Experimental and numerical investigations of the centrifugal pump performance at non-cavitating and cavitating flow conditions were carried out in the present study. Experiments were performed by applying a vacuum to a closed-loop system to investigate the effects of the net positive suction head available (NPSHa), flow rate, water temperature and pump speed on the centrifugal pump performance. Accordingly, many of the important parameters concerning cavitation phenomenon were calculated. Also, the noise which is accompanied by cavitation was measured. Numerical analysis was implemented for two phase flow (the water and its vapor) using a 2-D simulation by ANSYS FLUENT software to investigate the internal flow of centrifugal pump under c

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

Motives: The research deals with the issue of urban sprawl on agricultural lands. It is an urban problem caused by rapid urbanization and poor planning. It is considered one problem that threatens cities with environmental and health disasters. It also threatens agricultural life and the green belt surrounding cities. Changes in urban sprawl on agricultural land are associated with complex processes that lead to multiple social, economic, political, and environmental risks and thus pose a threat and an obstacle to the sustainability of cities. Aim: The research aims to study and evaluate the reality of the city of Baghdad and the extent of its ability and flexibility to withstand the disaster of urban sprawl on agricultural lands. T

This paper presents seven modified Adomian Decomposition Method (ADM) techniques for efficiently solving initial value problems, especially those involving non-homogeneous and nonlinear differential equations. While the classical ADM is effective for linear homogeneous cases, it has difficulties solving more complex problems. The proposed modifications—from MADM1 to MLADM—include Maclaurin and Taylor expansions, Laplace transforms, and single-step iterations.• These modifications enhance convergence, reduce complexity, and improve accuracy.• Each method offers specific advantages, such as accelerating convergence (MADM2, RADM4), simplifying computation (TSADM5), and achieving higher accuracy (MLADM).• Numerical examples confirm th

INTRODUCTION: A range of tools and technologies are at disposal for the purpose of defect detection. These include but are not limited to sensors, Statistical Process Control (SPC) software, Artificial Intelligence (AI) and machine learning (ML) algorithms, X-ray systems, ultrasound systems, and eddy current systems. OBJECTIVES: The determination of the suitable instrument or combination of instruments is contingent upon the precise production procedure and the category of flaw being identified. In certain cases, defects may necessitate real-time monitoring and analysis through the use of sensors and SPC software, whereas more comprehensive analysis may be required for other defects through the utilization of X-ray or ultrasound sy

       Vegetation monitoring is considered an important application in remote sensing task due to variation of vegetation types and their distribution. The vegetation concentration around the Earth is increase in 5% in 2000 according to NASA monitoring. This increase is due to the Indian vegetable programs. In this research, the vegetation monitoring in Baghdad city was done using Normalized Difference Vegetation Index (NDVI) for temporal Landsat satellite images (Landsat 5 TM& Landsat 8 OIL). These images had been used and utilize in different times during the period from 2000, 2010, 2015 & 2017. The outcomes of the study demonstrate that a change in the vegetation Cover (VC) in Baghdad city. (NDVI) generally shows a

Excessive torque and drag can be critical limitation during drilling highly deviated oil wells. Using the modeling is regarded as an invaluable process to assist in well planning and to predict and prevent drilling problems. Identify which problems lead to excessive torque and drag to prevent cost losses and equipment damage. Proper modeling data is highly important for knowing and prediction hole problems may occur due to torque and drag and select the best method to avoid these problems related to well bore and drill string. In this study, Torque and drag well plan program from landmark worldwide programming group (Halliburton Company) used to identify hole problems.one deviated well in Zubair oil fields named, ZB-250 selected for anal