Estimates of confinement time and energy gain for plasma liner driven magnetoinertial fusion using an analytic self-similar converging shock model

2009 ◽  
Vol 16 (11) ◽  
pp. 112707 ◽  
Author(s):  
J. T. Cassibry ◽  
R. J. Cortez ◽  
S. C. Hsu ◽  
F. D. Witherspoon
Keyword(s):  
Energy Gain ◽  
Shock Model ◽  
Confinement Time ◽  
Plasma Liner ◽  
Self Similar ◽  
Time And Energy

scholarly journals STOCHASTIC ELECTRON ACCELERATION IN SNR RX J1713.7-3946

2013 ◽  
Vol 23 ◽  
pp. 319-323 ◽  
Author(s):  
ZHONGHUI FAN ◽  
SIMING LIU
Keyword(s):  
Diffusion Coefficients ◽  
Planck Equation ◽  
Plasma Waves ◽  
Numerical Code ◽  
Model Parameters ◽  
Similar Model ◽  
Fokker Planck Equation ◽  
Self Similar ◽  
Time And Energy ◽  
Fokker Planck

Stochastic acceleration of charged particles due to their interactions with plasma waves may be responsible for producing superthermal particles in a variety of astrophysical systems. This process can be described as a diffusion process in the energy space with the Fokker-Planck equation. In this paper, a time-dependent numerical code is used to solve the reduced Fokker-Planck equation involving only time and energy variables with general forms of the diffusion coefficients. We also propose a self-similar model for particle acceleration in Sedov explosions and use the TeV SNR RX J1713.7-3946 as an example to demonstrate the model characteristics. Markov Chain Monte Carlo method is utilized to constrain model parameters with observations.

scholarly journals Possible energy gain for a plasma-liner-driven magneto-inertial fusion concept

2014 ◽  
Vol 21 (7) ◽  
pp. 070701 ◽  
Author(s):  
C. E. Knapp ◽  
R. C. Kirkpatrick
Keyword(s):  
Energy Gain ◽  
Inertial Fusion ◽  
Plasma Liner ◽  
Fusion Concept

Self-similar collapse with non-radial motions

2006 ◽  
Vol 20 ◽  
pp. 1-4
Author(s):  
A. Nusser
Keyword(s):  
Self Similar

The Recent Revolution in High Performance Computing

MRS Bulletin ◽  
1997 ◽  
Vol 22 (10) ◽  
pp. 5-6
Author(s):  
Horst D. Simon
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
New Technologies ◽  
New Technology ◽  
Parallel Architecture ◽  
Time Frame ◽  
Good News ◽  
Computing Industry ◽  
Time And Energy ◽  
Performance Computing

Recent events in the high-performance computing industry have concerned scientists and the general public regarding a crisis or a lack of leadership in the field. That concern is understandable considering the industry's history from 1993 to 1996. Cray Research, the historic leader in supercomputing technology, was unable to survive financially as an independent company and was acquired by Silicon Graphics. Two ambitious new companies that introduced new technologies in the late 1980s and early 1990s—Thinking Machines and Kendall Square Research—were commercial failures and went out of business. And Intel, which introduced its Paragon supercomputer in 1994, discontinued production only two years later.During the same time frame, scientists who had finished the laborious task of writing scientific codes to run on vector parallel supercomputers learned that those codes would have to be rewritten if they were to run on the next-generation, highly parallel architecture. Scientists who are not yet involved in high-performance computing are understandably hesitant about committing their time and energy to such an apparently unstable enterprise.However, beneath the commercial chaos of the last several years, a technological revolution has been occurring. The good news is that the revolution is over, leading to five to ten years of predictable stability, steady improvements in system performance, and increased productivity for scientific applications. It is time for scientists who were sitting on the fence to jump in and reap the benefits of the new technology.

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