Relevant bibliographies by topics / Stochastic Simulation of Chemical Reactions

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Stochastic Simulation of Chemical Reactions'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Stochastic Simulation of Chemical Reactions"

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Zenyuk, Dmitry Alexeyevich. "Stochastic simulation of chemical reactions in subdiffusion medium." Computer Research and Modeling 13, no. 1 (2021): 87–104. http://dx.doi.org/10.20537/2076-7633-2021-13-1-87-104.

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Cai, Xiaodong. "Exact stochastic simulation of coupled chemical reactions with delays." Journal of Chemical Physics 126, no. 12 (2007): 124108. http://dx.doi.org/10.1063/1.2710253.

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Nicolau, Dan V., and Kevin Burrage. "Stochastic simulation of chemical reactions in spatially complex media." Computers & Mathematics with Applications 55, no. 5 (2008): 1007–18. http://dx.doi.org/10.1016/j.camwa.2006.12.085.

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Zhou, Wen, Xinjun Peng, Zhenglou Yan, and Yifei Wang. "Accelerated stochastic simulation algorithm for coupled chemical reactions with delays." Computational Biology and Chemistry 32, no. 4 (2008): 240–42. http://dx.doi.org/10.1016/j.compbiolchem.2008.03.007.

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Vereecken, Luc, Guido Huyberechts, and Jozef Peeters. "Stochastic simulation of chemically activated unimolecular reactions." Journal of Chemical Physics 106, no. 16 (1997): 6564–73. http://dx.doi.org/10.1063/1.473656.

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Thanh, Vo Hong. "RSSALib: a library for stochastic simulation of complex biochemical reactions." Bioinformatics 36, no. 18 (2020): 4825–26. http://dx.doi.org/10.1093/bioinformatics/btaa602.

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Abstract Motivation Stochastic chemical kinetics is an essential mathematical framework for investigating the dynamics of biological processes, especially when stochasticity plays a vital role in their development. Simulation is often the only option for the analysis of many practical models due to their analytical intractability. Results We present in this article, the simulation library RSSALib, implementing our recently developed rejection-based stochastic simulation algorithm (RSSA) and a wide range of its improvements, to accelerate the simulation and analysis of biochemical reactions. RS
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Cai, Xiaodong, and Zhouyi Xu. "K-leap method for accelerating stochastic simulation of coupled chemical reactions." Journal of Chemical Physics 126, no. 7 (2007): 074102. http://dx.doi.org/10.1063/1.2436869.

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Xu, Yuting, and Yueheng Lan. "The N-leap method for stochastic simulation of coupled chemical reactions." Journal of Chemical Physics 137, no. 20 (2012): 204103. http://dx.doi.org/10.1063/1.4767343.

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LI, QIAN SHU, and RUI ZHU. "STOCHASTIC SIMULATION OF CHEMICAL CHUA SYSTEM." International Journal of Bifurcation and Chaos 14, no. 03 (2004): 1053–57. http://dx.doi.org/10.1142/s0218127404009582.

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A master equation for a scheme of chemical Chua system has been simulated stochastically. Two pairs of reaction simulations, one pair corresponding to deterministic chaos and the other pair to limit cycle, are carried out. The initial conditions differ with only one molecule for the former, while one hundred molecules for the latter. The rapid separation of time traces is shown only in the former case. This marked difference of dynamic behavior between the two cases might reveal the intrinsic random nature of deterministic chemical chaos, i.e. initial-condition sensitivity based on random coll
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MOREAU, M., O. BÉNICHOU, C. LOVERDO, and R. VOITURIEZ. "STOCHASTIC SEARCH PROCESSES AND CHEMICAL REACTIVITY IN HETEROGENEOUS MEDIA." International Journal of Bifurcation and Chaos 19, no. 10 (2009): 3519–24. http://dx.doi.org/10.1142/s0218127409024955.

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Intermittent search processes alternate between two different stochastic motions in order to reach a given target. If the faster motion has a lower probability to detect the target, a question arises concerning the efficiency of both processes, and it may be possible to minimize the search time by a convenient choice of the parameters. This argument has been used to interpret observations in molecular biology or to explain the behavior of animals when searching for food. It can also have interesting consequences for the kinetics of reactions in heterogeneous media. In particular, the reaction
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Dissertations / Theses on the topic "Stochastic Simulation of Chemical Reactions"

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Dao, Duc Khanh. "Modeling and analysis of neuronal networks, stochastic chemical reactions in cellular micro-domains and telomere dynamics." Paris 6, 2013. http://www.theses.fr/2013PA066513.

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Nous modélisons différents évènements aléatoires intervenant en biologie. Dans une première partie, on étudie certaines propriétés de populations de neurones. En utilisant un modèle de facilitation dépression synaptique, on étudie le phénomène de bursts synchrones observés à différentes échelles de populations. On étudie ensuite la transition entre état haut et bas de neurones induite par le bruit. Afin de comprendre le phénomène d’oscillations du temps de séjour dans l’état haut, onétudie le problème de premier temps de passage pour une classe de processus stochastiquesdans un domaine avec un
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Hellander, Andreas. "Multiscale Stochastic Simulation of Reaction-Transport Processes : Applications in Molecular Systems Biology." Doctoral thesis, Uppsala universitet, Avdelningen för teknisk databehandling, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-152098.

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Quantitative descriptions of reaction kinetics formulated at the stochastic mesoscopic level are frequently used to study various aspects of regulation and control in models of cellular control systems. For this type of systems, numerical simulation offers a variety of challenges caused by the high dimensionality of the problem and the multiscale properties often displayed by the biochemical model. In this thesis I have studied several aspects of stochastic simulation of both well-stirred and spatially heterogenous systems. In the well-stirred case, a hybrid method is proposed that reduces the
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Zavar, Moosavi Azam Sadat. "Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/82491.

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Simulations and modeling of large-scale systems are vital to understanding real world phenomena. However, even advanced numerical models can only approximate the true physics. The discrepancy between model results and nature can be attributed to different sources of uncertainty including the parameters of the model, input data, or some missing physics that is not included in the model due to a lack of knowledge or high computational costs. Uncertainty reduction approaches seek to improve the model accuracy by decreasing the overall uncertainties in models. Aiming to contribute to this area,
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Shepherd, Tricia D. "Models for chemical processes : activated dynamics across stochastic potentials." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/27062.

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Wu, Wenwei. "Chemical reactions in turbulence : numerical studies through direct numerical simulations." Thesis, Littoral, 2021. http://www.theses.fr/2021DUNK0577.

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Le présent travail se concentre sur les propriétés statistiques des scalaires réactifs subissant des réactions chimiques réversibles en turbulence incompressible. Une analyse théorique des propriétés statistiques des scalaires à différents ordres de moments a été réalisée sur la base d'approximations et de modèles convenablement proposés. Les résultats théoriquement dérivés ont ensuite été comparés aux résultats numériques obtenus par simulation numérique directe (DNS). Dans la simulation numérique directe, les dérivés spatiales ont été principalement approximées en utilisant une méthode pseud
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Ulissi, Zachary Ward. "Modeling and simulation of stochastic phenomena in carbon nanotube-based single molecule sensors." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98716.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 199-218).<br>Shrinking sensors to the nanoscale introduces novel selectivity mechanisms and enables the ultimate sensitivity limit, single-molecule detection. Single-walled carbon nanotubes, with a bright fluorescence signal and no photobleaching, are a platform for implantable near-IR sensors capable of selectively detecting a range of small-molecules including the radical signalling molecule nitric oxide, the h
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Sun, Guangyuan. "Stochastic Simulation of Lagrangian Particle Transport in Turbulent Flows." BYU ScholarsArchive, 2015. https://scholarsarchive.byu.edu/etd/5838.

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This dissertation presents the development and validation of the One Dimensional Turbulence (ODT) multiphase model in the Lagrangian reference frame. ODT is a stochastic model that captures the full range of length and time scales and provides statistical information on fine-scale turbulent-particle mixing and transport at low computational cost. The flow evolution is governed by a deterministic solution of the viscous processes and a stochastic representation of advection through stochastic domain mapping processes. The three algorithms for Lagrangian particle transport are presented within t
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de, Roulhac Selma Lee. "COMPARISON OF CHEMICAL PROCESS SIMULATION PROGRAMS FOR EDUCATION." Thesis, The University of Arizona, 1985. http://hdl.handle.net/10150/275282.

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Greenfield, Daniel Leo Computer Science &amp Engineering Faculty of Engineering UNSW. "New and hybrid methods for simulating biochemical systems." Awarded by:University of New South Wales. Computer Science and Engineering, 2006. http://handle.unsw.edu.au/1959.4/23990.

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It is a dream of Systems-Biology to efficiently simulate an entire cell on a computer. The potential medical and biological applications of such a tool are immense, and so are the challenges to accomplish it. At the level of a cell, the number of reacting molecules is so low that stochastic effects can be crucial in deciding the system-level behaviour of the cell. Despite the recent development of many new and hybrid stochastic approaches, exact stochastic simulation algorithms are still needed, and are widely employed in most current biochemical simulation packages. Unfortunately, the perform
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Nair, Nitish. "Theoretical and simulation tools for electron transfer and chain reactions in single walled carbon nanotubes." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/51630.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2009.<br>Includes bibliographical references (p. 124-130).<br>Single walled carbon nanotubes (SWNT) are cylindrical sheets of graphene whose electronic structures and diameters are determined by their chiralities. Current synthetic methods produce batches of nanotubes containing a variety of electronic properties. The separation of these mixtures into semiconductors and metals will greatly enhance their utility for nanoelectronic devices. Progress has been achieved in this area at the laboratory scale throug
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Books on the topic "Stochastic Simulation of Chemical Reactions"

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Warshel, Arieh. Computer modeling of chemical reactions in enzymes and solutions. Wiley, 1997.

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J, Tóth, ed. Mathematical models of chemical reactions: Theory and applications of deterministic and stochastic models. Manchester University Press, 1989.

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Doraiswamy, L. K. The analysis of chemically reacting systems: A stochastic approach. Gordon and Breach Science Publishers, 1987.

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Computer modeling of chemical reactions in enzymes and solutions. Wiley, 1991.

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Péter, Érdi. Mathematical models of chemical reactions: Theory and applications of deterministic and stochastic models. Princeton University Press, 1989.

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Hippe, Z. Artificial intelligence in chemistry: Structure elucidation and simulation of organic reactions. Elsevier, 1991.

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Stewart, Warren E., and Warren E. Stewart. Computer-aided modeling of reactive systems. Wiley, 2008.

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Geochemical reaction modeling: Concepts and applications. Oxford University Press, 1996.

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Kaznessis, Yiannis Nikolaos. Statistical thermodynamics and stochastic kinetics: An introduction for engineers. Cambridge University Press, 2012.

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Bethke, Craig. Geochemical and biogeochemical reaction modeling. 2nd ed. Cambridge University Press, 2008.

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Book chapters on the topic "Stochastic Simulation of Chemical Reactions"

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Karni, Y., M. Goldstein, and E. Bar-Ziv. "Simulation of Diffusion and Chemical Reactions with a Cell-Mixing Stochastic Model." In Springer Series in Chemical Physics. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-83224-6_28.

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Backenköhler, Michael, Luca Bortolussi, and Verena Wolf. "Control Variates for Stochastic Simulation of Chemical Reaction Networks." In Computational Methods in Systems Biology. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31304-3_3.

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Bentele, Martin, and Roland Eils. "General Stochastic Hybrid Method for the Simulation of Chemical Reaction Processes in Cells." In Computational Methods in Systems Biology. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-25974-9_22.

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Sekimoto, Ken. "Fluctuations in Chemical Reactions." In Stochastic Energetics. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-05411-2_3.

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Britz, Dieter. "Coupled Homogeneous Chemical Reactions." In Digital Simulation in Electrochemistry. Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-662-02549-9_7.

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Holcman, David, and Zeev Schuss. "Markov Models for Stochastic Chemical Reactions." In Stochastic Narrow Escape in Molecular and Cellular Biology. Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-3103-3_6.

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Yoshimi, M., Y. Osana, T. Fukushima, and H. Amano. "Stochastic Simulation for Biochemical Reactions on FPGA." In Field Programmable Logic and Application. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30117-2_13.

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Segers, John, Johan Lukkien, and Peter Hilbers. "Parallel Monte Carlo simulation of chemical surface reactions: A case study." In High-Performance Computing and Networking. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61142-8_553.

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Shoev, Georgy, and Yevgeny A. Bondar. "Numerical Simulation of the Flow with Chemical Reactions Around a Wedge." In 30th International Symposium on Shock Waves 1. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46213-4_58.

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Benkö, Gil, Christoph Flamm, and Peter F. Stadler. "Explicit Collision Simulation of Chemical Reactions in a Graph Based Artificial Chemistry." In Advances in Artificial Life. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11553090_73.

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Conference papers on the topic "Stochastic Simulation of Chemical Reactions"

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Mane, Vibha, Monica F. Bugallo, and Petar M. Djuric. "Stochastic simulation of coupled chemical reactions using recursive methods." In ICASSP 2008 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/icassp.2008.4517694.

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Eldeeb, Mazen A., and Benjamin Akih-Kumgeh. "Reduced Chemical Kinetic Models Using Alternate and Stochastic Species Elimination." In ASME 2018 Power Conference collocated with the ASME 2018 12th International Conference on Energy Sustainability and the ASME 2018 Nuclear Forum. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/power2018-7242.

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This work extends the species sensitivity method of model reduction known as Alternate Species Elimination (ASE) to a stochastic version. The new Stochastic Species Elimination (SSE) approach allows for a linear reduction in the number of species retained in the course of reduction. It improves the computational cost and offers flexibility to the user in terminating the reduction process when an acceptable model size is attained. Larger chemical kinetic models, such as the recent literature model of n-octanol, are approached with the SSE method coupled with multiple species sampling. This furt
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Eldeeb, Mazen A., and Malshana Wadugurunnehalage. "Chemical Kinetic Model Reduction and Analysis of Tetrahydrofuran Combustion Using Stochastic Species Elimination." In ASME 2020 Power Conference collocated with the 2020 International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/power2020-16583.

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Abstract In this work, a chemical kinetic modeling study of the high-temperature ignition and laminar flame behavior of Tetrahydrofuran (THF), a promising second-generation transportation biofuel, is presented. Stochastic Species Elimination (SSE) model reduction approach (Eldeeb and Akih-Kumgeh, Proceedings of ASME Power Conference 2018) is implemented to develop multiple skeletal versions of a detailed chemical kinetic model of THF (Fenard et al., Combustion and Flame, 2018) based on ignition delay time simulations at various pressures and temperature ranges. The detailed THF model contains
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Soyhan, Hakan Serhad, Terese Løvås, and Fabian Mauss. "A Stochastic Simulation of an HCCI Engine Using an Automatically Reduced Mechanism." In ASME 2001 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/2001-ice-416.

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Abstract Homogeneous Charge Compression Ignition (HCCI) Engines are a promising alternative to the existing Spark Ignition Engines and Compression Ignition Engines. In an HCCI engine, the premixed fuel/air mixture ignites when sufficiently high temperature and pressure is reached. The entire bulk will auto-ignite at almost the same time because the physical conditions are similar throughout the combustion chamber. Therefore it is a justified assumption to consider the chemical reactions to be the rate-determining step for the ignition process. This gives us the opportunity to formulate a simpl
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Donaldson, Finn E., and James C. Coburn. "Stochastic Simulation of Modular Connections in Total Hip Replacement." In ASME 2013 Conference on Frontiers in Medical Devices: Applications of Computer Modeling and Simulation. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/fmd2013-16078.

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Several modern Total Hip Arthroplasty (THA) implants have been associated with increased release of metallic debris through combined mechanical fretting wear and chemical corrosion. These particles can lead to painful Adverse Reaction to Metallic Debris, often requiring early revision [1]. While much research has focused on improving the performance of bearing surfaces, the key parameters driving release of metallic debris at modular junctions remains unclear.
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Cangelosi, Davide. "SSALeaping: efficient leap condition based direct method variant for the stochastic simulation of chemical reacting system." In 3rd International ICST Conference on Simulation Tools and Techniques. ICST, 2010. http://dx.doi.org/10.4108/icst.simutools2010.8665.

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Albert, J. "Stochastic simulation of reaction subnetworks: Exploiting synergy between the chemical master equation and the Gillespie algorithm." In INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2016 (ICCMSE 2016). Author(s), 2016. http://dx.doi.org/10.1063/1.4968765.

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Safari, Mehdi. "Local Entropy Generation in Large Eddy Simulation of Turbulent Reacting Flows." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-71525.

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Analysis of local entropy generation is an effective means to investigate sources of efficiency loss in turbulent combustion from the standpoint of the second law of thermodynamics. A methodology, termed the entropy filtered density function (En-FDF), is developed for large eddy simulation (LES) of turbulent reacting flows to include the transport of entropy, which embodies the complete statistical information about entropy variations within the subgrid scale. The modeled En-FDF contains a stochastic differential equation (SDE) for entropy which is solved by a Lagrangian Monte Carlo method. In
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Jeschke, Matthias, Alfred Park, Roland Ewald, Richard Fujimoto, and Adelinde M. Uhrmacher. "Parallel and Distributed Spatial Simulation of Chemical Reactions." In 2008 ACM/IEEE/SCS Workshop on Principles of Advanced and Distributed Simulation ( PADS). IEEE, 2008. http://dx.doi.org/10.1109/pads.2008.20.

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SPRIK, MICHIEL. "Density functional techniques for simulation of chemical reactions." In Proceedings of the International School of Physics. WORLD SCIENTIFIC, 1998. http://dx.doi.org/10.1142/9789812839664_0013.

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Reports on the topic "Stochastic Simulation of Chemical Reactions"

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Kusaka, Jin, Akinori Morishima, Nobuhiko Horie, and Yasuhiro Daisho. A Numerical Study on Diesel Combustion Using a Computational Fluid Dynamics Code Accounting for the Finite-Rate Elementary Chemical Reactions~Three-Dimensional Simulation by the Use of a Fast Ordinary Differential Equation Solver. SAE International, 2005. http://dx.doi.org/10.4271/2005-08-0314.

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