Bibliografías temáticas / Particle methods (Numerical analysis)

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Literatura académica sobre el tema "Particle methods (Numerical analysis)"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 26 de enero de 2023

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Artículos de revistas sobre el tema "Particle methods (Numerical analysis)"

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Neunzert, Helmut, and Jens Struckmeier. "Particle Methods for the Boltzmann Equation." Acta Numerica 4 (January 1995): 417–57. http://dx.doi.org/10.1017/s0962492900002579.

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In the following chapters we will discuss particle methods for the numerical simulation of rarefied gas flows.We will mainly treat a billiard game, that is, our particles will be hard spheres. But we will also touch upon cases where particles have internal energies due to rotation or vibration, which they exchange in a collision, and we will talk about chemical reactions happening during a collision.Due to the limited size of this paper, we are only able to mention the principles of these real-gas effects. On the other hand, the general concepts of particle methods to be presented may be used
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KOSHIZUKA, Seiichi. "Numerical Analysis of Continuous Media Using Particle Methods." JOURNAL OF THE JAPAN WELDING SOCIETY 75, no. 2 (2006): 126–28. http://dx.doi.org/10.2207/jjws.75.126.

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Bagtzoglou, Amvrossios C., Andrew F. B. Tompson, and David E. Dougherty. "Projection functions for particle-grid methods." Numerical Methods for Partial Differential Equations 8, no. 4 (July 1992): 325–40. http://dx.doi.org/10.1002/num.1690080403.

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Havlak, Karl J., and Harold Dean Victory. "On Deterministic Particle Methods for Solving Vlasov--Poisson--Fokker--Planck Systems." SIAM Journal on Numerical Analysis 35, no. 4 (August 1998): 1473–519. http://dx.doi.org/10.1137/s0036142996302529.

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Wollman, Stephen. "On the Approximation of the Vlasov--Poisson System by Particle Methods." SIAM Journal on Numerical Analysis 37, no. 4 (January 2000): 1369–98. http://dx.doi.org/10.1137/s0036142999298528.

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Ganguly, Keshab, and H. D. Victory, Jr. "On the Convergence of Particle Methods for Multidimensional Vlasov–Poisson Systems." SIAM Journal on Numerical Analysis 26, no. 2 (April 1989): 249–88. http://dx.doi.org/10.1137/0726015.

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Draghicescu, C. I. "An Efficient Implementation of Particle Methods for the Incompressible Euler Equations." SIAM Journal on Numerical Analysis 31, no. 4 (August 1994): 1090–108. http://dx.doi.org/10.1137/0731057.

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Patterson, Robert I. A., and Wolfgang Wagner. "Cell Size Error in Stochastic Particle Methods for Coagulation Equations with Advection." SIAM Journal on Numerical Analysis 52, no. 1 (January 2014): 424–42. http://dx.doi.org/10.1137/130924743.

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Guo, Meizhai, Megan S. Lord, and Zhongxiao Peng. "Quantitative wear particle analysis for osteoarthritis assessment." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 231, no. 12 (October 5, 2017): 1116–26. http://dx.doi.org/10.1177/0954411917735081.

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Osteoarthritis is a degenerative joint disease that affects millions of people worldwide. The aims of this study were (1) to quantitatively characterise the boundary and surface features of wear particles present in the synovial fluid of patients, (2) to select key numerical parameters that describe distinctive particle features and enable osteoarthritis assessment and (3) to develop a model to assess osteoarthritis conditions using comprehensive wear debris information. Discriminant analysis was used to statistically group particles based on differences in their numerical parameters. The anal
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Victory, Jr., H. D., Garry Tucker, and Keshab Ganguly. "The Convergence Analysis of Fully Discretized Particle Methods for Solving Vlasov–Poisson Systems." SIAM Journal on Numerical Analysis 28, no. 4 (August 1991): 955–89. http://dx.doi.org/10.1137/0728051.

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Tesis sobre el tema "Particle methods (Numerical analysis)"

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Shanmugam, Bala Priyadarshini. "Investigation of kernels for the reproducing kernel particle method." Birmingham, Ala. : University of Alabama at Birmingham, 2009. https://www.mhsl.uab.edu/dt/2009m/shanmugam.pdf.

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Yang, Weixuan. "Temperature-dependent homogenization technique and nanoscale meshfree particle methods." Diss., University of Iowa, 2007. http://ir.uiowa.edu/etd/147.

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Bunch, Peter Joseph. "Particle filtering and smoothing for challenging time series models." Thesis, University of Cambridge, 2014. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708151.

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Borovies, Drew A. "Particle filter based tracking in a detection sparse discrete event simulation environment." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion.exe/07Mar%5FBorovies.pdf.

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Thesis (M.S. in Modeling, Virtual Environment, and Simulation (MOVES))--Naval Postgraduate School, March 2007.<br>Thesis Advisor(s): Christian Darken. "March 2007." Includes bibliographical references (p. 115). Also available in print.
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Bhojwani, Shekhar. "Smoothed particle hydrodynamics modeling of the friction stir welding process." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2007. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Piqueras, García Miguel Ángel. "Numerical Methods for Multidisciplinary Free Boundary Problems: Numerical Analysis and Computing." Doctoral thesis, Universitat Politècnica de València, 2018. http://hdl.handle.net/10251/107948.

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Multitud de problemas en ciencia e ingeniería se plantean como ecuaciones en derivadas parciales (EDPs). Si la frontera del recinto donde esas ecuaciones han de satisfacerse se desconoce a priori, se habla de "Problemas de frontera libre", propios de sistemas estacionarios no dependientes del tiempo, o bien de "Problemas de frontera móvil", asociados a problemas de evolución temporal, donde la frontera cambia con el tiempo. La solución a dichos problemas viene dada por la expresión de la(s) variable(s) dependiente(s) de la(s) EDP(s) junto con la función que determina la posición de la frontera
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Casas, González Guillermo. "Numerical analysis of particle-laden flows with the finite element method." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/666324.

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In this work we study the numerical simulation of particle-laden fluids, with a focus on Newtonian fluids and spherical, rigid particles. We are thus dealing with a multi-phase (more precisely, a multi-component) problem, with two phases: the fluid (continuous phase) and the the particles (disperse phase). Our general strategy consists in using the discrete element method (DEM) to model the particles and the finite element method (FEM) to discretize the Navier-Stokes equations, which model the continuous phase. The interaction model between both phases is (must be) based on a multiscale conce
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Kwok, Ting On. "Adaptive meshless methods for solving partial differential equations." HKBU Institutional Repository, 2009. http://repository.hkbu.edu.hk/etd_ra/1076.

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Stewart, Dawn L. "Numerical Methods for Accurate Computation of Design Sensitivities." Diss., Virginia Tech, 1998. http://hdl.handle.net/10919/30561.

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This work is concerned with the development of computational methods for approximating sensitivities of solutions to boundary value problems. We focus on the continuous sensitivity equation method and investigate the application of adaptive meshing and smoothing projection techniques to enhance the basic scheme. The fundamental ideas are first developed for a one dimensional problem and then extended to 2-D flow problems governed by the incompressible Navier-Stokes equations. Numerical experiments are conducted to test the algorithms and to investigate the benefits of adaptivity an
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Bréhier, Charles-Edouard. "Numerical analysis of highly oscillatory Stochastic PDEs." Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2012. http://tel.archives-ouvertes.fr/tel-00824693.

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In a first part, we are interested in the behavior of a system of Stochastic PDEs with two time-scales- more precisely, we focus on the approximation of the slow component thanks to an efficient numerical scheme. We first prove an averaging principle, which states that the slow component converges to the solution of the so-called averaged equation. We then show that a numerical scheme of Euler type provides a good approximation of an unknown coefficient appearing in the averaged equation. Finally, we build and we analyze a discretization scheme based on the previous results, according to the H
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Libros sobre el tema "Particle methods (Numerical analysis)"

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K, Liu W., ed. Meshfree particle methods. Berlin: Springer, 2004.

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B, Liu M., ed. Smoothed particle hydrodynamics: A meshfree particle method. New Jersey: World Scientific, 2003.

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Oñate, Eugenio. Particle-Based Methods: Fundamentals and Applications. Dordrecht: Springer Science+Business Media B.V., 2011.

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Heinz, Konietzky, ed. Numerical modeling in micromechanics via particle methods: Proceedings of the 1st International PFC Symposium, Gelsenkirchen, Germany, 6-8 November 2002. Lisse: Balkema, 2003.

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Numerical methods for exterior problems. Hackensack, NJ: World Scientific, 2006.

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1946-, Chen Zhongying, and Wu Wei 1929-, eds. Generalized difference methods for differential equations: Numerical analysis of finite volume methods. New York: M. Dekker, 2000.

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Allgower, E. L. Introduction to numerical continuation methods. Philadelphia: SIAM, 2003.

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1948-, Hackbusch W., Trottenberg U, and European Multigrid Conference (3rd : 1990 : Bonn, Germany), eds. Multigrid methods III. Basel: Birkhäuser Verlag, 1991.

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Multi-grid methods and applications. Berlin: Springer-Verlag, 1985.

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Evans, Gwynne. Numerical methods for partial differential equations. London: Springer, 2000.

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Capítulos de libros sobre el tema "Particle methods (Numerical analysis)"

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Sibille, Luc, Florent Prunier, François Nicot, and Félix Darve. "Discrete Numerical Analysis of Failure Modes in Granular Materials." In Particle-Based Methods, 187–210. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0735-1_7.

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Williams, Mike. "Numerical Methods and Data Analysis Techniques in Particle Physics." In Springer Proceedings in Physics, 337–58. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12238-0_8.

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Yoshioka, Keita, Mathias Nest, Daniel Pötschke, Amir Shoarian Sattari, Patrick Schmidt, and David Krach. "Numerical Platform." In GeomInt–Mechanical Integrity of Host Rocks, 63–95. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-61909-1_3.

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AbstractAn essential scientific goal of the GeomInt project is the analysis of potentials and limitations of different numerical approaches for the modelling of discontinuities in the rocks under consideration in order to improve the understanding of methods and their synergies with regard to theoretical and numerical fundamentals. As numerical methods, the “Lattice Element Method” (LEM), the non-continuous discontinuum methods “Discrete Element Method” (DEM), the “Smoothed Particle Hydrodynamics” (SPH), the “Forces on Fracture Surfaces” (FFS) as well as the continuum approaches “Phase-Field Method” (PFM), “Lower-Interface-Method” (LIE), “Non-Local Deformation” (NLD) and the “Hybrid-Dimensional Finite-Element-Method” (HDF) will be systematically investigated and appropriately extended based on experimental results (Fig. 3.1).
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Meliani, Mohammed Hadj, Hassane Moustabchir, and Zitouni Azari. "T-Stress by Stress Difference Method (SDM): Numerical Analysis on Mode (I) Loading." In Particle and Continuum Aspects of Mesomechanics, 253–60. London, UK: ISTE, 2010. http://dx.doi.org/10.1002/9780470610794.ch25.

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Monforte, Lluís, Marcos Arroyo, Maxat Mamirov, and Jong R. Kim. "Numerical Analysis of Soil Ploughing Using the Particle Finite Element Method." In Springer Series in Geomechanics and Geoengineering, 390–93. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97112-4_87.

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Chaskalovic, Joël. "Applications of Functional Analysis to Partial Differential Equations." In Mathematical and Numerical Methods for Partial Differential Equations, 3–61. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03563-5_1.

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Giriprasad, A., B. Shruthi, Poonam Upadhyay, and T. Nireekshana. "Analysis on Movement of Conducting Particle by Varying the Particle Dimensions in Gas Insulated Busduct Using Numerical Methods." In Lecture Notes in Electrical Engineering, 595–608. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8439-8_49.

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Canuto, Claudio, and Marco Verani. "On the Numerical Analysis of Adaptive Spectral/hp Methods for Elliptic Problems." In Analysis and Numerics of Partial Differential Equations, 165–92. Milano: Springer Milan, 2013. http://dx.doi.org/10.1007/978-88-470-2592-9_11.

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Oda, Tsuyoshi, Nobuyuki Satofuka, and Hidetoshi Nishida. "Numerical Analysis of Particle Behavior Penetrating into Liquid by Level Set Method." In Computational Fluid Dynamics 2002, 529–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-59334-5_79.

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Haghighi, Kamyar, and Eun Kang. "A Knowledge-Based Approach to the Adaptive Finite Element Analysis." In Modeling, Mesh Generation, and Adaptive Numerical Methods for Partial Differential Equations, 267–76. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4612-4248-2_14.

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Actas de conferencias sobre el tema "Particle methods (Numerical analysis)"

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Francomano, Elisa, Adele Tortorici, Elena Toscano, Guido Ala, Theodore E. Simos, George Psihoyios, and Ch Tsitouras. "Multiscale Particle Method in Solving Partial Differential Equations." In Numerical Analysis and Applied Mathematics. AIP, 2007. http://dx.doi.org/10.1063/1.2790115.

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Schiller, Annika, Godehard Sutmann, Luis Martinell, Pieter Bellens, Rosa Badia, Theodore E. Simos, George Psihoyios, and Ch Tsitouras. "Particle Methods on Multicore Architectures: Experiences and Future Plans." In ICNAAM 2010: International Conference of Numerical Analysis and Applied Mathematics 2010. AIP, 2010. http://dx.doi.org/10.1063/1.3498233.

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Geiser, Jürgen, and Frederik Riedel. "Integrators for particle in cell methods: Comparison and applications." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2015 (ICNAAM 2015). Author(s), 2016. http://dx.doi.org/10.1063/1.4952245.

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Tofighi, N., A. Zainali, and M. Yildiz. "Modelling of bubble rising by smoothed particle hydrodynamics method." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756071.

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Lewtak, Robert, Theodore E. Simos, George Psihoyios, and Ch Tsitouras. "Numerical Simulation of Particulate Flows using the Multiphase Particle-In-Cell Method." In Numerical Analysis and Applied Mathematics. AIP, 2007. http://dx.doi.org/10.1063/1.2790147.

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Rowlands, R. E., Z. Feng, and T. D. Dudderar. "Quantitative fluid flow analysis by laser speckle velocimetry and numerical processing." In ICALEO® ‘89: Proceedings of the Optical Methods in Flow & Particle Diagnostics Conference. Laser Institute of America, 1989. http://dx.doi.org/10.2351/1.5058304.

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Darabi, Jeff. "Numerical Analysis of Dielectrophoretic-Based DNA Separation and Trapping." In ASME 2022 Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/fedsm2022-87076.

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Abstract In this study, dielectrophoresis (DEP) has been coupled with field-flow fractionation (FFF) for the sorting and trapping of the biological particles. A numerical simulation is performed to compute particle trajectories under the influence of DEP, drag, gravitational, and buoyancy forces, as well as Brownian motion. The simulation was performed using OpenFOAM CFD software. Both positive and negative DEP methods are examined as possible separation techniques for DNA fragments. Positive DEP forces are used to attract the particles to the electrodes and trap them in groups of similar part
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Shibata, K., S. Koshizuka, and Y. Oka. "Numerical Analysis of Droplet Size Distribution Using Particle Method." In ASME/JSME 2003 4th Joint Fluids Summer Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/fedsm2003-45165.

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A continuous jet changes to droplets where jet breakup occurs. In this study, two-dimensional numerical analysis of jet breakup is performed using MPS method (Moving Particle Semi-implicit Method) which is a particle method for incompressible flows. The continuous fluid surrounding the jet is neglected. The size distribution of droplets is in agreement with the Nukiyama-Tanasawa distribution which has been widely used as an experimental correlation. Effects of the Weber number and the Froude number on the size distribution are also obtained from the calculation.
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Asaoka, Tatsunori, Masashi Okada, Yoshikazu Teraoka, and Akihiro Tsumura. "Numerical Analysis of Natural Convection of Suspension With Particle Sedimentation." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-22141.

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A new method for the numerical analysis of natural convection of suspension was proposed. Natural convection phenomena of suspension appear in some industrial fields, such as water disposal process and food engineering process. It is difficult to comprehend the behavior of the natural convection of the suspensions, because the convection of the suspension is caused by the interactive effects of the temperature distribution and particle-concentration distribution in the suspension. In this study, a numerical model for the natural convection phenomena of the suspension accompanied by particle se
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Bento, David, Diana Pinho, Ana I. Pereira, and Rui Lima. "Genetic algorithm and particle swarm optimization combined with Powell method." In 11TH INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2013: ICNAAM 2013. AIP, 2013. http://dx.doi.org/10.1063/1.4825557.

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Informes sobre el tema "Particle methods (Numerical analysis)"

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Sparks, Paul, Jesse Sherburn, William Heard, and Brett Williams. Penetration modeling of ultra‐high performance concrete using multiscale meshfree methods. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41963.

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Terminal ballistics of concrete is of extreme importance to the military and civil communities. Over the past few decades, ultra‐high performance concrete (UHPC) has been developed for various applications in the design of protective structures because UHPC has an enhanced ballistic resistance over conventional strength concrete. Developing predictive numerical models of UHPC subjected to penetration is critical in understanding the material's enhanced performance. This study employs the advanced fundamental concrete (AFC) model, and it runs inside the reproducing kernel particle method (RKPM)
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Zheng, Jinhui, Matteo Ciantia, and Jonathan Knappett. On the efficiency of coupled discrete-continuum modelling analyses of cemented materials. University of Dundee, December 2021. http://dx.doi.org/10.20933/100001236.

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Computational load of discrete element modelling (DEM) simulations is known to increase with the number of particles. To improve the computational efficiency hybrid methods using continuous elements in the far-field, have been developed to decrease the number of discrete particles required for the model. In the present work, the performance of using such coupling methods is investigated. In particular, the coupled wall method, known as the “wall-zone” method when coupling DEM and the continuum Finite Differences Method (FDM) using the Itasca commercial codes PFC and FLAC respectively, is here
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Rozovskii, Boris, and Alexander Tartakovsky. Nonlinear Filtering: Analysis and Numerical Methods. Fort Belvoir, VA: Defense Technical Information Center, November 2001. http://dx.doi.org/10.21236/ada399200.

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Flanagan, R. D., M. A. Tenbus, and R. M. Bennett. Numerical methods for analysis of clay tile infills. Office of Scientific and Technical Information (OSTI), October 1993. http://dx.doi.org/10.2172/10186487.

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Clayton, John D., Peter W. Chung, Michael A. Greenfield, and WIlliam D. Nothwang. Numerical Methods for Analysis of Charged Vacancy Diffusion in Dielectric Solids. Fort Belvoir, VA: Defense Technical Information Center, December 2006. http://dx.doi.org/10.21236/ada459751.

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Page, William, Brian Fisk, and William Zimmerman. Development of Numerical Simulation Methods for Analysis of Laser Guided Arc Discharge. Fort Belvoir, VA: Defense Technical Information Center, February 2008. http://dx.doi.org/10.21236/ada483004.

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Eisenberg, Michael. Descriptive Simulation: Combining Symbolic and Numerical Methods in the Analysis of Chemical Reaction Mechanisms. Fort Belvoir, VA: Defense Technical Information Center, September 1989. http://dx.doi.org/10.21236/ada214678.

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Citerley, Richard L., and Narendra S. Khot. Numerical Methods for Imperfection Sensitivity Analysis of Stiffened Cylindrical Shells. Volume 1. Development and Applications. Fort Belvoir, VA: Defense Technical Information Center, September 1986. http://dx.doi.org/10.21236/ada179686.

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Chan, Tony F. Numerical Methods for Solving Large Sparse Eigenvalue Problems and for the Analysis of Bifurcation Phenomena. Fort Belvoir, VA: Defense Technical Information Center, October 1991. http://dx.doi.org/10.21236/ada244273.

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Chan, Tony F. Numerical Methods for Solving Large Sparse Eigenvalue Problems and for the Analysis of Bifurcation Phenomena. Fort Belvoir, VA: Defense Technical Information Center, October 1991. http://dx.doi.org/10.21236/ada246470.

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