Engineering Commons^™

Effect Of Size And Shape Parameters On Microstructure Of Additively Manufactured Inconel 718, Showmik Ahsan

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Additive Manufacturing (AM) methods are promising in applications where complex part geometries, exotic materials and small lot sizes are required. Aerospace manufacturing stands to use AM methods extensively in the future, and frequently requires temperature- and corrosion-resistant alloy materials such as Inconel 718. However, the microstructural evolution of Inconel 718 during additive manufacturing is poorly understood and depends on part size and shape. We studied the microstructure of Inconel 718 parts manufactured by Laser Powder Bed Fusion in order to further elucidate these dependencies. Microstructural analysis, SEM imaging, EBSD scans and Microhardness testing were performed.

Rankine Cycle Investigation On Meeting Power And Thermal Requirements Of High-Speed Aircraft, Jacob J. Spark

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This work is investigating a dual mode Rankine cycle for aircraft applications, specifically meeting vehicle thermal and power requirements. This multiconfigurational approach allows the Thermal Management System (TMS) to be controlled based on aircraft needs. In this design, waste heat is removed from critical areas of the aircraft (e.g., propulsion, structure, subsystems) using the fuel as a heat sink. Hot fuel is then forced through a heat exchanger actively boiling water. The vapor byproduct is fed to a turbine coupled to a generator, providing power. The low-pressure steam is then condensed using cold fuel drawn from its tank; however, when …

Multi-Variable Phase And Gain Calibration For Multi-Channel Transmit Signals, Ryan C. Ball

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A method for software-defined radio array calibration is presented. The method implements a matched filter approach to calculate the phase shift between channels. The temporal stability of the system and calibration coefficients are shown through the standard deviation over the course of four weeks. The standard deviation of the phase correction was shown to be less than 2 deg. for most channels in the array and within 8 deg. for the most extreme case. The standard deviation in amplitude scaling was calculated to be less than 0.06 for all channels in the array. The performance of the calibration is evaluated …

Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams

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Most of today’s time series data contain anomalies and multiple seasonalities, and accurate anomaly detection in these data is critical to almost any type of business. However, most mainstream forecasting models used for anomaly detection can only incorporate one or no seasonal component into their forecasts and cannot capture every known seasonal pattern in time series data. In this thesis, we propose a new multi-seasonal forecasting model for anomaly detection in time series data that extends the popular Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Our model, named multi-SARIMA, utilizes a time series dataset’s multiple pre-determined seasonal trends to increase …

Comparative Study Of Mof's In Phosphate Adsorption, Eniya Karunamurthy

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High concentrations of phosphate are known to adversely affect the environment. Excess phosphate can lead to eutrophication that eventually fosters uncontrollable growth of aquatic plants and algae. This can result in depletion of oxygen content which adversely impacts underwater organism’s survival rates. Metal organic frameworks (MOFs) consist of organic linkers in conjunction with metal ions or clusters arranged within a crystalline structure. They are highly porous and have larger surface area due to their ability to possess extensive void spaces while remaining bulky in nature. MOFs can absorb phosphate from aqueous solutions. We have investigated the use of commercially available …

Path-Safe: Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan

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Deploying Mandatory Access Controls (MAC) is a popular way to provide host protection against malware. Unfortunately, current implementations lack the flexibility to adapt to emergent malware threats and are known for being difficult to configure. A core tenet of MAC security systems is that the policies they are deployed with are immutable from the host while they are active. This work looks at deploying a MAC system that leverages using encrypted security tokens to allow for redeploying policy configurations in real-time without the need to stop a running process. This is instrumental in developing an adaptive framework for security systems …

Characterization Of Aerosol Jet Printed Silver Thin Films Sintered By A Scanning Laser, William A. Metzger

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Direct write printing, which is part of additive manufacturing (AM) technology, offers unique capabilities that can complement traditional methods of electronics fabrication. Printing of electrical interconnects via aerosolization is one of the areas in AM that is very important in electronics fabrication. Post-print sintering is a critical step in printed electrical interconnects because it strongly influences the electrical resistivity of the interconnects. Interconnects require the lowest possible resistivity to achieve better performance. Thermal sintering is the most common technique employed in printed interconnects. However, it is limited to substrates that can handle the high temperature requirement for sintering. For polymers …

Fault Diagnosis And Accommodation In Quadrotor Simultaneous Localization And Mapping Systems, Anthony J. Green

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Simultaneous Localization and Mapping (SLAM) is the process of using distance measurements to points in the surrounding environment to build a digital map and perform localization. It has been observed that featureless environments like tunnels or straight hallways will cause positioning faults in SLAM. This research investigates the fault diagnosis and accommodation problem for a laser-rangefinder-based SLAM systems on a quadrotor. A potential solution of using optical flow as velocity estimate and an extended Kalman filter (EKF) to perform position estimation is proposed. A fault diagnosis method for detecting faults in positional SLAM data or optical flow velocity data is …

Digital Beamforming Array Phase Calibration Techniques For Multi-Pass Interferometric Sar, Kelly Cheung

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Calibration plays a critical role in the optimal performance of algorithms in digital beamforming arrays. Phase incoherency between elements results in poor beamforming with decreased gain and higher sidelobes, leading to a decrease in accuracy and sensitivity of measurements. A similar problem exists in performing multi-pass interferometric SAR (IFSAR) processing of SAR data stacks to generate topological maps of the scene, where phase errors translate to height errors. By treating each SAR image in the data stack like an element of a uniform linear array, this thesis explores several phase calibration techniques that can be used to calibrate digital beamforming …

A Machine Learning Framework For Hypersonic Vehicle Design Exploration, Atticus Beachy

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The design of Hypersonic Vehicles (HVs) requires meeting multiple unconventional and often conflicting design requirements in a hostile, high-energy environment. The most fundamental difference between ordinary aerospace design and hypersonic flight is that the extreme conditions of hypersonic flight require parts to perform multiple functions and be tightly integrated, resulting in significant coupled effects. Critical couplings among the disciplines of aerodynamics, structures, propulsion, and thermodynamics must be investigated in the early stages of design exploration to reduce the risk of requiring major design changes and cost overruns later. In addition, due to a lack of validated test data within the …

Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal

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Heart failure is a syndrome which effects a patient’s quality of life adversely. It can be caused by different underlying conditions or abnormalities and involves both cardiovascular and non-cardiovascular comorbidities. Heart failure cannot be cured but a patient’s quality of life can be improved by effective treatment through medicines and surgery, and lifestyle management. As effective treatment of heart failure incurs cost for the patients and resource allocation for the hospitals, predicting length of stay of these patients during each hospitalization becomes important. Heart failure can be classified into two types: left sided heart failure and right sided heart failure. …

Bandgap Engineering Of 2d Materials And Its Electric And Optical Properties, Kumar Vishal

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Since their invention in 1958, Integrated Circuits (ICs) have become increasingly more complex, sophisticated, and useful. As a result, they have worked their way into every aspect of our lives, for example: personal electronic devices, wearable electronics, biomedical sensors, autonomous driving cars, military and defense applications, and artificial intelligence, to name some areas of applications. These examples represent both collectively, and sometimes individually, multi-trillion-dollar markets. However, further development of ICs has been predicted to encounter a performance bottleneck as the mainstream silicon industry, approaches its physical limits. The state-of-the-art of today’s ICs technology will be soon below 3nm. At such …

Investigation Of Surface Roughness Effects On Additively Manufactured Metals Under Dynamic Loading, Rachel Elizabeth Tullis

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The as-printed surfaces of parts produced through laser powder bed fusion are significantly rougher than surfaces produced through traditional manufacturing processes. This increased roughness can have a significant impact on mechanical properties, with perhaps the most notable detriment in the fatigue life of the part. Therefore, the as-printed surface roughness in additively manufactured materials must be studied more extensively to determine its impact on fatigue performance. This work investigates the surface roughness of additively manufactured specimens through the investigation of processing parameters and their effects on surface roughness in metal additive manufacturing. Furthermore, the relationships between as-printed surface roughness and …

Kv2.1 Dysfunction Underlies The Onset Of Symptoms In Sod1-G93a Mouse Model Of Als, Andrew J. Deutsch

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Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease which targets motoneurons (MNs), yet underlying disease mechanisms are not well understood. Evaluating the intrinsic excitability of MNs in ALS could lead to a better understanding of mechanisms causing neurodegeneration. The SOD1-G93A (SOD) model is the most commonly studied animal model of ALS. However, past studies have shown highly conflicting results on SOD MN excitability. Interestingly, I show that depending on the level of membrane depolarization, SOD MNs show opposite results of both hyper- and hypo-excitability. This reveals that differences in the methodology of measuring excitability can heavily impact the study results. …

Lipin1 Improves Membrane Integrity In Dystrophic Muscles Of Mdx Mice, Abdulrahman Jama

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Duchenne muscular dystrophy (DMD) is an X-linked genetic disorder that affects 1 in 3500 male births worldwide. It is characterized by mutations in the dystrophin gene that results in the loss of functional dystrophin. Dystrophin deficiency leads to instability of the sarcolemma alongside increased inflammation, necrosis and fibrosis resulting in membrane rupture and eventual muscle fiber death. There are currently no effective treatments for DMD. Here we show that Lipin1 expression is significantly downregulated at the mRNA and protein levels in gastrocnemius muscle of mdx mice, the DMD mouse model. Lipin1 has a dual function as a phosphatidic acid phosphatase …

Dna Instability At (Attct) Microsatellites In Human Cells, Venicia Alhawach

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Microsatellites are short tandem repeats of DNA (1-9 nucleotides) that are unstable in the genome. They can expand and contract which leads to mutations and rearrangements that jeopardize genomic integrity. When encountered by a replication fork, repeats of these microsatellites can form non-B DNA structures which cause replication forks to stall and collapse eventually leading to double stranded breaks (DSBs) and replication stress. One form of repair of replication dependent DSBs happens via break induced replication (BIR), a highly mutagenic repair pathway. The main objective of this study is to understand how ATTCT pentanucleotide repeats affect replication and chromosomal instability …

Understanding And Enhancing The Efficiency And Efficacy Of Machine Learning-Assisted Software Vulnerability Detection, Daniel J. Grahn

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As our world has become dependent upon software for nearly every aspect of modern society, software security has followed as an essential feature. The first line of defense against vulnerabilities is secure coding. While today’s programmers are carefully taught secure coding best practices, they can make mistakes or intentionally introduce vulnerable code. The traditional backstop to human errors and insider threats is the adoption of automated security analysis tools. These analysis tools have limitations. Static analysis suffers from high false positive rates that may cause annoyance and complacency among developers. Dynamic analysis can be difficult to set up and very …

Microsatellite Induced Genomic Instability And Mutagenesis Through Break Induced Replication, Rujuta Yashodhan Gadgil

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Faithful DNA replication is essential to maintain genomic integrity. Compromises in this process are among the prime causes of cancer and other genetic disorders. Among several factors that can interfere with error-free DNA replication, the formation of non-B DNA structures by microsatellite sequences is critical. Microsatellites are 1-9 bp long tandem repetitive regions that can form secondary structures like hairpins, triplex, Gquadruplex etc. and undergo expansions due to replication fork stalling to cause several diseases. Hairpin forming microsatellites have been shown to induce DNA DSBs and lead to genetic instability and mutagenesis. The goal of this study is to understand …

Building Services Engineering January/February 2023

Building Services Engineering

No abstract provided.

Seamless Air Travel: Siproavi's Technological Advancements, Mohammed Owais

Student Works

Siproavi's Role in Revolutionizing Air Travel: In our pursuit of revolutionizing air travel, Siproavi introduces a comprehensive suite of services catering to seasoned travelers and newcomers alike:

Ticket Booking: Our user-friendly platform empowers travelers to swiftly search, compare, and book flights that align seamlessly with their preferences and schedules. This service has substantially reduced booking time for travelers, often completing the process within 2 minutes.

Baggage Handling: We have conquered the age-old woes of baggage handling. Siproavi's cutting-edge services ensure the safety and security of your belongings from check-in to arrival, resulting in a 30% decrease in baggage-related complaints. …

Mixing, Metabolism, And Climate Change: A Modeling Case Study Of A Shallow Hypereutrophic, Polymictic Lake, Benjamin C. Reuss

Dissertations, Master's Theses and Master's Reports

Globally, lakes are sites of significant carbon cycling, respiring an estimated 0.07 to 0.15 Pg as CO2 and sequestering 0.03 to 0.07 Pg C in sediments annually. These processes can be affected by nutrient availability, with seasonal mixing regulating nutrient transport in monomictic and dimictic systems. However, the effect of intermittent mixing on ecosystem production in polymictic systems has been much less studied. The timing and frequency of lake mixing are expected to be altered by climate change, which has the potential to impact nutrient transport. The first chapter of this thesis introduces lake mixing dynamics and indices of mixing. …

Neuroevolution And Machine Learning Research Applied To Connected Automated Vehicle And Powertrain Control, Frédéric F. Jacquelin

Dissertations, Master's Theses and Master's Reports

This dissertation focuses on advancing Predictive Energy Management (PrEM) functions applied to modern connected and automated vehicles (CAV) cohorts. PrEM aims to utilize connectivity and ADAS functions to adaptively minimize vehicle energy consumption in a wide array of operations, extending the original control designed around a reduced set of test cycle procedures to adapt to real-world stochastic operating conditions. This research document is built upon three journal publications covering two PrEM schemes; the global cohort and local vehicle optimization paths. Both optimal control solutions are generated using various Neuroevolution centric processes.

Chapter 1 discusses the methods and reasoning behind the …

Memory Optimizations For High-Throughput Computer Systems, Zhiyuan Lu

Dissertations, Master's Theses and Master's Reports

The emergence of new non-volatile memory (NVM) technology and deep neural network (DNN) inferences bring challenges related to off-chip memory access. Ensuring crash consistency leads to additional memory operations and exposes memory update operations on the critical execution path. DNN inference execution on some accelerators suffers from intensive off-chip memory access. The focus of this dissertation is to tackle the issues related to off-chip memory in these high performance computing systems.

The logging operations, required by the crash consistency, impose a significant performance overhead due to the extra memory access. To mitigate the persistence time of log requests, we introduce …

Interest-Based Recommendation System Using Gmail Topic Modelling, Pranav Ghaskadbi

Master's Projects

Emails are a fundamental part of modern communication. Much of communicative discourse in modern society occurs over email, resulting in personal collections for each mail user which are rich in latent user’s interests. Conventional recommendation systems require historical data of user activity and interactions to derive user interests. The absence of activity and interaction data poses an interesting challenge for generating relevant recommendations for users. We were motivated to investigate approaches to identify user interests in the absence of historical data to generate personalized content recommendations. There is opportunity to derive user interests from email data, which can be used …

Identifying Potential Alzheimer’S Disease Biomarkers Beyond Amyloid-Beta And Tau, Frank Cai

Master's Projects

Alzheimer's Disease (AD) and other forms of Mild Cognitive Impairment (MCI) affect millions of people around the world. The buildup of Amyloid-Beta (Aβ) and Tau proteins in the brain produced by amyloid precursor protein (APP) has been identified as an important cofactor in the onset and progression of AD. However, although patients diagnosed with AD exhibit Aβ and Tau buildup, about 40% of the subjects with Aβ and Tau buildup are not diagnosed with AD. In this project, we hypothesize the involvement of other epigenetic interactions between APP and related genes in addition to the buildup of Aβ and Tau …

Development Of Automated Egg Incubator With Backup Power Supply, Allen N. Maroma, Dolly P. Maroma, Bernardo A. Pangilinan

ASEAN Journal of Community Engagement

This study addresses the development of an automated egg incubator with backup power supply that could benefit farmer communities through the developmental research approach. A prototype is developed to respond to the needs for uninterrupted incubation which is affected by the frequent power outages that reduce its efficiency in egg handling. In this project, the automated egg incubator with a backup power supply is designed to hatch a capacity of 150 eggs (75 setters and 75 hatchers) every 21 days, ensuring continuous operation even in the absence of a consistent power supply. An inverter, connected to a battery, ensures a …

A Survey Of Vision And Force Guidance In Robot Manipulation, Yicheng Zhu, Xiaoyi Wu, Qiyu Meng, Yun-Hsuan Su, Biao Zhang, Kevin Huang

Engineering: Faculty Publications

This manuscript provides a survey of seminal and state-of-the-art methods for visual guidance and force control in robotic manipulation, with particular interest in combined vision and force methods. Other reviews outline similar methods; however, they present outdated approaches and thus lack recent pertinent breakthroughs. The purpose of this report, therefore, is to provide a holistic review of the most recent research advances in vision and force integration for robotic manipulation and the supporting prior art they rely on. In this document, both visual guidance and force control methods are explored from a historical perspective. Additionally, the general technical approaches to …

Computational Investigation Of A Series Of Small Molecules As Potential Compounds For Lysyl Hydroxylase-2 (Lh2) Inhibition, Yazdan Maghsoud, Erik Antonio Vázquez-Montelongo, Xudong Yang, Chengwen Liu, Zhifeng Jing, Juhoon Lee, Matthew Harger, Ally K. Smith, Miguel Espinoza, Hou-Fu Guo, Jonathan M. Kurie, Kevin N. Dalby, Pengyu Ren, G. Andrés Cisneros

Markey Cancer Center Faculty Publications

The catalytic function of lysyl hydroxylase-2 (LH2), a member of the Fe(II)/αKG-dependent oxygenase superfamily, is to catalyze the hydroxylation of lysine to hydroxylysine in collagen, resulting in stable hydroxylysine aldehyde-derived collagen cross- links (HLCCs). Reports show that high amounts of LH2 lead to the accumulation of HLCCs, causing fibrosis and specific types of cancer metastasis. Some members of the Fe(II)/αKG-dependent family have also been reported to have intramolecular O2 tunnels, which aid in transporting one of the required cosubstrates into the active site. While LH2 can be a promising target to combat these diseases, efficacious inhibitors are still lacking. We …

A Phase Change Memory And Dram Based Framework For Energy-Efficient And High-Speed In-Memory Stochastic Computing, Supreeth Mysore

Theses and Dissertations--Electrical and Computer Engineering

Convolutional Neural Networks (CNNs) have proven to be highly effective in various fields related to Artificial Intelligence (AI) and Machine Learning (ML). However, the significant computational and memory requirements of CNNs make their processing highly compute and memory-intensive. In particular, the multiply-accumulate (MAC) operation, which is a fundamental building block of CNNs, requires enormous arithmetic operations. As the input dataset size increases, the traditional processor-centric von-Neumann computing architecture becomes ill-suited for CNN-based applications. This results in exponentially higher latency and energy costs, making the processing of CNNs highly challenging.

To overcome these challenges, researchers have explored the Processing-In Memory (PIM) …

Establishing The Foundation To Robotize Complex Welding Processes Through Learning From Human Welders Based On Deep Learning Techniques, Rui Yu

Theses and Dissertations--Electrical and Computer Engineering

As the demand for customized, efficient, and high-quality production increases, traditional manufacturing processes are transforming into smart manufacturing with the aid of advancements in information technology, such as cyber-physical systems (CPS), the Internet of Things (IoT), big data, and artificial intelligence (AI). The key requirement for integration with these advanced information technologies is to digitize manufacturing processes to enable analysis, control, and interaction with other digitized components. The integration of deep learning algorithm and massive industrial data will be critical components in realizing this process, leading to enhanced manufacturing in the Future of Work at the Human-Technology Frontier (FW-HTF).

This …