Engineering Commons^™

Co-Simulation Of Electric Power Distribution Systems And Buildings Including Ultra-Fast Hvac Models And Optimal Der Control, Evan S. Jones, Rosemary E. Alden, Huangjie Gong, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Smart homes and virtual power plant (VPP) controls are growing fields of research with potential for improved electric power grid operation. A novel testbed for co-simulation of electric power distribution systems and distributed energy resources (DERs), is employed to evaluate VPP scenarios and propose an optimization procedure. DERs of specific interest include behind-the-meter (BTM) solar photovoltaic (PV) systems as well as heating, ventilation, and air-conditioning (HVAC) systems. Simulation of HVAC systems is enabled by a machine learning procedure that produces ultra-fast models for electric power and indoor temperature of associated buildings that are up to 133 times faster than typical …

Composite Solid Rocket Motor Case Optimization With Matlab Genetic Algorithm, Aleksandr Breit

Master's Theses

This study utilizes MATLAB genetic algorithm (GA) to perform optimization on a solid rocket motor (SRM) chamber structure. The (SRM) structure is modelled as a cylindrical composite laminate where unidirectional fiber orientations are the primary design variable in the optimization problem formulation. Additional design variables such as chamber length, diameter, and internal pressure are altered along with the ply angles to minimize the safety margin towards a near-zero value and encourage efficient layup design. Classical lamination theory with Tsai-Wu failure criterion are used to calculate ply-level safety margins. A thickness minimization scheme is employed to reduce the ply count from …

Distributed Control Of Servicing Satellite Fleet Using Horizon Simulation Framework, Scott Plantenga

Master's Theses

On-orbit satellite servicing is critical to maximizing space utilization and sustainability and is of growing interest for commercial, civil, and defense applications. Reliance on astronauts or anchored robotic arms for the servicing of next-generation large, complex space structures operating beyond Low Earth Orbit is impractical. Substantial literature has investigated the mission design and analysis of robotic servicing missions that utilize a single servicing satellite to approach and service a single target satellite. This motivates the present research to investigate a fleet of servicing satellites performing several operations for a large, central space structure.

This research leverages a distributed control approach, …

Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young

Electronic Theses and Dissertations

While marker-based motion capture remains the gold standard in measuring human movement, accuracy is influenced by soft-tissue artifacts, particularly for subjects with high body mass index (BMI) where markers are not placed close to the underlying bone. Obesity influences joint loads and motion patterns, and BMI may not be sufficient to capture the distribution of a subject’s weight or to differentiate differences between subjects. Subjects in need of a joint replacement are more likely to have mobility issues or pain, which prevents exercise. Obesity also increases the likelihood of needing a total joint replacement. Accurate movement data for subjects with …

Learning–Assisted Constraint Filtering To Enhance Power System Optimization Performance, Fouad Hasan

LSU Doctoral Dissertations

Machine learning (ML) is a powerful tool that provides meaningful insights for operators to make fast and efficient decisions by analyzing data from power systems. ML techniques have great potential to assist in solving optimization problems within a shorter time frame and with less computational burden. AC optimal power flow (ACOPF), dynamic economic dispatch (D-ED), and security-constrained unit commitment (SCUC) are the three energy management optimization functions studied in this dissertation. ACOPF is solved every 5~15 minutes. Because of the nonconvex and complex nature of ACOPF, solving this problem for large systems is computationally expensive and time-consuming. Classification and regression …

Selecting The Optimal Formwork System For Horizontal Elements, Alaa Allam, Emad Elbeltagi, Mohamed Naguib Abouelsaad, Mohamed E. El Madawy

Mansoura Engineering Journal

Various types of formworks are available in the market for construction of cast-in-place concrete structures. Formwork has a significant impact on both construction time and cost. As such, decision making on the optimal formwork system is difficult and timeconsuming for designers or planners particularly for high-rise buildings, where any reduction in the cost of single-story formwork significantly decrease total construction cost. Formworks must be designed effectively as numerous accidents have happened as a result of poor design decisions. This article presents a Genetic Algorithm optimization model to select the optimal formwork system among Cuplock, Shore brace and Props systems that …

An Analysis Of The Production Of Pharmaceutical-Grade Acetone Via The Dehydrogenation Of Isopropanol (Ipa), Jordan Desplas

Honors Theses

The production of 99.9 wt% acetone from isopropanol in Unit 1100 is designed to start up in 2025 and operate for 12 years after startup. The engineering team was tasked with designing the process, creating an economic model, and optimizing the net present value (NPV). The process was simulated in AVEVA PRO/II Simulation for the design process, and the economic analysis was estimated in Microsoft Excel. Parametric and topological optimization was performed linearly on the unit operations in the process. The NPV was improved by $14M from a base case of $122M to an optimized case of $136M. The project …

Comparative Design Space For Bistable Composites: An Integrated Framework Of Optimization, Finite Element Analysis, And Experimental Testing, Jonathan Bolanos

All Theses

Bistable composites are a class of advanced materials that can actuate between two stable shapes, making them attractive for a wide range of engineering applications. However, designing these composites to achieve optimal performance remains a challenging task. To address the challenge, this research develops an integrated framework that combines a genetic algorithm optimization technique, finite element analysis in Abaqus, and experimental testing to explore the design comparative space for square bistable composites composed of DA 409 carbon fibers. This leads to the study of generating an optimization algorithm to account for the relationship between the chances of a successful maximum …

A Value-Based Sequential Optimization Framework For Efficient Materials Design Considering Uncertainty And Variability, Maher Alghalayini

All Dissertations

Many problems in engineering and science can be framed as decision problems in which we choose values for decision variables that lead to desired outcomes. Notable examples include maximizing lift in airplane wing design, improving the efficiency of a power plant, or identifying processing protocols resulting in structural materials with desired mechanical properties. These problems typically involve a significant degree of uncertainty about the often-complex underlying relationships between the decision variables and the outcomes. Solving such decision problems involves the use of computational models or physical experimentation to generate data to make predictions and test hypotheses. As a result, both …

Addressing The Challenged Of Dcop Based Decision-Making Algorithms In Modern Power Systems, Luis Daniel Ramirez Burgueno

Open Access Theses & Dissertations

Natural disasters have been determined as the leading cause of power outages, causing not only huge economic losses, but also the interruption of crucial welfare activities and the arise of security concerns. Because of the later, decision-making considering grid modernization, power system economics, and system resiliency has been a crucial theme in power systemsâ?? research. The need to better withstand catastrophic events and reducing the dependency of bulky generating units has propelled the development and better management of behind-the-meter generation or distributed energy resources (DERs). DERs can assist in the grid in different manners, not only by meeting energy demand …

Accelerating The Derivation Of Optimal Powertrain Control Strategies Using Reinforcement Learning And Virtual Prototypes, Daniel Egan

All Dissertations

The push for improvements in fuel economy while reducing tailpipe emissions has resulted in significant increases in automotive powertrain complexity, subsequently increasing the resources, both time and money, needed to develop them. Powertrain performance is heavily influenced by the quality of their controller/calibration with modern powertrains reaching levels of complexity where using traditional design of experiment-based methodologies to develop them can take years. Recently, reinforcement learning (RL), a machine learning technique, has emerged as a method to rapidly create optimal controllers for systems of unlimited complexity directly which creates an opportunity to use RL to reduce the overall time and …

Editorial: Innovative Shared Transportation, Marco Nie, Hai Wang, Wai Yuen Szeto

Research Collection School Of Computing and Information Systems

Recent technological developments—mobile computing, autonomous driving, alternative fuel vehicles, and blockchain, to name a few—have enabled numerous innovations in mobility, transportation, and logistics services. They offer unprecedented opportunities to transform conventional transportation systems, for both personal travel and freight logistics, with novel solutions. Of these solutions, those built on the emerging concept of shared economy, such as Uber, Didi, and Cargostream, have received much attention recently. The rapidly expanding scope of shared transportation services now includes ride-sourcing, ridesharing, car sharing, hitch service, flexible paratransit, shared freight delivery, shared logistics, bike sharing, shared last-mile service, parking space sharing, and so on.

Chance Constrained Stochastic Optimal Control Of Discrete Time Linear Stochastic Systems With Applications In Multi-Satellite Operations, Shawn Priore

Electrical and Computer Engineering ETDs

Stochastic disturbances arise in a variety of engineering applications. For tractability, Gaussian disturbances are often assumed. However, this may not always be valid, such as when a disturbance exhibits heavy-tailed or skewed phenomena. As autonomous systems become more ubiquitous, non-Gaussian disturbances will become more common due to the compounding effects of sensing, actuation, and external forces. Despite this, little has been done to develop formal methods that are both computationally efficient and allow for analytical assurances with non-Gaussian disturbances. Addressing convex polytopic set acquisition and non-convex collision avoidance chance constraints with quantile and moment-based reformulations, this dissertation proposes novel stochastic …

Network Economics-Based Crowdsourcing In Online Social Networks, Natasha S. Kubiak

Electrical and Computer Engineering ETDs

This thesis addresses the challenge of user recruitment by various competing marketing agencies (MAs) in Online Social Networks. A labor economics approach, following the principles of contract theory, is devised to enable MAs to reveal the potential of each participating user to contribute a personalized level of quality and quantity of information to the crowdsourcing process. The MAs objective is to maximize their personal benefit, i.e., total utility obtained, given its budget. The latter optimization problem is formulated as a Generalized Colonel Blotto (GCB) game among the MAs, where each MA aims at incentivizing each user to report its information. …

Effect Of Fast Charging On Lithium-Ion Batteries: A Review, Ehab Bayoumi

Mechanical Engineering

In recent years we have seen a dramatic shift toward the use of lithium-ion batteries (LIB) in a variety of applications, including portable electronics, electric vehicles (EVs), and grid storage. Even though more and more car companies are making electric models, people still worry about how far the batteries will go and how long it will take to charge them. It is common knowledge that the high currents that are necessary to quicken the charging process also lower the energy efficiency of the battery and cause it to lose capacity and power more quickly. We need an understanding of atoms …

Leveraging Automated Fiber Placement Computer Aided Process Planning Framework For Defect Validation And Dynamic Layup Strategies, Joshua Allen Halbritter

Theses and Dissertations

Process planning represents an essential stage of the Automated Fiber Placement (AFP) workflow. It develops useful and efficient machine processes based upon the working material, composite design, and manufacturing resources. The current state of process planning requires a high degree of interaction from the process planner and could greatly benefit from increased automation. Therefore, a list of key steps and functions are created to identify the more difficult and time-consuming phases of process planning. Additionally, a set of metrics must exist by which to evaluate the effectiveness of the manufactured laminate from the machine code created during the Process Planning …

Comprehensive Process Planning Optimization Framework For Automated Fiber Placement, Alex Ryan Brasington

Theses and Dissertations

Advanced composite materials came about in 1966 and have since been widely used due to the possibility of superior structural performance while also achieving weight reductions. Such opportunities have led to composite materials being used to fabricate complex components, often in the aerospace sector. Most components, especially in aviation, are on a large scale and are outside the capabilities of traditional composite manufacturing techniques. Traditional manufacturing methods are also labor intensive, time consuming, have a high level of material scrap, and are prone to human error. This has led to the need for innovative manufacturing solutions to withstand the ever-increasing …

Computationally Efficient Analysis And Optimization Of Induction Motors, Hossein Nejadi Koti

Dissertations (1934 -)

The goal of this dissertation is to establish computationally efficient large-scale design optimization procedures for induction motors that are not only computationally efficient, but also do not sacrifice the accuracy of the results. To achieve this goal, the topic of the lengthy numerical transient response of Time-Stepping Finite Element Analysis (TS-FEA) of induction motors was investigated. This is because this lengthy transient affects the computational efficiency aspect of the optimization process. The effect of different parameters on the numerical transient response phenomenon were studied, and two different techniques for mitigation of this numerical transient were evaluated. The superior one amongst …

Optimizing Locations And Sizes Of Asphalt Concrete Plants In Karbala, Iraq, Ghayath Ali, Sawsan R Mohammad, Alaa M. Abdulhussein

Al-Bahir

This study develops and presents a methodology for determining the optimal geographic distribution and size of asphalt concrete plants in Karbala, Iraq, in order to minimize the cost of asphalt concrete produced. The purpose of this study is to discuss these points. The methodology can identify potential locations for asphalt concrete plants within a study area, considering the plants' operation and capital costs and the costs of transporting raw materials to the plants and asphalt concrete to demand centers. Matrix Laboratory (MATLAB) software have been used to program the methodology. This methodology has been applied to Karbala using actual data. …

The Electromagnetic Bayonet: Development Of A Scientific Computing Method For Aperture Antenna Optimization, Michael P. Ingold

Theses and Dissertations

The quiet zone of a radar range is the region over which a transmitted EM field approximates a uniform plane wave to within some finite error tolerance. Any target to be measured must physically fit within this quiet zone to prevent excess measurement error. Compact radar ranges offer significant operational advantages for performing RCS measurements but their quiet zone sizes are constrained by space limitations. In this work, a scientific computing approach is used to investigate whether equivalent-current transmitters can be designed that generate larger quiet zones than a conventional version at short range. A time-domain near-field solver, JefimenkoModels, was …

Team And Skill Matching For Disaster Recovery Operations, Emily B. Frahm

Theses and Dissertations

United States Air Force (USAF) bases are key power projection platforms that ensure mission readiness and help bring humanitarian aid to locations in need. Recovering airfields after attack or natural disaster is a key mission of USAF civil engineers, and accomplishing this repair as swiftly as possible is key to maintaining our position in the global order. Accomplishing a disaster recovery project is a set of teams, each assigned to a specific task, and made up of a series of personnel. The question answered within this paper is: how do we match the right person with the appropriate skills to …

Unmanned-Aircraft-System-Assisted Early Wildfire Detection With Air Quality Sensors †, Doaa Rjoub, Ahmad Alsharoa, Ala'eddin Masadeh

Electrical and Computer Engineering Faculty Research & Creative Works

Numerous Hectares of Land Are Destroyed by Wildfires Every Year, Causing Harm to the Environment, the Economy, and the Ecology. More Than Fifty Million Acres Have Burned in Several States as a Result of Recent Forest Fires in the Western United States and Australia. According to Scientific Predictions, as the Climate Warms and Dries, Wildfires Will Become More Intense and Frequent, as Well as More Dangerous. These Unavoidable Catastrophes Emphasize How Important Early Wildfire Detection and Prevention Are. the Energy Management System Described in This Paper Uses an Unmanned Aircraft System (UAS) with Air Quality Sensors (AQSs) to Monitor Spot …

A Novel Covid-19 Herd Immunity-Based Optimizer For Optimal Accommodation Of Solar Pv With Battery Energy Storage Systems Including Variation In Load And Generation, Sumanth Pemmada, Nita Patne, Divyesh Kumar, Ashwini Manchalwar

Turkish Journal of Electrical Engineering and Computer Sciences

The world has now looked towards installing more renewable energy sources type distributed generation (DG), such as solar photovoltaic DG (SPVDG), because of its advantages to the environment and the quality of power supply it produces. However, these sources' optimal placement and size are determined before their accommodation in the power distribution system (PDS). This is to avoid an increase in power loss and deviations in the voltage profile. Furthermore, in this article, solar PV is integrated with battery energy storage systems (BESS) to compensate for the shortcomings of SPVDG as well as the reduction in peak demand. This paper …

Hybrid Modeling For Electrochemical Systems, Luis Alejandro Briceno-Mena

LSU Doctoral Dissertations

The discovery of new materials like catalysts, polymeric films, and biomolecules, is driven by industrial needs such as improving reaction or separation selectivity, enhancing therapeutic effects on medical treatments, or reducing costs of replacement. However, deployment of these advances in industrial applications is often hindered by the lack of models needed for design and optimization. Due to the novelty of materials and devices, experimental data and first principles' knowledge are scarce, making it hard to build models either via data-driven or knowledge based approaches. In this context, a way to efficiently combine domain knowledge with data could provide a pathway …

Development Of The Tlvmie Force Field And A Standardized Methodology For Improved Pure-Component And Mixture Liquid Viscosity Predictions, Daniel J. Carlson

Theses and Dissertations

Existing viscosity prediction methods and relevant literature are reviewed. An exhaustive review of group contribution, corresponding states, and interpolative prediction methods finds that even the best of these models produces large prediction errors and often require significant experimental data. Molecular dynamics simulation techniques for viscosity prediction are evaluated and compared to one another to determine the best choice for this work. A thorough investigation finds that Equilibrium Molecular Dynamics (EMD) simulations are the best option for reproducible and reliable liquid viscosity predictions. The many tuning parameters available in molecular dynamics simulations are investigated for their effects on prediction uncertainty and …

Expression Optimization Of The Gst-Gfp Fusion Protein Through The Alteration Of Induction Conditions, Matthew J. Vaccaro

Honors Undergraduate Theses

This research sought to determine which induction condition resulted in the greatest GST-GFP fusion protein expression. It will hopefully serve as a guide for future researchers trying to produce their own recombinant protein containing GST and GFP-tags. The CDNB Enzyme Assay was used to determine the quantity of GST-GFP fusion protein present and tested three variables: IPTG concentration, duration, and temperature of induction. The findings showed that IPTG concentration, temperature, and induction duration all had a significant impact on protein expression. Induction temperatures of 20 °C and 25 °C showed better protein expression at IPTG concentrations of 1.0 mM IPTG …

Scheduling Electric Vehicle Charging For Grid Load Balancing, Zhixin Han, Katarina Grolinger, Miriam Capretz, Syed Mir

Electrical and Computer Engineering Publications

In recent years, electric vehicles (EVs) have been widely adopted because of their environmental benefits. However, the increasing volume of EVs poses capacity issues for grid operators as simultaneously charging many EVs may result in grid instabilities. Scheduling EV charging for grid load balancing has a potential to prevent load peaks caused by simultaneous EV charging and contribute to balance of supply and demand. This paper proposes a user-preference-based scheduling approach to minimize costs for the user while balancing grid loads. The EV owners benefit by charging when the electricity cost is lower, but still within the user-defined preferred charging …

Non-Intrusive Reduced Order Model Formulation For Inverse Shape Design Including Deforming Meshes And Multiphysics Problems., Kapil Aryal

Mechanical and Aerospace Engineering Dissertations - Archive

Despite significant advancements in computer capabilities for numerical simulations, engineers continue to face limitations when dealing with large-scale full-order model(FOM) simulations. These simulations often necessitate repeated solves, such as those encountered in inverse design, real-time solution prediction, error quantification, and solver convergence, among others. To address these challenges, reduced order modeling (ROM) has emerged as a valuable approach. This thesis focuses on the development of an ROM framework that combines Proper Orthogonal Decomposition (POD) with machine learning techniques. This integrated approach is applied to a diverse range of heat transfer and fluid flow inverse design problems. POD constructs optimal sets …

A Framework For The Automatic Identification Of Optimized Yield Surface Parameters, Kevin Hanekom

Honors Undergraduate Theses

Advanced engineering materials are designed to display tensile-compressive asymmetry (TCA) and anisotropy to provide unique attributes to critical components necessary in the hot section of turbines. The never-ending chase for higher efficiencies, and with them, higher temperature gradients, intrinsically leads to more and more of these complex materials, like single crystal turbine blades, embedded within the turbine environment. Mathematical models, known as yield criteria, allow engineers to visualize the mechanical behavior of these materials in various orientations under complex loading. Yield criteria are dependent on three key items in determination of their governing parameters: material test data, mathematical constraints, and …

Environmental Efficiency Assessment Of Dublin Port Using Two-Stage Non-Radial Dea Model, Boban Djordjević, Raja Maitra, Bidisha Ghosh

Articles

Global maritime trade has reached 11 billion tons and accounts for more than 80% of global merchandise trade (United Nations Conference on Trade & Development (UNCTAD), 2019). As a result, there is a wide range of vessels, from very large bulk carriers (coal, ores, grains, etc., and crude oil/refinery carriers) to container ships to various cruise ships and naval vessels. To efficiently accommodate these various vessels, ports have had to evolve from wharves to efficient logistical hubs within the larger supply chain that move vessels deeper into the hinterland. Port development is critical to managing the growing volume of cargo …