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Investigation of the State Vectors and Prediction of the Orbital Elements for Spot-6 Satellite during 1300 periods with Perturbations
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Abstract<p>Computer simulations were carried out to investigate the dependence of the main perturbation parameters (Sun and Moon attractions, solar radiation pressure, atmosphere drag, and geopotential of Earth) on the orbital behavior of satellite. In this simulation, the Cowell method for accelerations technique was adopted, the equation of motion with perturbation was solved by 4<sup>th</sup> order Runge-Kutta method with step (1/50000) of period to obtain the state vectors for position and velocity. The results of this simulation have been compared with data that available on TLEs (NORD data in two line elements). The results of state vectors for satellites (Cartosat-2B, Gsat-14 and Spot-6) shows excellent correlation and this is leading us to extend our study for (spot-6) satellite to include the orbital behavior during 13000 periods under the effect of one type of perturbation or all types. The results indicate that all perturbation have clear effect on spot-6 orbit, reduced the perigee and apogee about 3 Km. during 89 days, also the time of period reduced 4.7 sec. Other conclusions present that the perigee angle increases 28.01 degree with any perturbation accept SRP. Furthermore, the geopotential have a big periodic effect but the atmospheric drag have accumulated effect on most orbital elements.</p>
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Publication Date
Mon May 01 2017
Journal Name
Ieee International Electrical Machines & Drives Conference Ieee (iemdc2017), Miami, Usa
The effect of power converter on the design of a Linear Alternator for use with a Joule Cycle-Free Piston Engine
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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
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

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Applied Engineering Science
Rutting prediction of hot mix asphalt mixtures reinforced by ceramic fibers
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One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to stu

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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Sun Dec 27 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Phytochemical Investigation of Aerial Parts of Iraqi Cardaria draba
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 The aim of this study was to study chemical constituents of aerial parts of Cardaria draba since no phytochemical investigation had been studied before in Iraq. Aerial parts of Cardaria draba were defatted by maceration in hexane for 72 h. The defatted plant materials were extracted using Soxhlet apparatus, the aqueous Methanol 90% as a solvent extraction for 18 h, and fractionated with petroleum ether- chloroform (CHCl3)- ethylacetate- and n-butanol respectivly. The ethyl acetate, n-butanol, and n-butanol after hydrolysis fractions were investigated by high performance liquid chromatography (HPLC) and thin-layer chromatography (TLC) for its phenolic acid and flavonoid contents. Flavono

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Publication Date
Mon Sep 16 2024
Journal Name
Plant Protection
In vitro investigation of phytochemical, antioxidant and antimicrobial activities of Harpagophytum procumbens seeds extracts
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Medicinal plants contain bioactive substances that are highly bioavailable in extracts or pure molecules, making them promising for therapeutic applications and precursors for chemo-pharmaceutical semi-synthesis. Harpagophytum procumbens (Devil’s Claw) is widely recognized as one of the most potent therapeutic herbs. This study aimed to extract seeds from H. procumbens using two types of solvents and to assess both qualitative and quantitative aspects of the extracts. The two extracts were evaluated for antibacterial and anti-biofilm activities using agar well diffusion assays against four bacterial isolates and two yeast isolates. Qualitative analysis identified the presence of alkaloids, flavonoids, tannins, saponins, and terpen

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Publication Date
Thu Nov 01 2018
Journal Name
Colloids And Surfaces B: Biointerfaces
Green synthesis of silver nanoparticles using turmeric extracts and investigation of their antibacterial activities
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Publication Date
Mon Sep 16 2024
Journal Name
Plant Protection
In vitro investigation of phytochemical, antioxidant and antimicrobial activities of Harpagophytum procumbens seeds extracts
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Medicinal plants contain bioactive substances that are highly bioavailable in extracts or pure molecules, making them promising for therapeutic applications and precursors for chemo-pharmaceutical semi-synthesis. Harpagophytum procumbens (Devil’s Claw) is widely recognized as one of the most potent therapeutic herbs. This study aimed to extract seeds from H. procumbens using two types of solvents and to assess both qualitative and quantitative aspects of the extracts. The two extracts were evaluated for antibacterial and anti-biofilm activities using agar well diffusion assays against four bacterial isolates and two yeast isolates. Qualitative analysis identified the presence of alkaloids, flavonoids, tannins, saponins, and terpen

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
NUMERICAL INVESTIGATION OF STATIC AND DYNAMIC STRESSES IN SPUR GEAR MADE OF COMPOSITE MATERIAL
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In this current work, Purpose; to clearly the fundamental idea for constructing a design and
investigation of spur gear made of composite material its comes from the combination of (high
speeds, low noise, oil-les running, light weight, high strength, and more load capability)
encountered in modern engineering applications of the gear drives, when the usual metallic gear
cannot too overwhelming these combinations.
An analyzing of stresses and deformation under static and dynamic loading for spur gear tooth
by finite element method with isoparametric eight-nodded in total of 200 brick element with 340
nods in three degree of freedom per node was selected for this analysis. This is responsible for the
catastropic fa

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