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Journal articles on the topic 'Computational Plasma Physics'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Koren, Barry, Ute Ebert, Tamas Gombosi, Hervé Guillard, Rony Keppens, and Dana Knoll. "Computational plasma physics." Journal of Computational Physics 231, no. 3 (February 2012): 717. http://dx.doi.org/10.1016/j.jcp.2011.11.012.

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2

Karney, Charles F. F. "Modern computational techniques in plasma physics." Physics of Plasmas 5, no. 5 (May 1998): 1632–35. http://dx.doi.org/10.1063/1.872831.

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3

Ostrikov, K., I. Levchenko, and S. Xu. "Computational plasma nanoscience: Where plasma physics meets surface science." Computer Physics Communications 177, no. 1-2 (July 2007): 110–13. http://dx.doi.org/10.1016/j.cpc.2007.02.049.

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4

Schultz, D. R., P. S. Krstic, T. Minami, M. S. Pindzola, F. J. Robicheaux, J. P. Colgan, S. D. Loch, et al. "Computational atomic physics for plasma edge modeling." Contributions to Plasma Physics 44, no. 13 (April 2004): 247–51. http://dx.doi.org/10.1002/ctpp.200410036.

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5

Phipps, Claude. "Laser Plasma Physics: Forces and the Nonlinearity Principle." Laser and Particle Beams 19, no. 2 (April 2001): 317. http://dx.doi.org/10.1017/s0263034601002221.

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This is a Landau/Lifschitz-class book. It is a critically important reference work for the whole field of high intensity and/or high plasma density laser-plasma interactions for years to come. It covers everything from single particles to dense fluids, from computational physics to the practical results in fusion, accelerators, you name it. It contains excellent and crystal-clear treatments of the theory of electrodynamics, laser-driven hydrodynamics, the Lorentz force, complex refractive index, and relativistic effects in plasmas. Although “the swamp of plasma physics” is mostly a classical place, Hora clearly indicates where quantum effects must be considered.

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6

Hewett, Dennis W. "Computational Plasma Physics: With Applications of Fusion and Astrophysics." Fusion Technology 17, no. 2 (March 1990): 362–63. http://dx.doi.org/10.13182/fst90-a39908.

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7

Mense, Allan T., and Jay I. Frankel. "Computational plasma physics with applications to fusion and astrophysics." Annals of Nuclear Energy 16, no. 9 (January 1989): 487. http://dx.doi.org/10.1016/0306-4549(89)90064-9.

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8

Hromadka, Jakub, Tomas Ibehej, and Rudolf Hrach. "Computational study of plasma sheath interaction." Physica Scripta T161 (May 1, 2014): 014068. http://dx.doi.org/10.1088/0031-8949/2014/t161/014068.

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9

Snytnikov, A. V., B. M. Glinskiy, G. B. Zagorulko, and Y. A. Zagorulko. "Ontological approach to formalization of knowledge in computational plasma physics." Journal of Physics: Conference Series 1640 (October 2020): 012013. http://dx.doi.org/10.1088/1742-6596/1640/1/012013.

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10

Cap, F. F. "Toroidal Boundary Problems in Plasma Physics." ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik 67, no. 1 (1987): 58–60. http://dx.doi.org/10.1002/zamm.19870670115.

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11

Huang, Jialong, Chi Wang, Lijie Chang, Ya Zhang, Zhebin Wang, Lin Yi, and Wei Jiang. "Computational characterization of electron-beam-sustained plasma." Physics of Plasmas 26, no. 6 (June 2019): 063502. http://dx.doi.org/10.1063/1.5091466.

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12

Cohen, Bruce I. "Perspectives on Research in Computational Plasma Physics With Applications to Experiments." IEEE Transactions on Plasma Science 48, no. 4 (April 2020): 757–67. http://dx.doi.org/10.1109/tps.2019.2944331.

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13

Hrach, R., P. Bartoš, and V. Hrachová. "Computational study of plasma-surface interaction in plasma-assisted technologies." European Physical Journal D 54, no. 2 (April 28, 2009): 417–23. http://dx.doi.org/10.1140/epjd/e2009-00122-9.

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14

Xu, Lan. "A Hamiltonian approach for a plasma physics problem." Computers & Mathematics with Applications 61, no. 8 (April 2011): 1909–11. http://dx.doi.org/10.1016/j.camwa.2010.06.028.

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15

Rabiński, Marek. "Computational Method for Parameter Identification of Plasma Models." Contributions to Plasma Physics 32, no. 3-4 (1992): 474–79. http://dx.doi.org/10.1002/ctpp.2150320345.

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16

Tang, W. M., and V. S. Chan. "Advances and challenges in computational plasma science." Plasma Physics and Controlled Fusion 47, no. 2 (January 11, 2005): R1—R34. http://dx.doi.org/10.1088/0741-3335/47/2/r01.

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17

Zhilkin, A. S., D. Yu Sychugov, L. I. Vysotsky, I. V. Zotov, S. Yu Soloviev, and A. D. Sadykov. "New open computational resource for plasma processes modelling." Journal of Physics: Conference Series 1730, no. 1 (January 1, 2021): 012048. http://dx.doi.org/10.1088/1742-6596/1730/1/012048.

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18

Andreev, V. F., and A. M. Popov. "Inverse coefficients of the problem for transport equations of plasma physics." Computational Mathematics and Modeling 6, no. 1 (1995): 16–24. http://dx.doi.org/10.1007/bf01128152.

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19

Giga, Yoshikazu, and Zensho Yoshida. "A Dynamic Free-Boundary Problem in Plasma Physics." SIAM Journal on Mathematical Analysis 21, no. 5 (September 1990): 1118–38. http://dx.doi.org/10.1137/0521062.

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20

Gary, S. Peter. "Short-wavelength plasma turbulence and temperature anisotropy instabilities: recent computational progress." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373, no. 2041 (May 13, 2015): 20140149. http://dx.doi.org/10.1098/rsta.2014.0149.

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Plasma turbulence consists of an ensemble of enhanced, broadband electromagnetic fluctuations, typically driven by multi-wave interactions which transfer energy in wavevector space via non- linear cascade processes. Temperature anisotropy instabilities in collisionless plasmas are driven by quasi-linear wave–particle interactions which transfer particle kinetic energy to field fluctuation energy; the resulting enhanced fluctuations are typically narrowband in wavevector magnitude and direction. Whatever their sources, short-wavelength fluctuations are those at which charged particle kinetic, that is, velocity-space, properties are important; these are generally wavelengths of the order of or shorter than the ion inertial length or the thermal ion gyroradius. The purpose of this review is to summarize and interpret recent computational results concerning short-wavelength plasma turbulence, short-wavelength temperature anisotropy instabilities and relationships between the two phenomena.

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21

Brooks, J. N., A. Hassanein, A. Koniges, P. S. Krstic, T. D. Rognlien, T. Sizyuk, V. Sizyuk, and D. P. Stotler. "Scientific and Computational Challenges in Coupled Plasma Edge/Plasma-Material Interactions for Fusion Tokamaks." Contributions to Plasma Physics 54, no. 4-6 (June 2014): 329–40. http://dx.doi.org/10.1002/ctpp.201410014.

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22

Rabiński, M., and K. Zdunek. "Computational studies of plasma dynamics in Impulse Plasma Deposition coaxial accelerator." Surface and Coatings Technology 201, no. 9-11 (February 2007): 5438–41. http://dx.doi.org/10.1016/j.surfcoat.2006.07.005.

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23

Rauf, S., A. Haggag, M. Moosa, and P. L. G. Ventzek. "Computational modeling of process induced damage during plasma clean." Journal of Applied Physics 100, no. 2 (July 15, 2006): 023302. http://dx.doi.org/10.1063/1.2216253.

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24

Cupini, E., and A. De Matteis. "Plasma-neutral elastic collisions in monte carlo computational models." Il Nuovo Cimento D 11, no. 10 (October 1989): 1489–500. http://dx.doi.org/10.1007/bf02450508.

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25

Eastwood, J. W. "Computing in Plasma Physics (Report on the Eighth Conference on Computational Physics, Eibsee, 13–16 May 1986)." Nuclear Fusion 27, no. 1 (January 1, 1987): 181–84. http://dx.doi.org/10.1088/0029-5515/27/1/019.

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26

Axford, W. I. "A review of: “Magnetospheric plasma physics”." Geophysical & Astrophysical Fluid Dynamics 32, no. 3-4 (July 1985): 342–45. http://dx.doi.org/10.1080/03091928508208793.

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27

Negrea, C., V. Manea, V. Covlea, and A. Jipa. "Computational technique for plasma parameters determination using Langmuir probe data." Plasma Physics Reports 37, no. 5 (May 2011): 455–60. http://dx.doi.org/10.1134/s1063780x11050096.

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28

Subramaniam, Vivek, Thomas C. Underwood, Laxminarayan L. Raja, and Mark A. Cappelli. "Computational and experimental investigation of plasma deflagration jets and detonation shocks in coaxial plasma accelerators." Plasma Sources Science and Technology 27, no. 2 (February 23, 2018): 025016. http://dx.doi.org/10.1088/1361-6595/aaabec.

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29

Kubečka, M., M. Snirer, A. Obrusník, V. Kudrle, and Z. Bonaventura. "Computational study of plasma-induced flow instabilities in power modulated atmospheric-pressure microwave plasma jet." Plasma Sources Science and Technology 29, no. 7 (July 13, 2020): 075001. http://dx.doi.org/10.1088/1361-6595/ab9b19.

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30

Donnelly, I. J., B. E. Clancy, and N. F. Cramer. "Alfvdén wave heating of a cylindrical plasma using axisymmetric waves. Part 1. MHD theory." Journal of Plasma Physics 34, no. 2 (October 1985): 227–46. http://dx.doi.org/10.1017/s0022377800002816.

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MHD theory with the Hall term has been used to analyse the Alfvén resonance heating of cylindrical plasmas using axisymmetric waves excited by an antenna. An analytic expression for the antenna impedance has been derived for a simple plasma model and this is used to help interpret the computational results for small, medium and large plasmas. Compressional wave eigenmodes give large antenna resistances; however, the energy is deposited near the plasma surface. At a frequency just above each eigenfrequency, the Alfvén resonance damping is zero. Below the first eigenfrequency, the energy can be deposited near the plasma centre; however, the antenna resistance is fairly low except for medium size plasmas with a nearly constant central density. Ion cyclotron wave resonances are briefly discussed. Some general concepts relevant to the penetration of wave energy into large plasmas are presented.

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31

Kim, D. W., S. J. You, J. H. Kim, H. Y. Chang, and W. Y. Oh. "Computational comparative study of microwave probes for plasma density measurement." Plasma Sources Science and Technology 25, no. 3 (May 18, 2016): 035026. http://dx.doi.org/10.1088/0963-0252/25/3/035026.

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32

Bakhmurov, A. G., V. V. Voevodin, N. N. Popova, R. L. Smelyanskii, and A. V. Khanov. "Laplace ? an experimental language for parallel programming of MHD-models in plasma physics." Computational Mathematics and Modeling 2, no. 4 (1991): 467–71. http://dx.doi.org/10.1007/bf01127968.

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33

Havlíčková, E., O. Maršálek, and R. Hrach. "Computational study of plasma-solid interaction in argon plasma with inclusion of magnetic field." European Physical Journal D 54, no. 2 (March 19, 2009): 313–18. http://dx.doi.org/10.1140/epjd/e2009-00099-3.

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34

Munafò, Alessandro, Andrea Alberti, Carlos Pantano, Jonathan B. Freund, and Marco Panesi. "A computational model for nanosecond pulse laser-plasma interactions." Journal of Computational Physics 406 (April 2020): 109190. http://dx.doi.org/10.1016/j.jcp.2019.109190.

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35

Vold, E. L., F. Najmabadi, and R. W. Conn. "Computational implementation of a coupled plasma-neutral fluid model." Journal of Computational Physics 101, no. 1 (July 1992): 229. http://dx.doi.org/10.1016/0021-9991(92)90070-f.

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36

Vold, E. L., F. Najmabadi, and R. W. Conn. "Computational implementation of a coupled plasma-neutral fluid model." Journal of Computational Physics 103, no. 2 (December 1992): 300–319. http://dx.doi.org/10.1016/0021-9991(92)90403-l.

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37

Takana, H., I. V. Adamovich, and H. Nishiyama. "Computational Simulation of Nanosecond Pulsed Discharge for Plasma Assisted Ignition." Journal of Physics: Conference Series 550 (November 26, 2014): 012051. http://dx.doi.org/10.1088/1742-6596/550/1/012051.

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38

Pert, G. J. "Computational modeling for X-ray lasers." Laser and Particle Beams 12, no. 2 (June 1994): 209–22. http://dx.doi.org/10.1017/s0263034600007692.

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Various problems involved in the simulation of current X-ray laser experiments are discussed. The methods are based on laser-plasma simulation techniques with simultaneous calculation of the ionization dynamics, and are particularly appropriate for collisional and recombination pumped systems.

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39

Lee, June-Yub, and Jin Keun Seo. "Identification of Two-Phase Free Boundary Arising in Plasma Physics." SIAM Journal on Mathematical Analysis 31, no. 6 (January 2000): 1295–306. http://dx.doi.org/10.1137/s0036141099351188.

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40

Vabishchevich, P. N. "Works of A.A. Samarskii on Computational Mathematics." Computational Methods in Applied Mathematics 9, no. 1 (2009): 5–36. http://dx.doi.org/10.2478/cmam-2009-0002.

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Abstract This is a review of the main results in computational mathematics that were obtained by the eminent Russian mathematician Alexander Andreevich Samarskii (February 19, 1919 – February 11, 2008). His outstanding research output addresses all the main questions that arise in the construction and justification of algorithms for the numerical solution of problems from mathematical physics. The remarkable works of A.A. Samarskii include statements of the main principles re- quired in the construction of difference schemes, rigorous mathematical proofs of the stability and convergence of these schemes, and also investigations of their algorith- mic implementation. A.A. Samarskii and his collaborators constructed and applied in practical calculations a large number of algorithms for solving various problems from mathematical physics, including thermal physics, gas dynamics, magnetic gas dynam- ics, plasma physics, ecology and other important models from the natural sciences.

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41

Hrubý, Vojtěch, Rudolf Hrach, and Jiří Šimek. "Computational study of plasma composition influence on sheath formation." Vacuum 84, no. 1 (August 2009): 101–3. http://dx.doi.org/10.1016/j.vacuum.2009.04.059.

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42

Begay, F. "Computational model for relativistic electron beam - dense carbon plasma heating experiments." Physica Scripta 40, no. 1 (July 1, 1989): 73–82. http://dx.doi.org/10.1088/0031-8949/40/1/009.

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43

Meng, Jian Bing, Xiao Juan Dong, and Wen Ji Xu. "Numerical Simulation of a Combined Plasma Arc Based on Sequentially Coupled Physics Analysis." Advanced Materials Research 129-131 (August 2010): 708–13. http://dx.doi.org/10.4028/www.scientific.net/amr.129-131.708.

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A three-dimensional axisymmetric mathematical model, including the influence of the swirl exiting in the plasma torch, was developed to describe the heat transfer and fluid flow within a combined plasma arc. In this model, a mapping method and a meshing method of variable step-size were adopted to mesh the calculation domain and to improve the computational precision. To overcome the problem issuing from a coexistence of non-transferred arc and transfer arc and a complicated interaction between electric, magnetic, heat flow and fluid flow phenomena in the combined plasma arc, a sequential coupling method and a physical environment approach were introduced into the finite element analysis on the behaviors of combined plasma arc. Furthermore, the characteristics of combined plasma arc such as temperature, velocity, current density and electromagnetic force were studied.

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44

Ter Haar, D. "A review of: “Basic plasma physics-II”." Geophysical & Astrophysical Fluid Dynamics 32, no. 3-4 (July 1985): 339–41. http://dx.doi.org/10.1080/03091928508208792.

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45

Von Finckenstein, Karl Graf Finck. "Difference methods for quasilinear parabolic systems from plasma physics." Numerical Methods for Partial Differential Equations 3, no. 4 (1987): 289–311. http://dx.doi.org/10.1002/num.1690030403.

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46

Parent, Bernard, and Kyle M. Hanquist. "Plasma Sheath Modelling for Computational Aerothermodynamics and Magnetohydrodynamics." International Journal of Computational Fluid Dynamics 35, no. 5 (May 28, 2021): 331–48. http://dx.doi.org/10.1080/10618562.2021.1949456.

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47

Havlicková, E., P. Bartos, and R. Hrach. "Computational study of plasma-solid interaction in DC glow discharge in argon plasma at medium pressures." Journal of Physics: Conference Series 63 (April 1, 2007): 012019. http://dx.doi.org/10.1088/1742-6596/63/1/012019.

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48

Kochkov, Dmitrii, Jamie A. Smith, Ayya Alieva, Qing Wang, Michael P. Brenner, and Stephan Hoyer. "Machine learning–accelerated computational fluid dynamics." Proceedings of the National Academy of Sciences 118, no. 21 (May 18, 2021): e2101784118. http://dx.doi.org/10.1073/pnas.2101784118.

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Numerical simulation of fluids plays an essential role in modeling many physical phenomena, such as weather, climate, aerodynamics, and plasma physics. Fluids are well described by the Navier–Stokes equations, but solving these equations at scale remains daunting, limited by the computational cost of resolving the smallest spatiotemporal features. This leads to unfavorable trade-offs between accuracy and tractability. Here we use end-to-end deep learning to improve approximations inside computational fluid dynamics for modeling two-dimensional turbulent flows. For both direct numerical simulation of turbulence and large-eddy simulation, our results are as accurate as baseline solvers with 8 to 10× finer resolution in each spatial dimension, resulting in 40- to 80-fold computational speedups. Our method remains stable during long simulations and generalizes to forcing functions and Reynolds numbers outside of the flows where it is trained, in contrast to black-box machine-learning approaches. Our approach exemplifies how scientific computing can leverage machine learning and hardware accelerators to improve simulations without sacrificing accuracy or generalization.

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49

Varchanis, S., Y. Dimakopoulos, C. Wagner, and J. Tsamopoulos. "How viscoelastic is human blood plasma?" Soft Matter 14, no. 21 (2018): 4238–51. http://dx.doi.org/10.1039/c8sm00061a.

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In this work, we evaluate for first time the viscoelastic properties of human blood plasma. Using computational rheology, a molecular-based constitutive model and experimental data, we predict accurately the rheological response of human blood plasma in strong extensional and constriction complex flows.

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50

Ido, S., M. Kashiwagi, M. Takahashi, and T. Yoshida. "Computational studies on generation and control in magnetron sputtering plasma." Computer Physics Communications 121-122 (September 1999): 665. http://dx.doi.org/10.1016/s0010-4655(06)70070-4.

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