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Improvement of Diesel Fuel Engine Performance by Nanoparticles Additives
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This study was done to investigate the impact of different nanoparticles on diesel fuel characteristics, Iraqi diesel fuel was supplied from al-Dura refinery and was treated to enhance performance by improving its characteristics. Two types of nanoparticles were mixed with Iraqi diesel fuel at various weight fractions of 30, 60, 90, and 120 ppm. The diesel engine was tested and run at a constant speed of 1600 rpm to examine and evaluate the engine's performance and determine emissions. In general, ZnO additives' performance analysis showed they are more efficient for diesel fuel engines than CeO. The performance of engine diesel fuel tests showed that the weight fraction of nanoparticles at 90 and 120 ppm give a similar performance, so, for economic aspects, the additives at 90 ppm of two types of nanoparticles gave good performance efficiency and the best reduction of gas emissions. The enhancement for ZnO additives is up to 34.28% compared to pure diesel fuel, while for nano CeO, the maximum enhancement is 20% compared to pure diesel fuel. The brake thermal efficiency increases with additives. The best improvements in brake thermal efficiency were 62% for ZnO and 59% for CeO, respectively, both at 120 ppm. A reduction in NOx, CO2, CO and UHC emissions was observed compared with the diesel fuel that was consumed from pure diesel fuel. The maximum reduction emissions values for NOx, CO, CO2 and un-burn hydrocarbon (UHC) were 63.77, 29.26, 56.41, and 57.37 % for ZnO, and 58.11, 37.80, 61.53, and 50.81 % for CeO additives. Therefore, it is recommended to utilize nanoparticles, especially ZnO, as a fuel additive with diesel fuel and consider them as an enhancer material to increase engine efficiency and reduce exhaust emissions.

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Tue Nov 01 2016
Journal Name
Materials Science Forum
Study the Effect of Liquid Layer Level on the Formation of Zinc Oxide Nanoparticles Synthesized by Liquid-Phase Pulsed Laser Ablation
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This work is focused on studying the effect of liquid layer level (height above a target material) on zinc oxide nanoparticles (ZnO and ZnO2) production using liquid-phase pulsed laser ablation (LP-PLA) technique. A plate of Zn metal inside different heights of an aqueous environment of cetyl trimethyl ammonium bromide (CTAB) with molarity (10-3 M) was irradiated with femtosecond pulses. The effect of liquid layer height on the optical properties and structure of ZnO was studied and characterized through UV-visible absorption test at three peaks at 213 nm, 216 nm and 218 nm for three liquid heights 4, 6 and 8 mm respectively. The obtained results of UV–visible spectra test show a blue shift accomp

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Publication Date
Mon Jan 25 2021
Journal Name
Engineering And Technology Journal
Performance evaluation of Photovoltaic Panels by a Proposed Automated System Based on Microcontrollers
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Publication Date
Mon Jan 01 2024
Journal Name
Aims Energy
The impact of different compression ratios on emissions, and combustion characteristics of a biodiesel engine
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<p>The current work investigated the combustion efficiency of biodiesel engines under diverse ratios of compression (15.5, 16.5, 17.5, and 18.5) and different biodiesel fuels produced from apricot oil, papaya oil, sunflower oil, and tomato seed oil. The combustion process of the biodiesel fuel inside the engine was simulated utilizing ANSYS Fluent v16 (CFD). On AV1 diesel engines (Kirloskar), numerical simulations were conducted at 1500 rpm. The outcomes of the simulation demonstrated that increasing the compression ratio (CR) led to increased peak temperature and pressures in the combustion chamber, as well as elevated levels of CO<sub>2</sub> and NO mass fractions and decreased CO emission values un

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Effect of internal curing on performance of self-compacting concrete by using sustainable materials
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This paper is devoted to investigate the effect of internal curing technique on the properties of self-compacting concrete. In this study, self-compacting concrete is produced by using limestone powder as partial replacement by weight of cement with percentage of (5%), sand is partially replaced by volume with saturated fine lightweight aggregate which is thermostone aggregate as internal curing material in three percentages of (5%, 10%, 15%) for self-compacting concrete, and the use of two external curing conditions which are water and air. The experimental work was divided into three parts: in the first part, the workability tests of fresh self-compacting concrete were conducted. The second part included conducting compressive str

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Publication Date
Sat Apr 25 2020
Journal Name
Indian Journal Of Forensic Medicine &amp; Toxicology
Flame Atomic Absorption Spectrophotometry Analysis of Heavy Metals in Some Food Additives Available in Baghdad Markets, Iraq
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Publication Date
Wed Apr 01 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Flame Atomic Absorption Spectrophotometry Analysis of Heavy Metals in Some Food Additives Available in Baghdad Markets, Iraq
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Flame atomic absorption spectrophotometer (FAAS) was used in this study to determine the concentrations of heavy metals such as Ca, Fe, Mn, Cd, Co, Cr, Ni, Cu, Pb and Zn in some food additives of Iraq. The order of metal contents in food additives was found to be Ca ˃ Mn ˃ Fe ˃ Cu ˃ Zn ˃ Pb ˃ Cr ˃ Ni ˃ Co ˃ Cd. The concentration level of each metal was compared with that recommended by food agriculture organisation (FAO) and world health organisation (WHO). Calibration curves were linear for all standard solutions of heavy metals in the range starting from 0.02-0.4 mg/kg for Cd to 11-100 mg/kg for Ca. The correlation coefficients values (R2) of calibrations were investigated and ranged from 0.9971 for Cr to 0.9999 for Ca. Th

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Publication Date
Thu Jan 01 2026
Journal Name
Aip Conference Proceedings
Biogenic selenium nanoparticles by probiotics streptococcus salivarius and effect on oprM gene expression from Pseudomonas aeruginosa
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
The Influence of Biologically Synthesized Copper Nanoparticles on the Biofilm Produced by Staphylococcus haemolyticus 1solated from Seminal Fluid
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     Staphylococcus haemolyticus is one of the most frequently isolated coagulase-negative staphylococci. The ability to form biofilm is considered as one of the most important virulence factors of coagulase negative staphylococci. There is only limited knowledge of the nature of S. haemolyticus biofilms. This study was aimed at evaluating the ability of S. haemolyticus strains to produce biofilm in the presence of copper oxide nanoparticles (CuONPs). The biological synthesis of nanoparticles is an environmentally friendly approach for large-scale production of nanoparticles. Copper oxide nanoparticles were produced in the current study from the S. haemolyticus viable cell filtrate. UV-visible (UV-Vis) spectroscopy, X-ray diffra

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Study of (Zn0.7 Mn0.3-x Ag0.3 Fe2O4) ferrite nanoparticles synthesized by auto combustion method for NO2 gas sensing
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