Calculation of dose composition outside shielding of high-energy accelerators by the Monte-Carlo method

1975 ◽  
Vol 38 (4) ◽  
pp. 288-290
Author(s):  
N. V. Mokhov ◽  
V. V. Frolov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
High Energy ◽  
The Monte Carlo Method

Simulation of 12 C+ 12 C elastic scattering at high energy by using the Monte Carlo method

2012 ◽  
Vol 36 (3) ◽  
pp. 205-209 ◽  
Author(s):  
Chen-Lei Guo ◽  
Gao-Long Zhang ◽  
I. Tanihata ◽  
Xiao-Yun Le
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Elastic Scattering ◽  
High Energy ◽  
The Monte Carlo Method

Application of the monte carlo method to high energy electron scattering (0.3-1.5 MeV)

1978 ◽  
Vol 36 (1) ◽  
pp. 202-203
Author(s):  
G. Soum ◽  
F. Arnal ◽  
J.L. Balladore ◽  
B. Jouffrey ◽  
P. Verdier
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Transmission Coefficient ◽  
Electron Scattering ◽  
High Energy ◽  
Angular Aperture ◽  
Method Of Calculation ◽  
Total Transmission ◽  
The Monte Carlo Method

Techniques for using the Monte-Carlo method for studying electron scattering in solids have been developed by several authors (1). The method is used to determine the angular distribution of electrons emerging from amorphous or polycrystalline specimens ; the total transmission and backscattering coefficients can also be obtained.- Method of calculation -Let Iθ be the intensity scattered in the direction making an angle θ with the incident electrons ; thus Iθ represents the number of electrons scattered in this direction within a solid angle Δw = πα2, where α is the semi-angle of the collector as seen from the specimen. For a specimen of thickness x, the angular distribution function may be written:I∘ denotes the intensity of the incident monoenergetic electron beam, Tα the transmission coefficient along the direction of incidence for a semi-angular aperture α and TθN the normalized transmission coefficient in the direction θ

UGR CALCULATION BASED ON THE LUMINANCE SPATIAL-ANGULAR DISTRIBUTION

2020 ◽  
Vol 2020 (4) ◽  
pp. 25-32
Author(s):  
Viktor Zheltov ◽  
Viktor Chembaev
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Visual Task ◽  
New Method ◽  
Lighting System ◽  
Preliminary Assessment ◽  
System A ◽  
The Monte Carlo Method

The article has considered the calculation of the unified glare rating (UGR) based on the luminance spatial-angular distribution (LSAD). The method of local estimations of the Monte Carlo method is proposed as a method for modeling LSAD. On the basis of LSAD, it becomes possible to evaluate the quality of lighting by many criteria, including the generally accepted UGR. UGR allows preliminary assessment of the level of comfort for performing a visual task in a lighting system. A new method of "pixel-by-pixel" calculation of UGR based on LSAD is proposed.

PSHA software review based on the Monte Carlo method

2020 ◽  
pp. 14-24
Author(s):  
V.A. Mironov ◽  
S.A. Peretokin ◽  
K.V. Simonov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Seismic Hazard ◽  
Hazard Analysis ◽  
Software Review ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Test Calculation ◽  
Seismic Surveys ◽  
The Monte Carlo Method

The article is a continuation of the software research to perform probabilistic seismic hazard analysis (PSHA) as one of the main stages in engineering seismic surveys. The article provides an overview of modern software for PSHA based on the Monte Carlo method, describes in detail the work of foreign programs OpenQuake Engine and EqHaz. A test calculation of seismic hazard was carried out to compare the functionality of domestic and foreign software.

Application of the Monte Carlo Method for the Prediction of Behavior of Peptides

2019 ◽  
Vol 20 (12) ◽  
pp. 1151-1157 ◽  
Author(s):  
Alla P. Toropova ◽  
Andrey A. Toropov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Natural Sciences ◽  
Monte Carlo Technique ◽  
Quantitative Structure ◽  
Structure Property ◽  
The Monte Carlo Method ◽  
Modern Natural

Prediction of physicochemical and biochemical behavior of peptides is an important and attractive task of the modern natural sciences, since these substances have a key role in life processes. The Monte Carlo technique is a possible way to solve the above task. The Monte Carlo method is a tool with different applications relative to the study of peptides: (i) analysis of the 3D configurations (conformers); (ii) establishment of quantitative structure – property / activity relationships (QSPRs/QSARs); and (iii) development of databases on the biopolymers. Current ideas related to application of the Monte Carlo technique for studying peptides and biopolymers have been discussed in this review.

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