The combined system of electrocoagulation (EC) and electro-oxidation (EO) is one of the most promising methods in dye removal. In this work, a solution of 200 mg/l of Congo red was used to examine the removal of anionic dye using an EC-EO system with three stainless steel electrodes as the auxiliary electrodes and an aluminum electrode as anode for the EC process, Cu-Mn-Ni Nanocomposite as anode for the EO process. This composite oxide was simultaneously synthesized by anodic and cathodic deposition of Cu (NO3)2, MnCl2, and Ni (NO3)2 salts with 0.075 M as concentrations of each salt with a fixed molar ratio (1:1:1) at a constant current density of 25 mA/cm2. The characteristics structure and surface morphology of the deposited nano oxides onto the graphite substrates were determined by (XRD), (FE-SEM), (AFM), and (EDX). The results shown that nano Cu-Mn-Ni oxides were successfully deposited onto the anode and cathode. The crystal size and root mean square for the cathode were 30.79 nm and 79.36 nm, respectively, while for the anode, they were 24.19 nm and 41.88 nm, respectively. Furthermore, the combined system was examined for C.D, NaCl concentration, and time. In the EC-EO combined system, the cathode and anode were efficient when used as anodes for the EO process, besides aluminum. The cathode was more effective in the removal process than the anode due to its larger crystal size and the rough, granular shape of its surface. When current density (C.D) increased from 3 to 6 mA/cm², the removal efficiency shifted from 95% to 98%. However, excellent removal of 98% and 96.5% was attained with 1.665 and 2.0859 kWh/kg of dye as energy consumption in the presence and absence of NaCl salt, respectively by applying 6 mA/cm2 within 20 min of electrolysis.
Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer
... Show MoreBackground: The rapid evolution of Artificial Intelligence (AI) has significantly influenced Education, demonstrating substantial potential to transform traditional teaching and learning methods. AI reshapes teacher-student interactions and the relationship with knowledge. Objective: To analyze the potential benefits, ethical challenges, and limitations of AI in Education based on recent scientific literature, emphasizing the balance between technology and human interaction. Methods: A documentary research approach with a descriptive focus was employed, following the PRISMA protocol for systematic reviews. The search strategy involved analyzing evidence from 18 scientific articles published within the last six years. Results:AI o
... Show MoreChannel estimation and synchronization are considered the most challenging issues in Orthogonal Frequency Division Multiplexing (OFDM) system. OFDM is highly affected by synchronization errors that cause reduction in subcarriers orthogonality, leading to significant performance degradation. The synchronization errors cause two issues: Symbol Time Offset (STO), which produces inter symbol interference (ISI) and Carrier Frequency Offset (CFO), which results in inter carrier interference (ICI). The aim of the research is to simulate Comb type pilot based channel estimation for OFDM system showing the effect of pilot numbers on the channel estimation performance and propose a modified estimation method for STO with less numb
... Show MorePredicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be
... Show MoreThis study deals with the estimation of critical load of unidirectional polymer matrix composite plates by using experimental and finite element techniques at different fiber angles and fiber volume fraction of the composite plate.
Buckling analysis illustrated that the critical load decreases in nonlinear relationship with the increase of the fiber angle and that it increases with the increase of the fiber volume fraction.
The results show that the maximum value of the critical load is (629.54 N/m) at (q = 0°) and (Vf = 40 %) for the finite element method, while the minimum val
... Show MoreGypseous soils represented one of the most complex salty soils that faced the geotechnical engineers. Structures that built on gypsum soil will undergo unexpected distortions that will eventually contribute to catastrophic failure. The purpose of this article is to understand the durability of gypsum soil against wetting drying cycles after improvement with polyurethane polymer especially investigate the effect of the wetting-drying cycle on collapsibility. The soil was brought from Sawa lake in AL-Muthanna Governorate in Iraq, with gypsum content 65.5%, A set of Odometer tests were performed to determine the collapsibility potential (CP) for treated and untreated gypsum soil. The result shows that adding a different per
... Show MoreThe toxic lead additives to gasoline are no longer used in many countries around the world. Many other countries are now phasing out the lead in gasoline. Although the lead fuel is still in use in Iraq, several plans are considered to phase out the lead. The use of organic compounds to replace the lead additives in gasoline is considered now as an option in Iraqi refineries. The main objective of this project was preparation of premium gasoline, by blending of gasoline with Alternative additives (alcohol, aromatic) to enhancing octane number of Al-Doura gasoline pool. Improved gasoline was tested by ASTM standard method which includes octane number measuring by CFR engine analyzer. Gasoline pool RON (80) was used and selective components
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