1-20 of 49
Machine learning
Close
Save search
Follow your search
Access your saved searches in your account
Close Modal
Sort by
Journal Articles

Supervised machine learning-based multivariate regression of parallel closures for a high-collisionality deuterium-carbon plasma

Min Uk Lee, Jeong-Young Ji, Hae June Lee
Journal: Physics of Plasmas
Phys. Plasmas 30, 112101 (2023)
https://doi.org/10.1063/5.0167904
Published: November 2023
View article titled, Supervised machine learning-based multivariate regression of parallel closures for a high-collisionality deuterium-carbon plasma
Open the PDF for Supervised machine learning-based multivariate regression of parallel closures for a high-collisionality deuterium-carbon plasma in another window
Journal Articles

Optimization of target compression for high-gain fast ignition via machine learning

Huanyu Song, Fuyuan Wu, Zhengming Sheng, Jie Zhang
Journal: Physics of Plasmas
Phys. Plasmas 30, 092707 (2023)
https://doi.org/10.1063/5.0159764
Published: September 2023
View article titled, Optimization of target compression for high-gain fast ignition via machine learning
Open the PDF for Optimization of target compression for high-gain fast ignition via machine learning in another window
Journal Articles

Empirical probability and machine learning analysis of m, n = 2, 1 tearing mode onset parameter dependence in DIII-D H-mode scenarios

L. Bardóczi, N. J. Richner, J. Zhu, C. Rea, N. C. Logan
Journal: Physics of Plasmas
Phys. Plasmas 30, 092505 (2023)
https://doi.org/10.1063/5.0165859
Published: September 2023
View article titled, Empirical probability and machine learning analysis of <em>m</em>, <em>n</em> = 2, 1 tearing mode onset parameter dependence in DIII-D H-mode scenarios
Open the PDF for Empirical probability and machine learning analysis of <em>m</em>, <em>n</em> = 2, 1 tearing mode onset parameter dependence in DIII-D H-mode scenarios in another window
Journal Articles

A physics-informed deep learning model of the hot tail runaway electron seed

Christopher J. McDevitt
Journal: Physics of Plasmas
Phys. Plasmas 30, 092501 (2023)
https://doi.org/10.1063/5.0164712
Published: September 2023
View article titled, A physics-informed deep learning model of the hot tail runaway electron seed
Open the PDF for A physics-informed deep learning model of the hot tail runaway electron seed in another window
Journal Articles

A shapelet-based neural network for binary and multi-class disruption prediction for prevention at JET

V. Artigues, P. C. de Vries, F. Jenko, JET Contributors
Journal: Physics of Plasmas
Phys. Plasmas 30, 082506 (2023)
https://doi.org/10.1063/5.0151511
Published: August 2023
View article titled, A shapelet-based neural network for binary and multi-class disruption prediction for prevention at JET
Open the PDF for A shapelet-based neural network for binary and multi-class disruption prediction for prevention at JET in another window
Journal Articles

Coupling multi-fidelity xRAGE with machine learning for graded inner shell design optimization in double shell capsules

N. N. Vazirani, M. J. Grosskopf, D. J. Stark, P. A. Bradley, B. M. Haines, E. N. Loomis, S. L. England, W. A. Scales
Journal: Physics of Plasmas
Phys. Plasmas 30, 062704 (2023)
https://doi.org/10.1063/5.0129565
Published: June 2023
View article titled, Coupling multi-fidelity xRAGE with machine learning for graded inner shell design optimization in double shell capsules
Open the PDF for Coupling multi-fidelity xRAGE with machine learning for graded inner shell design optimization in double shell capsules in another window
Journal Articles

Data-driven assessment of magnetic charged particle confinement parameter scaling in magnetized liner inertial fusion experiments on Z

William E. Lewis, Owen M. Mannion, D. E. Ruiz, Christopher A. Jennings, Patrick F. Knapp, Matthew R. Gomez, Adam J. Harvey-Thompson, Matthew R. Weis, Stephen A. Slutz, David J. Ampleford, Kristian Beckwith
Journal: Physics of Plasmas
Phys. Plasmas 30, 052701 (2023)
https://doi.org/10.1063/5.0142805
Published: May 2023
View article titled, Data-driven assessment of magnetic charged particle confinement parameter scaling in magnetized liner inertial fusion experiments on Z
Open the PDF for Data-driven assessment of magnetic charged particle confinement parameter scaling in magnetized liner inertial fusion experiments on Z in another window
Journal Articles

Disruption event characterization and forecasting in tokamaks

S. A. Sabbagh, J. W. Berkery, Y. S. Park, J. Butt, J. D. Riquezes, J. G. Bak, R. E. Bell, L. Delgado-Aparicio, S. P. Gerhardt, C. J. Ham, J. Hollocombe, J. W. Lee, J. Kim, A. Kirk, J. Ko, W. H. Ko, L. Kogan, B. P. LeBlanc, J. H. Lee, A. Thornton, S. W. Yoon
Journal: Physics of Plasmas
Phys. Plasmas 30, 032506 (2023)
https://doi.org/10.1063/5.0133825
Published: March 2023
View article titled, Disruption event characterization and forecasting in tokamaks
Open the PDF for Disruption event characterization and forecasting in tokamaks in another window
Journal Articles

Neural network surrogate models for equations of state

Katherine L. Mentzer, J. Luc Peterson
Journal: Physics of Plasmas
Phys. Plasmas 30, 032704 (2023)
https://doi.org/10.1063/5.0126708
Published: March 2023
View article titled, Neural network surrogate models for equations of state
Open the PDF for Neural network surrogate models for equations of state in another window
Journal Articles

Ambient-temperature liquid jet targets for high-repetition-rate HED discovery science

F. Treffert, G. D. Glenn, H.-G. J. Chou, C. Crissman, C. B. Curry, D. P. DePonte, F. Fiuza, N. J. Hartley, B. Ofori-Okai, M. Roth, S. H. Glenzer, M. Gauthier
Journal: Physics of Plasmas
Phys. Plasmas 29, 123105 (2022)
https://doi.org/10.1063/5.0097857
Published: December 2022
View article titled, Ambient-temperature liquid jet targets for high-repetition-rate HED discovery science
Open the PDF for Ambient-temperature liquid jet targets for high-repetition-rate HED discovery science in another window
Includes: Supplementary data
Journal Articles

Modeling compressed turbulent plasma with rapid viscosity variations

Sébastien Thévenin, Nicolas Valade, Benoît-Joseph Gréa, Gilles Kluth, Olivier Soulard
Journal: Physics of Plasmas
Phys. Plasmas 29, 112310 (2022)
https://doi.org/10.1063/5.0115272
Published: November 2022
View article titled, Modeling compressed turbulent plasma with rapid viscosity variations
Open the PDF for Modeling compressed turbulent plasma with rapid viscosity variations in another window
Journal Articles

Preface to special topic: The High Repetition Rate Frontier in High-Energy-Density Physics

P. V. Heuer, S. Feister, D. B. Schaeffer, H. G. Rinderknecht
Journal: Physics of Plasmas
Phys. Plasmas 29, 110401 (2022)
https://doi.org/10.1063/5.0130801
Published: November 2022
View article titled, Preface to special topic: The High Repetition Rate Frontier in High-Energy-Density Physics
Open the PDF for Preface to special topic: The High Repetition Rate Frontier in High-Energy-Density Physics in another window
Journal Articles

Transfer learning driven design optimization for inertial confinement fusion

K. D. Humbird, J. L. Peterson
Journal: Physics of Plasmas
Phys. Plasmas 29, 102701 (2022)
https://doi.org/10.1063/5.0100364
Published: October 2022
View article titled, Transfer learning driven design optimization for inertial confinement fusion
Open the PDF for Transfer learning driven design optimization for inertial confinement fusion in another window
Journal Articles

Enhanced analysis of experimental x-ray spectra through deep learning

D. A. Mariscal, C. M. Krauland, B. Z. Djordjević, G. G. Scott, R. A. Simpson, E. S. Grace, K. Swanson, T. Ma
Journal: Physics of Plasmas
Phys. Plasmas 29, 093901 (2022)
https://doi.org/10.1063/5.0097777
Published: September 2022
View article titled, Enhanced analysis of experimental x-ray spectra through deep learning
Open the PDF for Enhanced analysis of experimental x-ray spectra through deep learning in another window
Journal Articles

Machine learning on the ignition threshold for inertial confinement fusion

Chen Yang, Cunbo Zhang, Congzhang Gao, Xuefeng Xu, Chengxin Yu, Shuaichuang Wang, Zhengfeng Fan, Jie Liu
Journal: Physics of Plasmas
Phys. Plasmas 29, 082702 (2022)
https://doi.org/10.1063/5.0097554
Published: August 2022
View article titled, Machine learning on the ignition threshold for inertial confinement fusion
Open the PDF for Machine learning on the ignition threshold for inertial confinement fusion in another window
Journal Articles

Machine learning in the study of phase transition of two-dimensional complex plasmas

He Huang, Vladimir Nosenko, Han-Xiao Huang-Fu, Hubertus M. Thomas, Cheng-Ran Du
Journal: Physics of Plasmas
Phys. Plasmas 29, 073702 (2022)
https://doi.org/10.1063/5.0096938
Published: July 2022
View article titled, Machine learning in the study of phase transition of two-dimensional complex plasmas
Open the PDF for Machine learning in the study of phase transition of two-dimensional complex plasmas in another window
Includes: Supplementary data
Journal Articles

TCAD augmented generative adversarial network for hot-spot detection and mask-layout optimization in a large area HARC etching process

Hyoungcheol Kwon, Hyunsuk Huh, Hwiwon Seo, Songhee Han, Imhee Won, Jiwoong Sue, Dongyean Oh, Felipe Iza, Seungchul Lee, Sung Kye Park, Seonyong Cha
Journal: Physics of Plasmas
Phys. Plasmas 29, 073504 (2022)
https://doi.org/10.1063/5.0093076
Published: July 2022
View article titled, TCAD augmented generative adversarial network for hot-spot detection and mask-layout optimization in a large area HARC etching process
Open the PDF for TCAD augmented generative adversarial network for hot-spot detection and mask-layout optimization in a large area HARC etching process in another window
Journal Articles

Understanding the surface wave characteristics using 2D particle-in-cell simulation and deep neural network

Rinku Mishra, S. Adhikari, Rupak Mukherjee, B. J. Saikia
Journal: Physics of Plasmas
Phys. Plasmas 29, 062104 (2022)
https://doi.org/10.1063/5.0082954
Published: June 2022
View article titled, Understanding the surface wave characteristics using 2D particle-in-cell simulation and deep neural network
Open the PDF for Understanding the surface wave characteristics using 2D particle-in-cell simulation and deep neural network in another window
Journal Articles

Effect of laser preheat in magnetized liner inertial fusion at OMEGA

L. S. Leal, A. V. Maximov, E. C. Hansen, J. R. Davies, D. H. Barnak, J. L. Peebles, K. M. Woo, P. V. Heuer, A. B. Sefkow, R. Betti
Journal: Physics of Plasmas
Phys. Plasmas 29, 042703 (2022)
https://doi.org/10.1063/5.0079577
Published: April 2022
View article titled, Effect of laser preheat in magnetized liner inertial fusion at OMEGA
Open the PDF for Effect of laser preheat in magnetized liner inertial fusion at OMEGA in another window
Journal Articles

Identification of high order closure terms from fully kinetic simulations using machine learning

B. Laperre, J. Amaya, S. Jamal, G. Lapenta
Journal: Physics of Plasmas
Phys. Plasmas 29, 032706 (2022)
https://doi.org/10.1063/5.0066397
Published: March 2022
View article titled, Identification of high order closure terms from fully kinetic simulations using machine learning
Open the PDF for Identification of high order closure terms from fully kinetic simulations using machine learning in another window