Majmaah University (MU) is located in Al Majma'ah, Saudi Arabia. It was founded in 2009. The university main campus is located in the south part of Majmaah City. Teaching and research are delivered in 13 academic schools. The university is established to serve a wide area including Majmmah, Zulfi, Remah, Ghat and Hawtat Sudair. The university has around 20 buildings for the administration, colleges, deanships, medical services and units.College of DentistryIn consonance with the expansion process of Majmaah University, the College of Dentistry effectively came into being during 2010-2011 academic session-https://www.mu.edu.sa/en/colleges/faculty-dentistry-al-zulfi/sections. We need to note here that Majmmah University operates multi-campus system in its catchment area to widen accessibility; hence its College of Dentistry is located at Zulfi. The college offers Bachelor of Dentistry degree to qualified students. Currently the following academic departments are functional at the college:1.Department of Oral and Maxillofacial Surgery and Diagnostic Sciences2.Department of Dental Repair3.Department of Preventive Dental Sciences 4.Department of Prosthodontics Dental Sciences5 Department of Basic Medical Sciences 6 Department of Dental EducationA Dental Teaching Center has also been set up to serve the twin purposes of clinical training and serving the community. An array of regulatory tasks and physical structures that could facilitate teaching and research has been put in place..
This research introduces and optimizes a novel multi-generation power system integrating a steam Rankine cycle (SRC), a gas turbine (GT), an absorption refrigeration cycle (ARC), a proton exchange membrane (PEM) electrolyzer, and a CO2 separation unit. This system is designed to improve energy efficiency while simultaneously capturing CO2 and producing hydrogen through electrolysis. Two configurations-with and without ARC-are evaluated using a genetic algorithm-based multi-objective optimization framework, which considers exergetic efficiency, CO2 emission reduction, and total cost rate. The findings demonstrate that the proposed system improves exergetic efficiency by up to 71% and reduces CO2 emissions by up to 3.9% compared to a standalone GT system. Furthermore, the system without ARC achieves higher hydrogen production, while the system with ARC provides valuable cooling. These findings demonstrate the feasibility and environmental advantages of integrated power, CO2 capture, and H 2 blending systems for sustainable energy generation.
Despite extensive research on nanofluids and magnetohydrodynamic (MHD) flows, the simultaneous investigation of melting heat transfer, thermal radiation, and ternary hybrid nanofluid (THNF) on inclined surfaces remains unexplored, presenting a significant gap in thermal management literature. This work addresses this gap by examining the combined effects of melting phenomena, MHD, and mixed convection in a THNF composed of copper (Cu), aluminum oxide ( Al 2 O 3 ), and titanium dioxide (TiO2) nanoparticles flowing over an inclined surface. Similarity transformations and numerical solution via the Keller box method are employed to solve the governing equations, incorporating mixed convection and thermal radiation effects. Key results demonstrate a substantial enhancement in the local Nusselt number of THNF by similar to 19% due to the melting phenomenon, accompanied by a 6% increase in the skin friction coefficient. The skin friction coefficient increases on the stretching sheet but decreases on the shrinking sheet. Furthermore, the melting parameter leads to a significant decrease in temperature profiles (around 18%), whereas the inclination parameter causes a minor increase (similar to 3%) for both stretching and shrinking scenarios. Notably, the analysis confirms that THNF demonstrates superior thermal performance compared to conventional hybrid and single-component nanofluids. These results provide actionable insights for designing nanoengineered thermal management systems applicable to solar thermal collectors, battery cooling systems, and advanced heat exchangers, directly supporting the development of efficient and sustainable energy technologies.
A novel switch-based Active-Neutral-Clamped (ANPC) inverter for low DC-link voltage is presented in this paper. The proposed ANPC topology minimizes switches and achieves 1.5 times better voltage gain than standard inverters. The main objective of this design is to reduce active switches in the inverter to increase system efficiency. A Flying Capacitor (FC) with self-voltage balancing makes this inverter unique. This flying capacitor enables the inverter to produce a 7-L output voltage. This study comprehensively analyses how it performs compared to existing technologies. The theoretical aspects of this proposed design have experienced thorough validation through a combination of experimental and simulation results, ensuring its efficacy and practical feasibility. The benchmark comparison further indicates reduced standing voltage requirement (TSV & times; Vin = 6.5) and a rated efficiency of 97.5%, supporting improved cost, control simplicity, and loss performance. Simulation and experimental results demonstrate the feasibility and effectiveness of the topology in terms of voltage balance, load adaptability, and modulation index adjustment. Simulation tests reveal stable voltage levels and current waveforms under different load conditions, with the peak output voltage reaching 1.5 times the initial input voltage. Experiments on a laboratory prototype validate the topology's dynamic response and self-balancing capability, showcasing its practical viability. The proposed 7L-ANPC topology offers a promising solution for enhancing power conversion efficiency and reliability in diverse applications.
This paper investigates the alpha-decay chain reaction of Uranium-238 (& Nscr;(U238)) into Thorium-234 (& Nscr;(Th234)) and Radium-226 (& Nscr;Ra226) through a combination of computational simulations and theoretical analysis. The study focuses on the role of varying Uranium-238 and decay constants on the final quantity. Results indicate that higher initial Uranium-238 quantities yield increased final quantities of both Thorium-234 and Radium-226, with decay constants significantly influencing the system's behavior. A fixed-point technique is employed to ensure the existence of solutions, confirming the system's stability and convergence to steady-state solutions. Additionally, the potential of artificial intelligence (AI) techniques is discussed, highlighting their utility in optimizing decay models and improving computational efficiency. The integration of AI offers deeper insights into parameter optimization and outcome prediction for complex decay systems. These findings contribute to the understanding of radioactive decay dynamics and provide a framework for more advanced computational models in nuclear science, as a process innovation.
Analysis of the water quality in rivers is important for people from all walks of life. The level of contamination is affecting human lives, animals, plants and ecosystem. In this paper, we consider the contamination transportation in rivers and sedimentation by the help of mathematical modeling, qualitative theoretical analysis, simulations and artificial intelligence. The model is composed of four classes of variables. The first variable is & Cscr;(x,t), representing contamination concentration in the water, the second one & Sscr;(x,t) is sediment concentration, The third variable & Uscr;(x,t) is velocity of the fluid and the fourth one lambda(x,t) is the decay rate. The model is considered in the Fractal-Fractional (FF) sense of derivative of FF-orders & rhov;(1),& rhov;(2) is an element of (0, 1] and investigated for the mathematical results including the existence of solution, uniqueness of solution, stability of Hyers-Ulam types, numerical simmulations, and finally, AI is applied for the analysis of the accuracy of the results and error in the patterns of the computational data, as a process innovation.
