Engineering Commons^™

Cyclic Thermal Stability Of Native Oxide Solar Thermal Absorbers On Femnnialcr High Entropy Alloys For Energy Applications, Xiaoxue Gao

Dartmouth College Ph.D Dissertations

High entropy alloys (HEAs) are promising candidates for cost-effective high-temperature materials in high-efficiency power cycles. A potential application is in concentrated solar power (CSP) systems, where native oxides of cost-effective FeMnNiAlCr HEAs can also synergistically serve as a high-efficiency solar thermal absorber. However, the huge and repetitive temperature change of the CSP system in day-night cycles greatly challenges its thermal stability. In this thesis, we investigated the cyclic oxidation behavior of FeMnNiAlCr HEAs to improve the optical performance and thermal stability of their native oxides as a solar absorber for next-generation CSP systems. We found that the duplex oxide scale …

Hitch Cart “Landing Gear”, Rebekah White, Jose Raygoza, Randy Hernandez, Brandon Leon

Mechanical Engineering

This report aims to allow our sponsor, to review our design process of the Hitch Cart Landing Gear Prototype. In the design overview section of this report, we discuss the primary design modifications we made to the wheel mechanism of the existing hitch cart prototype, including the addition of the ACME screws and the folding brackets. This allows our sponsor to see the intended improvements made to the past prototype and understand the primary goal of our project. Then, in the implementation section, we cover the entire manufacturing process to allow our sponsor to understand what manufacturing steps must be …

Pseudo Gps For Romi, Emmanuel Baez, Owen Guinane, Gabriel Coria, Conor Schott

Mechanical Engineering

The Pseudo-GPS system for Romi robots addresses the need for precise real-time location tracking in Cal Poly's Mechatronics lab. This project, developed by Emmanuel Baez, Gabriel Coria, Owen Guinane, and Conor Schott, under the guidance of instructor Charlie Refvem, provides a proof-of-concept system to enhance the Romi robots' geolocation capabilities for advanced robotic algorithms.

The proposed system uses a Raspberry Pi 4 equipped with a Pi camera module and ArUco markers to track the position and orientation of Romi robots within a lab environment. Custom 3D-printed stands secure markers on the robots, and a designated origin marker defines the coordinate …

Expandable And Retractable Wheel Design, Ethan Fortenberry, Emily Cottrell, Keegan Martin, Benjamin Mcconnell

Mechanical Engineering

Our sponsor, Jeremy Goren, wants to see his patented expandable wheel design come to life. He requires a functional final product actuated by linear actuators and with a continuous, circular outer shell. The overall design can be broken up into 2 parts: the inner hub and outer shell. The wheel's shell will consist of a 12-piece outer shell that guides the 6 inner shell pieces. The outer shell pieces will be connected via a UBracket. The hub will consist of 3 identical parts that will hold 2 linear actuators each. The pieces will be bolted together to create 1 singular …

The Waterbug: Adaptive Paddle Board Frame, Remy James Elio Lacchia, Katie Kellum, Madeline Evenson, Shelbi Sullaway

Mechanical Engineering

People with disabilities, particularly wheelchair users, face limitations in participating in outdoor activities like paddleboarding. Central Cal Adaptive, a nonprofit organization, aims to bridge this gap by offering adapted paddleboarding experiences. However, their current paddleboard presents challenges such as portability, range of motion, stability, and safety. Our team, comprising Madeline Evenson, Remy Lacchia, Katie Kellum, and Shelbi Sullaway, has collaborated with Central Cal Adaptive to refine the existing paddleboard design. The team’s goal is to enhance the paddleboard's functionality to better cater to wheelchair users' needs, ensuring lightweight, portable, and safe features for an improved outdoor experience.

Our paddleboard concept …

Piston Crown Design, Kurt L. Lippmann, Liam T. Janssen, Alex Rangel, Larry J. Davis

Mechanical Engineering

This project investigates the effects of dimpling a piston crown, and its impact on engine combustion dynamics. Through computational methods, the effects of piston crown dimpling on flow characteristics were evaluated. Theoretical results were verified with experimental methods. Experimental methods included characterization of exhaust gas content, engine horsepower and torque, and exhaust opacity.

Swim Fly Drone, Alia Wolken, Sha'anan Levy, Andrew Jwaideh, Eduardo Santos

Mechanical Engineering

This project addresses the need for a versatile drone that is capable of operation in both air and water environments, with potential applications in infrastructure inspection, defense, search and rescue, and ocean exploration. This project focuses on the design and development of a waterproof aerial drone capable of floating on the water surface and submerging underneath to controlled depths with the integration of a custom detachable buoyancy chamber. The buoyancy chamber design utilizes syringes to compress and decompress air inside of the chamber, changing the volume of the chamber, with an actuation system controlled by a closed-loop control system that …

Development Of A Manifold Microchannel Heat Sink For The Electrification Of Aircraft, Joshua Mora Sanchez

Mechanical Engineering Undergraduate Honors Theses

The miniaturization of microprocessors and power electronics is leading to critical thermal management challenges. For instance, the heat flux generated in modern computer chips is at the order of 100W/cm², which is well beyond the limit of air cooling. This high heat generation can cause a variety of thermal or mechanical failures in electronic devices. As such, there is a pressing need to devise effective cooling strategies for these microelectronic devices. Liquid cooling with microchannel heat sinks is a promising technology for high power loads. Nevertheless, traditional heat sinks with straight microchannels suffer from two critical challenges: high pressure drop …

Nlp-Based Quantitative Methods For Measuring Highway Project Similarity To Support Project Clustering And Bundling, Quan Do

All Dissertations

State highway agencies (SHAs) often need to classify similar projects into distinct work type clusters, enabling them to correlate new projects with historical data on cost, schedule, pay item production rates, and project complexity. This classification also facilitates the identification of similar projects for project bundling. However, the conventional method for classifying projects into work types is inefficient, relying heavily on subjective judgment and manual review of project scope. This inefficiency hinders SHAs’ ability to effectively apply knowledge gained from historical projects to future projects. Moreover, the subjective nature of project classification is time-consuming and can result in inconsistencies and …

Space Operations Education Research: Studying Undergraduate Experiences As Predictors Of Early Career Performance For Military Space Operations Officers, Keith Balts

All Dissertations

Undergraduate students who go on to operate space systems, e.g., satellites, launch systems, and ground-based systems, come from a diverse set of demographics and undergraduate experiences. The United States Space Force (USSF), and United States Air Force (USAF) before them, like many professions, have a demonstrated interest in who enters their ranks, but have had limited research available to them to inform their recruiting, selection, training, and early career development policies and processes.

This Profession-Based Education Research study, a term introduced here in contrast to Discipline-Based Education Research, focused on the military space operations profession. This study analyzed newly commissioned …

Quantitative Evaluation Of Baseflow Separation Methods Using An Integrated Hydrologic Model: A Case Study In A Snow-Dominated Watershed, Jihad Othman

All Graduate Reports and Creative Projects, Fall 2023 to Present

Baseflow, commonly referred to as the groundwater contribution to streamflow, constitutes approximately 50% of streamflow in mountainous regions of the Western United States. Accurately quantifying the amount of baseflow is critical for water management and decision-making, as it significantly impacts stream water quality, low flow availability, and ecosystem health. Traditionally, baseflow has been estimated using conceptual and automated baseflow separation methods, which are known to be both arbitrary and ambiguous, posing a challenge to validate them. In this study, we developed an integrated hydrologic model that seamlessly integrated the exchange between surface and subsurface flows to physically quantify the baseflow …

Equivalent-Area Studies For Sonic Boom Loudness Mitigation On A Commercial Supersonic Aircraft Configuration, Zachary N. Foster

All Graduate Reports and Creative Projects, Fall 2023 to Present

Since the early 1970s, the FAA has banned commercial supersonic flight over populated areas. This ban has limited aerospace manufacturers’ and commercial aircraft companies’ ability to design and operate subsonic aircraft in their fleets. Since then, research has been conducted to understand the sonic boom and learn how to minimize its loudness. The work presented in this project report aims to use a 1D low-fidelity analysis to study the effect of perturbations to the outer mold line (OML) of a representative model of the N+2 Quiet Commercial Supersonic Concept Aircraft. Using a 1D analysis that employs an equivalent area method, …

Investigating Functionalized Cvd Graphene Heterostructures As Platforms For Hydrogen Gas Sensing, Evans Asiedu Addo-Mensah

Graduate Theses and Dissertations

The hydrogen economy is rapidly advancing and is poised to become one of the world's largest economies, driven by the abundance of hydrogen gas. Several organizations, particularly in the United States of America, are closely or have been monitoring this development, with rapidly increasing interest. Considering that hydrogen gas has no taste, smell (odor), or color, and very combustible, it’s imperative to develop detectors and sensors capable of rapidly detecting leaks to prevent application disasters. Owing to its extraordinary mechanical and electrical characteristics, graphene is the material that has been studied the most. When combined with hexagonal boron nitride (hBN), …

Multimodal Spectroscopy To Study Tumor Microenvironmental Changes In Vivo, April Mordi

Graduate Theses and Dissertations

Every year there are millions of new cancer diagnoses and deaths worldwide. While great strides have been made in technologies and drugs for cancer treatment, there is still a need to understand tumor response to therapy as many patients still endure treatment failure after completing their treatment regimen. Current clinical imaging techniques for detecting response to therapy are utilized weeks to months after the course of treatment, and present limitations to measuring response during treatment. Optical spectroscopy techniques can help meet this need to determine the response of tumors to treatment as it allows for near real-time in vivo characterization …

Causal Discovery In Time Series Data Using Deep Learning Techniques, Saima Zahin Farhana Absar

Graduate Theses and Dissertations

Causal structure learning from observational data has been an active field of research over the past decades. In the literature, different algorithms and models have been proposed, such as constrained-based methods and score-based methods including the emerging deep learning-based methods. However, most of the approaches apply to static and non-dynamic data only. In many applications, the data is temporal. For example, monitoring systems, weather surveillance systems, and stock data, to name but a few. Incorporating temporal information is an important extension of the causal discovery field. With the growth of observational data these days, the discovery of causal relationships from …

Influence Of Glycopolymer Structure On Amphiphilic, Hybrid, Linear Branched Block Copolymer Properties For Use In Biomedical Applications, Kevin Green

Dissertations

The focus of this dissertation is evaluating and adding fundamental knowledge regarding the structure-property relations of glycopolymers used in the design of hybrid block copolymers (HBC) that are cable of self-assembling into delivery vehicles for biomedical applications. A shift to the utilization of natural materials in the design and fabrication of drug-delivery vehicles has garnered significant attention. Understanding the effects of linear glycopolymers content and composition on the resulting HBCs properties can provide valuable insight into how these materials may be tailored for use in targeted biological applications.

The first chapter introduces current literature on the need for improvement in …

Finite Element Analysis And Verification Of Transverse Mechanical Properties Of Generally Cylindrical Orthotropic Constitutive Modeling Of 3-Phase Nanocomposite Unit Cell, Christopher J. Hawkins

Master's Theses

Fiber-reinforced composites are increasingly popular due to their specific strength and stiffness, making them ideal for high-performance applications. However, these materials primarily exhibit superior properties in-plane, while their out-of-plane characteristics remain comparatively weaker. Previous research has shown that the most effective method to enhance out-of-plane properties involves the incorporation of carbon nanotubes. Experimental tests have demonstrated significant improvements in properties such as tension, flexural, short beam shear, and fracture toughness. Alongside these experimental studies, analytical equations have been developed to predict the behavior of these composites under various loading conditions, including tension, bending, shear, and fracture. Existing models primarily address …

Clusteredlog: Optimizing Log Structures For Efficient Data Recovery And Integrity Management In Database Systems, Mariha Siddika Ahmad, Brajendra Panda

Electrical Engineering and Computer Science Faculty Publications and Presentations

In modern database systems, efficient log management is crucial for ensuring data integrity and facilitating swift recovery from potential data corruption or system failures. Traditional log structures, which store operations sequentially as they occur, often lead to significant delays in accessing and recovering specific data objects due to their scattered nature across the log. ClusteredLog addresses the limitations of traditional logging methods by implementing a novel logical organization of log entries. Instead of simply storing operations sequentially, it groups related operations for each data item into clusters. As a result, ClusteredLog enables faster identification and recovery of damaged data items …

Theoretical Advancements In Hawkes Processes And Their Practical Applications, Xi Zhang

Theses and Dissertations

Hawkes self-exciting point processes have been widely used in fields such as seismology, finance and social media analysis. Despite decades of research focusing on these processes, several key aspects remain under-explored. These include broadly applicable methods for model evaluation and selection, intuitive nonparametric inference approaches akin to kernel density estimation for probability density functions, and strategies to enhance the performance of generative point process models in predictive tasks. In this dissertation, first, we extend the time-rescaling theorem, which is traditionally limited to non-terminating processes with complete observations, to accommodate terminating processes and incomplete observations as well. This extension allows for …

Dynamic Key-Based Privacy-Preserving Authentication Scheme For Internet Of Drones, Zain Chaudhary

Honors Theses

The Internet of Drones (IoD) proliferation has catalyzed transformative changes across various industries, from agriculture to urban management. However, expanding drone networks also presents significant security challenges concerning secure communication and authentication. This paper introduces a robust privacy-preserving key-based authentication scheme tailored explicitly for the IoD, utilizing a matrix key generated by Hierarchical Message Authentication Codes (HMAC) and the SHA-256 algorithm to address these vulnerabilities. Our system enhances security by ensuring each drone in the network can authenticate securely and reliably with a central unit, preventing unauthorized access and securing communications against common threats like eavesdropping and impersonation attacks. Our …

Regulating Cox Conversion Through Catalyst Design And Reaction Energy Input, Ewa Chukwu

All Dissertations

Carbon dioxide (CO₂) emissions, primarily from fossil fuel use in energy and chemical production, are the leading driver of global warming. The chemical industry is the third-largest source of these emissions, so reducing its carbon footprint—and ultimately achieving “CO₂ emissions-free” chemical manufacturing—is critical to combating global warming. Thermal catalysis is the workhorse of industrial chemical manufacturing, generating CO₂ emissions from two main sources: the actual chemical transformations of fossil feedstocks and burning of fossil fuels to provide the process heat. Therefore, developing and implementing technologies to mitigate the carbon emissions associated with these emissions sources is essential for decarbonizing the …

Modeling Instrument Design Risks In Medical Device Reprocessing, Manuel Andres Gutierrez

All Dissertations

Medical device reprocessing is an essential practice in healthcare delivery. While FDA regulations require device manufacturers to develop and validate reprocessing procedures, the increasing complexity of medical device designs and their use environments can increase the risks of inadequate reprocessing and associated device malfunctions and potential patient injury. While some design features present known difficulties for reprocessing, critical information needed to define relative risks or feature-specific parameters that increase or decrease risks of inadequate reprocessing is lacking. There is an urgent need for tools to quantify and predict reprocessing risks associated with design features used in surgical instruments.

The broad …

Deformation Mechanism In Gold Nanoparticles Under Compressive Loading: Insights From Atomistic Modelling And Unsupervised Machine Learning, Tanuj Gupta

All Dissertations

Gold nanoparticles (AuNPs) offer exciting possibilities due to their inertness, malleability, and tunable structures, making them valuable for applications ranging from nanomedicine to electronics. Their optical, mechanical, and other properties can be tailored by modifying shape and structure, underscoring the importance of understanding their deformation behaviour at the nanoscale. This study used classical molecular dynamics simulations with LAMMPS to investigate the deformation mechanisms of gold nanospheres (AuNS) under uniaxial compression. Employing the embedded atom method (EAM) potential to model atomic interactions, AuNS with 20 nm in diameter were compressed along the z-direction using planar indenters moving at a constant …

Neural Operator And Physics-Informed Deep Learning Approaches For Inverse Design Of Composites And Manufacturing Processes, Minglei Lu

All Dissertations

In this dissertation, artificial intelligence (AI) models are designed and used to accelerate inverse design of composites and manufacturing processes. The critical bottlenecks in machine learning (ML) including data availability, data quality, model generalization and adaptation, interpretability, physical consistency, and the ’black box’ nature of models for the inverse design are addressed. And the proposed AI models are tested under different engineering scenarios. Firstly, a fast deep neural operator (DNO) structure was developed to significantly reduce training time. This model was tested in the context of additive manufacturing, a transformative industrial technology that allows for the creation of materials with …

Advancing Visual Geometric Perception: Camera-Based Depth, Reconstruction, And Active Vision, Ziyue Feng

All Dissertations

The advancement of autonomous driving technology and intelligent robotic applications has emerged as a focal point in the realm of autonomy. One of the driving forces behind this trend is the profound understanding of the environment, and at the core of this endeavor lies the three-dimensional geometric perception. This dissertation embarks on a comprehensive exploration of this domain, emphasizing the advances of depth prediction, 3D scene reconstruction, and active vision to enhance geometric perception and scene understanding capabilities in autonomous driving, embodied AI, and robotics. In the domain of depth prediction, this research addresses the challenges of accurately inferring three-dimensional …

Investigation Of Conductive Die-Top Thermal Capacitors During Short Circuit Operation Of Silicon Carbide Devices, Youssef Abotaleb

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Silicon carbide (SiC) power devices have garnered significant attention in recent years due to their superior thermal and electrical properties compared to traditional silicon devices. However, SiC power devices suffer from severe reliability issues arising from their mechanical properties. This is because the Young's modulus of SiC is about three times larger than that of silicon, which correspondingly raises the mechanical stresses acting on the bonding structure, often leading to device failure under power shock events.

Traditional packaging materials and designs tend to constrain SiC performance, as hot-spot temperature resulting from a power shock is one of the key factors …

Using Symbolic Execution To Analyze The Hardware Tcp Protocol, Nianhang Hu

School of Computing: Dissertations, Theses, and Student Research

As the demand for high performance and flexible networking capabilities increases, the shift from software to hardware implementations of stateful networking functions (such as TCP) is becoming increasingly important. This transition not only enhances processing efficiency in modern networking environments where data transmission rates are rising, but it also reduces the inherent CPU overhead found in software implementations, allowing hardware devices to handle network traffic more efficiently. However, validating the correctness of these hardware designs poses significant challenges due to the complex timing requirements and the vast input space associated with packet-level properties.

The verification of packet-level properties requires coverage …

Not All Samples Are Created Equal: Task-Aware Informative Sampling And Adaptive Inference For Efficient Edge Ai, Rebati Gaire

School of Computing: Dissertations, Theses, and Student Research

The rapid proliferation of Internet of Things (IoT) devices has resulted in an unprecedented influx of data generated at the edge by billions of sensors. Traditional approaches relying on cloud-based processing are increasingly inadequate due to constraints in bandwidth, latency, and privacy. Edge computing has emerged as a transformative paradigm, enabling real-time data processing and decision-making by decentralizing computation to the edge. While the integration of deep learning into edge environments—termed edge intelligence—promises autonomous and personalized operations, it is hindered by challenges such as limited computational resources, energy constraints, and data redundancies.

This thesis addresses these challenges by presenting three …

Prevalence Of Autism Spectrum Characteristics In Students Taking Undergraduate Computing Courses, Rachel Michaela Mettenbrink

School of Computing: Dissertations, Theses, and Student Research

The incidence rate of autism spectrum condition (ASC) has increased significantly in recent decades, as awareness of the condition and its impacts increases amongst clinicians, parents, and the general population. Medical literature has proposed that there may be a relationship between ASC and participation in the computing field. This study tests for the prevalence of autism spectrum condition traits measured by delivering the Autism Spectrum Quotient (AQ) to a population of undergraduate computer science students. We examine the relationships between AQ scores and students taking undergraduate computer science classes, sex, socioeconomic status, and parents in the computing industry. Additionally, we …

Model Reference Adaptive Control For Mobile Manipulators And Beyond, Srivatsan Srinivasan

All Dissertations

In recent years, robotics has expanded into various sectors, including manufacturing, transportation, and household services, making the integration of autonomy a critical area of research. This shift aims to ensure safety and enhance the utility of autonomous systems. Traditionally, robotic applications focused separately on mobility, like automated guided vehicles, and manipulation, such as serial-chain arms in manufacturing. Today, however, we see a merging of these capabilities in the growing field of mobile manipulator robots that combine movement with purposeful interactive functionalities.

A typical mobile manipulator is a robotic arm mounted on a wheeled base. This thesis focuses on advancing control …