Percolation in networks of 1-dimensional objects: comparison between Monte Carlo simulations and experimental observations

2018 ◽  
Vol 3 (5) ◽  
pp. 545-550 ◽  
Author(s):  
Daniel P. Langley ◽  
Mélanie Lagrange ◽  
Ngoc Duy Nguyen ◽  
Daniel Bellet
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Percolation Threshold ◽  
Real World ◽  
Silver Nanowire ◽  
Matlab Simulation ◽  
Sem Image ◽  
Simulation Based ◽  
Nanowire Networks ◽  
The Impact

This work directly compares the percolation threshold of silver nanowire networks to predictions from Monte Carlo simulations, focusing particularly on incorporating the impact of real world imperfections. This SEM image of silver nanowire networks compared to MATLAB simulation based on the physical characteristics of the sample.

Influence of polyvinylpyrrolidone (PVP) capping layer on silver nanowire networks: theoretical and experimental studies

RSC Advances ◽  
2016 ◽  
Vol 6 (37) ◽  
pp. 30972-30977 ◽  
Author(s):  
Jinyoung Hwang ◽  
Youngseon Shim ◽  
Seon-Mi Yoon ◽  
Sang Hyun Lee ◽  
Sung-Hoon Park
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Optical Properties ◽  
Monte Carlo Simulations ◽  
Layer Thickness ◽  
Experimental Studies ◽  
Silver Nanowire ◽  
Electrical And Optical Properties ◽  
Capping Layer ◽  
Nanowire Networks

By adjusting the polyvinylpyrrolidone (PVP) capping layer thickness on silver nanowire networks, improved electrical and optical properties were obtained, which was confirmed both experimentally and theoretically (Molecular dynamics and Monte Carlo simulations).

scholarly journals The effect of ionic defect interactions on the hydration of yttrium-doped barium zirconate

2021 ◽  
Author(s):  
Sebastian Eisele ◽  
Fabian M. Draber ◽  
Steffen Grieshammer
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
First Principles ◽  
Barium Zirconate ◽  
First Principles Calculations ◽  
Defect Interactions ◽  
The Impact ◽  
Ionic Defect

First principles calculations and Monte Carlo simulations reveal the impact of defect interactions on the hydration of barium-zirconate.

scholarly journals A Monte Carlo Determination of Dose and Range Uncertainties for Preclinical Studies with a Proton Beam

Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1889
Author(s):  
Arthur Bongrand ◽  
Charbel Koumeir ◽  
Daphnée Villoing ◽  
Arnaud Guertin ◽  
Ferid Haddad ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Proton Beam ◽  
Dose Response ◽  
Small Animal ◽  
Absorbed Dose ◽  
Normal Tissue Damage ◽  
Dose Homogeneity ◽  
And Control ◽  
The Impact

Proton therapy (PRT) is an irradiation technique that aims at limiting normal tissue damage while maintaining the tumor response. To study its specificities, the ARRONAX cyclotron is currently developing a preclinical structure compatible with biological experiments. A prerequisite is to identify and control uncertainties on the ARRONAX beamline, which can lead to significant biases in the observed biological results and dose–response relationships, as for any facility. This paper summarizes and quantifies the impact of uncertainty on proton range, absorbed dose, and dose homogeneity in a preclinical context of cell or small animal irradiation on the Bragg curve, using Monte Carlo simulations. All possible sources of uncertainty were investigated and discussed independently. Those with a significant impact were identified, and protocols were established to reduce their consequences. Overall, the uncertainties evaluated were similar to those from clinical practice and are considered compatible with the performance of radiobiological experiments, as well as the study of dose–response relationships on this proton beam. Another conclusion of this study is that Monte Carlo simulations can be used to help build preclinical lines in other setups.

The electron transport that occurs within wurtzite zinc oxide and the application of stress

MRS Advances ◽  
2017 ◽  
Vol 2 (48) ◽  
pp. 2627-2632 ◽  
Author(s):  
Poppy Siddiqua ◽  
Michael S. Shur ◽  
Stephen K. O’Leary
Keyword(s):  
Monte Carlo ◽  
Zinc Oxide ◽  
Electron Transport ◽  
Velocity Field ◽  
Monte Carlo Simulations ◽  
Significant Role ◽  
Energy Gap ◽  
Device Application ◽  
The Impact

ABSTRACTWe examine how stress has the potential to shape the character of the electron transport that occurs within ZnO. In order to narrow the scope of this analysis, we focus on a determination of the velocity-field characteristics associated with bulk wurtzite ZnO. Monte Carlo simulations of the electron transport are pursued for the purposes of this analysis. Rather than focusing on the impact of stress in of itself, instead we focus on the changes that occur to the energy gap through the application of stress, i.e., energy gap variations provide a proxy for the amount of stress. Our results demonstrate that stress plays a significant role in shaping the form of the velocity-field characteristics associated with ZnO. This dependence could potentially be exploited for device application purposes.

Benchmarking Fuel Economy of Connected and Automated Vehicles in Real World Driving Conditions via Monte Carlo Simulation

2020 ◽  
Author(s):  
Shreshta Rajakumar Deshpande ◽  
Shobhit Gupta ◽  
Dennis Kibalama ◽  
Nicola Pivaro ◽  
Marcello Canova
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Fuel Economy ◽  
Real World ◽  
Human Subjects ◽  
Driver Model ◽  
Traffic Information ◽  
Vehicle Speed ◽  
Instrumented Vehicle ◽  
The Impact

Abstract Connectivity and automation have accelerated the development of algorithms that use route and real-time traffic information for improving energy efficiency. The evaluation of such benefits, however, requires establishing a reliable baseline that is representative of a real-world driving environment. In this context, virtual driver models are generally adopted to predict the vehicle speed based on route data and presence of lead vehicles, in a way that mimics the response of human drivers. This paper proposes an Enhanced Driver Model (EDM) that forecasts the human response when driving in urban conditions, considering the effects of Signal Phasing and Timing (SPaT) by introducing the concept of Line-of-Sight (LoS). The model was validated against data collected on an instrumented vehicle driven on public roads by different human subjects. Using this model, a Monte Carlo simulation is conducted to determine the statistical distribution of fuel consumption and travel time on a given route, varying driver behavior (aggressiveness), traffic conditions and SPaT. This allows one to quantify the impact of uncertainties associated to real-world driving in fuel economy estimates.

Exact site-percolation probability on the square lattice

2021 ◽  
Author(s):  
Stephan Mertens
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Percolation Threshold ◽  
Percolation Cluster ◽  
Square Lattice ◽  
Site Percolation ◽  
Exact Probability ◽  
Percolation Probability ◽  
A Site ◽  
Time And Space Complexity

Abstract We present an algorithm to compute the exact probability $R_{n}(p)$ for a site percolation cluster to span an $n\times n$ square lattice at occupancy $p$. The algorithm has time and space complexity $O(\lambda^n)$ with $\lambda \approx 2.6$. It allows us to compute $R_{n}(p)$ up to $n=24$. We use the data to compute estimates for the percolation threshold $p_c$ that are several orders of magnitude more precise than estimates based on Monte-Carlo simulations.

A Preliminary Assessment of the Robustness of Signal Detection Theory Estimates Using Monte Carlo Simulations for Human Factors Professionals

2018 ◽  
Vol 62 (1) ◽  
pp. 1301-1305
Author(s):  
Brittany Neilson ◽  
Dmitrii Paniukov ◽  
Martina I. Klein
Keyword(s):  
Monte Carlo ◽  
Human Factors ◽  
Monte Carlo Simulations ◽  
Signal Detection ◽  
Signal Detection Theory ◽  
Detection Theory ◽  
Preliminary Assessment ◽  
Assumption Violations ◽  
Homogeneity Of Variance ◽  
The Impact

Signal detection theory is commonly utilized in the field of human factors. Despite its common use, the assessment of the signal detection theory assumptions is not often cited. The purpose of this research was to provide a preliminary assessment of the impact of assumption violations on estimates of sensitivity commonly used in signal detection theory research. This assessment was performed using Monte Carlo simulations. Our research indicated that violating the homogeneity of variance assumption resulted in estimates of sensitivity varying with changes in the response criterion. However, an unequal number of signal and noise trials, which is common in vigilance research, did not impact the estimates of sensitivity. Based upon our findings, caution should be taken with regard to violations of homogeneity of variance. Future research aims to determine the impact of multiple assumption violations on estimates of sensitivity.

Qualitative Equivalence Between Electrical Percolation Threshold and Effective Thermal Conductivity in Polymer/Carbon Nanocomposites

2011 ◽  
Vol 134 (1) ◽  
Author(s):  
Majid Baniassadi ◽  
Akbar Ghazavizadeh ◽  
Yves Rémond ◽  
Said Ahzi ◽  
David Ruch ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Percolation Threshold ◽  
Effective Thermal Conductivity ◽  
Electrical Percolation ◽  
Aspect Ratios ◽  
Wide Range ◽  
Statistical Continuum ◽  
Electrical Percolation Threshold

In this study, a qualitative equivalence between the electrical percolation threshold and the effective thermal conductivity of composites filled with cylindrical nanofillers has been recognized. The two properties are qualitatively compared on a wide range of aspect ratios, from thin nanoplatelets to long nanotubes. Statistical continuum theory of strong-contrast is utilized to estimate the thermal conductivity of this type of heterogeneous medium, while the percolation threshold is simultaneously evaluated using the Monte Carlo simulations. Statistical two-point probability distribution functions are used as microstructure descriptors for implementing the statistical continuum approach. Monte Carlo simulations are carried out for calculating the two-point correlation functions of computer generated microstructures. Finally, the similarities between the effective conductivity properties and percolation threshold are discussed.

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