In this study, the hydromorphodynamic simulation of a stretch of the Euphrates River was conducted. The stretch of the Euphrates River extended from Haditha dam to the city of Heet in Al-Anbar Governorate and it is estimated to be 124.4 km. Samples were taken from 3 sites along the banks of the river stretch using sampling equipment. The samples were taken to the laboratory for grain size analysis where the median size (D₅₀) and sediment load were determined. The hydromorphodynamic simulation was conducted using the NACY 2DH solver of the iRIC model.  The model was calibration using the Manning roughness,    sediment load, and median particle size and the validation process showed that the error between th

Predicting vertical stress was indeed useful for controlling geomechanical issues since it allowed for the computation of pore pressure for the formation and the classification of fault regimes. This study provides an in-depth observation of vertical stress prediction utilizing numerous approaches using the Techlog 2015 software. Gardner's method results in incorrect vertical stress values with a problem that this method doesn't start from the surface and instead relies only on sound log data. Whereas the Amoco, Wendt non-acoustic, Traugott, average technique simply needed density log as input and used a straight line as the observed density, this was incorrect for vertical computing stress. The results of these methods

Greywater is a possible water source that can be improved for meeting the quality required for irrigation. Treatment of greywater can range from uncomplicated coarse filtration to advanced biological treatment. This article presents a simple design of a small scale greywater treatment plant, which is a series of physical and natural processes including screening, aeration, sedimentation, and filtration using granular activated carbon filter and differentiates its performance with sand filter. The performance of these units with the dual filter media of (activated carbon with sand) in treatment of greywater from Iraqi house in Baghdad city during 2019 and that collected from several points including washbasins, kitchen si

Solanum americanum is a new annual shrubby plant seen recently in fields and gardens of Baghdad city. A new species is described and illustrated, inhabit wet or semi dry places and have consequently a mesophytic habit. A detailed morphological study of the stems, leaves, Inflorescence, flower, male and female reproductive organs and fruits has been done, revealed several interesting taxonomic characteristics, which have not previously been studied in Iraq. Also, anatomical studies reveals constant taxonomical characteristics such as the presence of anthocayanine in outer row of epidermis, distinct chlorenchyma in whole cortex, the wide pith of stems, and presence of distinct mesophyll that differentiated into palisade layer and spongy laye

In order to achieve overall balance in the economy to be achieved in different markets and at one time (market commodity, monetary and labor market and the balance of payments and public budget), did not provide yet a model from which to determine the overall balance in the economy and the difficulty of finding the inter-relationship between all these markets and put them applied in the form of allowing the identification of balance in all markets at once.

One of the best models that have dealt with this subject is a model
(LM-BP-IS), who teaches balance in the commodity market and money market and balance of payments and the importance of this issue This research tries to shed light on the reality

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The possibility of predicting the mass transfer controlled CaCO₃ scale removal   rate has been investigated.

Experiments were carried out using chelating agents as a cleaning solution at different time and Reynolds’s number. The results of CaCO₃ scale removal or (mass transfer rate) (as it is the controlling process) are compared with proposed model of prandtl’s and Taylor particularly based on the concept of analogy among momentum and mass transfer.

Correlation for the variation of Sherwood number ( or mass transfer rate ) with Reynolds’s number have been obtained .

     An experimental study was carried out to improve the surface roughness quality of the stainless steel 420 using magnetic abrasive finishing method (MAF). Four independent operation parameters were studied (working gap, coil current, feed rate, and table stroke), and their effects on the MAF process were introduced. A rotating coil electromagnet was designed and implemented to use with plane surfaces. The magnetic abrasive powder used was formed from 33%Fe and 67% Quartz of (250µm mesh size). The lubricant type SAE 20W was used as a binder for the powder contents. Taguchi method was used for designing the experiments and the optimal values of the selected parameters were found. An empirical equation representing the r