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ijcpe-333
Prediction and Correlations of Residual Entropy of Superheated Vapor for Pure Compounds
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Prediction of accurate values of residual entropy (SR) is necessary step for the
calculation of the entropy. In this paper, different equations of state were tested for the
available 2791 experimental data points of 20 pure superheated vapor compounds (14
pure nonpolar compounds + 6 pure polar compounds). The Average Absolute
Deviation (AAD) for SR of 2791 experimental data points of the all 20 pure
compounds (nonpolar and polar) when using equations of Lee-Kesler, Peng-
Robinson, Virial truncated to second and to third terms, and Soave-Redlich-Kwong
were 4.0591, 4.5849, 4.9686, 5.0350, and 4.3084 J/mol.K respectively. It was found
from these results that the Lee-Kesler equation was the best (more accurate) one
compared with the others, but this equation is sometimes not very preferable. It was
noted that SRK equation was the closest one in its accuracy to that of the Lee-Kesler
equation in calculating the residual entropy SR of superheated vapor, but it was
developed primarily for calculating vapor-liquid equilibrium and to overcome this
problem, efforts were directed toward the possibility of modifying SRK equation to
increase its accuracy in predicting the residual entropy as much as possible. The
modification was made by redefining the parameter α in SRK equation to be a
function of reduced pressure, acentric factor, and polarity factor for polar compounds
in addition to be originally function of reduced temperature and n parameter –which is
also function of acentric factor– by using statistical methods. This correlation is as
follows:

α =[1+n(γ)]2  , γ=-0.920338Pr-0.34091 +0.064049Tr4 ω +0.370002ω-Pr0.996932 Tr-4x
This new modified correlation decreases the deviations in the results obtained by
using SRK equation in calculating SR when comparing with the experimental data.
The AAD for 2791 experimental data points of 20 pure compounds is 4.3084 J/mol.K
while it becomes 2.4621 J/mol.K after modification. Thus SRK equation after this
modification gives more accurate results for residual entropy of superheated vapor of
pure 20 compounds than the rest of the equations mentioned above.

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Prediction of Coefficient of Permeability of Unsaturated Soil
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A simple technique is proposed in this paper for estimating the coefficient of permeability of an unsaturated soil based on physical properties of soils that include grain size analysis, degree of saturation or water content, and porosity of the soil. The proposed method requires the soil-water characteristic curve for the prediction of the coefficient of permeability as most of the conventional methods. A procedure is proposed to define the hydraulic conductivity function from the soil water characteristic curve which is measured by the filter paper method. Fitting methods are applied through the program (SoilVision), after indentifying the basic properties of the soil such as Attereberg limits, specific gravity, void ratio, porosity, d

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Publication Date
Tue Mar 20 2018
Journal Name
Day 2 Wed, March 21, 2018
Numerical Approach for the Prediction of Formation and Hydraulic Fracture Properties Considering Elliptical Flow Regime in Tight Gas Reservoirs
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Abstract<p>As tight gas reservoirs (TGRs) become more significant to the future of the gas industry, investigation into the best methods for the evaluation of field performance is critical. While hydraulic fractured well in TRGs are proven to be most viable options for economic recovery of gas, the interpretation of pressure transient or well test data from hydraulic fractured well in TGRs for the accurate estimation of important reservoirs and fracture properties (e.g. fracture length, fracture conductivity, skin and reservoir permeability) is rather very complex and difficult because of the existence of multiple flow profiles/regimes. The flow regimes are complex in TGRs due to the large hydraulic fractures n</p> ... Show More
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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Synthesis and Characterization of some new heterocyclic derivatives from aromatic carbonyl ‎compounds and carboxylic acids with Evaluation some of them for biological activity
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     In this research investigation, a total of eighteen diverse tetra- and penta-lateral cyclic compounds were synthesized. These included 1,3,4-thiadiazole, thiazolidin-4-one (via an alternative method), 1,2,4-triazole, carbothioamide, thiazole-4-one, azetidin-2-one, and oxazole. The synthesis procedure entailed a sequence of reactions. The thiazolidine-4-one 1 was obtained by reaction p-aminobenzoic acid with thiosemicarbazide, followed by treatment with p-tolualdehyde to produce Schiff base 2. Reaction Schiff base 2 with mercaptoacetic acid in dry benzene was carried out to produce thiazolidine-4-one 3. In another synthesis pathway, the esterification of p-nitro benzoic acid with ethanol in the presence of sulfuric acid was

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Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Preparation and study the structure of pure and impure barium titanate with Mg2+ ion
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Pure and doped barium titanate with Mg2+ ion at two molar ratios x= (5%, 10%) mol. has been synthesized by solid state reaction technique. The powders sintered at two temperatures (1000 °C and 1400 °C). An XRD technique was used in order to study the crystal structure of pure and doped barium titanate, which confirmed the formation of the tetragonal phase of BaTiO3, and then calculate the lattice parameters of pure and doped barium titanate, the addition of magnesium ion Mg2+ can lead to decreases lattice parameters.

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Publication Date
Tue Dec 11 2018
Journal Name
Iraqi Journal Of Physics
Preparation and study the structure of pure and impure barium titanate with Mg2+ ion
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Pure and doped barium titanate with Mg2+ ion at two molar ratios x= (5%, 10%) mol. has been synthesized by solid state reaction technique. The powders sintered at two temperatures (1000 °C and 1400 °C). An XRD technique was used in order to study the crystal structure of pure and doped barium titanate, which confirmed the formation of the tetragonal phase of BaTiO3, and then calculate the lattice parameters of pure and doped barium titanate, the addition of magnesium ion Mg2+ can lead to decreases lattice parameters.

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Publication Date
Thu Sep 08 2022
Journal Name
Al-khwarizmi Engineering Journal
Performance Prediction in EDM Process for Al 6061 Alloy Using Response Surface Methodology and Genetic Algorithm
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The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Permeability Prediction for Nahr-Umr Reservoir / Subba field by Using FZI Method
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 The permeability determination in the reservoirs that are anisotropic and heterogeneous is a complicated problem due to the limited number of wells that contain core samples and well test data. This paper presents hydraulic flow units and flow zone indicator for predicting permeability of rock mass from core for Nahr-Umr reservoir/ Subba field. The Permeability measurement is better found in the laboratory work on the cored rock that taken from the formation. Nahr-Umr Formation is the main lower cretaceous sandstone reservoir in southern of Iraq. This formation is made up mainly of sandstone. Nahr-Umr formation was deposited on a gradually rising basin floor. The digenesis of Nahr-Umr sediments is very important du

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Publication Date
Thu Nov 29 2018
Journal Name
Al-khwarizmi Engineering Journal
Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling
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Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

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