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Theoretical Calculations of the Electron Transport Parameters in CH4-Ar and CH4-Ne Mixtures Gases Using Monte Carlo Method

    The result of concentration varying of mixture methane with argon and neon gas are believed to study the change in electrons energy distribution function and then the change of the electrons transport parameters including the drift velocity, the mean energy, characteristics energy and diffusion coefficient. In the present work,a contemporary developed computer, simulation program known as Bolsig+ is being used for calculating the electron transport parameters.
 

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Publication Date
Thu Dec 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Simulation the Radiation Zone of Al-Mussaib Power Plant by Using Monte Carlo Method

The temperature distributions are to be evaluated for the furnace of Al-Mussaib power plant. Monte Carlo simulation procedure is used to evaluate the radiation heat transfer inside the furnace, where the radiative transfer is the most important process occurring there. Weighted sum of gray-gases model is used to evaluate the radiative properties of the non gray gas in the enclosure. The energy balance equations are applied for each gas, and surface zones, and by solving these equations, both the temperature, and the heat flux are found.

   Good degree of accuracy has been obtained, when comparing the results obtained by the simulation with the data of the designing company, and the data obtained by the zonal method. In

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Publication Date
Thu Sep 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Calculation of Full Energy Peak Efficiency for HPGe Detector Using Monte Carlo Method

This research presents results on the full energy peak efficiency of a high purity germanium (HPGe) detector from point source as a function of photon energy and source-detector distance. The directions of photons emitted from the source and the photon path lengths in the detector were determined by Monte Carlo technique. A major advantage of this technique is the short computation time compared to the experiments. Another advantage is the flexibility for inputting detector-related parameters (such as source–detector distance, detector radius, length and attenuation coefficient) into the algorithm developed, thus making it an easy and flexible method to apply to other detector systems and configurations. It has been designed and writte

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
monte carlo simulation in the kinetics and mileculare

The primary focus of the study factor reverse polymerization styrene polymer kinetics and distribution weight Aljaia in Blma Aldhur free reverse The study was conducted wi Mamahakah and using the Monte Carlo method

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Publication Date
Sun Jun 04 2017
Journal Name
Baghdad Science Journal
Studying the Electron Energy Distribution Function (EEDF) and Electron Transport Coefficients in SF6 – He Gas Mixtures by Solving the Boltzmann Equation

The Boltzmann equation has been solved using (EEDF) package for a pure sulfur hexafluoride (SF6) gas and its mixtures with buffer Helium (He) gas to study the electron energy distribution function EEDF and then the corresponding transport coefficients for various ratios of SF6 and the mixtures. The calculations are graphically represented and discussed for the sake of comparison between the various mixtures. It is found that the various SF6 – He content mixtures have a considerable effect on EEDF and the transport coefficients of the mixtures

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
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Publication Date
Thu Oct 20 2016
Journal Name
Sociological Methods & Research
Mean Monte Carlo Finite Difference Method for Random Sampling of a Nonlinear Epidemic System

In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Monte Carlo Simulation of the Backscattering Gamma Ray System

A Monte Carlo simulation has been used to design program which simulate gamma rays backscattering system. Gamma ray backscattering is very important to get useful information about shielding, absorption and counting problems. Simulation was done of a 661.6 KeV from a collimated point source of 137Cs. When increasing the scattering angle of photon which emerging from Iron target , as the incident gamma beam angles of 15°, 45° and 75°, the results showed that the single scattering count decreases. Whereas, this count increased by increasing the incident angle. In addition, the single scattering peak (count) increases according to the sample thickness until „saturation thickness‟. Our simulation results are useful to evaluate the opt

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Publication Date
Tue Jan 01 2019
Journal Name
Aip Conference Proceedings
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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
The Vertical variations of Atmospheric Methane (CH4) concentrations over selected cities in Iraq based on AIRS data

The Atmospheric Infrared Sounder (AIRS) on EOS/Aqua satellite provides diverse measurements of Methane (CH4) distribution at different pressure levels in the Earth's atmosphere. The focus of this research is to analyze the vertical variations of (CH4) volume mixing ratio (VMR) time-series data at four Standard pressure levels SPL (925, 850, 600, and 300 hPa) in the troposphere above six cities in Iraq from January 2003 to September 2016. The analysis results of monthly average CH4VMR time-series data show a significant increase between 2003 and 2016, especially from 2009 to 2016; the minimum values of CH4 were in 2003 while the maximum values were in 2016. The vertical distribution of CH4<

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