Semi-Empirical Model of X-ray Tube Facility

2010 ◽  
Author(s):  
Igor V. Shchegolkov ◽  
Igor N. Sheino ◽  
Nikolai M. Borisov ◽  
Viktor V. Kalashnikov ◽  
Alexander A. Molin ◽  
...  
Keyword(s):  
X Ray ◽  
1981 ◽  
Vol 8 (2) ◽  
pp. 251-251
Author(s):  
Sain D. Ahuja ◽  
Steven L. Stroup ◽  
Marion G. Bolin

1995 ◽  
Vol 163 ◽  
pp. 174-175
Author(s):  
U. Wessolowski ◽  
W.-R. Hamann ◽  
L. Koesterke ◽  
D. J. Hillier ◽  
J. Puls
Keyword(s):  
X Ray ◽  

Results from pointed ROSAT PSPC observations of nine single WN-type Wolf-Rayet stars are presented. Spectra of sufficient quality were obtained for two of them (WR1, WR110). The long exposure (35.5 ksec) X-ray spectrum of WR1 is more closely investigated with a semi-empirical model developed by Baum et al. (1992).


1980 ◽  
Vol 7 (5) ◽  
pp. 537-544 ◽  
Author(s):  
Sain D. Ahuja ◽  
Steven L. Stroup ◽  
Marion G. Bolin

2013 ◽  
Author(s):  
N. López-Pino ◽  
F. Padilla-Cabal ◽  
J. A. García-Alvarez ◽  
L. Vázquez ◽  
K. D' Alessandro ◽  
...  

2016 ◽  
Vol 107 ◽  
pp. 152-159 ◽  
Author(s):  
Marco Bontempi ◽  
Lucia Andreani ◽  
Claudio Labanti ◽  
Paulo Roberto Costa ◽  
Pier Luca Rossi ◽  
...  
Keyword(s):  
X Ray ◽  

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 412
Author(s):  
Shao-Ming Li ◽  
Kai-Shing Yang ◽  
Chi-Chuan Wang

In this study, a quantitative method for classifying the frost geometry is first proposed to substantiate a numerical model in predicting frost properties like density, thickness, and thermal conductivity. This method can recognize the crystal shape via linear programming of the existing map for frost morphology. By using this method, the frost conditions can be taken into account in a model to obtain the corresponding frost properties like thermal conductivity, frost thickness, and density for specific frost crystal. It is found that the developed model can predict the frost properties more accurately than the existing correlations. Specifically, the proposed model can identify the corresponding frost shape by a dimensionless temperature and the surface temperature. Moreover, by adopting the frost identification into the numerical model, the frost thickness can also be predicted satisfactorily. The proposed calculation method not only shows better predictive ability with thermal conductivities, but also gives good predictions for density and is especially accurate when the frost density is lower than 125 kg/m3. Yet, the predictive ability for frost density is improved by 24% when compared to the most accurate correlation available.


2021 ◽  
Author(s):  
Paul FitzGerald ◽  
Stephen Araujo ◽  
Mingye Wu ◽  
Bruno De Man

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