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Recent Submissions

Multi-objective RIME algorithm-based techno economic analysis for security constraints load dispatch and power flow including uncertainties model of hybrid power systems
(Elsevier, 2024) Pandya, Sundaram B.; Kalita, Kanak; Jangir, Pradeep; Čep, Robert; Migdady, Hazem; Chohan, Jasgurpreet Singh; Abualigah, Laith; Mallik, Saurav
In recent times, the landscape of power systems has undergone significant evolution, particularly with the integration of diverse renewable energy sources (RESs). This advancement presents an invaluable opportunity to enhance energy efficiency in the modern power grid, primarily by bolstering the role of stochastic RESs. The challenge lies in the optimal power flow (OPF), a multifaceted and non-linear optimization challenge that grows more complex with the inclusion of stochastic RESs that aims to optimize the allocation of power system resources to minimize the operational cost while maintaining the stability and security of the system. Addressing this, the current study introduces an innovative optimization approach, the Multi-Objective RIME (MORIME) algorithm. Drawing inspiration from the physical phenomenon of rime-ice, called the RIME, the MORIME seeks to effectively tackle OPF issues. This algorithm enhances solution accuracy by smartly dividing with nondominated sorting and crowding distance mechanism. The proposed OPF model incorporates three types of RESs: solar photovoltaic, wind and small-scale hydropower units. While uncertainties in wind speed and solar irradiation are managed through Monte Carlo simulations, the small hydro unit is considered a constant power source. The efficacy of the MORIME algorithm is tested on IEEE 30 bus systems and results indicate that the MORIME method identifies the optimal solution for the multi-objective OPF problem while satisfying the power system constraints, thereby proving its effectiveness and superiority over MOWOA, MOGWO, MOALO, MOMRFO and MOAGDE in terms of Hyper Volume (HV) and reciprocal of Pareto Sets Proximity (1/PSP) metrices. The MORIME source code is available at: https://github.com/kanak02/MORIME
Calculating torque, back-EMF, inductance, and unbalanced magnetic force for a hybrid electrical vehicle by in-wheel drive application
(Springer Nature, 2024) Hosseinpour, Alireza; Rahideh, Akbar; Abbas, Ahmed; Iqbal, Atif; El-Bayeh, Claude Ziad; Flah, Aymen; Ali, Enas; Ghaly, Ramy N. R.
To use a Hybrid Excitation Synchronous Machine (HESM) in a hybrid electrical vehicle (HEV), its performance indicators such as back-EMF, inductance and unbalanced magnetic force should be computed preferably by an analytical method. First, the back-EMF is calculated by considering alternate-teeth and all-teeth non-overlapping and overlapping windings. The effects of three types of magnetization patterns including the radial, parallel and Halbach magnetizations on the back-EMF waveform have also been investigated. Then, the self-inductance of the stator and rotor windings, the mutual inductance between the stator and rotor windings, and the mutual inductance between the stator phases are computed. Next, the components of the unbalanced magnetic force (UMF) in the direction of the x and y axes and its amplitude are computed. Moreover, the effects of the magnetization patterns on those magnetic pulls are investigated. To minimize the UMFs, symmetry must be implemented in the excitation sources; therefore, first the stator winding then the permanent magnet and rotor winding are modified in such a way that the UMFs are reduced. Increasing the temperature leads to a weakening of the magnet's residual flux density, which strongly affects the performance characteristics of the electric machine such as Back-EMF and UMF. Finally, the ratio of the permanent magnet flux to the rotor flux is determined in such a way that the average torque is maximized. In this section, the effects of three magnetization patterns will be investigated.
Advanced materials for micro/nanorobotics
(Royal Society of Chemistry, 2024) Kim, Jeonghyo; Mayorga-Burrezo, Paula; Song, Su-Jin; Mayorga-Martinez, Carmen C.; Medina-Sánchez, Mariana; Pané, Salvador; Pumera, Martin
Autonomous micro/nanorobots capable of performing programmed missions are at the forefront of next-generation micromachinery. These small robotic systems are predominantly constructed using functional components sourced from micro- and nanoscale materials; therefore, combining them with various advanced materials represents a pivotal direction toward achieving a higher level of intelligence and multifunctionality. This review provides a comprehensive overview of advanced materials for innovative micro/nanorobotics, focusing on the five families of materials that have witnessed the most rapid advancements over the last decade: two-dimensional materials, metal-organic frameworks, semiconductors, polymers, and biological cells. Their unique physicochemical, mechanical, optical, and biological properties have been integrated into micro/nanorobots to achieve greater maneuverability, programmability, intelligence, and multifunctionality in collective behaviors. The design and fabrication methods for hybrid robotic systems are discussed based on the material categories. In addition, their promising potential for powering motion and/or (multi-)functionality is described and the fundamental principles underlying them are explained. Finally, their extensive use in a variety of applications, including environmental remediation, (bio)sensing, therapeutics, etc., and remaining challenges and perspectives for future research are discussed.
Optimal structure to maximize torque per volume for the consequent-pole PMSM and investigating the temperature effect
(IEEE, 2024) Hosseinpour, Alireza; Abbas, Ahmed; Sadegh, Mahmoud Oukati; Iqbal, Atif; Flah, Aymen; Prokop, Lukáš; Ali, Enas; Ghaly, Ramy N. R.
Heat removal, maximizing torque, minimizing losses, volume, cost, and temperature effect play essential roles in electrical vehicle applications. An inner-rotor consequent-pole permanent magnet synchronous machine (CPPMSM) merits suitable losses, cost, and heat rejection. Hence, first, a two-dimensional model of CPPMSM is explained based on solving Maxwell's equations in all regions of the machine. Then, all the components of torque, back-EMF, inductance, and unbalanced magnetic forces in the direction of the X-axis and Y-axis and their magnitudes are calculated. Afterward, the overload capability and the torque-speed characteristic are determined based on the average torque. Therefore, to maximize the torque/volume ratio, four metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), and Teaching Learn Base Optimization (TLBO), have been implemented, and the mentioned index is optimized. Since the said algorithms usually can minimize, its inverse is minimized instead of the index mentioned above being maximized. At this stage, the effect of three types of magnetization patterns, i.e., radial, parallel, and bar magnet in shifting, is also considered. The flux density of the permanent magnet changes concerning temperature. Finally, the effect of these changes on cogging, reluctance, and instantaneous torque, as well as back-EMF, unbalance magnetic force (UMF), torque-speed characteristic, and overload capability diagram, will be analyzed. The simulation was performed using MATLAB software.
Measuring the energy for the molecular graphs of antiviral agents: Hydroxychloroquine, Chloroquine and Remdesivir
(Elsevier, 2024) Aftab, Muhammad Haroon; Akgül, Ali; Riaz, Muhammad Bilal; Hussain, Muhammad; Jebreen, Kamel; Kanj, Hassan, Hassan
We consider the energy for the molecular graphs of antiviral agents like Hydroxychloroquine, Remdesivir and Chloroquine. These drugs play a vital role in the treatment of COVID-19. Let Gamma(1), Gamma(2) and Gamma(3) be the n-dimensional graphs of the molecular structures of antiviral agents Hydroxychloroquine, Chloroquine and Remdesivir, respectively. We define their energies as E '(Gamma(1)) = Sigma vertical bar lambda(i)'vertical bar, E '(Gamma 2) = Sigma vertical bar lambda(j)'vertical bar and E '(Gamma 3) = Sigma vertical bar lambda(k)'vertical bar, respectively. Where the sets {lambda(1)'(Gamma(1)), lambda(2)'(Gamma(1)), lambda(3)'(Gamma(1)), ..., lambda(n)'(Gamma(1))}, {lambda(1)'(Gamma(2)), lambda(2)'(Gamma(2)), lambda(3)'(Gamma(2)), ..., lambda(n)'(Gamma(2))} and { lambda(1)'(Gamma 3), lambda(2)'(Gamma 3), lambda(3)'(Gamma 3), ..., lambda(n)'(Gamma 3)} depict the eigenvalues for the adjacency matrices of Gamma 1, Gamma 2 and Gamma 3, respectively. We have developed some basic ideas and properties in order to measure the energies for the antiviral agents Hydroxychloroquine, Chloroquine and Remdesivir.