8,886 research outputs found
GA-Fuzzy PID control simulation waveform diagram.
No full textAs is well known, the metal annealing process has the characteristics of heat concentration and rapid heating. Traditional vacuum annealing furnaces use PID control method, which has problems such as high temperature fluctuation, large overshoot, and long response time during the heating and heating process. Based on this situation, some domestic scholars have adopted fuzzy PID control algorithm in the temperature control of vacuum annealing furnaces. Due to the fact that fuzzy rules are formulated through a large amount of on-site temperature data and experience summary, there is a certain degree of subjectivity, which cannot ensure that each rule is optimal. In response to this drawback, the author combined the technical parameters of vacuum annealing furnace equipment, The fuzzy PID temperature control of the vacuum annealing furnace is optimized using genetic algorithm. Through simulation and comparative analysis, it is concluded that the design of the fuzzy PID vacuum annealing furnace temperature control system based on GA optimization is superior to fuzzy PID and traditional PID control in terms of temperature accuracy, rise time, and overshoot control. Finally, it was verified through offline experiments that the fuzzy PID temperature control system based on GA optimization meets the annealing temperature requirements of metal workpieces and can be applied to the temperature control system of vacuum annealing furnaces.</div
Electric Grid Resilience Enhancement During Natural Disasters: An Optimization-Based UAV Inspection and Dynamic Crew Dispatch Model
No full textA Master of Science thesis in Electrical Engineering by Yousef Serag entitled, “Electric Grid Resilience Enhancement During Natural Disasters: An Optimization-Based UAV Inspection and Dynamic Crew Dispatch Model”, submitted in April 2025. Thesis advisor is Dr. Mostafa Shaaban and thesis co-advisor is Dr. Mahmoud Ibrahim. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Natural disasters pose significant challenges to power grid resilience, often resulting in prolonged outages and substantial economic losses due to inefficient restoration processes. Traditional methods primarily focus on optimizing repair crew (RC) sequences while neglecting the critical inspection phase, leading to delayed fault detection and increased costs of interruption . This thesis introduces a holistic, UAV-assisted framework that integrates unmanned aerial vehicle (UAV) inspections, dynamic RC dispatch, and strategic charger placement to address these shortcomings. The approach leverages probabilistic failure analysis to prioritize high-risk lines, optimizes UAV inspection sequences with battery-aware path planning, and dynamically coordinates repair efforts to minimize COI.
The framework’s efficacy is evaluated using three distinct methods: Optimization based Approach, (GA), and Deep Learning (DL). OPTIMIZATION BASED APPROACH provides high accuracy in simplified scenarios but lacks scalability for real-time applications. GA offers a balanced trade-off between accuracy and computational efficiency, while DL delivers rapid, scalable solutions with acceptable accuracy, making it ideal for urgent disaster response. Tested on a 33-bus system, the framework achieves a 56.34% reduction in COI compared to conventional strategies, demonstrating its superiority in reducing downtime and enhancing resilience. The novelty of this work lies in its comprehensive integration of inspection and repair processes, utilizing advanced technologies for real-time adaptability. By addressing the overlooked inspection phase and optimizing resource allocation, this thesis presents a scalable, data-driven solution that significantly advances post-disaster grid restoration, offering a practical approach to mitigate the socio-economic impacts of power outages in large-scale disaster scenarios.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Increasing science, technology, engineering, and mathematics skills using Project Lead the Way
No full textIncludes bibliographical references
Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
No full textA Master of Science thesis in Electrical Engineering by Mohammad Tarek Khayata entitled, "Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids," submitted in April 2017. Thesis advisor is Dr. Mostafa Shaaban. Soft and hard copy available.This work proposes a new method for renewable distributed generation (DG) allocation in smart grid. The main objective is to minimize the overall investment which includes the capital cost of DG units, the operation and maintenance costs of DG units, and the cost of purchasing energy from the grid. The proposed approach takes into consideration the uncertainty and variability associated with generation, demand, and energy cost in addition to the communication infrastructure which is the main contribution of this work. The communication infrastructure under the smart grid paradigm will allow real-time control of the system assets. Therefore, considering this property during the planning phase enhances the system performance and optimizes the overall investment. The proposed approach relies on developing probabilistic models for each generation technology, energy prices, and demand. Then, these models are combined into one multi-state gen-load-price probabilistic model that describes all possible conditions of the system. The number of states in the final model is a tradeoff between the accuracy of results and computational time. Genetic algorithm (GA) optimization technique is utilized in this study to solve the DG planning problem. Simulation results on a typical distribution system are provided to prove the effectiveness of the proposed approach in increasing the renewable DG penetration in smart grids while maximizing the profit of the investment. Moreover, the results obtained through the use of the proposed smart operation are compared with the conventional planning methodologies to demonstrate the targeted added value. A significant cost saving of 28.3% and 254% higher percentage of DG penetration are achieved with the proposed DGs curtailment technique to mitigate technical system violations, which proves the significant advantage of adopting smart grid operation in planning problems.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
High-loading Ga-exchanged MFI zeolites as selective and coke-resistant catalysts for nonoxidative ethane dehydrogenation
No full textIn this paper, we investigated the effects of the Ga loading amount and H-2 treatment temperature for the reductive solid-state ion-exchange reaction on the generated Ga species in Ga-exchanged MFI zeolites (Ga-MFIs) as well as their catalysis for ethane dehydrogenation (EDH). For the formation of isolated Ga hydrides in the zeolites, [GaH](2+) ions were preferentially formed in the low-loading Ga-MFI (Ga/Al = 0.3) treated with H-2 at 550 degrees C, corresponding to the conventional preparation conditions, (Ga-MFI-0.3(550)), while the high Ga loading (Ga/Al = 1.0) and high-temperature H-2 treatment (800 degrees C) (Ga-MFI-1.0(800)) induced the formation of [GaH2](+) ions as the major Ga hydrides, as revealed by in situ Fourier transform infrared spectroscopy including the isotope experiment using D-2. In the context of other Ga species, such as Ga+ cations and partially reduced Ga oxides (GaOX), Ga+ cations and GaOX coexist in Ga-MFI-0.3(550), as indicated by pyridine adsorption experiments. On the other hand, GaOX was hardly observed and a larger amount of Ga+ cations was formed in Ga-MFI-1.0(800). The remaining Bronsted acid sites (BASs) were also characterized by the NH3 adsorption experiment. In the EDH reaction, Ga-MFI-1.0(800) exhibited high selectivity owing to low coke formation, resulting in the highest durability among the series of Ga-MFIs tested. Under the optimized conditions, Ga-MFI-1.0(800) exhibited the highest C2H4 formation rate among previously reported Pt-free catalysts. Based on the combined results of characterization, catalyst tests, and kinetic studies, the high selectivity and durability of Ga-MFI-1.0(800) can be ascribed to the low amount of the remaining BASs by isolated Ga species ([GaH](2+), [GaH2](+) ions and Ga+ cations) as well as the major formation of [GaH2](+) ions among isolated Ga hydrides
Element Distribution in Porous Ga Oxide Obtained by Anodizing Ga in Phosphoric Acid
No full textA STEM/EDS study of a porous Ga oxide film formed by an anodization process was conducted in this study to examine the crystalline structure of the film and the elemental distribution in the oxide film before and after heat treatment. The as-formed anodic film with a morphology resembling the well-known porous anodic Al oxide film was amorphous, crystallizing after heat treatment at 600 degrees C without changing the morphology and elemental distribution. The EDS elemental maps disclosed the duplex nature of the pore wall oxide; the phosphate anion was contaminated in the outer oxide layer next to the pores, and the inner layer consisted of relatively pure Ga oxide, practically free from phosphate. The similarity of morphology and elemental distributions between the porous anodic Al and Ga oxides suggests that the growth of both anodic oxide films proceeds under the same mechanism. In addition, crystallized porous Ga oxides are expected to be applied to fabricate various functional devices requiring geometrically controlled semiconductor nanohole arrays, such as devices for hydrogen formation. (c) 2023 The Electrochemical Society ("ECS"). Published on behalf of ECS by IOP Publishing Limited
Effect of thermal treatments in Ni-Fe-Ga with Co substitutions and Ni-Mn-Ga melt spun ribbons
No full textAbstractThe effect of “in situ” thermal treatments (by DSC measurements) on the martensitic transformation in two representative Ni-Fe-Ga and Ni-Mn-Ga alloys has been studied and discussed by correlating the structural and magnetic properties. The alloys were prepared from high purity elements, by arc melting under argon protective atmosphere as bulk and also as melt-spun ribbons - an alternative preparation route that also allows to assess the influences of grains size and strain induced by this processing method. All samples presented reversible thermo-elastic transformations. The thermal treatments promote a reduction of the martensitic transformation temperatures in the Ni-Fe-Ga investigated samples, as opposed to the stoichiometric Ni2MnGa where the temperatures increase with increasing the annealing temperatures. Interestingly however, the off-stoichiometric Ni-Mn-Ga with increased Ni content recovers the behaviour with reduction of transformation temperatures by thermal treatments. The precipitation of the secondary FCC (γ) phase is inherently found in Ni-Fe-Ga alloys with Ga ≤ 27% at, and also -although in lower amounts- in the off-stoichiometric Ni-Mn-Ga. The γ phase is considered to contribute to the decrease of the MT temperatures (via valence electrons concentration depletion of the main matrix) and of the transformation heat as well as to the final structural degradation if the temperature of the thermal treatments is further increased. In addition, this phase, located mainly at the grain boundaries, is responsible for the improved ductility of Ni-Fe-Ga based alloys. Changes in the transformation heat due to thermal treatments are observed and discussed in both types of alloys, the maxima of the transformation heat being associated with the highest atomic order. Thermo-magnetic measurements show that Ni-Fe-Ga alloys have close magnetic and structural transitions temperatures, with promising applications for magnetic refrigeration
A Comprehensive Framework for Optimizing and Integrating Electric Bus Service with Smart Grids for Sustainable Public Transportation
No full textA Master of Science thesis in Electrical Engineering by Aisha Abdalla AlAli entitled, “A Comprehensive Framework for Optimizing and Integrating Electric Bus Service with Smart Grids for Sustainable Public Transportationl”, submitted in May 2025. Thesis advisor is Dr. Mostafa Shaaban and thesis co-advisor is Dr. Abdelfatah Mohamed. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The electrification of public transportation plays a pivotal role in the global transition toward cleaner energy and carbon neutrality, aligning with the Net Zero 2050 strategy. However, large-scale deployment of electric bus (EB) fleets introduces complex challenges in infrastructure and resource planning. This research supports the roadmap for public transit electrification by presenting a comprehensive optimization framework for EB operations and associated infrastructure. It focuses on the strategic deployment of EB fleets, the implementation of advanced charging technologies, and the optimization of service assignments and charging schedules. Furthermore, the research integrates electric bus chargers into smart grid, addressing the optimal allocation of distributed generation (DG) units and assessing the need for line upgrades. This work combines genetic algorithms (GA) for resource optimization with mathematical optimization techniques for scheduling (e.g., GAMS). This hybrid framework leverages the strengths of GA in solving large, nonlinear problems and the reliability of mathematical optimization in enforcing system constraints, ensuring applicability to real-world, large-scale systems. The proposed approach has been studied with different types of EB charging technologies and is evaluated under various scenarios, considering variations in operational strategy and energy demand. An electric 38‐bus network and a representative multi-route bus service are used to simulate and validate the framework. Results showed that the Genetic Algorithm reliably produced cost-efficient solutions by effectively positioning distributed generation units, selectively upgrading the transmission lines, and optimizing the charger types for multi-routes. The results demonstrate the effectiveness of the framework in minimizing costs while successfully meeting the operational requirements of the bus service and the technical limitations of the electric grid, contributing to the development of efficient and resilient electric transit systems.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Using group interaction history in the wild
No full textInspired by theories of how professionals enter into a reflective conversation with their work materials, the research area of interaction history seeks to make use of the accumulated actions of many people in working with digital objects. Despite compelling system designs and empirical results in laboratory settings, group interaction histories have not been widely employed. I outline a series of research questions, plans and tools that will be among the first to investigate and evaluate the use of shared interaction history in the day-to-day work of individuals and groups
Improved tunneling magnetoresistance in (Ga,Mn)As/AlO(x)/CoFeB magnetic tunnel junctions
No full textWe fabricated (Ga,Mn)As/AlO(x)/Co(40)Fe(40)B(20) magnetic tunnel junctions with ferromagnetic semiconductor/insulator/ferromagnetic metal (S/I/F) structure. The treatments of pre-annealing and post-plasma cleaning on the (Ga,Mn) As film were introduced before the growth of the subsequent layers. A high tunneling magnetoresistance (TMR) ratio of 101% is achieved at 2 K, and the spin polarization of (Ga,Mn) As, P = 56.8%, is deduced from Julliere's formula. The improved TMR ratio is primarily due to the improved magnetism of (Ga,Mn) As layer by low-temperature annealing and cleaned interface between (Ga,Mn) As and AlO(x) attained by subsequent plasma cleaning process. (C) 2011 American Institute of Physics. [doi:10.1063/1.3603946
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