Drilling with casing (DWC) can be considered as a modern drilling technique in which both of drilling and casing operations done in the same time by using the casing to transfer the hydraulic and mechanical power to the bit instead of traditional drilling string. To overcome oil well control, minimizing the total cost through enhancing drilling efficiency, drilling with casing was proposed as an enabling technology.

   Two surface sections (17 1/2 - and 12 1/4- inch) were drilled successfully in Rumaila oil field with  casing strings which reached 655m and 1524m measured depths respectively.

   By using DWC technique, the total drill/case phase time was reduced up to 20% comparing to conventional

Dynamic Thermal Management (DTM) emerged as a solution to address the reliability challenges with thermal hotspots and unbalanced temperatures. DTM efficiency is highly affected by the accuracy of the temperature information presented to the DTM manager. This work aims to investigate the effect of inaccuracy caused by the deep sub-micron (DSM) noise during the transmission of temperature information to the manager on DTM efficiency. A simulation framework has been developed and results show up to 38% DTM performance degradation and 18% unattended cycles in emergency temperature under DSM noise. The finding highlights the importance of further research in providing reliable on-chip data transmission in DTM application.

Non-prismatic reinforced concrete (RC) beams are widely used for various practical purposes, including enhancing architectural aesthetics and increasing the overall thickness in the support area above the column, which gives high assurance to services that this will not result in the distortion of construction features and can reduce heights. The hollow sections (recess) can also be used for the maintenance of large structural sections and the safe passage of utility lines of water, gas, telecommunications, electricity, etc. They are generally used in large and complex civil engineering works like bridges. This study conducted a numerical study using the commercial finite element software ANSYS version 15 for analysing RC beams, hol

The full energy peak efficiency (ɛ) relation of HpGe detector is determined and compared with the "spectrum shape" relation of natural background (BG) for the (121.8-1408) keV energy range. A one liter Marinelli beaker soil standard containing the Eu-152 material is used in calibration and measurement. A MATLAB fitting program were used obtain the efficiency relation from the experimental values, and to obtain the BG "spectrum shape" relation from the count rates at the corresponding energy values used. The ɛ / BG factor values were 1.154 at the 121.8keV and increase with energy till reaching a maximum value of 4.358 at about 778keV energy and then decrease. These values may be used to extract efficiency from the BG values at the

Metal oxide nanoparticles demonstrate uniqueness in various technical applications due to their suitable physiochemical properties. In particular, yttrium oxide nanoparticle(Y₂O₃NPs) is familiar for technical applications because of its higher dielectric constant and thermal stability. It is widely used as a host material for a variety of rare-earth dopants, biological imaging, and photodynamic therapies. In this investigation, yttrium oxide nanoparticles (Y₂O₃NPs) was used as an ecofriendly corrosion inhibitor through the use of scanning electron microscopy (SEM), Fourier transforms infrared spectroscopy (FT-IR), UV-Visible spectroscopy, X-ray diffraction (XRD), and energy dispersive X-ray spe

In Baghdad city, Iraq, the traffic volumes have rapidly grown during the last 15 years. Road networks need to reevaluate and decide if they are operating properly or not regarding the increase in the number of vehicles. Al-Jadriyah intersection (a four-leg signalized intersection) and Kamal Junblat Square (a multi-lane roundabout), which are two important intersections in Baghdad city with high traffic volumes, were selected to be reevaluated by the SIDRA package in this research. Traffic volume and vehicle movement data were abstracted from videotapes by the Smart Traffic Analyzer (STA) Software. The performance measures include delay and LOS. The analysis results by SIDRA Intersection 8.0.1 show that the performance of the roundab

The agricultural lands that depend on supplementary irrigation methods for winter wheat cultivating in wide areas of the Nineveh province are most vulnerable to climate change concerns. Due to frequent rainfall shortages and the temperature increase recently noticed and predicted by the climate scenarios. Hence important to assess the climate effect on the crop response in terms of water consumption during the periods (2021-2040) and (2041-2060) by using high-resolution data extracted from 6 global climate data GCMs under SSP5-8.5 fossil fuel emission scenarios in changing and fixed CO₂ concentration. And validate the Aqua-Crop model to estimate the yield and water productivity. And gives the RRSME of 7.1- 4.1

Expected to The organizational commitment by employees increases their loyalty towards their organization and thus contribute to enhancing their performance , therefore this study aimed to discover the relationship and the impact between the organizational commitment (emotional commitment, standard commitment, continuous commitment) and the performance of employees in the company researched, additional to know the available organizational commitment levels of employees in the company researched and its impact on the performance of employees, Research was conducted at the General Company for products in the dairy to achieve the goals of research has been developed questionnaire conation (22 ) items to collect data from the study s

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al