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Articles 8281 - 8310 of 9234
Full-Text Articles in Engineering
Applying X-Ray Fluorescence With Monte Carlo Methods For Analysis Of Surface Defects On Coated Zr4, James Tyler Cahill
Applying X-Ray Fluorescence With Monte Carlo Methods For Analysis Of Surface Defects On Coated Zr4, James Tyler Cahill
Theses and Dissertations
Chromium-coated Zircaloy-4 cladding represents a novel solution for creating nuclear cladding that has passive safety features. This and related developments aimed at improving nuclear safety are broadly categorized as accident-tolerant fuel and cladding. However, implementing this material presents practical challenges such as the vulnerability that cladding has to surface damage such as fretting wear. This research aims to determine if the pre-existing technique of X-ray fluorescence analysis is applicable for detecting these defects on the surface of the cladding. This was done by developing Monte Carlo N-Particle Transport models of a handheld device, the XL-5, alongside experimental measurements using this …
Assessment Of Surface Waviness In A Wire Arc Additive Manufacturing Process, Shammas Mahmood Shafi
Assessment Of Surface Waviness In A Wire Arc Additive Manufacturing Process, Shammas Mahmood Shafi
Dissertations, Master's Theses and Master's Reports
Wire Arc Additive Manufacturing (WAAM) is increasingly recognized for its ability to produce metal components with high deposition rates and efficiency, particularly in the aerospace and automotive sectors. However, one significant challenge that WAAM faces is achieving surface quality that complies with industry standards, as well as creating geometries that closely resemble the initial design. A crucial factor contributing to this challenge is surface waviness, which is an inherent characteristic of the WAAM process. This waviness arises from the geometry of the weld beads and the overlap distance between them. It can adversely affect the fusion quality of successive layers, …
Interplay Of Discharge Rates, Slope, And Sediment Size In River Meandering Dynamics: Insights From Experimental Studies, Yifan Zhang
Dissertations, Master's Theses and Master's Reports
Sinuosity is an important concept in various fields including hydrology, geomorphology, and ecology. It not only presents the degree of curviness of a river channel but also reflects the ecological sustaining ability. By studying the sinuosity of a stream or river channel, important implications could also be found including the transportation and deposition of the sediments, the habitats of the riverbanks, and the types of species that are able to live on the watershed and river. To study the factors that could heavily affect the sinuosity of a river channel, a full set of laboratory experiments was designed to perform …
Nickel Superalloy Composition And Process Optimization For Weldability, Cost, And Strength, Sophie A. Mehl
Nickel Superalloy Composition And Process Optimization For Weldability, Cost, And Strength, Sophie A. Mehl
Dissertations, Master's Theses and Master's Reports
To advance sustainability efforts, electric power plants have reduced specific carbon dioxide emissions by increasing operating temperatures and pressures to improve power generation efficiency. The latest improvements are utilized in advanced ultra-supercritical power generation. To meet these operating conditions, nickel superalloys are used in the highest temperature components; however, they are expensive and present weldability challenges. This project aims to experimentally optimize a nickel superalloy to improve material weldability and decrease cost without compromising strength. Three optimized compositions were developed, and their microstructures and mechanical properties were compared to Nimonic 263, a common nickel superalloy in electric power plants. The …
Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa
Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa
Dissertations, Master's Theses and Master's Reports
Reactivity Controlled Compression Ignition (RCCI) engines operates has capacity to provide higher thermal efficiency, lower particular matter (PM), and lower oxides of nitrogen (NOx) emissions compared to conventional diesel combustion (CDC) operation. Achieving these benefits is difficult since real-time optimal control of RCCI engines is challenging during transient operation. To overcome these challenges, data-driven machine learning based control-oriented models are developed in this study. These models are developed based on Linear Parameter-Varying (LPV) modeling approach and input-output based Kernelized Canonical Correlation Analysis (KCCA) approach. The developed dynamic models are used to predict combustion timing (CA50), indicated mean effective pressure (IMEP), …
Anaerobic Reductive Bioleaching Of Manganese Ores, Neha Sharma
Anaerobic Reductive Bioleaching Of Manganese Ores, Neha Sharma
Dissertations, Master's Theses and Master's Reports
Manganese extraction by biological methods is a green and economical way to produce manganese from low as well as high grade manganese ores. This is especially important for US ores, which are primarily either small in extent, low-grade with a high iron content, or both. They are therefore not suitable for conventional mining, which is very capital-intensive and requires a large up-front investment and are therefore imported at high costs. The goal is therefore to develop a process that can be applied at small scales, with minimal startup costs, and low equipment and labor requirements. It is also critical to …
Initial Solution Improvements To A Tethered Robotic Path Planner Using Random Geometric Graph Configurations And Biased Sampling, Austen J. Goddu
Initial Solution Improvements To A Tethered Robotic Path Planner Using Random Geometric Graph Configurations And Biased Sampling, Austen J. Goddu
Dissertations, Master's Theses and Master's Reports
With NASA's ongoing efforts to establish a presence on the lunar surface to eventually move on to exploring mars, the development of intelligent robotic systems is more important than ever. The ability of robotics to explore hazardous and extreme terrain, coupled with long communication times from earth places an ever increasing need on more robust and efficient autonomy. Tethered robotics offer unique advantages to explore scientific targets both on the lunar and martian surfaces, capable of using their tether as a physical or metaphorical lifeline to allow the exploration of slopes, extreme dark regions, or areas in which wireless communication …
Exploring The Diffusion Potential Of A Collaborative Mobile Platform For Disaster Management And Relief, Joao De Mendonca Salim
Exploring The Diffusion Potential Of A Collaborative Mobile Platform For Disaster Management And Relief, Joao De Mendonca Salim
Honors Undergraduate Theses
This thesis describes the creation of a collaborative digital platform for disaster management and relief, focusing on the case study of the city of Petrópolis natural disaster in February 2022. The frequency and intensity of natural disasters are rising, necessitating efficient and timely disaster response efforts. This thesis details the development of a software application that fosters collaboration among governmental agencies, emergency services, non-governmental organizations (NGOs), and civil society to enhance logistical planning and situational awareness during disasters. The proposed platform harnesses the power of social networking and leverages the ubiquitous presence of smartphones equipped with cameras, GPS, and sensors …
Functional Verification Of Additively Manufactured Metallopolymer Structures For Structural Electronics Design, Nathan D. Singhal
Functional Verification Of Additively Manufactured Metallopolymer Structures For Structural Electronics Design, Nathan D. Singhal
Honors Undergraduate Theses
As an attempt to improve the overall cost-effectiveness and ease of structural electronics manufacturing, this study characterizes the mechanical and electrical responses of structures which are fabricated from a novel metallopolymer composite material by fused deposition modeling as they are subjected to quasi-static, uniaxial mechanical tension. Baseline values of tensile properties and electrical resistivity were first obtained via ASTM D638-22 standard testing procedures and linear sweep voltammetry (LSV), respectively. A hybrid procedure to measure in-situ mechanically dependent electrical behavior was subsequently developed and implemented. The mechanical and electromechanical testing was followed by the derivation of stochastic values for several mechanical …
Adaptation Of A Commercially Available Galvanic Skin Response Sensor To Measure Respiration Across The Chest For Heart Rate Variability Monitoring, Breno C. Dobal
Honors Undergraduate Theses
Heart rate variability (HRV) is a naturally occurring cardiovascular phenomenon referring to the changing timing between consecutive heartbeats. The connection between HRV and overall cardiovascular health and autonomic nervous system function has been well established through prior research and well documented in existing literature. The existing studies, however, included shorter HRV subject recording session, using traditional HRV monitoring methods that do not typically combine electrocardiogram (ECG), seismocardiogram (SCG) and galvanic skin response (GSR) respiration monitoring. The inclusion of longer HRV subject recording may allow for further insight on the possible effects of given observable biological phenomenon on HRV.
The current …
Analysis Of Variations In Flow-Independent Liquid Jet-In-Crossflow Injections, Michael Scott
Analysis Of Variations In Flow-Independent Liquid Jet-In-Crossflow Injections, Michael Scott
Honors Undergraduate Theses
Liquid fuel injection is a critical mechanism for the deliverance of liquid fuel in contemporary aircraft propulsion combustion systems due to its outsized influence in providing optimal combustion conditions and improving overall aircraft efficiency and performance. Despite this, these liquid jet in crossflow (LJIC) systems are highly variable due to conditions in the jet and the surrounding airflow, leading to variability in performance behavior and inconsistency in fuel mixing and combustion efficiency. This has prompted the introduction of solid pintile obstructions of novel designs to provide a more flow-independent fuel injection scheme and decrease variability of the jet properties against …
Reinforcement Learning From Human Feedback For Ethically Robust Ai Decision-Making, Marco M. Plasencia
Reinforcement Learning From Human Feedback For Ethically Robust Ai Decision-Making, Marco M. Plasencia
Honors Undergraduate Theses
The emergence of reinforcement learning from human feedback (RLHF) has made great strides toward giving AI decision-making the ability to learn from external human advice. In general, this machine learning technique is concerned with producing agents that learn to work toward optimizing and achieving some goal, advanced by interactions with the environment and feedback given in terms of a quantifiable reward. In the scope of this project, we seek to merge the intricate realms of AI robustness, ethical decision-making, and RLHF. With no way to truly quantify human values, human feedback is an essential bridge in the learning process, allowing …
Guarding The Grid: Exploring Iot And Iiot Security Vulnerabilities In Smart Power Systems, Nicole G. Parker
Guarding The Grid: Exploring Iot And Iiot Security Vulnerabilities In Smart Power Systems, Nicole G. Parker
Honors Undergraduate Theses
The Internet of Things (IoT) encompasses the collective network of electrical devices and the technology that enables them to send and receive data. The use of IoT technologies in industrial settings, such as transportation, manufacturing, and energy is referred to as the Industrial Internet of Things (IIoT). With the expansion of IoT in homes and IIoT in the energy sector has come an increase in the number of devices connected with each other. Engineers have utilized this network to develop sophisticated smart systems that combine sensing, processing, actuation, and control to produce smart environments. Along with the benefits of IoT …
Enhancing Medical Chatbots With Image Diagnosis, Swatisri Chavali
Enhancing Medical Chatbots With Image Diagnosis, Swatisri Chavali
Master's Projects
Medical chatbots, at the conjunction of artificial intelligence and healthcare, are the very cornerstone of a transformative force in diagnostic capabilities and communication channels for healthcare professionals. The history of this journey, from early chatbot models to sophisticated systems, is born out of a relentless pursuit of accuracy and contextual understanding. This proposal acknowledges the critical role played by NLTK in raising the interpretability and communicative capabilities of intelligent systems, meeting challenges that arise from varying writing styles and accommodating the standards of the medical field. The integration of NLTK is a linchpin, bridging the gap between sophisticated technological architectures …
Multimodal Emotion Detection In Conversations And Dialogues: A Fusion Model Approach, Abhinay Jatoth
Multimodal Emotion Detection In Conversations And Dialogues: A Fusion Model Approach, Abhinay Jatoth
Master's Projects
Emotion recognition is gaining traction due to its wide range of potential applications across different fields. With the rise of social media, chat platforms, and voice assistants, there is a vast increase in data through which humans implicitly and explicitly carry emotional cues. With new algorithms being developed for understanding the nuances of human language and emotion, businesses can tailor more personalized and empathetic service. Sentiment analysis, expresses a positive, negative, or neutral viewpoint laid the foundation of Emotion classification. Emotion classification in conversations represents the most advanced stage of classification. It is also challenging due to the existence and …
Transitioning To A Lower Global Warming Refrigerant, A Performance Study Of R-513a And Hfc-134a In Commercial Chillers, Hossein Abedsoltan, Mark B. Shiflett
Transitioning To A Lower Global Warming Refrigerant, A Performance Study Of R-513a And Hfc-134a In Commercial Chillers, Hossein Abedsoltan, Mark B. Shiflett
Chemical and Biochemical Engineering Faculty Research & Creative Works
The performance of R-513A and HFC-134a refrigerants is compared in two identical chillers operating at the University of Kansas. R-513A is a more environmentally friendly refrigerant due to its lower global warming potential that can be used as a retrofit replacement for HFC-134a in chillers. This study investigates the performance comparison of transitioning from HFC-134a to R-513A. The chillers have been in operation for two years, and cooling capacity, coefficient of performance, and other operating parameters are compared under similar cooling conditions. Cooling capacities ranged from 100 to 500 kW for both chillers. Overall, the energy consumption and coefficient of …
Root Water Uptake Patterns Are Controlled By Tree Species Interactions And Soil Water Variability, Gökben Demir, Andrew J. Guswa, Janett Filipzik, Johanna Clara Metzger, Christine Römermann, Anke Hildebrandt
Root Water Uptake Patterns Are Controlled By Tree Species Interactions And Soil Water Variability, Gökben Demir, Andrew J. Guswa, Janett Filipzik, Johanna Clara Metzger, Christine Römermann, Anke Hildebrandt
Engineering: Faculty Publications
Root water uptake depends on soil moisture which is primarily fed by throughfall in forests. Several biotic and abiotic elements shape the spatial distribution of throughfall. It is well documented that throughfall patterns result in reoccurring higher and lower water inputs at certain locations. However, how the spatial distribution of throughfall affects root water uptake patterns remains unresolved. Therefore, we investigate root water uptake patterns by considering spatial patterns of throughfall and soil water in addition to soil and neighboring tree characteristics. In a beech-dominated mixed deciduous forest in a temperate climate, we conducted intensive throughfall sampling at locations paired …
Economic Profitability Of Sustainable Buildings Industry, Mohanad Ibrahim Altuma, Hanadi Abdulridha Lateef, Ayad Abdulkhaleq Al-Yousuf
Economic Profitability Of Sustainable Buildings Industry, Mohanad Ibrahim Altuma, Hanadi Abdulridha Lateef, Ayad Abdulkhaleq Al-Yousuf
Al-Esraa University College Journal for Engineering Sciences
The increasing global awareness of the Earth's deteriorating condition and the unpredictable effects of climate change has given rise to worldwide phenomena that impact several elements like the economy, agricultural security, water availability, and energy supplies. Buildings contribute significantly to the generation of greenhouse gases, as well as the disposal of pollutants and energy consumption. Therefore, they play a crucial role in addressing environmental issues.
Although sustainable buildings are widely acknowledged as a potential advancement, professionals in the property market still believe that the upfront costs of creating sustainable buildings are significantly higher than those of conventional buildings. This view …
Designing A Visual Control Framework Based On Feature Point Analysis To Guide Robots In Uncharted Areas, Isam Sadiq Rasham Al-Ghadhbawi
Designing A Visual Control Framework Based On Feature Point Analysis To Guide Robots In Uncharted Areas, Isam Sadiq Rasham Al-Ghadhbawi
Al-Esraa University College Journal for Engineering Sciences
Image processing may be made more accurate and efficient with the use of optical processing technologies. In order to make better design judgments early in the package design process, visual packaging art simulation aims to swiftly develop realistic packaging effects. Conventional simulation techniques frequently yield findings that are neither realistic or detailed, and they also take a lot of time and human resources. Optical processing-based machine vision technology can fully utilize computer vision and image processing techniques to simulate package designs accurately and efficiently. This research proposes a foundation for machine vision technologies based on image optical processing. Real package …
Machine-Learning-Assisted Design Of Deep Eutectic Solvents Based On Uncovered Hydrogen Bond Patterns, Usman Lame Abbas, Yuxuan Zhang, Joseph Tapia, Md Selim, Jin Chen, Jian Shi, Qing Shao
Machine-Learning-Assisted Design Of Deep Eutectic Solvents Based On Uncovered Hydrogen Bond Patterns, Usman Lame Abbas, Yuxuan Zhang, Joseph Tapia, Md Selim, Jin Chen, Jian Shi, Qing Shao
Markey Cancer Center Faculty Publications
Non-ionic deep eutectic solvents (DESs) are non-ionic designer solvents with various applications in catalysis, extraction, carbon capture, and pharmaceuticals. However, discovering new DES candidates is challenging due to a lack of efficient tools that accurately predict DES formation. The search for DES relies heavily on intuition or trial-and-error processes, leading to low success rates or missed opportuni- ties. Recognizing that hydrogen bonds (HBs) play a central role in DES formation, we aim to identify HB features that distinguish DES from non-DES systems and use them to develop machine learning (ML) models to discover new DES systems. We first analyze the …
Perfluorooctanesulfonic Acid Exposure Leads To Downregulation Of 3-Hydroxy-3-Methylglutaryl-Coa Synthase 2 Expression And Upregulation Of Markers Associated With Intestinal Carcinogenesis In Mouse Intestinal Tissues, Josiane Weber Tessmann, Pan Deng, Jerika Durham, Chang Li, Moumita Banerjee, Qingding Wang, Ryan A. Goettl, Daheng He, Chi Wang, Eun Y. Lee, B. Mark Evers, Bernhard Hennig, Yekaterina Y. Zaytseva
Perfluorooctanesulfonic Acid Exposure Leads To Downregulation Of 3-Hydroxy-3-Methylglutaryl-Coa Synthase 2 Expression And Upregulation Of Markers Associated With Intestinal Carcinogenesis In Mouse Intestinal Tissues, Josiane Weber Tessmann, Pan Deng, Jerika Durham, Chang Li, Moumita Banerjee, Qingding Wang, Ryan A. Goettl, Daheng He, Chi Wang, Eun Y. Lee, B. Mark Evers, Bernhard Hennig, Yekaterina Y. Zaytseva
Markey Cancer Center Faculty Publications
Perfluorooctanesulfonic acid (PFOS) is a widely recognized environment pollutant known for its high bio- accumulation potential and a long elimination half-life. Several studies have shown that PFOS can alter multiple biological pathways and negatively affect human health. Considering the direct exposure to the gastrointestinal (GI) tract to environmental pollutants, PFOS can potentially disrupt intestinal homeostasis. However, there is limited knowledge about the effect of PFOS exposure on normal intestinal tissues, and its contribution to GI- associated diseases remains to be determined. In this study, we examined the effect of PFOS exposure on the gene expression profile of intestinal tissues of …
Investigation Of Delta-Focused Ictal Electrical Source Imaging In Refractory Focal Epilepsy, Jared A. Rybarczyk
Investigation Of Delta-Focused Ictal Electrical Source Imaging In Refractory Focal Epilepsy, Jared A. Rybarczyk
Theses and Dissertations--Electrical and Computer Engineering
Refractory focal epilepsy is characterized by the presence of seizures that cannot be controlled via anti-seizure medications. For patients suffering from this form of epilepsy, accurate identification of the seizure onset zone is a crucial step for many modalities of treatment. Electrical source imaging (ESI) allows for estimation of the seizure onset zone from electroencephalography. EEG feature extraction is an important step that can impact the final accuracy of source estimates. This work provides a review of 23 ictal ESI studies and proposes a delta-focused ictal ESI methodology. Our proposed delta-focused ictal ESI is implemented across 33 refractory focal epilepsy …
Electronics Design For Krepe Atmospheric Entry Capsule Avionics, Matt Ruffner
Electronics Design For Krepe Atmospheric Entry Capsule Avionics, Matt Ruffner
Theses and Dissertations--Electrical and Computer Engineering
This research documents the design, testing, and implementation of sensing, control, and communications subsystems for small atmospheric entry capsules. Atmospheric entry capsules pose a unique electronics design challenge given mission requirements, environmental constraints, and inherent risk involved in space based missions. Previous work on small satellites developed the CubeSat platform as a means of ensuring reliability after university-led small satellite missions experienced failures. The publication of the CubeSat platform allowed researchers to focus on the payload science utilizing a standardized form-factor and reusable electronics. Environmental and operational constraints of CubeSats and atmospheric entry capsules overlap and best-practices associated with building …
Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai
Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai
Theses and Dissertations--Electrical and Computer Engineering
Artificial Intelligence (AI) has experienced remarkable success in recent years, solving complex computational problems across various domains, including computer vision, natural language processing, and pattern recognition. Much of this success can be attributed to the advancements in deep learning algorithms and models, particularly Artificial Neural Networks (ANNs). In recent times, deep ANNs have achieved unprecedented levels of accuracy, surpassing human capabilities in some cases. However, these deep ANN models come at a significant computational cost, with billions to trillions of parameters. Recent trends indicate that the number of parameters per ANN model will continue to grow exponentially in the foreseeable …
Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso
Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso
Theses and Dissertations--Electrical and Computer Engineering
The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …
Mitigation Of Reflected Overvoltage In Wind-Turbine Generator-Converter Systems With A Smart Coil Concept, Lulu Wei
Theses and Dissertations--Electrical and Computer Engineering
In the recent decade, ultra-fast wide bandgap switching devices such as Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) have been increasingly utilized in power electronic converters for renewable energy power generation systems due to their advantages of enabling high energy efficiency and high power density. However, the much higher voltage slew rate (i.e., dv/dt) with SiC power converters may induce voltage reflection and reliability concerns in machine-converter systems, especially for medium-voltage systems with long cable connections. In wind-turbine power generation systems, generators are typically located in the nacelles, and medium-voltage power converters are mostly placed at the bottom of the …
Multi-Physics Modeling Of Immersion Cooled Electric Power Apparatuses, Reza Ilka
Multi-Physics Modeling Of Immersion Cooled Electric Power Apparatuses, Reza Ilka
Theses and Dissertations--Electrical and Computer Engineering
Electric power conversion apparatuses such as electromagnetic transformers and power electronic converters play a backbone role in the global power and energy industries, such as power transmission and distribution, electrified transportation vehicle systems, industry automation, and the like. To investigate the performance (efficiency, reliability, etc.) of such critical power conversion apparatuses, high-fidelity multi-physics modeling becomes critical which involves dedicated coupling among multiple physical domains, including electrical, magnetic, thermal, mechanical, and material engineering. Nevertheless, the majority of the existing models for these power conversion apparatuses focus only on one or two physical domains, and the modeling fidelity needs to be further …
A Novel Processor Architecture Implementing The Stacked Error Diffusion Algorithm And Its Zynq-Based Realization, Qishi Hu
Theses and Dissertations--Electrical and Computer Engineering
Digital halftoning reproduces continuous-tone images using patterns of black and white dots, while multitoning extends this concept by incorporating inks with intermediate intensities. These techniques are extensively utilized in the printing industry to accommodate the limited range of inks available in printers. Stacked error diffusion is a high-quality multitoning algorithm that adheres to the blue-noise dithering standard. This thesis research studies the potential parallelism inherent in the algorithm and introduces the design of a novel processor architecture optimized for efficient execution. The architecture is realized on an FPGA development board featuring a Zynq SoC. Additionally, the hardware prototype can also …
Information-Theoretic Learning Framework Based On Covariance Operators On Reproducing Kernel Hilbert Spaces, Jhoan Keider Hoyos Osorio
Information-Theoretic Learning Framework Based On Covariance Operators On Reproducing Kernel Hilbert Spaces, Jhoan Keider Hoyos Osorio
Theses and Dissertations--Electrical and Computer Engineering
Information theory provides tools to quantify uncertainty, dependence, and similarity between probability distributions, which are crucial for addressing various machine-learning problems. However, estimating these quantities is challenging because data distributions are usually unknown, and only observations are available for analysis. In this dissertation, we advance the field of information-theoretic learning by developing a comprehensive framework using kernel methods for analyzing probability distributions using reproducing kernel Hilbert spaces (RKHS). By leveraging covariance operators in this representation space, we propose approaches to estimate a set of fundamental information-theoretic quantities, that, because of their resemblance with conventional quantities in information theory, we call …
Optimal Control And Evaluation Of Shipboard Power Systems, Musharrat Sabah
Optimal Control And Evaluation Of Shipboard Power Systems, Musharrat Sabah
Theses and Dissertations--Electrical and Computer Engineering
Electric warships are involved in complex missions consisting of multiple simultaneous operations. In order to ensure mission success, future ships must be designed in a way that optimizes their performance in the presence of complex mission loads. The focus of this research is an effort to optimally control the performance of shipboard systems during missions involving multiple scenarios or vignettes. The evaluation of the performance of mission-oriented power systems is based on the degree to which these systems deliver power to the loads required to perform the mission at hand. The performance of such systems involves a dynamic interplay between …