Stability of a Plasma with a Continuous Density Distribution

1961 ◽  
Vol 4 (8) ◽  
pp. 1053 ◽  
Author(s):  
B. Lehnert
1951 ◽  
Vol 113 ◽  
pp. 496 ◽  
Author(s):  
Pierre A. Carrus ◽  
Phyllis A. Fox ◽  
Felix Haas ◽  
Zdenek Kopal

Author(s):  
Kai Liu ◽  
Andrés Tovar ◽  
Emily Nutwell ◽  
Duane Detwiler

This work introduces a multimaterial density-based topology optimization method suitable for nonlinear structural problems. The proposed method consists of three stages: continuous density distribution, clustering, and metamodel-based optimization. The initial continuous density distribution is generated following a synthesis strategy without penalization, e.g., the hybrid cellular automaton (HCA) method. In the clustering stage, unsupervised machine learning (e.g., K-means clustering) is used to optimally classify the continuous density distribution into a finite number of clusters based on their similarity. Finally, a metamodel (e.g., Kriging interpolation) is generated and iteratively updated following a global optimization algorithm (e.g., genetic algorithms) to ultimately converge to an optimal material distribution. The proposed methodology is demonstrated with the design of multimaterial stiff (minimum compliance) structures, compliant mechanisms, and a thin-walled S-rail structure for crashworthiness.


Author(s):  
R. A. Crowther

The reconstruction of a three-dimensional image of a specimen from a set of electron micrographs reduces, under certain assumptions about the imaging process in the microscope, to the mathematical problem of reconstructing a density distribution from a set of its plane projections.In the absence of noise we can formulate a purely geometrical criterion, which, for a general object, fixes the resolution attainable from a given finite number of views in terms of the size of the object. For simplicity we take the ideal case of projections collected by a series of m equally spaced tilts about a single axis.


Author(s):  
H.-J. Cantow ◽  
H. Hillebrecht ◽  
S. Magonov ◽  
H. W. Rotter ◽  
G. Thiele

From X-ray analysis, the conclusions are drawn from averaged molecular informations. Thus, limitations are caused when analyzing systems whose symmetry is reduced due to interatomic interactions. In contrast, scanning tunneling microscopy (STM) directly images atomic scale surface electron density distribution, with a resolution up to fractions of Angstrom units. The crucial point is the correlation between the electron density distribution and the localization of individual atoms, which is reasonable in many cases. Thus, the use of STM images for crystal structure determination may be permitted. We tried to apply RuCl3 - a layered material with semiconductive properties - for such STM studies. From the X-ray analysis it has been assumed that α-form of this compound crystallizes in the monoclinic space group C2/m (AICI3 type). The chlorine atoms form an almost undistorted cubic closed package while Ru occupies 2/3 of the octahedral holes in every second layer building up a plane hexagon net (graphite net). Idealizing the arrangement of the chlorines a hexagonal symmetry would be expected. X-ray structure determination of isotypic compounds e.g. IrBr3 leads only to averaged positions of the metal atoms as there exist extended stacking faults of the metal layers.


2019 ◽  
Vol 139 (5) ◽  
pp. 302-308 ◽  
Author(s):  
Shinji Yamamoto ◽  
Soshi Iwata ◽  
Toru Iwao ◽  
Yoshiyasu Ehara

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