Analysis of Experimental Data for Polystyrene Orientation during Stress Relaxation Using Semigrand Canonical Monte Carlo Simulation

2002 ◽  
Vol 35 (15) ◽  
pp. 6032-6042 ◽  
Author(s):  
Frederick L. Colhoun ◽  
Robert C. Armstrong ◽  
Gregory C. Rutledge
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Stress Relaxation

scholarly journals A Simulation of the Effects of Badminton Serve Release Height

2021 ◽  
Vol 11 (7) ◽  
pp. 2903
Author(s):  
John Rasmussen ◽  
Mark de Zee
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
World Federation ◽  
Forward Dynamics ◽  
Dynamics Model ◽  
Rib Cage ◽  
Female Player ◽  
Ballistic Trajectory ◽  
Release Height

In this work, we develop and calibrate a model to represent the trajectory of a badminton shuttlecock and use it to investigate the influence of serve height in view of a new serve rule instated by the Badminton World Federation. The new rule means that all players must launch the shuttlecock below a height of 1.15 m, as opposed to the old rule whereby the required launch height was under the rib cage of the server. The model is based on a forward dynamics model of ballistic trajectory with drag, and it is calibrated with experimental data. The experiments also served to determine the actual influence of the new rule on the shuttlecock launch position. The model is used in a Monte Carlo simulation to determine the statistical influence of the new serve rules on the player’s ability to perform good serves; i.e., serves with little opportunity for the receiver to attack. We conclude that, for the female player in question, serving below a height of 1.15 m makes it marginally more difficult to perform excellent serves. We also conclude that there might be alternative launch positions that would be less likely to produce the best serves but could be exploited as a tactical option.

scholarly journals A Monte-Carlo Simulation of the Behaviour of Electron Swarms in Hydrogen Using an Anisotropic Scattering Model

1978 ◽  
Vol 31 (4) ◽  
pp. 299 ◽  
Author(s):  
HA Blevin ◽  
J Fletcher ◽  
SR Hunter
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Electron Transport ◽  
Anisotropic Scattering ◽  
Isotropic Scattering ◽  
Transport Parameters ◽  
Simulation Code ◽  
Scattering Model ◽  
Good Agreement

Hunter (1977) found that a Monte-Carlo simulation of electron swarms in hydrogen, based on an isotropic scattering model, produced discrepancies between the predicted and measured electron transport parameters. The present paper shows that, with an anisotropic scattering model, good agreement is obtained between the predicted and experimental data. The simulation code is used here to calculate various parameters which are not directly measurable.

Simulated X-ray Spectra and X-ray Maps: Evaluation of Models Used in MC X-Ray Monte Carlo Simulation Program and Comparison with Experimental Data

2012 ◽  
Vol 18 (S2) ◽  
pp. 1022-1023 ◽  
Author(s):  
P. Michaud ◽  
R. Gauvin ◽  
H. Demers ◽  
N. Brodusch ◽  
M.J. Guinel
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Program ◽  
X Ray ◽  
Monte Carlo Simulation Program ◽  
Comparison With Experimental Data

Extended abstract of a paper presented at Microscopy and Microanalysis 2012 in Phoenix, Arizona, USA, July 29 – August 2, 2012.

MONTE CARLO SIMULATION OF THE SURFACE SEGREGATION OF Au75Pd25 AT (110) SURFACE USING AN ANALYTIC EMBEDDED ATOM METHOD

2007 ◽  
Vol 14 (03) ◽  
pp. 411-417 ◽  
Author(s):  
YU CHEN ◽  
SHUZHI LIAO
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Surface Segregation ◽  
Embedded Atom Method ◽  
Depth Profiles ◽  
The Third ◽  
Embedded Atom ◽  
Reconstructed Surface ◽  
Concentration Depth Profiles

The surface concentrations and concentration depth profiles to the (110) surface of an Au 75 Pd 25 alloy is studied by modified analytical embedded atom method (MAEAM) with the Monte Carlo simulations. The results indicate that Au enriched in the two topmost layers, but depleted in the third layer. The Au concentration in the non-reconstructed surface is less than that in the reconstructed surface. Au concentration in third layer of reconstructed surface, which is more agreement with experimental data in present simulations, is about 63% 61% and 55%, at 800K, 600K and 400K respectively. Thus the present simulations are helpful for a better understanding of surface segregation of AuPd alloys.

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