Engineering Commons^™

Developing Workflows For Passive Acoustic Detection Of Bedload Transport, Quinn Morgan

Dissertations and Theses

Bedload transport is defined as the amount of sediment, including gravel and rocks, traveling down stream. Monitoring bedload transport is important for river safety, hydrological studies and conservation efforts. Existing methods of directly measuring bedload transport (or bedload flux) involve lowering a collection device into a river and measuring the sediment collected; which can be expensive and time consuming. Hydroacoustic sensors, such as hydrophones, have had success tracking bedload flux remotely. This works by measuring the relatively high frequency of sediment impacts to map onto total bedload transported. No perfected method for detection of sediment generated noise (SGN) currently exists. …

Nitric Oxide Radiometer Development, Deron Scott, Phil Scott, Trent Newswander, Marty Mlynczak

Space Dynamics Laboratory Publications

SDL developed a small satellite payload to support the NICEcube mission concept capable of measuring vertical profiles of infrared radiance at 5.3 µm from nitric oxide (NO) in the atmospheric limb (100-250 km). These radiance measurements can be directly inverted to achieve vertical profiles of infrared cooling rates which are crucial to understanding the density response to the thermosphere in times of elevated geomagnetic activity. The payload was designed to fit on a 12U cube sat, function at low power and small mechanical envelope. Completed work includes building the telescope, integrating a representative detector, alignment, test planning, and initial testing. …

Ferric Metal-Organic Frameworks (Mofs)-Based Electrospinning Fibers For Supercapacitors, Samar A. Salim, Hani Nasser Abdelhamid

Nanotechnology Research Centre

Ferric-based metal-organic frameworks (Fe-MOFs) were synthesized and incorporated into poly(methyl methacrylate) (PMMA) using electrospinning to produce PMMA_Fe-MOF nanofibers. The materials were analyzed using X-ray diffraction (XRD), attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR), and scanning electron microscopy (SEM). The electrospun materials were directly integrated into nickel foam (NF) electrodes for energy storage applications, e.g., supercapacitors. The electrochemical performance was assessed using cyclic voltammetry (CV), galvanostatic charge-discharge curves (GCDC), linear sweep voltammetry (LSV), and electrochemical potentiokinetic reactivation (EPR). The PMMA_Fe-MOF electrodes exhibited outstanding capacitive performance, achieving specific capacitances of up to 1017.5 F/g at 1 A/g for the 2.5 % Fe-MOF …

Underwater Acoustic Integrated Sensing And Communication: A Spatio-Temporal Freshness For Intelligent Resource Prioritization, Ananya Hazarika, Mehdi Rahmati

Electrical and Computer Engineering Faculty Publications

Underwater acoustic communication faces significant challenges including limited bandwidth, high propagation delays, severe multipath fading, and stringent energy constraints. While integrated sensing and communication (ISAC) has shown promise in radio frequency systems, its adaptation to underwater environments remains challenging due to the unique acoustic channel characteristics and the inadequacy of traditional delay-based performance metrics that fail to capture the spatio-temporal value of information in dynamic underwater scenarios. This paper presents a comprehensive underwater ISAC framework centered on a novel Spatio-Temporal Information-Theoretic Freshness metric that fundamentally transforms resource allocation from delay minimization to value maximization. Unlike conventional approaches that treat all …

Development Of Gelma-Based Hydrogel Scaffolds With Tunable Mechanical Properties For Applications In Peripheral Nerve Regeneration, Kylie M. Schmitz, Tanner L. Larson, Michael W. Borovich, Xianfang Wu, Geyou Ao, Megan Jack, Liqun Ning

Chemical & Biomedical Engineering Faculty Publications

Peripheral nerve injuries (PNIs) have a significant impact on the quality of life for patients suffering from trauma or disease. In injuries with critical nerve gaps, PN regeneration requires tissue scaffolds with appropriate physiological properties that promote cell growth and functions. Hydrogel scaffolds represent a promising platform for engineering soft tissue constructs that meet key physiological requirements. Nonetheless, ongoing innovation remains essential, as current designs continue to fall short of replicating the functional performance of autografts in bridging critical-sized nerve defects. In this study, gelatin methacrylate (gelMA)-based hydrogels are evaluated to fully characterize their pore structure, compressive stiffness, viscoelasticity, and …

A Polar Turbulence Invariant Map With Applicability To Realisable Machine Learning Turbulence Models, James G. Wnek, Christopher Schrock, Eric M. Wolf, Mitch Wolff

Mechanical and Materials Engineering Faculty Publications

Invariant maps are a useful tool for turbulence modelling, and the rapid growth of machine learning-based turbulence modelling research has led to renewed interest in them. They allow different turbulent states to be visualised in an interpretable manner and provide a mathematical framework to analyse or enforce realisability. Current invariant maps, however, are limited in machine learning models by the need for costly coordinate transformations and eigendecomposition at each point in the flow field. This paper introduces a new polar invariant map based on an angle that parametrises the relationship of the principal anisotropic stresses, and a scalar that describes …

09.08.2025 Ored Connect, Liz Williamson

ORED Newsletter

• Researcher training opportunities
• Project to increase PhD student success
• ORED online training opportunities

Detecting Electrical Submersible Pump (Esp) Failures And Estimating Run Life Using Artificial Neural Networks, Mostafa Ahmed Sobhy

Theses and Dissertations

Electric Submersible Pumps (ESPs) are one of the important artificial lift methods for sustaining production in mature and high-water-cut wells; but may suffer frequent failures due to mechanical, electrical, hydraulic, chemical, and operational failures. These failures can yield substantial deferred production and intervention costs. Plenty of ESP installations are fitted with downhole sensors. Yet, it is observed that the current industry practice underutilizes the wealth of available sensor and operational data and lacks standardized, explainable failure-type identification and classification.

In this thesis, a comprehensive Machine Learning (ML) and Deep Learning (DL) framework was introduced for ESPs that simultaneously estimates remaining …

Impact Of Composite Materials Research On Underrepresented Communities, Neil Mahesh Bedagkar, Ramanan Sritharan, Wyatt Barnes

Mechanical Engineering

This research assesses how advancements in composites material research affect communities from lower socioeconomic backgrounds, using a dual track strategy to quantitatively and qualitatively examine their impact. A keyword-based classification algorithm was applied to a sample of research papers from ScienceDirect spanning the last 24 years to quantify which engineering industries benefit most from this research. The findings indicate that the construction industry benefits the most, followed by the automotive, defense, renewable energy, and biomedical sectors. A broader qualitative analysis of the social implications of these industries was also conducted to provide context. Each sector were found to have either …

Evaluation Of User Interactions And Preferences Of Shared Bicycle And Pedestrian Transit Platforms, Nathan Mcneil, Sirisha Kothuri, Jennifer Dill, Chris Monsere, Elizabeth Yates, Julia Plotts

Civil and Environmental Engineering Faculty Publications and Presentations

Shared bike and bus platforms have been deployed in an effort to minimize conflicts between bicycles and buses (and other motor vehicles) on streets with bike lanes and bus transit service. This paper assesses bicycle/micromobility user and pedestrian behavior in shared bicycle and transit platforms along a bus rapid transit corridor in Portland, OR. Research objectives include understanding interactions between these users and potential conflicts between people on foot (or wheelchair/mobility devices) who are waiting for, boarding, and/or alighting a bus and people on bicycles riding in the bike lane. The research also assessed how well the shared transit platforms …

Activity Design Principles To Support Engineering Engagement For Families With Preschool-Age Children From Low-Income English-And Spanish-Speaking Communities, Scott A. Pattison, Smirla Ramos Montañez, Viviana López Burgos, Gina Svarovsky, María Quijano, Amy Corbett, Catherine Wagner, Diana Contreras

Journal of Pre-College Engineering Education Research (J-PEER)

Existing evidence highlights the significance of family STEM learning experiences during early childhood. However, there is a lack of research specific to early childhood family-based learning in the field of engineering, especially with preschool-age children (three to five years old). To address this gap and inform engineering education programs for young children, we conducted a design-based research study in collaboration with 15 Spanish-and English-speaking families with preschool-age children from low-income communities. Our study aimed to develop and test a series of family-based engineering design activities while also identifying underlying design principles. Guided by an asset-based family learning framework, which acknowledges …

A Test Rig For An Aircraft Propeller Powered By Battery Motor, C. M. Vigneswaran, J. Induja, K. S. Bharath, M. J. Spoorthi, R. Chethana

Journal of Aviation Technology and Engineering

The propeller test rig is a crucial component in aeronautical engineering that plays a vital role in the development, testing, and optimization of propeller systems for aircraft. This research outlines the design, development, and performance evaluation of a state-of- the- art propeller test rig developed for research and testing purposes. The primary objective of this project is to enhance the understanding of propeller dynamics and efficiency, leading to the improvement of aircraft propulsion systems. The test rig provides a controlled environment to evaluate and compare multiple propeller designs, aiding engineers in making informed decisions during the design process. An advanced …

A Framework For Test Planning Of A Vision System Supporting Aerial Refueling, Jonathon K. Parry, Donald H. Costello, Michael D. M. Kutzer, Charles J. Doherty, Sarah M. Hubbard

Journal of Aviation Technology and Engineering

This essay presents a framework for evaluating a computer vision system providing perception for an uncrewed aircraft completing the automated air-to-air refueling (A3R) task. As the Department of Defense acquires capabilities that exhibit increasing levels of autonomy, the test and evaluation community must adapt the current framework to provide airworthiness officials the information required to accurately access the risks associated with the system underdoing testing. Following a brief introduction to A3R, this essay lays out a testing framework that leverages dendritic analysis and effectively deconstructs the critical issue into measurable data elements that can be used to support test and …

Valuing Fruit Tree Lease Contracts Under Uncertainty: A Probabilistic Framework For Fair Pricing, Abdurakhman Abdurakhman, Agus Sihabuddin, Kurniawan Chandra Wijaya, Evita Purnaningrum, Di Asih I Maruddani

Iraqi Journal for Computer Science and Mathematics

Fruit tree lease contracts are a prevalent economic practice in Indonesia, especially within rural communities. This study addresses the challenge of establishing equitable contract prices for both lessees and tree owners, specifically by integrating the inherent uncertainties associated with crop yield and fruit price fluctuations. To achieve this, we develop and employ two distinct models: Fixed-Time Discount Model (FTD) and the Dynamic-Time Discount Model (DTD). Each model is mathematically formulated, leveraging a Poisson distribution to capture yield uncertainty and a Uniform distribution to represent fruit price variability. Through computations, we evaluate the impact of key parameters - average yield ( …

Ada-Application Of Decision Analysis For Developing A Healthcare System To Predict Fetal Health, Melfi Alrasheedi, Theyazn.H.H Aldhyani

Iraqi Journal for Computer Science and Mathematics

A fatal health condition involves an unborn baby that persists throughout the embryonic stage until delivery. The fetus grows and develops during each trimester of pregnancy. Obstetricians may detect fetal anomalies and select medical interventions based on cardiotocogram (CTG) data. However, the obstetrician's visual assessment of CTG data can sometimes be subjective or inaccurate. Therefore, automated analysis using machine learning approaches for CTG data is essential. This research employs decision analysis techniques, including decision trees (DT), gradient boosting (GB), and type-2 fuzzy neural networks (FNN), for prenatal analysis and prediction. The system was tested using a standard dataset consisting of …

Retracted: Hotspot Issue Handling And Reliable Data Forwarding Technique For Ocean Underwater Sensor Networks, Omar Adil Mahdi, Yusor Rafid Bahar Al-Mayouf, Sameer Sami Hassan Al-Obaidi, Bourair Al-Attar, Hamed Balogun, Suleman Khan

Iraqi Journal for Computer Science and Mathematics

Underwater Wireless Sensor Networks (UWSNs) have emerged as a promising technology for a wide range of ocean monitoring applications. The UWSNs suffer from unique challenges of the underwater environment, such as dynamic and sparse network topology, which can easily lead to a partitioned network. This results in hotspot formation and the absence of the routing path from the source to the destination. Therefore, to optimize the network lifetime and limit the possibility of hotspot formation along the data transmission path, the need to plan a traffic-aware protocol is raised. In this research, we propose a traffic-aware routing protocol called PG-RES, …

Building Multimodal Knowledge Graphs: Automation For Enterprise Integration, Ritvik Garimella, Hong Yung Yip, Revathy Venkataramanan, Amit P. Sheth

Publications

As enterprises increasingly aim to incorporate artificial intelligence into their workflows to tackle complex, multimodal tasks, the demand for intelligent, robust, and trustworthy systems is paramount. While multimodal large language models offer initial capabilities for processing diverse data streams, their dependence on embedding-based representations limit their effectiveness in delivering semantically grounded explanations and reasoning, as well as qualities essential for enterprise-grade applications. Neurosymbolic approaches provide a promising alternative by enabling traceable, context-aware decision making. However, constructing enterprise-level multimodal knowledge graphs (MMKGs) that enable neurosymbolic approaches remains largely impractical. Although prior efforts have explored MMKG construction, they fall short in addressing …

Event-Based Sensor Noise Modeling For Space-Based Space Domain Awareness, Rachel Oliver, Brian Mcreynolds, Dmitry Savransky

Faculty Publications

Building off the foundation of a physics-based end-to-end model for event-based vision sensors (EVS) observing resident space objects (RSOs), we apply new techniques to model realistic low-light sensor noise. While previous approaches simulate memorized current leakage and apply temporal noise models, our methods improve on these approaches and additionally account for current-following noise as an event source. These improvements are key components for accurate event-generating simulators which can advise requirements and concepts of operations for dedicated event-based Space Domain Awareness (SDA) architectures. The EVS pixel’s independent and asynchronous recording of changes in photocurrent produces data with high temporal resolution and …

The Green Approach Of Arabic Gum-Based Adsorbent In Wastewater Treatment, Atheel H. Alwash

AUIQ Technical Engineering Science

The natural polysaccharide Arabic gum is a multifunctional, sustainable material used widely in wastewater treatment technology. Its active functional groups such as hydroxyl, carboxyl, and amino groups facilitate the efficient removal of heavy metals, dyes, pesticides, pharmaceuticals, and persistent organic pollutants. The high surface area and active functional groups facilitate its modification to form various structures such as hydrogels, nanocomposites, or biochar integrated into hybrid adsorption–photocatalysis systems. This review highlights the most familiar forms of Arabic gum in wastewater treatment technology, such as hydrogels, hydrogels nanocomposite, stabilizing agents, coating agents, and bio-activated carbon derived from Arabic gum using different preparation …

Memf-Net: A Mega-Ensemble Of Multi-Feature Cnns For Classification Of Breast Histopathological Images, Alaa Hussein Abdulaal, Ali H. Abdulwahhab, Aqeel Majeed Breesam, Zahra Hasan Oleiwi, Riyam Ali Yassin, Morteza Valizadeh, Saja Nafea Mohsin

Iraqi Journal for Computer Science and Mathematics

Pathological anatomical images play a pivotal role in diagnosing diseases, notably breast cancer, which affects women globally. These images, obtained through biopsies or post-mortem examinations, are preserved to maintain their structural integrity. Software tools, like computer-aided diagnosis, aid doctors in early detection and treatment planning, contributing to reduced mortality rates. In this context, convolutional neural networks (CNNs) have emerged as valuable tools for diagnosing benign and malignant breast cancers. This paper introduces a Mega Ensemble Net method, leveraging multi-scale combination features on the breast histopathology dataset. Three fine-tuned deep learning models, namely ResNet-18, ResNet-34, and ResNet-50, are integrated into this …

Retracted: Capsule Network Model For Detecting Spoofing Attack In The Internet Of Medical Things (Iomt), Mohammad A. Alsharaiah, Mohammed Amin Almaiah, Mansour Obeidat, Rami Shehab

Iraqi Journal for Computer Science and Mathematics

The Internet of Medical Things (IoMT) has transformed healthcare delivery through real-time monitoring and data exchange. However, this integration of smart medical devices has also introduced critical cybersecurity threats, particularly spoofing attacks, which can compromise patient safety and system reliability. Conventional Intrusion Detection Systems (IDS) often fail to address IoMT-specific challenges such as class imbalance, computational constraints, and the need for real-time adaptability. This study proposes a Capsule Network (CapsNet)-based IDS that leverages spatial dependency modeling and hierarchical feature relationships to detect spoofing attacks in IoMT environments. Using the CICIoMT2024 dataset, we implemented a binary classification framework where spoofing instances …

Modeling Of Urea Drying And Granulation Process In Fluidized Bed, Jalolitdin Pakhritdinovich Mukhitdinov, Aleksey Viktorovich Schulz

Chemical Technology, Control and Management

This article is devoted to the mathematical modeling of urea drying and granulation processes in a fluidized bed. A brief description is provided for the functional blocks included in the mathematical model, along with the required parameters that form an integrated representation of the technological process. The SR-POLAR model is used to describe a phase equilibrium between the components involved. The interconnections between functional blocks are shown in the process flow diagram. Block diagrams for modeling a multi-chamber granulation unit and the cooling system for the resulting granules are presented. Granule growth in the fluidized bed is described using a …

Increasing The Robustness Of A Control System For A Complex Dynamic Plant By Correcting Nonlinearity In The Warping Process, Tukhtamurod Khayitmurodovich Avezov, Zokhid Ergashboyevich Iskandarov

Chemical Technology, Control and Management

The paper discusses the challenges of enhancing the robustness of a control system for a complex dynamic plant by addressing nonlinearity in the warping process. Devices that ensure the stability of the control system against parameter non-stationarity on the warping machine are referred to as state controllers. The operating principle of these devices relies on providing artificial nonlinearity to the rear connection circuit of the control system's actuator. However, this nonlinearity is implemented using components that consider the parameters of low control quality. Therefore, it is necessary to continuously adjust the nonlinearity parameters to, on one hand, reduce the load …

Optimizing Beer Fermentation Through Intelligent Control, Azizbek Nodirbekovich Yusupbekov, Mirjalol Yusupov

Chemical Technology, Control and Management

This paper presents an intelligent control approach for optimizing the beer fermentation process using fuzzy logic and adaptive neuro-fuzzy inference systems. By incorporating multivariable inputs—temperature error and pH deviation—the proposed system effectively handles the nonlinear dynamics and biological variability inherent in fermentation. Simulation results demonstrate improved control accuracy, responsiveness, and robustness compared to conventional methods, making the approach suitable for integration in modern brewery automation systems.

A C++ Library For Turbulent Mixing Simulation Using Hierarchical Parcel Swapping (Hips), Masoomeh Behrang, Tommy Starick, Heiko Schmidt, David O. Lignell

Faculty Publications

Turbulence models are crucial for simulating flows at all scales, capturing both large-scale structures and small-scale mixing. Software libraries that implement such models should support modular integration, customization, and scalability across different simulation frameworks. This paper presents Hierarchical Parcel Swapping (HiPS), a C++ library documented with Doxygen and available on GitHub. HiPS supports both mixing and reactions and can be used as a standalone model or as a subgrid model in CFD simulations. The code includes examples for users to run it as a standalone model. Additionally, considerations for using it as a subgrid model are provided.

Performance Analysis Of Flapping-Foil Energy Harvesters Under Shear-Flow Conditions, Maqusud Alam, Bubryur Kim, Shehnaz Akhtar, Sujeen Song, Zengshun Chen, Jinwoo An

Civil Engineering Faculty Publications

Flapping-foil energy harvesters represent a promising technology for extracting energy from fluid flows, although their performance under shear-flow conditions is poorly understood. To address this research gap, we investigated the impact of power-law shear flow on the performance of flapping-foil energy harvesters. We conducted numerical simulations at different Reynolds numbers (Re = 1000, 50 000, and 500 000) under uniform-flow and shear-flow conditions. Based on the results, shear flow minimally affected the power outputs at Re = 1000 and 50 000, where viscous forces dominate the flow dynamics. However, at Re = 500 000, shear flow significantly reduced the …

Algorithms For The Synthesis Of Adaptive Control Systems Based On The Speed-Gradient Method, Oxunjon Boborayimov

Chemical Technology, Control and Management

This paper discusses the synthesis algorithms for adaptive control systems based on the speed-gradient method. Adaptive control systems with implicit reference and adjustable models are synthesized using speed-gradient techniques, which reduce the requirements for the main control loop structure and the completeness of measurement data. Stable adaptive decentralized control algorithms are developed for a class of interconnected systems with nonlinear local dynamics and uncertainties, ensuring the stability of individual subsystems and the overall system while accounting for their interactions. To incorporate inter-subsystem interactions into the overall control law, an adaptation algorithm based on the speed-gradient method is introduced. A synthesis …

Modern Methods Of Self-Monitoring, Diagnostics, And Fault Tolerance In Flow Measurement Systems, Elbek Ortiqov

Chemical Technology, Control and Management

This article investigates various methods and tools for self-monitoring and fault tolerance in flow measurement transducers used in industrial processes. The study focuses on key techniques such as the use of redundancy, generation of reference values, analysis of measurement signals, and control of disturbance variables. These methods allow transducers to detect potential faults, ensure reliable operation, and maintain measurement accuracy even under adverse conditions. The article highlights how self-monitoring contributes to improving system safety, increasing reliability, and reducing downtime. It also discusses the integration of intelligent monitoring systems that support predictive maintenance and real-time diagnostics. Fault-tolerant sensors with self-monitoring capabilities …

Finding The Shortest And Optimal Path With Metaheuristic And Madm Methods, Narmin Ibrahim Hasanli

Chemical Technology, Control and Management

The article had described a method for finding the shortest and most optimal path among cities. The data had been taken from the TSPLIB library, which had provided standard examples for the Traveling Salesman Problem. This approach had integrated the advantages of the meta-heuristic technique and the Multi Attribute Decision Making method to solve the problem effectively. In the first stage, the population based meta-heuristic method ACO (Ant Colony Optimization) had found optimal solutions in large search spaces. The use of pheromone trails, heuristic information and an iterative search process had given the opportunity to find the best or near-best …

Research And Development Of Intelligent Measurement Systems, Odil Abdujalilovich Jumaev, Mahmudov Giyosjon Baqoyevich

Chemical Technology, Control and Management

The article discusses modern methods for developing intelligent measuring systems. Intelligent measuring systems are systems based on intelligent technologies that not only accurately measure physical or chemical quantities, but also have the ability to self-analyze, diagnose and make management decisions. The article comprehensively examines the architecture, components of such systems, the organization of their software and hardware, the relationship of sensors and artificial intelligence algorithms. It also analyzes the practical application and prospects of intelligent measuring systems in such areas as industry, medicine, energy, ecology, transport.