94 resultados para Classification, Markov chain Monte Carlo, k-nearest neighbours
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Monte Carlo(DSMC-PE),,Legge(1991)D(?)ring(1990);,AllegreRaffin(1992),,DSMC-PE
Resumo:
The density fluctuations below the onset of convection in the Rayleigh-Benard problem are studied with the direct simulation Monte Carlo method. The particle simulation results clearly show the connection between the static correlation functions of fluctuations below the critical Rayleigh number and the flow patterns above the onset of convection for small Knudsen number flows (Kn=0.01 and Kn=0.005). Furthermore, the physical nature for no convection in the Rayleigh-Benard problem under large Knudsen number conditions (Kn>0.028) is explained based on the dynamics of fluctuations.
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The direct simulation Monte Carlo (DSMC) method is a widely used approach for flow simulations having rarefied or nonequilibrium effects. It involves heavily to sample instantaneous values from prescribed distributions using random numbers. In this note, we briefly review the sampling techniques typically employed in the DSMC method and present two techniques to speedup related sampling processes. One technique is very efficient for sampling geometric locations of new particles and the other is useful for the Larsen-Borgnakke energy distribution.
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We demonstrate that the parametric resonance in a magnetic quadrupole trap can be exploited to cool atoms by using Bird's method. In our programme the parametric resonance was realized by anisotropically modulating the trap potential. The modulation frequency dependences of temperature and fraction of the trapped atoms are explored. Furthermore, the temperature after the modulation as functions of the modulation amplitude and the mean elastic collision time are also studied. These results are valuable for the experiment of parametric resonance in a quadrupole trap.
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(FB),MetroplisMetropolis1.6,,0.330.362kcal/mol,-229
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We report the growth of well-ordered InAs QD chains by molecular beam epitaxy system. In order to analyze and extend the results of our experiment, a detailed kinetic Monte Carlo simulation is developed to investigate the effects of different growth conditions to the selective growth of InAs quantum dots (QDs). We find that growth temperature plays a more important role than growth rate in the spatial ordering of the QDs. We also investigate the effect of periodic stress on the shape of QDs in simulation. The simulation results are in good qualitative agreement with our experiment. (c) 2006 Elsevier Ltd. All rights reserved.
Resumo:
(MAH)(PP)(PE) Monte CarloMAHPPPEMAHPPMAHMAH(2.5 wt%)MAHPPMAH(2.5 wt%)MAHPPMAHPPMAH(13C)PP(NMR)MAHMAHPPMAHNMR= 32.0 ppmMAHPPMAHNMR=30.3 ppmMAHMAHPEMAHPEMAHPEMAHMAHMAH Monte CarloAABAA-BA-B-AB-A-BA-BA-B-AB-A-BA-BA/BABABA-B-AAB-A-BA/BA/B/A-g-BB-g-AA/BAB 6(PA6)PPPA6fracture tip streaming SEBSSEBS-g-MAHPA6SEBS
