This article uses coupled Eulerian–Lagrangian finite element algorithm to conduct a three-dimensional thermomechanical study to capture the shape and characteristics of defect type generated while achieving the dissimilar friction stir welding of aluminium alloys. The volume-of-fluid method is used to model the Eulerian region and predict the localised formation of process defects. Three different tool shapes are utilised to achieve the dissimilar friction stir welding joining between AA 2024-T3 on the advancing side and AA 6061-T6 on the retreating side. Process parameter effects such as rotational tool speed, traverse tool speed and tool tilt angle are also investigated. The finite element model results are validated by comparing with the results of a previous experimental study. The results showed the augmentation of the traverse welding speed from 40 to 80 mm/min is a key factor in causing process imperfections such as void and tunnel defects. The lower tilt angle value of 1° resulted in long tunnel defects when high rotational speeds are applied. Also, the combination of high rotational and low transverse speeds promotes the production of a free-defect friction stir welding joint.
This study was conducted in College of Science \ Computer Science Department \ University of Baghdad to compare between automatic sorting and manual sorting, which is more efficient and accurate, as well as the use of artificial intelligence in automated sorting, which included artificial neural network, image processing, study of external characteristics, defects and impurities and physical characteristics; grading and sorting speed, and fruits weigh. the results shown value of impurities and defects. the highest value of the regression is 0.40 and the error-approximation algorithm has recorded the value 06-1 and weight fruits fruit recorded the highest value and was 138.20 g, Gradin
The measurement data of the raw water quality of Tigris River were statistically analyzed to measure the salinity value in relation to the selected raw water quality parameters. The analyzed data were collected from five water treatment plants (WTPs) assembled alongside of the Tigris River in Baghdad: Al-Karkh, Al-Karama, Al-Qadisiya, Al-Dora, and Al-Wihda for the period from 2015 to 2021. The selected parameters are total dissolved solid (TDS), electrical conductivity (EC), pH and temperature. The main objective of this research is to predicate a mathematical model using SPSS software to calculate the value of salinity along the river, in addition, the effect of electrical conductivi
Zubair Formation is one of the richest petroleum systems in Southern Iraq. This formation is composed mainly of sandstones interbedded with shale sequences, with minor streaks of limestone and siltstone. Borehole collapse is one of the most critical challenges that continuously appear in drilling and production operations. Problems associated with borehole collapse, such as tight hole while tripping, stuck pipe and logging tools, hole enlargement, poor log quality, and poor primary cement jobs, are the cause of the majority of the nonproductive time (NPT) in the Zubair reservoir developments. Several studies released models predicting the onset of borehole collapse and the amount of enlargement of the wellbore cross-section. However, assump
... Show MoreModern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan
... Show MoreThe aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.
Nowadays, most of the on-chip plasmonic single-photon sources emit an unpolarized stream of single photons that demand a subsequent polarizer stage in a practical quantum cryptography system. In this paper, we numerically demonstrated the coupling of the light emitted from a quantum emitter (QE) at 700 nm wavelength to the propagation mode supported by an on-chip hybrid plasmonic waveguide (HPW) polarization rotator. Our results proved that the light emitted is linearly polarized at 0º, 45º/−45º, and 90º with propagation lengths of 5 μm, 3.3 μm, and 3.9 μm, respectively. Moreover, high power-conversion efficiency was obtained from an applied transverse magnetic (TM) mode (0º-polarization) to a transverse electric (TE) (90º-polari
... Show MoreChemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi
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