Engineering Commons^™

Discrete-Time Signal Processing, Carl Greco

ATU Faculty OER Books and Materials

No abstract provided.

Experimental Study For Improving Oil Recovery Using Organic Alkaline And Nano-Silica For An Egyptian Oil Field, Attia Attia, Mohamed Sadek Hamedi Al, Mayar Abdelrahman Hassan Eng.

Petroleum Engineering and Gas

The oil and gas industry continually seeks innovative methods to enhance hydrocarbon recovery due to the declining productivity of conventional techniques. Current recovery methods, such as water flooding and chemical flooding, often face limitations like high interfacial tension, unfavorable wettability, and reduced mobility of oil, especially under harsh reservoir conditions of high salinity. To address these challenges, this study explores the implementation of nanotechnology in enhanced oil recovery (EOR), focusing on the distinct and unique properties of nanoparticles. Nanoparticles, particularly SiO2, were chosen for their ability to significantly decrease interfacial tension, alter wettability, and improve oil mobility. SiO2 nanoparticles exhibit …

Solid-State Crystallization Of Zeolites And Their Use In Plastic Upcycling Applications, Yixin Liao

Doctoral Dissertations

Plastics have been an irreplaceable component of modern technology as well as everyday life. They have brought much convenience to us with their characteristics of great malleability, durability, and stability. The versatile and low-cost nature of plastics also enables their wide engagement in many modern industries including automobile, medical, communication as well as aerospace. Polyethylene (“PE”), made from polymerization of ethylene, is one of the most widely used plastics in the world. Being cheap, flexible, and long-lasting, they are extensively used in the packaging industry, especially for plastic bags and other sorts of containers. However, the durability of plastics, on …

Novel Approach To Traveling-Wave-Based Fault Location In Nonhomogeneous Transmission Lines, John Parker Burrell

Master's Theses

Accurate fault location is a critical aspect of power system protection, ensuring grid reliability and minimizing downtime. Traditional traveling-wave-based fault location methods face limitations when applied to nonhomogeneous transmission lines due to the reliance on precise segment velocities and propagation time data. This thesis addresses these challenges by proposing a novel algorithm that leverages historical fault data to estimate segment velocities and refine these estimates as more faults occur. The algorithm was rigorously tested using the digital model of an 11-segment, 65.694 km real overhead transmission line and validated using both simulations and hardware tests using commercially available time-domain protective …

Celebrating Black Women, Ashley S. Mcguire

Patent Coloring Books

Patent coloring book

Gravel Road Performance Enhancement, Bora Cetin, Kristin Cetin, Charan Sai Vangaveeti, Mehdi Bulduk, Md Mahir Asif

Nebraska Department of Transportation: Research Reports

Nearly 30% of roads in the U.S. are unpaved, significantly impacting rural connectivity with Nebraska alone having approximately 75% unpaved roads. This study systematically evaluates local materials to improve gravel road performance, reduce maintenance frequency, and decrease financial burdens on counties. Survey responses revealed that nearly 70% of counties follow NDOT specifications for gravel road design, while more than 90% lack knowledge of local material quality. The most common distresses identified were raveling, loss of crown, dust, and improper drainage. These findings indicate that construction practices rely heavily on experience, rather than systematic design, highlighting the need for a performance-based …

Coe Annual Technical Review 2024, Jianshun Zhang

SyracuseCoE

No abstract provided.

Collaborative Ai: Oer Materials For Exploring Ai As A Partner Rather Than A Tool, David Smith

Open Educational Resources

The Collaborative AI Open Educational Resource (OER) explores how artificial intelligence can act as a creative and analytical collaborator rather than a tool. Centered on the Balanced Blended Space (BBS) framework and the philosophy of the Center for Holistic Integration (CHI), the OER includes curriculum materials, theoretical models, and live research environments. It offers an interesting approach to blending physical, virtual, and conceptual spaces through shared human–AI agency and invites ongoing participation in interdisciplinary meta-projects.

Impact Of Aggregate Characteristics On Frictional Performance Of Asphalt-Based High Friction Surface Treatments, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High Friction Surface Treatments (HFST) are recognized for their effectiveness in enhancing skid resistance and reducing road accidents. While Epoxy-based HFSTs are widely applied, they present limitations such as compatibility issues with existing pavements, high installation and removal costs, and durability concerns tied to substrate quality. As an alternative to traditional Epoxy-based HFSTs, this study investigated the effects of aggregate gradation as designated by agencies on the performance of asphalt-based HFST. Various aggregate types were assessed to evaluate friction performance and the impact of polishing cycles on non-Epoxy HFST. It was found that adjustments in aggregate size and gradation may …

Real-Time Prediction Of Dynamical Systems Using A Hybrid Analog Computer: Network Traffic Modeling, Majd Zuhair Tahat

Doctoral Dissertations

As the number of online users grows exponentially, the number and severity of cyber threats escalate, urgently requiring advancements in real-time network modeling and response. Swiftly predicting and analyzing network traffic is crucial for effective network monitoring and control, preventing cyber breaches, and maintaining healthy network functionality. This research presents a novel approach to real-time modeling based on analyzing evolving properties and patterns in a dynamical network system using a hybrid analog-digital computer. An analog computer was utilized as a co-processor to compute differential equations that model the Transmission Control Protocol (TCP) window size. A comparative analysis was conducted between …

A Human-In-The-Loop Framework For Scalable And Interpretable Event Triaging In Large-Scale Systems, Ibrahim Khaled Al-Agha

Doctoral Dissertations

This dissertation presents a comprehensive and scalable framework for real-time fault detection and event triage in industrial systems, addressing critical challenges such as class imbalance, ambiguous feature boundaries, and the prioritization of complex, high-dimensional event data. The proposed framework integrates advanced methodologies, including micro-batch processing, retrospective divergence-based event detection (DB-RED), association rule mining (ARM), clustering, and Dempster-Shafer Theory (DST) for conflict resolution. Together, these components enable the systematic stratification of events into actionable priority levels, ensuring robust and interpretable decision-making in real-time environments. DB-RED forms the cornerstone of the framework, leveraging KL-divergence and PE-divergence metrics to detect subtle and transient …

Creating A Framework To Develop Project-Based Platforms To Support Engineering And Technology Education, Casey Daniel Kidd

Doctoral Dissertations

Engineering education has evolved over the last few decades to increasingly include project-based learning (PBL) throughout the curriculum to give students more hands-on experience. However, there can be a hesitancy from faculty and instructors to move from traditional lectures to PBL-based curricula. Research has been conducted to identify barriers to research-based instructional strategies (RBIS), which include PBL. However, this research does not go into depth about the specific barriers for these individual RBIS. Furthermore, it has been found that the adoption of a new practice within a community has more success through a propagation paradigm, where the change agents are …

Designing Pull-Based Energy System Rules For Public Buildings: An Application Of Modularity, Lei Wang

Dissertations and Theses Collection (Open Access)

Building energy systems, particularly Heating, Ventilation, and Air Conditioning (HVAC) systems, play a pivotal role in global sustainability efforts. Yet, traditional centralized HVAC systems continue to face major challenges: high energy consumption, significant operational costs, and limited adaptability to dynamic energy demands. These inefficiencies are compounded by the difficulty of integrating renewable energy sources into outdated system designs. As a result, substantial energy waste persists, posing obstacles to cost-effective, environmentally sustainable building operations.

This dissertation proposes a modular, pull-based energy framework to address these critical challenges. By combining the principles of modularity theory with demand-driven energy distribution, the framework enables …

Life Safety In The Reliability-Based Design And Assessment Of Structures, Mahesh Pandey, Celeste Viljoen, Andrew Way, Katharina Fischer, Miroslav Sykora, Dimitris Diamantidis, Raphael D. J. M. Steenbergen, Niels Lind, Dan M. Frangopol, David Y. Yang, Multiple Additional Authors

Civil and Environmental Engineering Faculty Publications and Presentations

We review the developments in life safety and the incorporation thereof in the design and assessment of structures over the last 50 years. Various measures of life safety are presented that have been developed according to the marginal life saving cost principle based on individual, societal and economic considerations. Target probabilities of failure, or target reliabilities, are central to modern structural design and assessment. These are derived either through back-calibration to existing practice or through life cycle cost minimisation, both of which yield comparable safety levels, and are underpinned by lower bounds from life safety. Life cycle cost minimisation is …

Scshm Benchmark Study On Bridge In-Service Structural Monitoring, Maria Pina Limongelli, Doug Thomson, Screenevas Alampalli, Aftab Mufti, Thomas Schumacher, Luca Martinelli, Othmane Lasri, Harry Shenton, Genda Chen, Mohammad Noori, Multiple Additional Authors

Civil and Environmental Engineering Faculty Publications and Presentations

The mission of the Society of Civil Structural Health Monitoring (SCSHM, previously known as ISHMII) is to advance the understanding and application of structural monitoring methodologies for the management of civil infrastructure systems. To enable comparative and contrasting studies of various monitoring issues and technologies, the SCSHM Committee on Data-Enhanced Infrastructures Management (DEIMC) identified the need for benchmark problems in the areas of bridge and building structural monitoring. This article reports and briefly discusses the first benchmark study on in-service structural monitoring of bridges that was developed in collaboration with the University of Manitoba, and presents the structure details, study …

A Low-Carbon Approach For Lime Production Using Self-Propagating High Temperature Synthesis-Driven Limestone Calcination, Shubham Agrawal, Sayee Srikarah Volaity, Srinivas Kilambi, Aditya Kumar, Narayanan Neithalath

Materials Science and Engineering Faculty Research & Creative Works

Limestone calcination produces calcium oxide (or lime), that forms the basis for the manufacturing of many critical engineering materials such as cement and iron-and-steel. Limestone calcination—an endothermic reaction—is regarded as one of the most energy-and-CO₂ intensive industrial chemical reactions, and is facilitated by fossil fuels, since the high temperature requirement (∼900 °C) renders it less conducive to electrification through renewable energy sources. In this study, a novel, low-temperature (∼450 °C) pathway for ultrafast calcination of limestone using combustion synthesis or self-propagating high-temperature synthesis (SHS) is developed. SHS leverages exothermic heat from the combustion of lignin or biomass—as low-carbon fuels—mixed …

Artificial Intelligence And Internet Of Things Integration In Pharmaceutical Manufacturing: A Smart Synergy, Reshma Kodumuru, Soumavo Sarkar, Varun Parepally, Jignesh Chandarana

Michigan Tech Publications

Background: The integration of artificial intelligence (AI) with the internet of things (IoTs) represents a significant advancement in pharmaceutical manufacturing and effectively bridges the gap between digital and physical worlds. With AI algorithms integrated into IoTs sensors, there is an improvement in the production process and quality control for better overall efficiency. This integration facilitates enabling machine learning and deep learning for real-time analysis, predictive maintenance, and automation—continuously monitoring key manufacturing parameters. Objective: This paper reviews the current applications and potential impacts of integrating AI and the IoTs in concert with key enabling technologies like cloud computing and data analytics, …

Development Of Measures For Highway Criticality Assessment, Xu Zhang, Mei Chen

Kentucky Transportation Center Research Report

Existing network criticality assessments, often biased towards heavily used highways in populous areas by incorporating traffic and sociodemographic attributes, can lead to an underestimation of the vital role of rural infrastructure. Consequently, rural highways, particularly low-volume roads, often receive less consideration despite their critical role in network connectivity and local access to services and economic opportunities. To address this, we develop a criticality framework based on the egalitarian principle, which prioritizes equitable consideration of all network links regardless of traffic volume or population density, comprising two complementary measures. First, the normalized betweenness centrality quantifies a road's relative importance in efficiently …

Efficacy Of Immersive Virtual Reality Gameplay In Environmental Attitude Change: The Case Of Abandoned Offshore Oil Platforms In Santa Barbara, Arun Prasad Srinivasan Manoharan

Master's Theses

Public perception plays an important role in shaping conservation policies and decisions, especially in contested environmental spaces. Offshore oil platforms, historically viewed as environmental hazards, have been found to serve as marine habitats that support diverse marine life. However, public perception remains largely negative, influenced by concerns over pollution from past oil spill accidents. Traditional environmental education methods, such as lectures and documentaries, often fail to engage audiences effectively or shift entrenched opinions. This study explores the efficacy of immersive Virtual Reality (VR) gameplay in changing environmental attitudes, specifically in the context of abandoned offshore oil platforms in Santa Barbara, …

Performance Of Neural Networks On Fpga For Embedded Devices Using Hls4ml Framework, Alam N. Romo Lopez

Master's Theses

As machine learning models such as neural networks are investigated for their applications across many fields, the demand for models that can be implemented on an embedded device grows. Field Programmable Gate Arrays (FPGAs) have become an attractive option for implementing these models in hardware. This thesis considers the viability of FPGA implementations for machine learning on low-resourced embedded systems. The hls4ml project is a promising prospect for machine learning on FPGA devices. To test hls4ml, we used a model trained on the MNIST digits dataset, which was then synthesized for the PYNQ-Z2 device. We fine tuned the performance by …

Reentry Vehicle Trajectory Analysis & Performance (Re-Tap) Development And Application To Spacex Starship, Emma L. Webb

Theses and Dissertations

A modeling simulation tool for exo-to-endo atmospheric flight is developed to characterize errors associated with varying simulation fidelities from 3 to 6 degrees-of-freedom (DOF). Engineering approximation errors are quantified and compared with flight data from Apollo 10 and the first Space Shuttle Orbiter reentry (STS-1). The reentry reachability optimal control problem (OCP) is formulated in 6DOF and compared with point-mass solutions, revealing that point-mass solutions oversimplify the problem. A cylindrical reentry vehicle (CRV-1), similar to the SpaceX Starship, is introduced with necessary details for 6DOF analysis. The performance and reentry control capabilities of CRV-1 are captured through 6DOF solutions of …

Palindrome: A Bi-Directional Multi-Object Detection Framework For Relative Navigation And Autonomous Docking, Liam A. Weinfurtner

Theses and Dissertations

This work introduces a bi-directional, multi-object detection framework that integrates pose estimates from both receiver- and tanker-mounted cameras to improve accuracy and redundancy. A modular YOLO-based detection pipeline is trained using synthetic and real imagery, leveraging a bootstrap transfer learning approach to enhance sim-to-real performance. System evaluation in both virtual and real-world environments demonstrates improved detection robustness, pose estimation accuracy, and scalability. These advancements contribute to the development of AI-driven vision systems for AAR and other autonomous docking applications.

Misalignment Uncertainty In Near-Field Thz Scattering Experiments, Philip Patterson

Theses and Dissertations

This research investigates the effect of misalignment on the near-field scattering of cylinders in the 550-700 GHz frequency band. A Type-1 calibration is performed on previously collected data, using a near-field physical optics solution to simulate scattering at various positions and orientations. The alignment of the cylinders at the time of measurement is predicted by comparing the range profiles of the theoretical and calibrated responses. The data with the most similar range profiles had a mean calibration difference metric of -2.78 dB and a standard deviation of -0.57 dB, demonstrating the presence of sources of error that are dominant over …

Improvement Of Microcracking And Mechanical Properties Of Tungsten Fabricated Via Laser Powder Bed Fusion Through Alloying With Reactive Secondary Constituents, William S. Mockel

Theses and Dissertations

Tungsten (W), a Group VI transition metal, possesses a number of advantageous properties, most notably its impressive mechanical performance at extreme temperatures. While tungsten's nature render traditional manufacturing methods difficult, additive manufacturing through laser powder bed fusion (LPBF) presents a promising avenue for fabricating tungsten components. However, the material’s high ductile-to-brittle transition temperature combined with the embrittling effect of impurities mean that the residual stresses imparted by LPBF result in microcracking in tungsten, degrading its usefulness. This study sought to improve the characteristics of LPBF-W through the removal of embrittling oxygen content via alloying with low concentrations of reactive elements, …

Mechanical Response Of Triply Periodic Minimal Surface Gyroid Structures Under Combined Loading, Jay B. Patel

Theses and Dissertations

This work explored combined tensile and torsional loads applied to additively manufactured Inconel 718 specimens employing Triply Periodic Minimal Surface (TPMS) structures. The gyroid TPMS unit cell was selected with two variations of cylindrical cell maps, a rectangular cell map, and a spherical cell map. All four variants were tested in an axial-torsion test frame at room temperature using equal parts of vertical and angular displacement control until failure. The combined loading in these tests utilized tension and torsion. The data from the tests were compared to finite element analysis (FEA) models to visualize when yielding was predicted. Finally, the …

Impact Of Stochastic Travel Times On The Military Port Selection Problem: A Stochastic Programming Approach, William M. Titus

Theses and Dissertations

This research models and analyzes the impact of stochastic travel times on port selection during a large-scale mobilization of equipment from continental United States installations to deployment locations using sealift ships. A stochastic mixed-integer programming model is developed to minimize the average arrival time of equipment into theater. The model is solved using Sample Average Approximation. In the first stage, the model selects ports to open and assigns installations, equipment, and ships to open ports. In the second stage, travel times are realized, and equipment is assigned to specific ships that are scheduled to depart. Results show that the marginal …

The Location Set Covering Disruption Problem, Richard A. Sheldon

Theses and Dissertations

This research models and analyzes a variant of the Location Set Covering Problem (LSCP) in a bilevel, game theoretic setting by posing the LSCP as a non-cooperative attacker-defender Stackelberg game, where facilities are to be emplaced by the defender from a boarder set of potential facility locations to cover a set of demands; however, an attacker removes the possibility of emplacing q specific facility locations with the objective to remove the maximum weighted value demands, and then lexicographically maximize the cost of coverage of remaining demands. A novel methodology leveraging lexicographic programming computed an optimal solution for 98% of all …

Forecasting Army Recruiting Mission Distribution, Maxwell A. Deihl

Theses and Dissertations

The Army’s recruiting landscape has changed markedly in recent years, raising questions about whether forecasting methods of Army contracts remain robust. This thesis recreates the presented models in Joshua McDonald’s 2015 thesis. It replicates and evaluates the models with updated data (2018–2023) to assess their current validity and compare them to novel alternative approaches, such as simpler regression models or neural networks. While the 2015 model remains a valuable baseline, results suggest that either refining its variables or adopting alternative methods can improve predictive accuracy and interpretability. Ultimately, the United States Army Recruiting Command has many options regarding how it …

Machine Learning Techniques To Detect Anomalies In T-38 Flight Sensor Data, Sydney M. Wekamp

Theses and Dissertations

Accurate sensors are critical for ensuring the safety of aircrew. However, detecting faulty sensors remains a significant challenge for the Test Pilot School at Edwards Air Force Base in California. Current methods rely on either student pilots identifying anomalies or waiting for sensors to fail completely before repairs are made—an approach that lacks reliability and consistency. This research aims to address these shortcomings by implementing machine learning techniques to detect sensor faults proactively. To date, applying machine learning to a dataset of this size, encompassing numerous sensors on the same aircraft, is unprecedented. The project focuses on establishing strong baseline …

Hyperparameter Tuning For Robust Autonomous Vehicle Vision, Nico D. De Ros

Theses and Dissertations

Classification “flickering,” where the classification of an object changes inconsistently between consecutive video frames, remains a persistent issue in modern object classification algorithms. This problem undermines the reliability of autonomous vision systems and poses significant risks in high-stakes applications such as autonomous vehicles. This thesis explores the use of response surface methodology, a statistical design of experiments technique, to optimize hyperparameters across three object classification pipelines. The first pipeline combines YOLOv8 with SORT to establish a benchmark. The second integrates a Bayesian back-end, while the third employs an exponential smoothing back-end. Hyperparameter tuning was conducted using a two-step process: an …