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Articles 1 - 14 of 14
Full-Text Articles in Engineering
A Techno-Economic Perspective On Efficient Hybrid Renewable Energy Solutions In Douala, Cameroon’S Grid-Connected Systems, Reagan Jean Jacques Molu, Serge Raoul Dzonde Naoussi, Mohit Bajaj, Patrice Wira, Wulfran Fendzi Mbasso, Barun K. Das, Milkias Berhanu Tuka, Arvind R. Singh
A Techno-Economic Perspective On Efficient Hybrid Renewable Energy Solutions In Douala, Cameroon’S Grid-Connected Systems, Reagan Jean Jacques Molu, Serge Raoul Dzonde Naoussi, Mohit Bajaj, Patrice Wira, Wulfran Fendzi Mbasso, Barun K. Das, Milkias Berhanu Tuka, Arvind R. Singh
Research outputs 2022 to 2026
Cameroon is currently grappling with a significant energy crisis, which is adversely affecting its economy due to cost, reliability, and availability constraints within the power infrastructure. While electrochemical storage presents a potential remedy, its implementation faces hurdles like high costs and technical limitations. Conversely, generator-based systems, although a viable alternative, bring their own set of issues such as noise pollution and demanding maintenance requirements. This paper meticulously assesses a novel hybrid energy system specifically engineered to meet the diverse energy needs of Douala, Cameroon. By employing advanced simulation techniques, especially the Hybrid Optimization Model for Electric Renewable (HOMER) Pro program, …
Reconfigurable, Reliable And Online Learning Enabled Memristive Neuromorphic Core Design For Brain-Inspired Computing, Nishith Nirjhar Chakraborty
Reconfigurable, Reliable And Online Learning Enabled Memristive Neuromorphic Core Design For Brain-Inspired Computing, Nishith Nirjhar Chakraborty
Doctoral Dissertations
For several years, the von Neumann architecture has served as the foundation of contemporary computers due to its straightforward, cost-effective architecture for processing units and memory. However, this design encounters a significant impediment in meeting the growing demand for increased parallelism in complex computations. Additionally, the post-Moore's law era emphasizes the need for energy-efficient computing with fewer resources and reduced space. As a response to these challenges, researchers are actively seeking alternatives to the von Neumann architecture, with neuromorphic computing emerging as a promising candidate. Neuromorphic computing garnered attention initially for its ability to harness the parallelism inherent in bio-inspired …
Graph-Based Modeling And Optimization Of Wpt Systems For Evs, Matthew J. Hansen, Greg Droge, Abhilash Kamineni
Graph-Based Modeling And Optimization Of Wpt Systems For Evs, Matthew J. Hansen, Greg Droge, Abhilash Kamineni
Electrical and Computer Engineering Student Research
A model of a system of wireless power transfer (WPT) pads is developed, where each WPT pad is modeled as a node and the coupling between pads is modeled as graph edges. This modeling approach is generalized to admit primary, secondary, and booster coils, where power can flow among the pads and a pad can fill multiple roles. An excitation in one pad induces voltage and current in all neighboring pads, causing each pad to act as both a booster coil and either a transmitter or a receiver. Power flow through the entire system can be modeled with the graph …
Discrete Time State-Space Modeling Framework For Switched-Mode Power Supplies, Jared Baxter
Discrete Time State-Space Modeling Framework For Switched-Mode Power Supplies, Jared Baxter
Doctoral Dissertations
Electrical power consumption has become ever prominent in modern society. Switch mode power supplies, now more than ever, have become a foundation for residential, commercial, and industrial electrical needs. These demands require numerous advanced power converters, and modeling plays a vital role in the design of these converters. Commonly, modeling is completed using either dedicated hand analysis, which must be completed individually for each topology, or time-stepping circuit simulations, which are insufficiently rapid for broad analysis considering a wide range of potential designs or operating points. Discrete time state-space modeling of switching converters has shown merits in rapid analysis and …
Techniques To Overcome Energy Storage Limitations In Electric Vehicles, Matthew J. Hansen
Techniques To Overcome Energy Storage Limitations In Electric Vehicles, Matthew J. Hansen
All Graduate Theses and Dissertations, Fall 2023 to Present
Electric vehicles are becoming increasingly popular, battery limitations (cost, size, and weight) complicate electric vehicle adoption. While important research on battery development is ongoing, this dissertation discusses two main approaches to overcome those limitations within the existing battery technology paradigm. Those thrusts are: improving battery health through an optimal charging strategy and minimizing necessary battery size through dynamic wireless power transfer. In this dissertation, relevant literature is discussed, with opportunities for further development considered. Within the two thrusts, three objectives sharpen the focus of the research presented here. First, a planning tool is defined for a battery electric bus fleet. …
Joint Energy And Security Optimization In Underwater Wireless Communication Networks, Kazi Y. Islam, Iftekhar Ahmad, Yue Rong, Daryoush Habibi
Joint Energy And Security Optimization In Underwater Wireless Communication Networks, Kazi Y. Islam, Iftekhar Ahmad, Yue Rong, Daryoush Habibi
Research outputs 2022 to 2026
Underwater wireless communication networks (UWCNs) can support a wide range of applications in the underwater domain, including mining and drilling, coastline monitoring, border surveillance, and submarine/mine detection. Some of these applications are sensitive in nature (e.g., military) and demand stringent security requirements for data communications. In order to prevent malicious attacks (e.g., jamming) in these UWCNs, robust security countermeasures must be implemented. Additionally, sensitive data communications must be protected. However, computationally expensive security protocols, such as encryption, can severely shorten UWCN lifetime, where battery-powered nodes already suffer from scarce energy supplies. In this work, we exploit content caching as a …
Optimization Of Human Interactions In The College Campus Model Via Simio Integration, Benjamin E. Chaback
Optimization Of Human Interactions In The College Campus Model Via Simio Integration, Benjamin E. Chaback
Doctoral Dissertations and Master's Theses
College campuses are a significant part of life in some cities. Many students each year attend university, pursuing additional knowledge from faculty members. Both staff and faculty members rely on these students to have successful jobs and to ensure the university functions. Yet recently, more and more students are attending, leading to overcrowding, lower admission rates, and difficulty getting into good programs. Previous work exists on qualitative student affairs and quantitative retention data, yet little on using simulations to model this problem. This work aimed to (a) Determine the ability to successfully model human interactions/people flow on a college campus, …
Synthesize A Neural Network Parameter Optimizer For An Adaptive Pid Controller, Nashvandova Gulruxsor Murot Qizi
Synthesize A Neural Network Parameter Optimizer For An Adaptive Pid Controller, Nashvandova Gulruxsor Murot Qizi
Chemical Technology, Control and Management
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters superstructuring. In the paper, the questions of optimization of PID-regulator parameters with application of methods of neural network technology are considered. A methodology for selecting the architecture of neural network optimizer designed to determine the tuned parameters of PID regulator is proposed. The algorithm of training of the neural network, with the set on the basis of the method of inverse gradient propagation is offered. The proposed improved PID-neural regulator allowed to provide stabilization of neural network operation and its trainability in the control loop …
Strategy For Predictive Control Of The Rectification Process Based On A Model Controller With A Given Forecast, Ildar Rafkatovich Sultanov
Strategy For Predictive Control Of The Rectification Process Based On A Model Controller With A Given Forecast, Ildar Rafkatovich Sultanov
Chemical Technology, Control and Management
A method is being developed to optimize the generated controls for the multicomponent distillation process with prediction, based on predictive data with a moving horizon. The difference between this method and the classical modeling approach, in which the percentage of the degree of opening of valves installed on the output streams of the column is used as control actions, is that control occurs on the feedback principle. The proposed method is based on the use of a dynamic process model to optimize control actions in real time in order to achieve certain production targets. The essence of the MPC approach …
Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk
Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk
Turkish Journal of Electrical Engineering and Computer Sciences
Mixed-integer linear programming (MILP) techniques are widely used in cryptanalysis, aiding in the discovery of optimal linear and differential characteristics. This paper delves into the analysis of block ciphers KLEIN and PRINCE using MILP, specifically calculating the best linear and differential characteristics for reduced-round versions. Both ciphers employ matrix multiplication in their diffusion layers, which we model using multiple XOR operations. To this end, we propose two novel MILP models for multiple XOR operations, which use fewer variables and constraints, proving to be more efficient than standard methods for XOR modeling. For differential cryptanalysis, we identify characteristics with a probability …
Complete Solution Of The Lady In The Lake Scenario, Alexander Von Moll, Meir Pachter
Complete Solution Of The Lady In The Lake Scenario, Alexander Von Moll, Meir Pachter
Faculty Publications
In the Lady in the Lake scenario, a mobile agent, L, is pitted against an agent, M, who is constrained to move along the perimeter of a circle. L is assumed to begin inside the circle and wishes to escape to the perimeter with some finite angular separation from M at the perimeter. This scenario has, in the past, been formulated as a zero-sum differential game wherein L seeks to maximize terminal separation and M seeks to minimize it. Its solution is well-known. However, there is a large portion of the state space for which the canonical solution does not …
A Charging Strategy For Large Commercial Electric Vehicle Fleets, Bassam Al-Hanahi, Iftekhar Ahmad, Daryoush Habibi, Pravakar Pradhan, Mohammad A. S. Masoum
A Charging Strategy For Large Commercial Electric Vehicle Fleets, Bassam Al-Hanahi, Iftekhar Ahmad, Daryoush Habibi, Pravakar Pradhan, Mohammad A. S. Masoum
Research outputs 2022 to 2026
The popularity of Commercial Electric Vehicles (CEVs) has experienced a surge in recent years, particularly in urban vocational contexts, as a means of advancing towards the goal of attaining net-zero emissions by 2050. The return-to-base charging strategy, which involves charging CEVs at depots, has become a prevalent practice for smaller CEV fleets. Nevertheless, for larger CEV fleets, the limited charging capacity at depots presents a significant challenge, leading to a reliance on both limited depot charging infrastructure and public charging infrastructure. This reliance can have a substantial impact on both the operational costs and the sustainability of logistics services. To …
Exploring Machine Learning Techniques For Embedded Hardware, Neel R. Vora
Exploring Machine Learning Techniques For Embedded Hardware, Neel R. Vora
Computer Science and Engineering Theses
This thesis delves into the intricate symbiosis between machine learning (ML) methodologies and embedded hardware systems, with a primary focus on augmenting efficiency and real-time processing capabilities across diverse application domains. It confronts the formidable challenge of deploying sophisticated ML algorithms on resource-constrained embedded hardware, aiming not only to optimize performance but also to minimize energy consumption. Innovative strategies are explored to tailor ML models for streamlined execution on embedded platforms, with validation conducted across various real-world application domains. Notable contributions include the development of a deep-learning framework leveraging a variational autoencoder (VAE) for compressing physiological signals from wearables while …
A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li
A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li
Electrical and Computer Engineering Faculty Research & Creative Works
This article proposes a new physics-assisted genetic algorithm (PAGA) for decoupling capacitor (decap) optimization in power distribution networks (PDNs), which is a highly efficient approach to minimizing the number of decaps within an enormous search space. In the proposed PAGA method, the priority of the decap ports is first determined based on their physical loop inductances. Then, an initial solution is quickly obtained by placing decaps sequentially on the port with the highest priority. Subsequently, a GA with prior physical knowledge is developed to find better decap solutions progressively. A port removal scheme that eliminates the low-priority ports and a …