuration of an interface with the process of development. I demonstrate that knowing how basic chemical processes work, thanks to DFT calculations, allows considering a process simulation based on the development of a Kinetic Monte Carlo software named "HIKAD. " Going beyond rather obvious mechanisms, I introduce the notion of densification mechanisms of deposited oxide layers. These mechanisms are the key element to understand how the growth of the layer in terms of coverage works. But even beyond that aspect, they allow to study the system's evolution towards a massive material, starting from molecular reactions. I shall discuss all those points in the light of recent experimental characterisation results concerning the deposition of hafnium oxides
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Bücher zum Thema "Monte Carlo Simulation Technique"

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Mun, Johnathan. Modeling risk: Applying Monte Carlo simulation, real options analysis, forecasting, and optimization techniques. 2nd ed. New York: Wiley, 2010.

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A, Viterna Larry, and Lewis Research Center, eds. ETARA PC version 3.3 user's guide: Reliability, availability, maintainability simulation model. Cleveland, Ohio: NASA Lewis Research Center, 1991.

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A, Viterna Larry, and Lewis Research Center, eds. ETARA PC version 3.3 user's guide: Reliability, availability, maintainability simulation model. Cleveland, Ohio: NASA Lewis Research Center, 1991.

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A, Viterna Larry, and Lewis Research Center, eds. ETARA PC version 3.3 user's guide: Reliability, availability, maintainability simulation model. Cleveland, Ohio: NASA Lewis Research Center, 1991.

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Mooney, Christopher. Monte Carlo Simulation. 2455 Teller Road, Thousand Oaks California 91320 United States of America: SAGE Publications, Inc., 1997. http://dx.doi.org/10.4135/9781412985116.

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Zhu, Zhen, and Hari Rajagopalan. Monte Carlo Simulation. 2455 Teller Road, Thousand Oaks California 91320 United States: SAGE Publications, Inc., 2023. http://dx.doi.org/10.4135/9781071908969.

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I, Schueller G., ed. Monte Carlo simulation. Lisse: A.A. Balkema, 2001.

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Hess, Karl, ed. Monte Carlo Device Simulation. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-4026-7.

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Thomopoulos, Nick T. Essentials of Monte Carlo Simulation. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6022-0.

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Brandimarte, Paolo. Handbook in Monte Carlo Simulation. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118593264.

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Buchteile zum Thema "Monte Carlo Simulation Technique"

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Frenkel, D. "Advanced Monte Carlo Techniques." In Computer Simulation in Chemical Physics, 93–152. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1679-4_4.

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Woolard, D. L., H. Tian, M. A. Littlejohn, R. J. Trew, and K. W. Kim. "The Application of Monte Carlo Techniques in Advanced Hydrodynamic Transport Models." In Monte Carlo Device Simulation, 219–66. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-4026-7_8.

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D'Elia, Massimo, Kurt Langfeld, and Biagio Lucini. "Advanced Monte Carlo simulation techniques." In Stochastic Methods in Scientific Computing, 177–243. Boca Raton: Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781315156156-5.

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Demirtas, Hakan. "A Multiple Imputation Framework for Massive Multivariate Data of Different Variable Types: A Monte-Carlo Technique." In Monte-Carlo Simulation-Based Statistical Modeling, 143–62. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3307-0_8.

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Sarrut, D., and N. Krah. "Artificial Intelligence and Monte Carlo Simulation." In Monte Carlo Techniques in Radiation Therapy, 251–58. 2nd ed. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003211846-20.

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Hanagaki, Kazunori, Junichi Tanaka, Makoto Tomoto, and Yuji Yamazaki. "Event Simulation." In Experimental Techniques in Modern High-Energy Physics, 115–23. Tokyo: Springer Japan, 2022. http://dx.doi.org/10.1007/978-4-431-56931-2_7.

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AbstractNot only real experimental data but also simulated data are necessary for modern data analyses because experiments, that is, detectors, etc. are getting complex so that we need the help of Monte Carlo (MC) simulation to understand the experimental data.
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L'Ecuyer, Pierre, François Le Gland, Pascal Lezaud, and Bruno Tuffin. "Splitting Techniques." In Rare Event Simulation using Monte Carlo Methods, 39–61. Chichester, UK: John Wiley & Sons, Ltd, 2009. http://dx.doi.org/10.1002/9780470745403.ch3.

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Shigeta, K., K. Tanaka, T. Iizuka, H. Kato, and H. Matsumoto. "A New Statistical Enhancement Technique in Parallelized Monte Carlo Device Simulation." In Simulation of Semiconductor Devices and Processes, 384–87. Vienna: Springer Vienna, 1995. http://dx.doi.org/10.1007/978-3-7091-6619-2_93.

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Thomson, Rowan M., Åsa Carlsson Tedgren, Gabriel Fonseca, Guillaume Landry, Brigitte Reniers, Mark J. Rivard, Jeffrey F. Williamson, and Frank Verhaegen. "Monte Carlo Simulation in Brachytherapy Patients and Applicator Modelling." In Monte Carlo Techniques in Radiation Therapy, 235–49. 2nd ed. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003211846-19.

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Allen, Theodore T. "Variance Reduction Techniques and Quasi-Monte Carlo." In Introduction to Discrete Event Simulation and Agent-based Modeling, 111–24. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-139-4_8.

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Konferenzberichte zum Thema "Monte Carlo Simulation Technique"

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Graham, G. E. "DZero Monte Carlo simulation." In ADVANCED COMPUTING AND ANALYSIS TECHNIQUES IN PHYSICS RESEARCH: VII International Workshop; ACAT 2000. AIP, 2001. http://dx.doi.org/10.1063/1.1405336.

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Jain, Pranav, Ziyin Qu, Peter Yichen Chen, and Oded Stein. "Neural Monte Carlo Fluid Simulation." In SIGGRAPH '24: Special Interest Group on Computer Graphics and Interactive Techniques Conference. New York, NY, USA: ACM, 2024. http://dx.doi.org/10.1145/3641519.3657438.

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Baoxin Li, R. Chellappa, and Hankyu Moon. "Monte Carlo simulation techniques for probabilistic tracking." In Conference Record. Thirty-Fifth Asilomar Conference on Signals, Systems and Computers. IEEE, 2001. http://dx.doi.org/10.1109/acssc.2001.986883.

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Amini, Abolfazl M., George E. Ioup, and Juliette W. Ioup. "Metropolis Monte Carlo deconvolution technique compared to iterative methods for noisy data." In Aerospace/Defense Sensing, Simulation, and Controls, edited by Ivan Kadar. SPIE, 2001. http://dx.doi.org/10.1117/12.436983.

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Abu Husain, M. K., N. I. Mohd Zaki, M. B. Johari, and G. Najafian. "Extreme Response Prediction for Fixed Offshore Structures by Monte Carlo Time Simulation Technique." In ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/omae2016-54200.

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For an offshore structure, wind, wave, current, tide, ice and gravitational forces are all important sources of loading which exhibit a high degree of statistical uncertainty. The capability to predict the probability distribution of the response extreme values during the service life of the structure is essential for safe and economical design of these structures. Many different techniques have been introduced for evaluation of statistical properties of response. In each case, sea-states are characterised by an appropriate water surface elevation spectrum, covering a wide range of frequencies. In reality, the most versatile and reliable technique for predicting the statistical properties of the response of an offshore structure to random wave loading is the time domain simulation technique. To this end, conventional time simulation (CTS) procedure or commonly called Monte Carlo time simulation method is the best known technique for predicting the short-term and long-term statistical properties of the response of an offshore structure to random wave loading due to its capability of accounting for various nonlinearities. However, this technique requires very long simulations in order to reduce the sampling variability to acceptable levels. In this paper, the effect of sampling variability of a Monte Carlo technique is investigated.
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Drosg, M., Marianne E. Hamm, and Robert W. Hamm. "Complete Monte Carlo Simulation of Neutron Scattering Experiments." In APPLICATIONS OF NUCLEAR TECHNIQUES: Eleventh International Conference. AIP, 2011. http://dx.doi.org/10.1063/1.3665300.

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BOWLES, ROLAND, TONY LAITURI, and GEORGE TREVINO. "A Monte Carlo simulation technique for low-altitude, wind-shear turbulence." In 28th Aerospace Sciences Meeting. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1990. http://dx.doi.org/10.2514/6.1990-564.

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Sadowsky, J. S., and J. A. Bucklew. "Large deviations theory techniques in Monte Carlo simulation." In the 21st conference. New York, New York, USA: ACM Press, 1989. http://dx.doi.org/10.1145/76738.76804.

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Perry, Vincent, Wendy Gao, Michael Chen, J. Michael Barton, and Simon Su. "Visualization Techniques for Large-Scale Monte Carlo Simulation." In 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9006423.

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Irimia, Daniel, and Jens O. M. Karlsson. "Monte Carlo Simulation of Ice Formation in Tissues." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-32681.

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Freezing is a common technique for preservation of isolated cells, and extending its applications to the preservation of tissues would have important implications for the storage and distribution of tissue engineered products. Unlike isolated cells in suspension, cells in tissue interact with each other, and this interaction is known to affect the outcome of tissue cryopreservation. As a consequence, our knowledge of the cryobiology of isolated cells cannot simply be extrapolated to tissues, and new models, which consider the interaction between cells, need to be developed. The model that we propose is based on previous quantitative analysis of intercellular ice propagation in a micropatterned two-cell system. We used Monte Carlo simulations to extrapolate the results from cell pairs to two-dimensional and three-dimensional tissues. Effects of tissue geometry, cellular connectivity, and degree of intercellular interaction were investigated.
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Berichte der Organisationen zum Thema "Monte Carlo Simulation Technique"

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Schipaunboord, W. N., M. A. Lont, and A. H. M. Kron. JTM-00-01 NDE Acceptance Criteria for Girth Defects Linked with Welding and Inspection Technique. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), January 2001. http://dx.doi.org/10.55274/r0011796.

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Experimental work was conducted on two girth welds in large diameter steel pipes. By a proper selection of welding consumables, yield strength mismatch was obtained from 5 to 12% undermatching and 45% overmatching. The girth welds were non-destructively tested using the time of flight diffraction technique by three NDE companies. The verification of the detection and sizing capabilities of TOFD inspection techniques has shown that the performance levels varied widely. This finding confirms the need to validate the NDE techniques. Tensile specimens, Charpy and CTOD specimens, and curved wide plate testes were taken out of the welded pipes for testing the mismatch ratio, fracture toughness behavior and failure mechanisms. The wide plate tests were supported by an ECA using BS 7910. This work has reconfirmed the validity of the basic toughness and overmatch requirements given by EPRG for the application of the Tier 2 defect limits. The wide plate tests demonstrated that failure to satisfy one (or both) of these requirements results in a significant reduction of the acceptable defect length limit. The derivation of ECA-based NDE acceptance criteria is not specified in the present standards. The way to deal with the performance of welding technique, the NDE systems and its relation to ECA-based acceptance criteria is not prescribed. In the present Dutch project the derivation of ECA-based acceptance criteria will be validated by a probabilistic approach. This approach is based on Monte Carlo simulations by which the effects of weld defect population; the NDE performance and acceptance criteria on the repair rate and integrity level can be investigated.
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Bednall, Timothy. Monte Carlo Simulations: Power Analysis and Beyond. Instats Inc., 2023. http://dx.doi.org/10.61700/gpienbvutyd38469.

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This 3-day workshop offers a comprehensive understanding of Monte Carlo simulations and power analysis using Mplus and R software. Tailored for PhD students, professors, and professional researchers across various disciplines, the workshop covers a range of topics from introduction to Monte Carlo simulations, principles of power analysis, to ethical considerations and future directions in the use of these techniques, equipping participants with practical skills and deep understanding of these advanced statistical tools.
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van der Mensbrugghe, Dominique. The META 21 Integrated Assessment Model in GAMS and LHS Sampling. GTAP Working Paper, May 2023. http://dx.doi.org/10.21642/gtap.wp95.

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The META 21 Integrated Assessment Model (Dietz et al., 2021) represents a fairly comprehensive climate change simulation model incorporating a number of features: (a) a recent simple climate model; (b) down-scaling of temperature change to the country level; (c) integration of a number of bio-physical tipping points linked to rising temperatures; and (d) economic damages linked to rising sea levels and temperature using recent country-level estimates from the literature. The original implementation of META 21 was in Excel and linked to the @Risk Excel add-in for performing Monte Carlo-type analysis. This paper reflects a translation of META 21 into GAMS. One of the key purposes is to allow for ready incorporation of many of the features of META 21 into other models—notably CGE-based IAMs. To replace the features provided by the @Risk Excel add-in, this paper also introduces a software package that produces random deviates—and, similar to @Risk, uses the Latin Hypercube Sampling (LHS) approach, which is a stratified sampling technique intended to cover the entire sampling space efficiently and, in addition, orders the sample to reflect a desired correlation matrix for the sampled random variables.
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Glaser, R. Monte Carlo simulation of scenario probability distributions. Office of Scientific and Technical Information (OSTI), October 1996. http://dx.doi.org/10.2172/632934.

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Xu, S. L., B. Lai, and P. J. Viccaro. APS undulator and wiggler sources: Monte-Carlo simulation. Office of Scientific and Technical Information (OSTI), February 1992. http://dx.doi.org/10.2172/10134610.

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Douglas, L. J. Monte Carlo Simulation as a Research Management Tool. Office of Scientific and Technical Information (OSTI), June 1986. http://dx.doi.org/10.2172/1129252.

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Aguayo Navarrete, Estanislao, Austin S. Ankney, Timothy J. Berguson, Richard T. Kouzes, John L. Orrell, Meredith D. Troy, and Clinton G. Wiseman. Monte Carlo Simulation Tool Installation and Operation Guide. Office of Scientific and Technical Information (OSTI), September 2013. http://dx.doi.org/10.2172/1095434.

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Xu, S. L., B. Lai, and P. J. Viccaro. APS undulator and wiggler sources: Monte-Carlo simulation. Office of Scientific and Technical Information (OSTI), February 1992. http://dx.doi.org/10.2172/5494991.

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Boyd, Lain D. Monte Carlo Simulation of Radiation in Hypersonic Flows. Fort Belvoir, VA: Defense Technical Information Center, September 2002. http://dx.doi.org/10.21236/ada414031.

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Clegg, Benjamin Wyatt, David H. Collins, Jr., and Aparna V. Huzurbazar. Petri Nets for Adversarial Models using Monte Carlo Simulation. Office of Scientific and Technical Information (OSTI), September 2018. http://dx.doi.org/10.2172/1473775.

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