Preferred Language
Articles
/
ijcpe-333
Prediction and Correlations of Residual Entropy of Superheated Vapor for Pure Compounds
...Show More Authors

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.

View Publication Preview PDF
Quick Preview PDF
Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
Wellbore Breakouts Prediction from Different Rock Failure Criteria
...Show More Authors

One of the wellbore instability problems in vertical wells are breakouts in Zubair oilfield. Breakouts, if exceeds its critical limits will produce problems such as loss circulation which will add to the non-productive time (NPT) thus increasing loss in costs and in total revenues. In this paper, three of the available rock failure criteria (Mohr-Coulomb, Mogi-Coulomb and Modified-Lade) are used to study and predict the occurrence of the breakouts. It is found that there is an increase over the allowable breakout limit in breakout width in Tanuma shaly formation and it was predicted using Mohr-Coulomb criterion. An increase in the pore pressure was predicted in Tanuma shaly formation, thus; a new mud weight and casing pr

... Show More
View Publication Preview PDF
Crossref (4)
Crossref
Publication Date
Mon Sep 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction in Carbonate Reservoir Rock Using FZI
...Show More Authors

Knowledge of permeability, which is the ability of rocks to transmit the fluid, is important for understanding the flow mechanisms in oil and gas reservoirs.
Permeability is best measured in the laboratory on cored rock taken from the reservoir. Coring is expensive and time-consuming in comparison to the electronic survey techniques most commonly used to gain information about permeability.
Yamama formation was chosen, to predict the permeability by using FZI method. Yamama Formation is the main lower cretaceous carbonate reservoir in southern of Iraq. This formation is made up mainly of limestone. Yamama formation was deposited on a gradually rising basin floor. The digenesis of Yamama sediments is very important due to its direct

... Show More
View Publication Preview PDF
Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
...Show More Authors

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
...Show More Authors

In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

... Show More
View Publication Preview PDF
Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
...Show More Authors

       

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

... Show More
View Publication Preview PDF
Crossref (3)
Crossref
Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Composites For Construction
Prediction of Concrete Cover Separation in Reinforced Concrete Beams Strengthened with FRP
...Show More Authors

View Publication
Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Composites For Construction
Prediction of Concrete Cover Separation in Reinforced Concrete Beams Strengthened with FRP
...Show More Authors

Scopus (17)
Crossref (15)
Scopus Clarivate Crossref
Publication Date
Tue Jan 01 2013
Journal Name
Journal Of Engineering
Numerical Prediction of Bond-Slip Behavior in Simple Pull-out Concrete Specimen
...Show More Authors

In this study the simple pullout concrete cylinder specimen reinforced by a single steel bar was analyzed for bond-slip behavior. Three-dimension nonlinear finite element model using ANSYS program was employed to study the behavior of bond between concrete and plain steel reinforcement. The ANSYS model includes eight-noded isoperimetric brick element (SOLID65) to model the concrete cylinder while the steel reinforcing bar was modeled as a truss member (LINK8). Interface element (CONTAC52) was used in this analysis to model the bond between concrete and steel bar. Material nonlinearity due to cracking and/or crushing of concrete, and yielding of the steel reinforcing bar were taken into consideration during the analysis. The accuracy of this

... Show More
Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Numerical Prediction of Bond-Slip Behavior in Simple Pull-Out Concrete Specimens
...Show More Authors

In this study the simple pullout concrete cylinder specimen reinforced by a single steel bar was analyzed for bond-slip behavior. Three-dimension nonlinear finite element model using ANSYS program was employed to study the behavior of bond between concrete and plain steel reinforcement. The ANSYS model includes eight-noded isoperimetric brick element (SOLID65) to model the concrete cylinder while the steel reinforcing bar was modeled as a truss member (LINK8). Interface element (CONTAC52) was used in this analysis to model the bond between concrete and steel bar. Material nonlinearity due to cracking and/or crushing of concrete, and yielding of the steel reinforcing bar were taken into consideration during the analysis. The accuracy of t

... Show More
View Publication Preview PDF
Crossref (4)
Crossref
Publication Date
Sat Sep 30 2023
Journal Name
Misan Journal For Academic Studies
The microhardness Property of the Biomedical commercially pure titaniumstrontium oxide composite alloy after anodic oxidation
...Show More Authors

Preview PDF