Digital Commons Network^™

Elevate Hardcase, Caleb J. Bailey, Colby M. Cordoba, Marissa Mccleod, Shaan Sandhu

Mechanical Engineering

The Elevate Hardcase project developed a portable mechanical elevation system that allows users to access rugged hard cases at a comfortable working height without needing a separate table or placing the case on uneven ground. The design focuses on improving ergonomics, portability, stability, and quick setup for users in field environments such as photography, hunting, and maintenance. Through customer research, concept development, prototyping, analysis, and testing, the final system was designed to support a loaded hard case, provide height adjustability, remain stable on uneven terrain, and be deployed by a single user in under five minutes. The final prototype demonstrates …

Design And Production Of A Carbon Fiber Longboard, John R. Beebe, Jacob Williams, Julia Stradinger, Vince Fitchtel, Jordan Cochran

Honors Theses

This thesis contains an overview of the design, prototyping, and manufacturing of a carbon fiber long board. The purpose of this capstone was to create a viable product for the real-world market and then determine how to manufacture it at scale with sustainable financial practices. In order to accomplish this task, engineering, accounting, and manufacturing challenges had to be overcome throughout all stages. The production process involved the carbon fiber layup, baking, water jet cutting, and assembly of the carbon fiber longboard. In order to optimize this process, continuous improvement and lean manufacturing problem solving techniques were applied. After a …

Simulation-Based Assessment Of Operational And Retrofit Solutions For Effluent Compliance Of A Capacity-Limited Oxidation Ditch Wwtp, Ahmed Sameh Harash

Theses and Dissertations

Oxidation-ditch wastewater treatment plants (WWTPs) across Egypt's Nile Delta are increasingly carrying hydraulic and organic loads beyond what they were designed for. This work can be considered pioneering as this work compared operational and structural retrofit alternatives for such a plant within a single verified simulation framework. The present study fills that gap by building a digital twin of the Qaha WWTP, a dual-train Carrousel oxidation ditch in Qalyubia Governorate, calibrated to a baseline flow of 7,420 m³/day in the SUMO24 platform (a third-generation, open-source wastewater treatment process simulation software) using the SUMO2c biokinetic model (a simplified variant of Activated …

Dynamic Baseline Schedule Updates Using Digital Twinning: A Case Study On Aluminum Formwork Construction, Ahmed Hamdi Sweilam

Theses and Dissertations

Repetitive high-rise construction using aluminum formwork couples consecutive floor cycles through a reused panel set and a floor-level inspection and pour barrier, so productivity loss compounds upward rather than being absorbed locally. The baseline schedule is nevertheless fixed before execution and is not revised as evidence of realized productivity accumulates. This thesis develops a simulation-based digital twin that updates the baseline from observed as-built durations and acts on its own forecast. A discrete-event simulation of a ten-story residential tower is built in AnyLogic® and verified analytically at 180.00 hours per floor. After each completed floor the twin infers activity productivity …

A Maximum Energy Release Rate Computational Framework For Fatigue Crack Trajectory And Life Prediction Under Mixed-Mode Proportional And Nonproportional Loading, Nahla Helmy Matar

Theses and Dissertations

The problem of mixed-mode fatigue crack growth has been a persistent research challenge. The determination of fatigue crack propagation direction directly impacts the safety and integrity of components and structures, making it crucial in various industrial applications, including welded drilling pipes, aerospace, and automotive engineering. Unlike uniaxial loading, mixed-mode cracks tend to change direction frequently (kinking), and nonproportional loading adds to the complexity of the problem. This research aims to estimate the crack propagation direction and fatigue crack life in linear elastic materials subjected to mixed-mode (I+II) loading conditions under proportional or non-proportional cyclic loading. Numerical software was developed based …

Sar Ship Detection Based On Shallow Feature Guidance, Chenxu Xia, Peng Chen, Ya Zhang, Ying Li

Journal of Marine Science and Technology–Taiwan

Maritime ship detection is of great significance for both military security and civilian applications. Synthetic Aperture Radar (SAR), with its all-weather and all-day imaging capability, plays a vital role in maritime surveillance. Nevertheless, SAR ship targets typically appear small in scale, embedded in complex backgrounds, blurred at boundaries, and easily confused with near-shore features, which pose substantial challenges for accurate detection. To address these issues, we propose a SAR ship detection network that integrates dual enhancements of small-object representation and edge information. The network introduces two key components: the Small Target Refine Pyramid (STRP) to strengthen shallow feature representation for …

Enhancing Shipboard Safety Management Under The Ism Code: An Innovative Risk Assessment Framework With A Stern Tube Case Study, Pi-Yen Lin

Journal of Marine Science and Technology–Taiwan

The shipboard safety management system (SMS) is designed to enhance safe operations, risk management, and emergency response to improve overall ship safety and efficiency. This paper demonstrates the use of an engine room simulator (ERS) for collecting failure modes and applies it to a comprehensive failure analysis of the stern tube lubricating oil system. A new risk closeness coefficient method was developed, integrating expert background knowledge and weighted risk assessments. The analysis, based on multiple expert evaluations, covered five subsystems, eight main components, 23 failure modes, and 112 failure causes. This study presents 26 recommendations for maritime practitioners and onboard …

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

A Data-Driven Koopman Framework For Station-Keeping On Near Rectilinear Halo Orbit, Anusha Sharma Malladi

Theses and Dissertations

Cislunar missions have gained significant attention in recent decades, motivating the need for efficient modeling and reliable control. In this work a Koopman operator based framework is developed for approximating the error dynamics around a reference Near Rectilinear Halo Orbit (NRHO) in the Earth-Moon Circular Restricted Three-Body Problem (CR3BP). A decoder free neural network is used to learn a lifted linear representation of the nonlinear CR3BP dynamics and a residual based approach is used to identify the corresponding control input matrix. The model is then implemented in a receding-horizon target point controller and compared with uncontrolled propagation and a State …

Developing Imitation Learning Policies By Exploring Diffusion Framework For Quadcopters, Likith Swamireddy

Theses and Dissertations

Imitation learning offers a promising approach in developing near-optimal onboard policies for nonlinear systems, by learning from computationally expensive trajectory planners during offline training. Existing State-of-the-art methods commonly learn deterministic mappings from observations to actions by training fast neural networks to mimic the expert demonstrations, which can limit their ability to capture the action distribution, when the policy is trained on multiple possible expert commands to reach the same target, and this may lead to unsafe scenarios in the obstacle environments. To address these challenges, this study explores Diffusion Models (DMs) as a feedback controller for quadcopters that learns the …

Enhancing Agricultural Sustainability Under Climate Change: A Multi-Scale Framework Integrating Climate Extremes, Resource Efficiency, And Data-Driven Modeling, Shahryar Fazli

Computational and Data Sciences (PhD) Dissertations

Agricultural systems are increasingly challenged by climate variability, where shifting temperature regimes, hydrological variability, and the rising frequency of compound and cascading extremes threaten global food security and resource sustainability. Addressing these challenges requires integrated frameworks that bridge biophysical monitoring, predictive modeling, and adaptive decision-making. This dissertation develops a data-driven, multi-scale framework to quantify and enhance agricultural resilience by integrating remote sensing, climate analytics, and machine learning across the United States, with a focus on California and the Western U.S.

First, hyperspectral and thermal remote sensing data from EMIT and OpenET are integrated to characterize crop nitrogen–water interactions and assess …

Scalable Quality Assessment Of Ground Motion Records Via Interpretable Deep Learning Architectures, Ali Montazeri Namin

All Graduate Theses and Dissertations, Fall 2023 to Present

Earthquake engineers rely on accurate recordings of ground shaking to design safe and resilient buildings. However, sorting through thousands of these recordings to find the reliable ones and throwing out those ruined by sensor errors or background noise is traditionally done by hand. Because modern seismic networks collect massive amounts of earthquake data every day, this manual checking process is much too slow. To fix this, researchers are turning to artificial intelligence to automatically check the quality of these recordings.

While artificial intelligence offers a fast solution, there are limitations. These computer models can become massive and expensive to run, …

Lrq-Solver: A Transformer-Based Neural Operator For Fast And Accurate Solving Of Large-Scale 3d Pdes, Peijian Zeng, Guan Wang, Haohao Gu, Xiaoguang Hu, Tiezhu Gao, Zhuowei Wang, Aimin Yang, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

Solving large-scale PDEs on complex three-dimensional geometries remains a central challenge in scientific and engineering computing, often due to expensive pre-processing stages and high computational overhead. We present Low-Rank Query-based PDE Solver (LRQ-Solver), a physics-integrated deep learning framework for efficient CAE simulations of complex three-dimensional geometries in CAD-driven design analysis. Built upon the Parameter-Conditioned Lagrangian Modeling (PCLM) that embeds physical consistency into the learning process and the Low-Rank Query Attention (LR-QA) module that reduces attention complexity from O(N2) to O(NC2+C3) via covariance decomposition, LRQ-Solver supports multi-configuration analysis within iterative design workflows. On two benchmark datasets, it achieves a 28.6% error …

Mind The Hazard: Modeling And Interpreting Comfort With Personalized Sensing, Yufei Zhang, Matteo Favero, Patrick Chwalek, Sailin Zhong, Denis Lalanne, A. Joseph Paradiso, Clayton Miller, Andrew Sonta

Research Collection College of Integrative Studies

Recent advances in personalized sensing and comfort feedback have spurred the development of data-driven comfort models tailored to individual needs. However, because current models treat sequential comfort feedback independently, they are subject to unstable predictions and limited interpretability, hindering their deployment in building management. This study introduces a dynamic modeling framework that utilizes a Neural Ordinary Differential Equations-based Continuous-time Markov Chain to model the transitions in comfort states over time. Our modeling approach, developed through a field study utilizing smart glasses and mobile app feedback, tracks occupants' comfort transitions across daily activities and contexts. The results demonstrate that this model …

Securing The Frontier: Environmental Adaptation Versus Urban Fortification In Strategic Border Gateways: The Case Of East Qantara, Ahmed M. Selim, Mohamed A. Shebl, Doha M. Saeed, Heba M. Gaber

HBRC Journal

Security-oriented urban design at strategic national gateways often restricts spatial openness, cultural identity, and social inclusion, all essential to functional public spaces. This study develops a multi-criteria framework for security-inclusive urban design at East Qantara, the primary vehicular gateway between continental Egypt and the Sinai Peninsula. This study employed a sequential quantitative–interpretive design approach. In the quantitative phase, 51 criteria were identified from Crime Prevention Through Environmental Design (CPTED) principles, Hostile Vehicle Mitigation (HVM) guidance, publicness theory, and context-specific desert and socio-cultural literature, and subsequently revised to 37 criteria through expert panel validation. A structured expert questionnaire with a five-point …

Estimation Of Unmeasurable External Disturbances Of A Dynamic Object Based On A Robust Adaptive Kalman Filter, Bunyod Mamurjon Ugli Buronov

Technical science and innovation

This article considers the problem of directly estimating unmeasurable external disturbances acting on a dynamic object under the condition that the state vector of the object is available for measurement. In the considered case, the problem is reduced to the estimation of an unknown input of a dynamic system. It is shown that when the system state is measurable, both a direct inversion scheme based on the object’s dynamic equation and filtering methods that eliminate the need for coarse numerical differentiation can be applied. For slowly varying disturbances, a random walk model with a small process noise covariance is proposed, …

Effect Of Waste Cooking Oil And Tapioca Starch On Energy Content And Combustion Performance Of Coconut Shell-Rice Husk Briquettes, Satworo Adiwidodo, Wirawan Wirawan, Kris Witono, Moh. Hartono, Asrori Asrori, Fauzan Baananto, Suliono Suliono, Syahrul Mubarok, Norhafana Binti Mohamed

Journal of Mechanical Engineering Science and Technology (JMEST)

Agricultural waste, such as coconut shells and rice husks, is widely utilized as solid fuel. Tapioca starch serves as the binder, while waste cooking oil (WCO) is used as an additive. Briquette performance is influenced by the type of biomass, binder, and additives used. However, the individual and interactive effects of WCO and tapioca starch on the performance of coconut shell-rice husk briquettes remain insufficiently established. This research focused on evaluating the effects of WCO and tapioca starch on calorific value (CV)  and mass consumption rate. The briquettes' base composition consisted of 75% coconut shell charcoal and 25% rice husk …

Automatic +1 Diffraction Order Detection In Off-Axis Digital Holographic Interferometry Using An Energy-Based Spectral Model, Nigora Alimdjanovna Akbarova, Dilnoza Ibrokhim Kizi Abdulkhayeva

Technical science and innovation

This paper presents an automatic +1 diffraction order detection algorithm for off-axis digital holographic interferometry (DHI Manual spectral filtering is widely used to find out the desired order of diffraction in the Fourier domain in conventional digital holographic reconstruction. Nevertheless, this approach is very subjective and must be subject to expert guidance, thus, the reconstruction reproducibility and stability can often deteriorate. To address these limitations, this designed scheme constructs a spectral model utilizing energy-maximization as well as adaptive DC suppression and dynamic filter radius estimates. The algorithm itself can automatically observe the distribution of energy in the hologram spectrum and …

Evaluation Of The Metrological Characteristics Of An Ultrasonic Flowmeter For Water Resources, Makhsud Idrisovich Makhmudov, Uktam Farkhodovich Mamirov, Siroj Sobirovich Nurov

Technical science and innovation

This paper presents the results of evaluating the metrological characteristics of a developed ultrasonic flowmeter intended for measuring water flow in open channels. The study analyzes the main sources of measurement errors and classifies them into methodological, instrumental, additional, systematic, and random components. Experimental investigations were carried out to estimate the random and systematic errors under steady-state flow conditions. Using the least-squares method, the systematic error was separated into additive and multiplicative components, providing a basis for calibration and correction of the measurement results. The reliability of the developed measuring instrument was evaluated using the failure rate method based on …

Evaluation Of Level Measurement Uncertainty For Three Types Of Laser Level Meters Using The Gum Methodology: Calculated Uncertainty Budgets, Uncertainty Profile, And Hardware Component Requirements, Lazizbek Furkatjanovich Saidoripov, Barat Makhmudovich Akhmedov

Technical science and innovation

A methodology is presented for evaluating the uncertainty of liquid petroleum product level measurements using laser level meters based on different measurands’ informative parameters: propagation time, phase difference, and image coordinates. Based on analytical expressions for error components and a traceability chain to the national length standard, calculated uncertainty budgets are developed in accordance with JCGM 100 for time-of-flight, phase-based, and laser–television level meters. Under the assumed input conditions, the expanded uncertainties (k = 2) are 1.66, 0.73, and 1.02 mm, respectively. For the laser–television level meter budget, the Gaussian approximation is verified using the Monte Carlo method (JCGM 101): …

Analysis And Study Of The Content Of Chloride Salts In Oil, Natalia Evgenievna Sheina, Muborak Akramovna Mirshomilova

Technical science and innovation

The article addresses the critical issue of crude oil quality control, specifically focusing on the determination of chloride salts (sodium, calcium, and magnesium), which exert a destructive impact on processing equipment. The paper provides a detailed analysis of the adverse effects of salts, which lead to severe equipment corrosion, scaling, and a reduced yield of valuable oil fractions. The chemical principles and specific applications of two standardized methods for analyzing aqueous extracts according to GOST 21534-2021 and ASTM D3230 are described: indicator (argentometric and mercurimetric) and potentiometric titration. The experimental section presents the results of a comparative analysis of crude …

Developing A Digital Facility Management Framework For Enhancing Operation And Maintenance Of Public Parks In Egypt, Alaa Ezzat, Alia Amer, Yasser M. El Sayed

HBRC Journal

Public parks in Cairo represent important urban assets, however, their operation and maintenance (O&M) face many challenges due to fragmented information, reactive maintenance practices, organizational constraints, and limited digital integration. Digital Facility Management discipline still lacks the tailored framework that adequately addresses the operational needs of public parks in Egypt with all its specific details. This study develops an integrated digital FM framework for improving the efficiency of the management process of public parks. A four-phase methodology was adopted, comprising a literature review, framework development, technical system specification, and expert assessment. The proposed framework integrates BIM, COBie, CMMS, IoT technologies, …

Machine Learning Models For Estimating The Consumed And Remaining Useful Life Of Haul Trucks In An Open-Pit Mine In Peru, Marco Cotrina, Jairo Marquina, Mario Sandoval, Jose Mamani, Johnny Ccatamayo

Journal of Sustainable Mining

The purpose of this study was to develop a machine learning-based model to predict the consumed useful life and estimate the remaining useful life of haul trucks in an open-pit mining operation in Peru. A comparative analysis of multiple machine learning models was conducted, including multiple linear regression (MLR), random forest + PSO, support vector regression (SVR), gradient boosting machine (GBM), decision tree + PSO, and artificial neural networks (ANN-MLP). The models were evaluated using performance metrics such as R², RMSE, and MAE, selecting the optimal model to estimate the remaining useful life based on a theoretical lifespan …

Development Of A Spectral Index And Web Application For Automated Marble Quarry Monitoring: A Sentinel-2 Based Approach For Change Detection And Monitoring, Konstantinos Ntouros, Vasileios Drimzakas - Papadopoulos, Georgios Gkologkinas, Georgios Ntouros, Dimitrios Markou

Journal of Sustainable Mining

This study introduces an automated workflow to monitor marble quarry operations using Sentinel-2 satellite data, providing a cost-effective and efficient tool for regulatory oversight focused on environmental sustainability. At the core of this workflow is the Quarry Change Detection Index (QCDI), a new spectral index specifically developed to leverage the unique spectral characteristics of quarry sites, enhancing the detection of land cover changes associated with quarry expansion. To facilitate practical application, a web-based tool was developed using Google Earth Engine and Streamlit. The user-centric design of this platform features an intuitive interface, allowing users to easily select parameters, visualize data, …

Integrating Gis With Interim Payment Valuation In Road Construction Projects: A Conceptual Framework, Abdulrahman I. Iro, Juma M. Matindana, Julian Ijumulana

Tanzania Journal of Engineering and Technology (TJET)

Abstract

Interim Payment Valuation is a critical process in road construction contract administration, yet conventional valuation practices remain heavily dependent on manual measurements, fragmented documentation, spreadsheets, and professional judgement. These limitations can affect measurement accuracy, transparency, traceability, and the timeliness of payment certification. Although Geographic Information Systems have increasingly been applied to construction planning, quantity measurement, progress monitoring, infrastructure management, and decision support, their integration with contractual and financial processes for interim payment valuation remains insufficiently explored. This study therefore develops a conceptual framework for integrating GIS with Interim Payment Valuation in road construction projects. A PRISMA-guided structured literature review …

Artificial Neural Network-Based Modelling And Prediction Of Key Performance Indicators In Road Construction Projects, Hussein Mativila, John M. Kafuku, Beatus A. T. Kundi

Tanzania Journal of Engineering and Technology (TJET)

Road construction projects in developing countries including Tanzania experience several challenges including cost overruns, schedule delays and poor quality. The causes of these challenges include complex interdependencies project’s uncertainty factors. This makes traditional methods for predicting Key Performance Indicators (KPIs) less effective. This study has developed a robust Artificial Neural Network (ANN) model for accurate modelling and predicting KPIs for road construction projects in Tanzania. The analysis was based on data obtained from 281 projects implemented by TANROADS in 11 regions from 2015 to 2025. Fourteen uncertainty factors were measured on a five-point Likert scale and screened using Principal Component …

Voltage-Related Power Quality Issues And Impacts On Distribution Networks With Sensitive Loads - A Review, Godwin Elinazi Mnkeni, Jackson Justo, Aviti Thadei Mushi, Bakari M. M. Mwinyiwiwa

Tanzania Journal of Engineering and Technology (TJET)

Voltage disturbances are the most important power quality (PQ) complications that customers and power utilities face in this smart era. The growing adoption of sophisticated electronic equipment and integration of renewable energy sources (RES) into power grids has increased the susceptibility of power distribution networks (PDNs) to voltage sags, swells, interruptions, flicker, and voltage imbalance. These disturbances, mainly caused by upstream faults, switching operations, and RES integration, compromise voltage PQ and system reliability. Consequently, they accelerate equipment degradation, increase electronic waste (e-waste), raise reactive power demand and maintenance costs, increase power losses, and impose substantial economic losses on customers and …

Could 'Real Existing Ai' Be Sentient?, Tim Crane

Animal Sentience

Jonathan Birch is rightly sceptical about the idea that today’s AI machines (e.g. LLMs) are candidates for sentience. Nonetheless, he gives three reasons for taking the future possibility of AI sentience seriously. I dispute them all. Birch fails to distinguish the very idea of an artificial mind from computational AI (what I call ‘Real Existing AI’); he does not adequately distinguish a simulation from a replica or copy; and he fails to acknowledge that the appeal to computational functionalism in this context is straightforwardly question-begging.

Implementation Of The Regfm_B1 Virtual Synchronous Machine Model With Supplementary Damping And Power System Stabilizer Extensions In Pstess., Kwabena Amadu

Honors Theses

The increasing penetration of inverter-based resources (IBRs) has motivated the development and verification of accurate grid-forming (GFM) control models for use in transient stability and dynamic simulation studies. This thesis presents an implementation of the REGFM_B1 virtual synchronous machine (VSM) model within the Power System Toolbox (PSTess) simulation environment. The implementation extends the baseline REGFM_B1 algorithm with a supplementary relative frequency damping path and a power system stabilizer (PSS). The implemented controller is verified on a simple three-machine test system and validated against an independent ideal VSM baseline implementation through simulations. This work establishes a validated PSTess implementation intended to …

Willingness To Pilot Under Varying Weather And Tower System Conditions: Mediating Effects Of Risk, Nathan Royal Schultz

Doctoral Dissertations and Master's Theses

The implementation of Remote Tower Systems (RTS) within the National Airspace System (NAS) offers potential improvements in operational efficiency, cost-effectiveness, and scalability; however, its success depends on pilots' willingness to operate in such environments. This study examined the effects of tower system type (RTS vs. Traditional Tower Systems [TTS]) and weather conditions (visual meteorological conditions [VMC], marginal visual meteorological conditions [MVMC], and instrument meteorological conditions [IMC]) on pilots’ willingness to pilot (WTP), while also evaluating the mediating role of perceived risk (PR). Grounded in Paul Slovic’s Risk Perception Theory (RPT), this research employed a quantitative experimental design using a factorial …