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Two Domain Flow Method for Leachate Prediction Through Municipal Solid Waste Layers in Al–Amari Landfill Site
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Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to 0.12 and effective storage and hydraulic conductivity of the wasted must be increased to 0.2 and 2.2 cm/s respectively. In the long term, a new modeling approach must be developed to adequately describe the moisture movement mechanisms.

 

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Publication Date
Thu Oct 01 2020
Journal Name
Alexandria Engineering Journal
The operational matrix of Legendre polynomials for solving nonlinear thin film flow problems
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Publication Date
Thu Oct 01 2020
Journal Name
Alexandria Engineering Journal
The operational matrix of Legendre polynomials for solving nonlinear thin film flow problems
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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
INTERACTION EFFECTS OF HYDRODYNAMICALLY FULLY DEVELOPED PRIMARY FLOW AND SECONDARY FLOW IN THE THERMAL ENTRANCE REGION OF ANNULAR DUCT
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Experiments have been conducted to study the local and average heat transfer by mixed
convection for hydrodynamically fully developed, thermally developing and fully developed
laminar upward air flow in an inclined annulus with adiabatic inner cast iron tube and uniform
heated outer aluminum tube with an aspect ratio ( Ω = 0.72) and (L/Dh≈40) for both calming and
test sections). A wide range of Reynolds number from 859 to 2024 has been covered, and heat
flux has been varied from 159 W/m2 to 812 W/m2 (these values of heat flux and Reynolds
number gave Richardson number range from 0.03 to 0.٣٨), with angles of annulus inclination
φ =0o (horizontal position), φ =60o (inclined position), and φ =90o (vertical posi

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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Drying of solid Materials by vacuum Fluidized Bed Dryer
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In the present study the performance of drying process of dffirent solid materials by batch fluidized bed drying
under vacuum conditions was investigated. Three, different solid materials, namely; ion exchange resin-8528,
aspirin and paracetamol were used. The behavior of the drying curves as well as the rate of drying of these
materials had been studied. The experiments were caried out in a 0.0381 m column diameter fluidized by hot
air under yacuum conditions. Four variables affecting on the rate of drying were studied' these variables are
vacuum pressure (100 - 500 mm Hg), air temperature (303-323 K), particle size (0.3-0.8 mm) and initial
moisture content (0.35-0.55 g/g solid)-for resin and (0.1-0.2 g/g soltid) for a

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Publication Date
Mon Oct 04 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Perforation location optimization through 1-D mechanical earth model for high-pressure deep formations
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Optimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Emergency Messages Dissemination Challenges Through Connected Vehicles for Efficient Intelligent Transportation Systems: A Review
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Recent growth in transport and wireless communication technologies has aided the evolution of Intelligent Transportation Systems (ITS). The ITS is based on different types of transportation modes like road, rail, ocean and aviation. Vehicular ad hoc network (VANET) is a technology that considers moving vehicles as nodes in a network to create a wireless communication network. VANET has emerged as a resourceful approach to enhance the road safety. Road safety has become a critical issue in recent years. Emergency incidents such as accidents, heavy traffic and road damages are the main causes of the inefficiency of the traffic flow. These occurrences do not only create the congestion on the road but also increase the fuel consumption and p

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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Univariate and Simplex Optimization for The Analysis of Diphenhydramine-HCl Through Ion-pair Formation
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    A Simple, rapid and sensitive extractive and spectrophotometric method has been described for the analysis of diphenhyldramine –HCl (DPH) in pure form and in pharmaceutical formulations. The method is based on the formation of chloroform soluble ion-pair  complex with Bromophenol blue(BPB) in a phthalate buffer at pH 3.0.The extracted complex shows maximum absorbance at 410 nm. Beer's law is obeyed in the concentration range 0.2-25.0 µg.ml-1. The molar absorptivity and Sandell's sensitivity for the system being  2.416x104 L.mol-1.cm-1 and 0.012µg.cm-2, respectively. The limit of detection was found to be 0.155 µg.ml-1.           The proposed me

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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Wed Mar 01 2017
Journal Name
Neural Computing And Applications
The potential of nonparametric model in foundation bearing capacity prediction
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