Dam operation and management have become more complex recently because of the need for considering hydraulic structure sustainability and environmental protect on. An Earthfill dam that includes a powerhouse system is considered as a significant multipurpose hydraulic structure. Understanding the effects of running hydropower plant turbines on the dam body is one of the major safety concerns for earthfill dams. In this research, dynamic analysis of earthfill dam, integrated with a hydropower plant system containing six vertical Kaplan turbines (i.e., Haditha dam), is investigated. In the first stage of the study, ANSYS-CFX was used to represent one vertical Kaplan turbine unit by designing a three-dimensional (3-D) finite element (FE) model. This model was used to differentiate between the effect of turbine units’ operation on dam stability in accordance to maximum and minimum reservoir upstream water levels, and the varying flowrates in a fully open gate condition. In the second stage of the analysis, an ANSYS-static modeling approach was used to develop a 3-D FE earthfill dam model. The water pressure pattern determined on the boundary of the running turbine model is transformed into the pressure at the common area of the dam body with turbines. The model is inspected for maximum and minimum upstream water levels. Findings indicate that the water stress fluctuations on the dam body are proportional to the inverse distance from the turbine region. Also, it was found that the cone and outlet of the hydropower turbine system are the most affected regions when turbine is running. Based on the attained results, a systematic operation program was proposed in order to control the running hydropower plant with minimized principal stress at selected nodes on the dam model and the six turbines.
Artificial intelligence (AI) offers significant benefits to biomedical research and academic writing. Nevertheless, using AI-powered writing aid tools has prompted worries about excessive dependence on these tools and their possible influence on writing proficiency. The current study aimed to explore the academic staff’s perspectives on the impact of AI on academic writing. This qualitative study incorporated in-person interviews with academic faculty members. The interviews were conducted in a semi-structured manner, using a predetermined interview guide consisting of open-ended questions. The interviews were done in person with the participants from May to November 2023. The data was analyzed using thematic analysis. Ten academics aged
... Show MoreThe relationships between the related parties constitute a normal feature of trading and business processes. Entities may perform parts of their activities through subsidiary entities, joint ventures and associate entities. In these cases, the entity has the ability to influence the financial and operating policies of the investee through control, joint control or significant influence, So could affect established knowledge of transactions and balances outstanding, including commitments, and relationships with related to the evaluation of its operations by users of financial statements, including the risks and opportunities facing the entity assess the parties. So research has gained importance of the importance of the availability
... Show MoreRudimentary non-communicating functional uterine horn with unicornuate uterus, originating from anomalous embryological development of one Mullerian duct, is prone to different complications either at the gynecological or obstetrical level such as chronic pelvic pain, hematometra, subfertility and decreased quality of life. This unique case report presents a 14-year-old female with a history of severe chronic pelvic pain. She was diagnosed with Familial Mediterranean Fever (FMF) and had an appendectomy for suspected appendicitis within the symptoms’ interval. Ultrasound showed a right 5*6 cm right complex cystic mass assuming ovarian in place. She underwent a suspected endometrioma cystectomy operation and was diagnosed with left unico
... Show MoreThe study aims to identify the colleges women in the USA where he was browsing the Internet for five universities and sixty-two women's college located these colleges in 25 states only three general and other civil 51% supported by the churches and religious associations of various began its founding in Alqrnn eighteenth and continued in the nineteenth and twentieth and to provide an opportunity for women to complete higher education, while most men's colleges opened their doors to the admission of women and turned it on coeducation
The term "semantic exchange" was popularized in Arabic, especially in derivatives, grammatical structures, etc., but it came under different names or terms, including deviation, deviation, transition, displacement, tooth breach, replacement, attention, etc. In the rooting of this term through its study in language and terminology, and among linguists, grammar and others, we have reached a number of results, including The existence of a harmonization between the lexical and idiomatic meaning of the term exchange, and the phenomenon of semantic exchange is a form of expansion in language, and that the first language scientists They had turned to this And studied under Cairo for different names, as noted above.
In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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