Monte Carlo Simulation of Long-Chain Branched Polyolefins Made with Dual Catalysts:  A Classification of Chain Structures in Topological Branching Families

2005 ◽  
Vol 44 (8) ◽  
pp. 2461-2468 ◽  
Author(s):  
Leonardo C. Simon ◽  
João B. P. Soares
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Long Chain

scholarly journals Monte-Carlo simulation for moderate seismic zones using artificial accelerograms

2022 ◽  
Author(s):  
ILIAS BOUNSIR
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Seismic Waves ◽  
Seismic Wave Propagation ◽  
Technical Note ◽  
Explicit Scheme ◽  
Statistical Characteristics ◽  
Seismic Zones ◽  
Artificial Accelerograms

Abstract The present technical note deals with a new method to generate seismic accelerograms based on statistical characteristics and the classification of seismic waves. A short heterogeneous sitebased analyse of these accelerograms is given with a seismic wave propagation code in 1D. After, a numerical simulation is done in order to obtain PGA using Newmark’s explicit scheme, and finally, Monte-Carlo simulation is used to determinate failure’s probability of structures localised in moderate seismic zones in hexagonal France.

DEA and Monte Carlo simulation approach towards green car selection

2017 ◽  
Vol 24 (5) ◽  
pp. 1234-1252 ◽  
Author(s):  
Anand Prakash ◽  
Rajendra P. Mohanty
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Secondary Data ◽  
Research Centre ◽  
Ride Quality ◽  
Data Envelopment ◽  
Distribution Fitting ◽  
Content Type ◽  
Statistical Inferences

Purpose Automakers are engaged in manufacturing both efficient and inefficient green cars. The purpose of this paper is to categorize efficient green cars and inefficient green cars followed by improving efficiencies of identified inefficient green cars for distribution fitting. Design/methodology/approach The authors have used 2014 edition of secondary data published by the Automotive Research Centre of the Automobile Club of Southern California. The paper provides the methodology of applying data envelopment analysis (DEA) consisting of 50 decision-making units (DMUs) of green cars with six input indices (emission, braking, ride quality, acceleration, turning circle, and luggage capacity) and two output indices (miles per gallon and torque) integrated with Monte Carlo simulation for drawing significant statistical inferences graphically. Findings The findings of this study showed that there are 27 efficient and 23 inefficient DMUs along with improvement matrix. Additionally, the study highlighted the best distribution fitting of improved efficient green cars for respective indices. Research limitations/implications This study suffers from limitations associated with 2014 edition of secondary data used in this research. Practical implications This study may be useful for motorists with efficient listing of green cars, whereas automakers can be benefitted with distribution fitting of improved efficient green cars using Monte Carlo simulation for calibration. Originality/value The paper uses DEA to empirically examine classification of green cars and applies Monte Carlo simulation for distribution fitting to improved efficient green cars to decide appropriate range of their attributes for calibration.

scholarly journals Monte Carlo Simulation of Long Chain Polymer Melts:  Crossover from Rouse to Reptation Dynamics

2001 ◽  
Vol 34 (4) ◽  
pp. 1105-1117 ◽  
Author(s):  
T. Kreer ◽  
J. Baschnagel ◽  
M. Müller ◽  
K. Binder
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Polymer Melts ◽  
Chain Polymer ◽  
Long Chain

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

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