Engineering Commons^™

Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa

Theses and Dissertations

“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …

On The Synthesis Of Optimal Control Laws, Meir Pachter, Isaac E. Weintraub

Faculty Publications

In this paper we advocate for Isaacs' method for the solution of differential games to be applied to the solution of optimal control problems. To make the argument, the vehicle employed is Pontryagin's canonical optimal control example, which entails a double integrator plant. However, rather than controlling the state to the origin, we correctly require the end state to reach a terminal set that contains the origin in its interior. Indeed, in practice, it is required to control to a prescribed tolerance rather than reach a desired end state; achieving tight tolerances is expensive, and from a theoretical point of …

Investigation Of An Optimized Occupancy-Driven Hvac Control Strategy And Development Of A Scalable House/Grid Simulation, Kaleb Pattawi

Mechanical Engineering Master's Theses

Energy consumption in buildings is projected to increase more than 50% by 2050. Renewable energy sources are expected to increase and will help alleviate some of the energy demand; however, the intermittent nature of renewables makes it tough to effectively use energy in buildings. Various pricing schemes, including time of use electricity pricing, are used to encourage users to shift loads. Buildings need to be able to proactively react to changing energy sources and electricity prices in order to reduce over-generation of electricity and save money. This work demonstrates an optimized Heating Ventilation and Air Conditioning (HVAC) control strategy that …

Torque Vectoring To Maximize Straight-Line Efficiency In An All-Electric Vehicle With Independent Rear Motor Control, William Blake Brown

Theses and Dissertations

BEVs are a critical pathway towards achieving energy independence and meeting greenhouse and pollutant gas reduction goals in the current and future transportation sector [1]. Automotive manufacturers are increasingly investing in the refinement of electric vehicles as they are becoming an increasingly popular response to the global need for reduced transportation emissions. Therefore, there is a desire to extract the most fuel economy from a vehicle as possible. Some areas that manufacturers spend much effort on include minimizing the vehicle’s mass, body drag coefficient, and drag within the powertrain. When these values are defined or unchangeable, interest is driven to …

Buckling Load Optimization Of Variable Stiffness Composite Plate Using Fem And Semi-Analytical Method, Jeegar Vallabhbhai Patel

Mechanical and Aerospace Engineering Theses - Archive

The advent of new composite manufacturing techniques like Automated Fiber Placement (AFP) offers greater flexibility in structural designs by allowing curvilinear fiber paths. Hence, it is now possible to change laminate stiffness locally, thereby enabling Variable Stiffness (VS) composite structures. Such structures demonstrate superior buckling performance over traditional constant stiffness structures. However, obtaining the optimum fiber paths to improve buckling performance remains an open area of research due to the complexity of determining such fiber paths. This research investigated two approaches for optimizing fiber paths; First, a Finite Element Method (FEM) approach that utilizes linear shape functions to interpolate local …

Melanoma Classification Based On Simulated Annealing Optimization Neural Network, Edi Jaya Kusuma, Ika Pantiawati, Sri Handayani

Knowledge Engineering and Data Science

Technology development in image processing and artificial intelligence leads to the high demand for smart systems, especially in the health sector. Cancer is one of the diseases with the highest mortality cases worldwide. Melanoma is one of the cancers commonly caused by high exposure to UV light. The earliest the melanoma is identified, the higher the patient's chance of recovering. Therefore, this study proposes melanoma detection based on BPNN optimized by a simulated annealing algorithm. This research utilizes PH2 dermoscopic image data containing 200 color digital images in BMP format. The data is processed using color feature extraction techniques to …

Development Of Metaheuristic Algorithms For The Efficient Allocation Of Power Flow Control Devices, Eduardo Jose Castillo Fatule

Open Access Theses & Dissertations

Modern energy grids have become extremely complex systems, requiring more variable and active flow control. As a remedy to this, Distributed Flexible AC Transmission Systems (D-FACTS) are cost-efficient devices used to mitigate power flow congestion and integrate renewable energies. The objective of this research is then to propose an efficient multiple objective evolutionary algorithm to solve a stochastic model for D-FACTS allocation, which aims to optimize various objectives related to cost, grid health, and environmental impacts. The model was implemented on a modified RTS-96 test system, and the results show that optimally allocating D-FACTS modules using the proposed model can …

Drone Location And Scheduling Problems In Humanitarian Logistics., Zabih Ghelichi

Electronic Theses and Dissertations

Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, are a promising technology for the last-mile delivery of medical and aid items in humanitarian logistics. In emergency scenarios, like disasters, where transportation networks are destroyed and people are stranded, drones can accelerate the delivery of urgently needed items, e.g., food and water, insulin shots and blood pressure pills, to those trapped in the disaster-affected areas. Drones can also provide logistics services in many non-emergency situations by delivering medical items, e.g., vaccine shots and lab specimens, to remote communities and hard-to-access locations. The contribution of using UAVs goes beyond merely having …

Performance Loss Rate And Temperature Modeling In Predictive Energy Yield Programs For Utility-Scale Solar Power Plants, Katelynn M. Dinius

Master's Theses

The Gold Tree Solar Farm, designed by REC Solar, has a rated output power of 4.5 MW and began operation in 2018 to provide electricity to Cal Poly’s campus. Gold Tree Solar Farm site terrain consists of rolling hills and uneven slopes. The uneven typography results in interrow shading, requiring a modified tracking control algorithm to maximize power production. Predicting a utility solar field’s lifetime energy yield is a critical step in assessing project feasibility and calculating project revenue. The MATLAB-based predictive power model developed for this field overpredicted power in the middle of the day. The purpose of this …

Pressure Retarded Osmosis: A Potential Technology For Seawater Desalination Energy Recovery And Concentrate Management, Joshua Benjamin

USF Tampa Graduate Theses and Dissertations

Currently, a significant challenge with reverse osmosis-based desalination is reducing the energy consumption and environmental impacts of the process. This project analyzed the viability of using pressure-retarded osmosis (PRO) for energy recovery in seawater desalination facilities using brine concentrate (the draw solution) and other water sources (the feed solution) such as wastewater effluent. The primary goal of this project is to decrease the cost and overall energy consumption of seawater desalination through PRO-based energy recovery. Process modeling, statistical and sensitivity analysis, energy and cost analysis, geospatial and GIS analysis, laboratory-scale testing, water quality analysis, SEM-EDS microscopy, computational fluid dynamics (CFD), …

Energy Harvesting For Self-Powered Sensors For Smart Transportation Infrastructures, Anil K. Agrawal, Mohsen Amjadian, Hani Nassif

Civil Engineering Faculty Publications

In this research project, an Electromagnetic Energy Harvesting System (EMEHS) is developed for harvesting the kinetic energy of ambient and traffic-induced vibrations and carry out a detailed feasibility study and impacts of such system for application on transportation infrastructures. The proposed EMEHS utilizes the innovative concept of creating array of large number of small permanent magnets through certain optimization criteria to achieve strong and focused magnetic field in a particular orientation. When these magnets are attached to a flexible sub-system and placed close to the copper coil, ambient and traffic-induced vibration of the sub-system induces eddy current in copper the …

Regularized Heuristic Method For Activation Monitor Neutron Spectrum Unfolding, Nicholas J. Quartemont, James E. Bevins

Faculty Publications

his paper describes an activation foil measurement based neutron flux unfolding method utilizing a heuristic optimization approach. A regularization parameter based on the differential neutron flux was introduced into the optimization cost function to remove large nonphysical oscillations in the unfolded neutron energy spectrum. The procedure was completed for two example case studies ranging from thermal energies up to 20 MeV demonstrating recovery of neutron flux energy information on radiation environments where a model was partially missing or there was a discrepancy in a reaction channel. The unfolded results provided a distribution of unfolded spectra that conformed to the activation …

Constructing Frameworks For Task-Optimized Visualizations, Ghulam Jilani Abdul Rahim Quadri

USF Tampa Graduate Theses and Dissertations

Visualization is crucial in today’s data-driven world to augment and enhance human understanding and decision-making. Effective visualizations must support accuracy in visual task performance and expressive data communication. Effective visualization design depends on the visual channels used, chart types, or visual tasks. However, design choices and visual judgment are co-related, and effectiveness is not one-dimensional, leading to a significant need to understand the intersection of these factors to create optimized visualizations. Hence, constructing frameworks that consider both design decisions and the task being performed enables optimizing visualization design to maximize efficacy. This dissertation describes experiments, techniques, and user studies to …

Guidelines For Structural Optimization And Sustainable Retrofitting Of Re-Purposed Buildings Using Bim, Mariam Ehab, Mina Maxi, Gehan Nagy

Civil Engineering

Nowadays energy problems resulting from the building industry become very polluting along with the high expenses of the building operation. Designers tend to propose another solution which is the refurbishment of old buildings to be energy-optimized and more efficient. As a result, some solutions are addressed to prioritize keeping the architectural theme of the city as well as reducing land use. An extensive investigation is conducted to review past research approaches regarding energy optimization requirements as well as scoping on structural optimization through building refurbishment. Structural optimization resulting from structural repurposing is not studied in depth recently, as a result, …

Interdependent Infrastructure Recovery Using Multilayered Networks And Optimization, Brigham A. Moore

Theses and Dissertations

Interdependent infrastructure recovery modeling and simulation are complicated due to various interdependent connections and complexities. Current efforts have identified both operational and restoration interdependency subtypes and coupling strategies that have not been integrated into one comprehensive model. This research presents a model which simultaneously integrates nine interdependency subtypes and four coupling strategies in a multi-objective format to provide the most tailorable and comprehensive network-based recovery model available. This research also created a defense-centric interdependent infrastructure database by modifying the existing CLARC database. This research then addressed assumptions regarding recovery work management in order to address the impact of work crew …

Optimal Incorporation Of Non-Traditional Sensors Into The Space Domain Awareness Architecture, Albert R. Vasso

Theses and Dissertations

The United States Government is the world’s de facto provider of space object cataloging data, but is challenged to maintain pace in an increasingly complex space environment. This work advances a multi-disciplinary approach to better understand and evaluate an underexplored solution recommended by national policy, in which current collection capabilities are augmented with non-traditional sensors. System architecting and literature identify likely needs, performance measures, and contributors to a conceptualized Augmented Network. Multiple hypothetical telescope architectures are modeled and simulated on four separate days throughout the year, then evaluated against performance measures and constraints using optimization. Decision analysis and Pareto optimality …

Zip Load Modeling For Single And Aggregate Loads And Cvr Factor Estimation, Yiqi Zhang, Yuan Liao, Evan S. Jones, Nicholas Jewell, Dan M. Ionel

Electrical and Computer Engineering Presentations

ZIP load modeling has been used in various power system applications. The aggregate load modeling is common practice in utility companies. However, little research has been done on the theoretical formulation of the aggregate load. This paper formulates the aggregate ZIP load model using the single ZIP load model. The factors that may affect aggregate ZIP load estimation are studied. Common ZIP parameter estimation methods including least squares method, optimization method and neural network method have been used in this paper to estimate ZIP parameters. The case studies are based on the IEEE 13-bus and 34-bus system built in OpenDSS. …

Regularized Coordinate-Based Neural Representation Learning For Optical Tomography, Renhao Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Neural representation learning recently shows outstanding performance in several computer vision tasks. In this thesis, we propose a novel self-supervised neural represented reconstruction method for optical tomography. Our method uses a Multi-Layer Perceptron (MLP) network to represent the target sample without the need for any ground truth or training data. The MLP weights serve as a latent representation of the target object. Any desired permittivity information can be inferred by querying the neural network within the sample domain. We also investigate applying regularization to implicitly restrict the manifold of MLP for better performance. Our experiments produce low artifacts results with …

Continuous-Time And Complex Growth Transforms For Analog Computing And Optimization, Oindrila Chatterjee

McKelvey School of Engineering Graduate Student Theses & Dissertations

Analog computing is a promising and practical candidate for solving complex computational problems involving algebraic and differential equations. At the fundamental level, an analog computing framework can be viewed as a dynamical system that evolves following fundamental physical principles, like energy minimization, to solve a computing task. Additionally, conservation laws, such as conservation of charge, energy, or mass, provide a natural way to couple and constrain spatially separated variables. Taking a cue from these observations, in this dissertation, I have explored a novel dynamical system-based computing framework that exploits naturally occurring analog conservation constraints to solve a variety of optimization …

Set-Theoretic Frameworks For Online Optimization, Estimation, And Control, Dignata Bhattacharjee

Mechanical and Aerospace Engineering Dissertations - Archive

This research is primarily focused on developing online frameworks, which are suited to real-time implementation, for performance optimization, estimation, and control of dynamical systems using set-theoretic concepts and/or having set-theoretic interpretations. First, two perturbation-based extremum seeking control schemes, based on the classical setup and equipped with novel adaptation laws for the perturbation signal amplitudes, are proposed for general single input single output nonlinear systems. The proposed schemes are able to extremize steady-state system output in a practical asymptotic sense, i.e., the system is driven to an arbitrarily small set centered at the true steady-state optimal operating point. The next development …

Haptic Interface Optimization For Virtual Anastomosis Surgery Training, Kangji Huang

Mechanical and Aerospace Engineering Theses - Archive

Virtual anastomosis surgery study allows surgeons to perform or practice suturing in virtual reality using a commercial haptic device. The haptic device can generate force feedback so that the user can feel the real touch sensation of the object in virtual reality. The virtual anastomosis surgery study has two requirements which are that the haptic device must be fixed on the operating table and haptic device location must be suitable for different surgeons. The goal is to use a commercially available haptic device for this purpose, rather than design a new device for each possible surgery that must be performed. …

Investigating A Finite Element Model Updating Methodology For Characterizing Mechanical Properties Of Ncf Composites, Pasworn Chanchai

Mechanical and Aerospace Engineering Theses - Archive

Composite materials have been a key breakthrough in developing aircraft structures. Their superior strength and stiffness-to-density ratio, which are unmatched by no other materials, allow engineers to create high strength and ultra-lightweight aircraft structures. Recently, non-Crimp Fabric (NCF) composites have emerged as attractive alternatives to traditional autoclave pre-impregnated composites allowing for lower production costs, better handling and improved shelf life while maintaining excellent in-plane mechanical properties compared to other types of textile composites. NCF out-of-plane mechanical properties can also be enhanced by stitching a high tensile strength yarn throughout their entire laminate thickness, improving the resistance to delamination. However, stitch-reinforced …

Surrogate Optimization Model For An Integrated Regenerative Methanol Transcritical Cycle, Yili Zhang

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In order to reduce the cost ($) per megawatts hour (MWh) of electrical energy generated by a nuclear power cycle with a novel small modular reactor (SMR), a new SMR-based nuclear power cycle with Methanol as working fluid was designed. It was built virtually with the Python & Coolprop software based on all components’ physical properties, and it is therefore called the physics-based model. The physics-based model would require seven user-defined values as input for the seven free design parameters, respectively. The physics-based model outcomes include LCOE (the cost per megawatts hour of electrical energy generated by the …

Interior Point Optimization Of Low-Thrust Spacecraft Trajectories, Jordan D. Frederiksen

Master's Theses

Low-thrust interplanetary spacecraft trajectory optimization poses a uniquely difficult problem to solve because of the inherent nonlinearities of the dynamics and constraints as well as the large size of the search space of possible solutions. Tools currently exist that optimize low-thrust interplanetary trajectories, but these tools are rarely openly available to the public, and when they are available they require multiple interfaces between multiple different packages. The goal of this work is to present a new piece of low-thrust interplanetary spacecraft trajectory optimization software that is open-source and entirely self-contained so that more people can have access to the ability …

Shape Optimization Of A Sandwich Composite Plate With Low-Velocity Impact Loading And Effect Of Finite Difference Sensitivity Analysis, Utsav Shah

Doctoral Dissertations and Master's Theses

The structural design of spacesuits is essential in an advancing future of both Lunar and Martian space exploration. A typical spacesuit is made of sandwich composite material and designed to withstand various pressure and loading conditions while also considering the safety and comfort of the astronauts. One of the critical load cases in spacesuit design is a low-velocity impact (LVI) which may occur due to tool drop and other similar scenarios. The objectives of this work were (a) to create a finite element (FE) model of a component of a spacesuit, (b) validation of the FE model through experiments, (c) …

Considering Social Impact When Engineering For Global Development, Hans Jorgen Ottosson

Theses and Dissertations

Every manufactured product has an environmental impact, a social impact, and an economic impact. As engineers, we should do our best to understand how our design decisions influence these impacts (the three pillars of sustainability), and at the same time make decisions that collectively lead to maximum positive impacts, or minimum negative impacts on the economy, environment, and society. Many times, engineers show interest and want to design for all three pillars of sustainability but are often constrained to focus on the environmental and economic aspects, leaving out social sustainability due to lack of understanding and resources. In practice, this …

Studying Complex Aquifer Systems From Large-Scale Stratigraphy Development To Local Aquifer Storage And Recovery, Hamid Vahdat Aboueshagh

LSU Doctoral Dissertations

Hydrostratigraphy model is an essential component of building valid groundwater models. Many challenges are associated with constructing hydrostratigraphy models which include geological complexities such as faults, domes, and angular unconformities. Developing a method with an emphasis on capturing big data to thoroughly inform large-scale models is one of the challenges addressed in the first part of this study. The method is predicated upon discretization of the study domain into tiles based on the geological dip direction and faults. The application of the method in the state of Louisiana with the utilization of more than 114000 well logs demonstrates promising results …

Optimization Of Vaccine Supply Chains In Low- And Middle-Income Countries Utilizing Drones, Maximilian Kolter

Graduate Theses and Dissertations

Despite tremendous efforts from governments and humanitarian organizations, millions of children in low- and low-middle-income countries (LICs and LMICs) are still excluded from the benefits of immunization. The vaccine distribution in LICs and LMICs is challenging for several reasons, such as limited cold chain capacities, vaccine wastage, uncertain demand, and lack of access to immunization services. A promising avenue to address these issues is the utilization of drones for vaccine delivery. Drones can fly at high speed on direct paths and could enable on-demand deliveries to mitigate limited storage capacities. Further, their independence of road networks could allow them reaching …

Scheduling Allocation And Inventory Replenishment Problems Under Uncertainty: Applications In Managing Electric Vehicle And Drone Battery Swap Stations, Amin Asadi

Graduate Theses and Dissertations

In this dissertation, motivated by electric vehicle (EV) and drone application growth, we propose novel optimization problems and solution techniques for managing the operations at EV and drone battery swap stations. In Chapter 2, we introduce a novel class of stochastic scheduling allocation and inventory replenishment problems (SAIRP), which determines the recharging, discharging, and replacement decisions at a swap station over time to maximize the expected total profit. We use Markov Decision Process (MDP) to model SAIRPs facing uncertain demands, varying costs, and battery degradation. Considering battery degradation is crucial as it relaxes the assumption that charging/discharging batteries do not …

Enabling The “Easy Button” For Broad, Parallel Optimization Of Functions Evaluated By Simulation, Andrew Gibson

Graduate Theses and Dissertations

Java Optimization by Simulation (JOBS) is presented: an open-source, object-oriented Java library designed to enable the study, research, and use of optimization for models evaluated by simulation. JOBS includes several novel design features that make it easy for a simulation modeler, without extensive expertise in optimization or parallel computation, to define an optimization model with deterministic and/or stochastic constraints, choose one or more metaheuristics to solve it and run, using massively parallel function evaluation to reduce wall-clock times.

JOBS is supported by a new language independent, application programming interface (API) for remote simulation model evaluation and a serverless computing environment …