Experiments on two-step heating of a dense plasma in the GOL-3 facility

This paper presents the results of experiments on two-stage heating of a dense plasma by a relativistic electron beam in the GOL-3 facility. A dense plasma with a length of about a meter and a hydrogen density up to 10¹⁷ cm⁻³ was created in the main plasma, whose density was 10¹⁵ cm⁻³. In the process of interacting with the plasma, the electron beam (1 MeV, 40 kA, 4 μs) imparts its energy to the electrons of the main plasma through collective effects. The heated electrons, as they disperse along the magnetic field lines, in turn reach the region of dense plasma and impart their energy to it by pairwise collisions. Estimates based on experimental data are given for the parameters of the flux of hot plasma electrons, the energy released in the dense plasma, and the energy balance of the beam-plasma system. The paper discusses the dynamics of the plasma, which is inhomogeneous in density and temperature, including the appearance of pressure waves. Zh. éksp. Teor. Fiz. 113, 897–917 (March 1998)     

DATA PREORDERING IN GENERALIZED PAV ALGORITHM FOR MONOTONIC REGRESSION

Monotonic regression （MR） is a least distance problem with monotonicity constraints induced by a partiaily ordered data set of observations. In our recent publication [In Ser. Nonconvex Optimization and Its Applications, Springer-Verlag, （2006） 83, pp. 25-33], the Pool-Adjazent-Violators algorithm （PAV） was generalized from completely to partially ordered data sets （posets）. The new algorithm, called CPAV, is characterized by the very low computational complexity, which is of second order in the number of observations. It treats the observations in a consecutive order, and it can follow any arbitrarily chosen topological order of the poset of observations. The CPAV algorithm produces a sufficiently accurate solution to the MR problem, but the accuracy depends on the chosen topological order. Here we prove that there exists a topological order for which the resulted CPAV solution is optimal. Furthermore, we present results of extensive numerical experiments, from which we draw conclusions about the most and the least preferable topological orders.     

Monotonicity recovering and accuracy preserving optimization methods for postprocessing finite element solutions

We suggest here a least-change correction to available finite element (FE) solution. This postprocessing procedure is aimed at recovering the monotonicity and some other important properties that may not be exhibited by the FE solution. Although our approach is presented for FEs, it admits natural extension to other numerical schemes, such as finite differences and finite volumes. For the postprocessing, a priori information about the monotonicity is assumed to be available, either for the whole domain or for a subdomain where the lost monotonicity is to be recovered. The obvious requirement is that such information is to be obtained without involving the exact solution, e.g. from expected symmetries of this solution.The postprocessing is based on solving a monotonic regression problem with some extra constraints. One of them is a linear equality-type constraint that models the conservativity requirement. The other ones are box-type constraints, and they originate from the discrete maximum principle. The resulting postprocessing problem is a large scale quadratic optimization problem. It is proved that the postprocessed FE solution preserves the accuracy of the discrete FE approximation.We introduce an algorithm for solving the postprocessing problem. It can be viewed as a dual ascent method based on the Lagrangian relaxation of the equality constraint. We justify theoretically its correctness. Its efficiency is demonstrated by the presented results of numerical experiments.     

On efficiently combining limited-memory and trust-region techniques

Limited-memory quasi-Newton methods and trust-region methods represent two efficient approaches used for solving unconstrained optimization problems. A straightforward combination of them deteriorates the efficiency of the former approach, especially in the case of large-scale problems. For this reason, the limited-memory methods are usually combined with a line search. We show how to efficiently combine limited-memory and trust-region techniques. One of our approaches is based on the eigenvalue decomposition of the limited-memory quasi-Newton approximation of the Hessian matrix. The decomposition allows for finding a nearly-exact solution to the trust-region subproblem defined by the Euclidean norm with an insignificant computational overhead as compared with the cost of computing the quasi-Newton direction in line-search limited-memory methods. The other approach is based on two new eigenvalue-based norms. The advantage of the new norms is that the trust-region subproblem is separable and each of the smaller subproblems is easy to solve. We show that our eigenvalue-based limited-memory trust-region methods are globally convergent. Moreover, we propose improved versions of the existing limited-memory trust-region algorithms. The presented results of numerical experiments demonstrate the efficiency of our approach which is competitive with line-search versions of the L-BFGS method.     

Numerical Simulation of Plasma Dynamics in a Nonuniform Magnetic Field

An efficient algorithm is proposed enabling numerical simulations of plasma dynamics in a nonuniform magnetic field. The present numerical data are in good agreement with experimental data obtained in a GOL-3 setup and with previous simulations. The experimentally observed effect of fast transfer of energy to ions is confirmed. __________ Translated from Prikladnaya Mekhanika i Tekhnicheskaya Fizika, Vol. 47, No. 1, pp. 35–45, January–February, 2006.     

A Limited-Memory Multipoint Symmetric Secant Method for Bound Constrained Optimization

A new algorithm for solving smooth large-scale minimization problems with bound constraints is introduced. The way of dealing with active constraints is similar to the one used in some recently introduced quadratic solvers. A limited-memory multipoint symmetric secant method for approximating the Hessian is presented. Positive-definiteness of the Hessian approximation is not enforced. A combination of trust-region and conjugate-gradient approaches is used to explore useful information. Global convergence is proved for a general model algorithm. Results of numerical experiments are presented.     

Multipurpose implanter for high technology development

To provide basic operations of semiconductor and radiation materials technologies, a multipurpose implanter with intense ion beams was developed at the Institute of Nuclear Physics. The generated beamparameters are as follows: ions are H⁺, O⁺; C⁺; the ion energy is up to 200 keV; the beam current is up to 2 mA; and the implantation mode is continuous. The size of the target to be processed can reach 76 × 76 mm². During the implanter operation, the target chamber vacuum reaches 10^?4 Pa. The entire process of target irradiation is fully automated.     

Mathematical Simulation of the Distribution of the Electron Beam Current during Pulsed Heating of a Metal Target

Journal of Applied and Industrial Mathematics - We study a model of the current distribution during heating of the surface of a tungsten sample under pulsed exposure to an electron beam. The model...     

Simulation of the motion and heating of an irregular plasma

A physicomathematical model for plasma heating and confinement is formulated on the basis of some assumptions on the behavior of a dense plasma cloud in a magnetic field. The model allows for the ionization and heating of the plasma cloud by the surrounding deuterium plasma due to heat conduction and heating by a superthermal electron current. The expansion of a plasma cloud in an external magnetic field is studied using some simplifications in a magnetohydrodynamic approximation. Plasma heating is modeled by an external source. The basic equations include continuity, motion, energy, and magneticfield equations. For numerical solution of the problem, we developed a finitedifference scheme of the type of a universal algorithm with splitting into physical processes and spatial directions, which allowed us to obtain separate solutions of the equations of magnetic induction and gas dynamics. Calculations of the propagation of a plasma cloud heated by a source in an external magnetic field were performed. The mechanism of the effect of the magnetic field and heat source on plasma cloud expansion is determined. The results agree qualitatively with experimental data.     

Direct observation of anomalously low longitudinal electron heat conductivity in the course of collective relaxation of a high-current relativistic electron beam in plasma

JETP Letters - The experimental results on a multiple-mirror trap GOL-3 with a short section of reduced magnetic field (“magnetic pit”) are presented. The reduced specific energy...