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Estimation of Minimum Miscibility Pressure for 〖CO〗_2 Flood Based on EOS
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CO2 Gas is considered one of the unfavorable gases and it causes great air pollution. It’s possible to decrease this pollution by injecting  gas in the oil reservoirs to provide a good miscibility and to increase the oil recovery factor. MMP was estimated by Peng Robinson equation of state (PR-EOS). South Rumila-63 (SULIAY) is involved for which the miscible displacement by  is achievable based on the standard criteria for success EOR processes. A PVT report was available for the reservoir under study. It contains deferential liberation (DL) and constant composition expansion (CCE) tests.  PVTi software is one of the (Eclipse V.2010) software’s packages, it has been used to achieve the goal.  Many trials have been done to match the data of DL test by tuning some of the PR-EOS parameters through the regression analysis process, but no acceptable match was obtained especially for saturation pressure. However; splitting the mole fraction of (C6+) to many pseudo components was carried out, and then a regression analysis process was made again to improve the matching by tuning some of the PR-EOS parameters. A good estimate of saturation pressure and a good match of PVT properties was noted. Ternary diagram has been constructed to represent the phase behavior of -Oil and to calculate MMP for the South Rumila-63 (SULIAY) oil well.  

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Modeling and analysis of thermal contrast based on LST algorithm for Baghdad city
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Publication Date
Sun Mar 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Simulation of five methods for parameter estimation and functionExponential distribution reliability
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The estimation process is one of the pillars of the statistical inference process as well as the hypothesis test, and the assessment is based on the collection of information and conclusions about the teacher or the community's teachers on the basis of the result
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Crossref
Publication Date
Thu Jan 01 2015
Journal Name
Mj Journal On Applied Mathematics
Mathematical models for estimation the concentration of heavy metals in soil
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Publication Date
Thu Jan 16 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparison of some reliability estimation methods for Laplace distribution using simulations
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In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Revolution In Science And Humanity
Nonparametric Estimation of Failure Periods for Log Normal Distribution Using Bootstra
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A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Experimental Estimation of Critical Buckling Velocities for Conservative Pipes Conveying Fluid
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Conservative pipes conveying fluid such as pinned-pinned (p-p), clamped–pinned (c-p) pipes and clamped-clamped (c-c) lose their stability by buckling at certain critical fluid velocities. In order to experimentally evaluate these velocities, high flow-rate pumps that demand complicated fluid circuits must be used.

     This paper studies a new experimental approach based on estimating the critical velocities from the measurement of several fundamental natural frequencies .In this approach low flow-rate pumps and simple fluid circuit can be used.

Experiments were carried out on two pipe models at three different boundary conditions. The results showed that the present approach is more accurate for est

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Co-digestion of Shumblan with Different Wastes as a Source for the Biogas Production
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Shumblan (SH) is one of the most undesirable aquatic plants widespread in the irrigation channels and water bodies. This work focuses on boosting the biogas potential of shumblan by co-digesting it with other types of wastes without employing any chemical or thermal pretreatments as done in previous studies. A maximum biogas recovery of 378 ml/g VS was reached using shumblan with cow manure as inoculum in a ratio of 1:1. The methane content of the biogas was 55%. Based on volatile solid (VS) and C/N ratios, biogas productions of 518, 434, and 580 ml/g VS were obtained when the shumblan was co-digested with food wastes (SH:F), paper wastes (SH:P), and green wastes (SH:G) respectively. No significant changes of methane contents were observ

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Biogas Recovery from Anaerobic Co-Digestion of Poultry House Wastes for Clean Energy Production
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Anaerobic digestion is a technology widely used for treatment of organic waste for biogas production as a source for clean energy. In this study, poultry house wastes (PHW) material was examined as a source for biogas production. The effects of inoculum addition, pretreatment of the substrate, and temperature on the biogas production were taken into full consideration. Results revealed that the effect of inoculum addition was more significant than the alkaline pretreatment of raw waste materials. The biogas recovery from inoculated waste materials exceeds its production from wastes without inoculation by approximately 70% at mesophilic conditions. Whereby, the increase of biogas recovery from pretreated wastes was by 20% higher than its

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Crossref
Publication Date
Tue Jan 01 2019
Journal Name
Italian Journal Of Pure And Applied Mathematics
Co-small monoform modules
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he concept of small monoform module was introduced by Hadi and Marhun, where a module U is called small monoform if for each non-zero submodule V of U and for every non-zero homomorphism f ∈ Hom R (V, U), implies that ker f is small submodule of V. In this paper the author dualizes this concept; she calls it co-small monoform module. Many fundamental properties of co-small monoform module are given. Partial characterization of co-small monoform module is established. Also, the author dualizes the concept of small quasi-Dedekind modules which given by Hadi and Ghawi. She show that co-small monoform is contained properly in the class of the dual of small quasi-Dedekind modules. Furthermore, some subclasses of co-small monoform are investiga

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