scholarly journals STUDY ON GRANULARITY DISTRIBUTION OF POWDER BY FRACTAL MODELS

Fractals ◽  
2017 ◽  
Vol 25 (04) ◽  
pp. 1740009 ◽  
Author(s):  
HUAQIANG CHU ◽  
FEI REN ◽  
ZHIMIN ZHENG ◽  
MINGYAN GU
Keyword(s):  
Monte Carlo ◽  
Fractal Theory ◽  
Cumulative Probability ◽  
Empirical Constant ◽  
New Approach ◽  
Fractal Models ◽  
Algebraic Expressions ◽  
Coal Particles ◽  
Granularity Distribution ◽  
Empirical Constants

The granularity distribution of powder is shown to have the fractal characters. Based on the fractal theory, three algebraic expressions for the fractal dimension, the cumulative probability and the mass distribution of particles were obtained. Three expressions are the functions of the concentration of particles, the diameter of particles, the maximum and the minimum particle diameters. No additional empirical constant is introduced in these expressions. These fractal models contain less empirical constants than the conventional correlations. The fractal behavior about coal particles was discussed in detail. Simulations were also performed by fractal Monte Carlo technique. The proposed technique may provide us a new approach to analyze the granularity distribution of powder.

scholarly journals A Monte Carlo Method of Solving Heat Conduction Problems

1980 ◽  
Vol 102 (1) ◽  
pp. 121-125 ◽  
Author(s):  
S. K. Fraley ◽  
T. J. Hoffman ◽  
P. N. Stevens
Keyword(s):  
Monte Carlo ◽  
Heat Conduction ◽  
Monte Carlo Method ◽  
Transport Equation ◽  
Heat Conduction Equation ◽  
Analytical Techniques ◽  
Conduction Equation ◽  
Geometric Complexity ◽  
New Approach ◽  
Temperature Distributions

A new approach in the use of Monte Carlo to solve heat conduction problems is developed using a transport equation approximation to the heat conduction equation. A variety of problems is analyzed with this method and their solutions are compared to those obtained with analytical techniques. This Monte Carlo approach appears to be limited to the calculation of temperatures at specific points rather than temperature distributions. The method is applicable to the solution of multimedia problems with no inherent limitations as to the geometric complexity of the problem.

Improved estimation is a prerequisite for successful terminal guidance

2005 ◽  
Vol 219 (2) ◽  
pp. 145-156 ◽  
Author(s):  
J Shinar ◽  
V Turetsky
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Estimation Errors ◽  
New Approach ◽  
Target Acceleration ◽  
The Future ◽  
New Ideas ◽  
Estimation System ◽  
Terminal Guidance

Successful interception of manoeuvring anti-surface missiles that are expected in the future can be achieved only if the estimation errors against manoeuvring targets can be minimized. The paper raises new ideas for an improved estimation concept by separating the tasks of the estimation system and by explicit use of the time-to-go in the process. The outcome of the new approach is illustrated by results of Monte Carlo simulations in generic interception scenarios. The results indicate that if an eventual ‘jump’ in the commanded target acceleration is detected sufficiently rapidly, small estimation errors and consequently precise guidance can be obtained.

New approach to Monte Carlo simulation of photon transport in the frequency domain

1995 ◽  
Author(s):  
Ilya V. Yaroslavsky ◽  
Anna N. Yaroslavsky ◽  
Hans-Joachim Schwarzmaier ◽  
Garif G. Akchurin ◽  
Valery V. Tuchin
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Frequency Domain ◽  
New Approach ◽  
Photon Transport

TACKLING THE SIGN PROBLEM

1994 ◽  
Vol 05 (02) ◽  
pp. 275-277
Author(s):  
T D Kieu ◽  
C J Griffin
Keyword(s):  
Monte Carlo ◽  
Ising Model ◽  
New Approach ◽  
Statistical Errors ◽  
Sign Problem ◽  
Complex Valued ◽  
1D Complex

To tackle the sign problem in the simulations of systems having indefinite or complex-valued measures, we propose a new approach which yields statistical errors smaller than the crude Monte Carlo using absolute values of the original measures. The 1D complex-coupling Ising model is employed as an illustration.

scholarly journals Measuring hospital spatial wingspan by using a discrete choice model with utility-threshold

2018 ◽  
Author(s):  
Saley Issa ◽  
Ribatet Mathieu ◽  
Molinari Nicolas
Keyword(s):  
Monte Carlo ◽  
Discrete Choice ◽  
Choice Model ◽  
Discrete Choice Models ◽  
Mcmc Methods ◽  
Hospital Competition ◽  
Policy Makers ◽  
New Approach ◽  
Asthma Patients ◽  
The One

AbstractPolicy makers increasingly rely on hospital competition to incentivize patients to choose high-value care. Travel distance is one of the most important drivers of patients’ decision. The paper presents a method to numerically measure, for a given hospital, the distance beyond which no patient is expected to choose the hospital for treatment by using a new approach in discrete choice models. To illustrate, we compared 3 hospitals attractiveness related to this distance for asthma patients admissions in 2009 in Hérault (France), showing, as expected, CHU Montpellier is the one with the most important spatial wingspan. For estimation, Monte Carlo Markov Chain (MCMC) methods are used.

A new approach to Monte Carlo simulations in statistical physics: Wang-Landau sampling

2004 ◽  
Vol 72 (10) ◽  
pp. 1294-1302 ◽  
Author(s):  
D. P. Landau ◽  
Shan-Ho Tsai ◽  
M. Exler
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Statistical Physics ◽  
New Approach

Advances and benefits of fractal models to predict streaming potentials in partially saturated porous media

2021 ◽  
Author(s):  
Damien Jougnot ◽  
Luong Duy Thanh ◽  
Mariangeles Soldi ◽  
Jan Vinogradov ◽  
Luis Guarracino
Keyword(s):  
Porous Media ◽  
Fractal Theory ◽  
Electrical Potential ◽  
Streaming Potential ◽  
Excess Charge ◽  
Distribution Law ◽  
Distribution Models ◽  
Streaming Potentials ◽  
Fractal Models ◽  
Partially Saturated Porous Media

<p>Understanding streaming potential generation in porous media is of high interest for hydrological and reservoir studies as it allows to relate water fluxes to measurable electrical potential distributions in subsurface geological settings. The evolution of streaming potential <span>stems</span> from electrokinetic coupling between water and electrical fluxes due to the presence of an electrical double layer at the interface between the mineral and the pore water. Two different approaches can be used to model and interpret the generation of the streaming potential in porous media: the classical coupling coefficient approach based on the Helmholtz-Smoluchowski equation, and the effective excess charge density. Recent studies based on both approaches use a mathematical up-scaling procedure that employs the so-called fractal theory. In these studies, the porous medium is represented by a bundle of tortuous capillaries characterized by a fractal capillary-size distribution law. The electrokinetic coupling between the fluid flow and electric current is obtained by averaging the processes that take place in a single capillary. In most cases, closed-form expressions for the electrokinetic parameters are obtained in terms of macroscopic hydraulic variables like permeability, saturation and porosity. In this presentation we propose a review of the existing fractal distribution models that predict the streaming potential in porous media and discuss their benefits compared against other published models.</p>

Production Yield Estimation by the Metamodel Method With a Boundary-Focused Experiment Design

1997 ◽  
Author(s):  
Chinghsin Tu ◽  
Russell R. Barton
Keyword(s):  
Monte Carlo ◽  
Robust Design ◽  
Simulation Models ◽  
Experiment Design ◽  
Production Yield ◽  
Design Stage ◽  
Yield Estimation ◽  
Simulation Code ◽  
New Approach ◽  
A Priority

Abstract The need for yield estimation strategies in the design stage is a priority recognized by industry. Yield estimates can be employed to assess the manufacturability of a design, and allow for modification to produce a robust design. Therefore, low yield of products can be avoided and costs for manufacturing can be reduced. This paper presents an accurate and time-efficient yield estimation approach for use with simulation models. We use a metamodel-based method, which is time-efficient compared to crude Monte Carlo yield estimation using the original simulation code. The approach employs a boundary-focused experiment design, which overcomes the inaccuracy of yield estimates that can occur when using a metamodel method. The results of two examples demonstrate the effectiveness of this new approach.

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