Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

A novel welded demountable shear connector for sustainable steel-concrete composite structures is proposed. The proposed connector consists of a grout-filled steel tube bolted to a compatible partially threaded stud, which is welded on a steel section. This connector allows for an easy deconstruction at the end of the service life of a building, promoting the reuse of both the concrete slabs and the steel sections. This paper presents the experimental evaluation of the structural behavior of the proposed connector using a horizontal pushout test arrangement. The effects of various parameters, including the tube thickness, the presence of grout infill, and the concrete slab compressive strength, were assessed. A nonlinear finite element mode

Background: The mechanical properties of 3D-printed denture base resins are crucial factors for determining the quality and performance of dentures inside a patient’s mouth. Tensile strength and diametral compressive strength are two properties that could play significant roles in assessing the suitability of a material. Although they measure different aspects of material behavior, a conceptual link exists between them in terms of overall material strength and resilience. Aim: This study aims to investigate the correlation between tensile strength and diametral compressive strength after incorporating 2% ZrO2 nanoparticles (NPs) by weight into 3D-printed denture base resin. Methods: A total of 40 specimens (20 dumbbell-shaped and

Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

I mpact strength for Epoxy/Polyurethane, Blends and their composites with two
layers of Glass fibers (0-90) are calculated.
The impact strength of the blends and composites decrease with increasing weight
by weisht percentage of polyurethane . This result is attributed to the high elasticity
of PU , and to the immiscibility between the polymer blends as well as the fiber
delaminates

osion and deposition are natural phenomena in rivers that can be identified by using velocity profiles and shear stress as indicators. The Shatt Al-Arab River located south of Iraq suffers from these phenomena. Based upon the basic principles of hydraulics, it is reasonably easy to identify shear stress distributions within the river reach of the Shatt Al-Arab; and that will allow us to know the locations of the erosion and deposition. For this purpose, a 2D model using HEC-RAS software was developed to simulate the flow within the lower reach of Shatt Al-Arab. The results showed that the maximum shear stress at the right bank of Shatt Al- Arab reached 0.1N/m2 at 12 km upstream of Ras- Al-Bisha. This value of shear stress was recorded durin

The increasing use of polymeric materials in the daily life, leads to challenges in the processing industry to deliver high performance materials with affordable terms. However, new processing techniques lead to high costs. In order to reduce processing costs it is necessary to understand the non-Newtonian behavior of the polymers in their molten state to be able to simulate the processes before the construction of the plants starts. Here the shear thinning behavior of the viscosity of polymeric melts is essential. Thus, this paper deals with the experimental investigation of the thermo-rheological behavior of the viscosity of one of the most used polymers (Polypropylene) over a wide range of temperatures and shear rates.  Furthermo