Engineering Commons^™

Radical-Based Oxidative Pretreatment Enhances Biofuel Production From Lignocellulosic Biomass Via Hydrothermal Liquefaction, João Vitor Dos Santos, Louis C. Bondurant, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

The sustainable production of biofuels from lignocellulosic biomass is a central goal in the transition to low-carbon energy systems. However, hydrothermal liquefaction (HTL), a promising thermochemical conversion pathway, is constrained by the high oxygen content and complex aromatic structure of lignin, which lowers bio-oil quality. Here, we used a model system of brown-rot-degraded white oak (Quercus alba) to test whether radical-based oxidative pretreatment could enhance HTL performance by converting lignin into more aliphatic intermediates. Oxidation was performed under simulated Fenton conditions using fixed Fe(II) (60 ppm) and two hydrogen peroxide concentrations (3 and 8 M), resulting in extensive lignin depolymerization …

Extraction And Characterization Of Fresh And Dehydrated Cactus (Opuntia Ficus Indica) Polysaccharide For Hydrogel Preparation, Aye Thwe Thwesoe, May Myat Khine

ASEAN Journal on Science and Technology for Development

In this research, extraction of polysaccharide compounds from Cactus (Opuntia Ficus Indica) leaves in both fresh and dehydrated condition by solvent precipitation method using three types of water, acid (HCL) and NaOH. Before extraction, the physicochemical properties were examined to determine optimum yield (%) of extracted polysaccharide by optimization of Box-Behnken Design (BBD) of response surface methodology (RSM). The polysaccharide-based acrylamide hydrogel was prepared by free radical polymerization. The functional and structural characterization was done by FTIR, XRD and SEM for examination of extracted polysaccharide as raw polymer backbone in hydrogel preparation and prepared hydrogel as adsorbent for metal removal. …

Beyond The Binary: Navigating Ai’S Role In Palliative Ethics-A Review, Reebu Sara Varghese, Tijo Cherian

ASEAN Journal on Science and Technology for Development

Palliative care is being influenced by artificial intelligence, especially when it comes to data-related aspects. In this context, care can be enhanced in terms of the quality of its results and the level of its efficiency, particularly with the help of technological tools such as artificial intelligence, which is capable of managing different types of information in the field of health care. Such characteristics have the potential to improve the quality of patient care while at the same time reducing the workload of healthcare professionals in palliative care. However, there are considerable ethical issues that need to be addressed with …

Ai-Assisted Hybrid Ga–Pso Channel Allocation Under 3gpp Tr 38.901 Uma For Efficient 5g Radio Resource Management, Sharada Narsingrao Ohatkar

ASEAN Journal on Science and Technology for Development

The increased traffic and heterogeneity in the 5G/B5G network require efficient radio resource management (RRM). However, the existing methods, such as GA and PSO, have poor convergence speed and require proper initial conditions. Additionally, learning-based methods have high computational complexity. Hence, in this paper, a novel AI-assisted Hybrid Channel Allocation (AI–HCA) framework is proposed by using a support vector regression (SVR)-based predictive initialization method and GA-PSO optimization. Simulation results using the 3GPP UMa channel model show that the proposed method has a 28% reduction in call blocking probability (CBP), a 15-25% enhancement in spectral efficiency (SE), and a 18-25% enhancement …

Virtualized And Distributed Neighborhood Data Centers, Benjamin T. Niccum

Computer Science and Engineering Theses

This thesis evaluates whether PCIe-fabric-based resource pooling can support a decentralized neighborhood micro-data-center model under real implementation constraints. The work combines architecture design, prototype deployment, performance benchmarking, and security assessment. Results show strong prototype-scale feasibility with low-latency and high-throughput behavior, while also identifying deployment-blocking security gaps and operational maturity requirements. The thesis contributes an evidence-traceable path from concept validation to deployment-grade roadmap planning.

The Rise In Height And Curb Weight Of The Top-Selling Vehicles In The United States From 1991 - 2025: Implications For Engineering Design And Vulnerable Road Users, Samuel L. Steinman-Friedman

Civil Engineering Theses

Road fatalities are higher in the United States than in other high-income regions. In 2024, 39,254 people died on roads in the United States compared to 19,940 in the European Union. These two regions have comparable exposure metrics, such as population size, roadway network length, and fatalities per mile traveled. Light trucks dominate the U.S. market, whereas hatchbacks are prevalent in Europe. The trendline of the average height and curb weight of the top-selling vehicles in the United States has increased by 0.24 inches and 23.52 pounds per year since 1991. The average 2025 top-selling U.S. passenger vehicle is 7.5 …

Integrated Thermal, Energy, And Structural Performance Assessment Of A Novel In-Service Shallow Geothermal Bridge Deicing System, Alireza Fakhrabadi

Civil Engineering Dissertations

Understanding the performance of bridge deck deicing systems under winter weather conditions is important for improving transportation safety and reducing long-term deterioration of bridge infrastructure. Bridge decks are more vulnerable to icing than ground-supported pavements because they are exposed to ambient air, wind, and radiation from multiple directions, while they do not receive thermal support from the underlying soil. Conventional deicing methods, especially chloride-based salts, can reduce ice formation in the short term, but repeated application may accelerate reinforcement corrosion, concrete damage, and environmental concerns. Therefore, shallow geothermal energy has been considered as a sustainable alternative for bridge deck deicing …

A Hybrid Geospatial And Remote Sensing Methodology For Drought Vulnerability Assessment In Semi-Arid Ecosystems, Kaifi Fakhir Chomani

Mansoura Engineering Journal

The Kurdistan Region of Iraq (KRI) faced significant drought challenges due to global and environmental changes, necessitating drought assessments. Advanced techniques of remote sensing, Geographic Information Systems (GIS), and Analytic Hierarchy Process (AHP) were combined in this research to perform drought vulnerability zonation for KRI. Average annual rainfall, Average number of rainy days, Average annual temperature, slope, elevation, normalised difference water index (NDWI), normalised difference vegetation index (NDVI), land surface temperature (LST), and temperature condition index (TCI) were selected as contributing parameters for drought vulnerability assessments. The considered parameters were weighted using pairwise comparison, and thematic maps were created to …

A Machine Learning–Based Framework For Traffic Classification And Threshold-Based Load Management In 5g Network Slicing, Safi Ibrahim, Younis S. Younis, Kamal S. Hamza, Mohamed M. Ashour

Mansoura Engineering Journal

This study proposes a machine learning–based framework that applies machine learning techniques to improve the efficiency of 5G network slicing through automated traffic classification and threshold-based load management . The proposed model optimizes resource allocation among the three standardized 5G slice types: enhanced Mobile Broadband (eMBB), ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC). Two supervised learning algorithms—K-Nearest Neighbors (KNN) and Support Vector Machine (SVM)—are trained using Quality of Service (QoS) parameters such as packet delay, loss rate, and Quality Class Identifier (QCI). Experimental evaluations were conducted on two large-scale datasets containing over 400,000 traffic instances, demonstrating that the …

A Hybrid Geoid Model For The Perlis Region, Malaysia Based On Cadastral Reference Marks And A Geometric Approach, Muhammad Aiman Haiqal Abdul Malek, Muhammad Faiz Pa’Suya, Ramazan Alpay Abbak, Ami Hassan Md Din, Noorfatekah Talib

Mansoura Engineering Journal

This study presents the development of a high-resolution local geoid model for the Perlis region, Malaysia, using a geometric approach that integrates GNSS-levelling benchmarks with Cadastral Reference Mark (CRM) data. A total of 38 GNSS-levelling benchmarks were used as reference points, while 3,725 CRMs were incorporated to significantly enhance spatial coverage for geoid modelling. Orthometric heights at the CRM points were first determined by transferring heights from the reference benchmarks using gravimetric geoid information. Subsequently, geometric geoid heights were computed from the differences between ellipsoidal and orthometric heights. Five interpolation techniques were evaluated to generate the geometric geoid surface, namely …

Effect Of Two Cut Off Rows On Seepage Underneath Hy-Draulic Structures Using Weak Form Differential Quadra-Ture Element Method: A Theoretical Approach, Esraa Ahmed, El-Masry A. A, Hossam A.A. Abdel Gawad, Ahmed Elhamrawy

Mansoura Engineering Journal

Investigating confined seepage underneath hydraulic structures is crucial to ensure the safety of these structures. The Weak Form Quadrature Element Method (WFQEM) is the basis of this paper, which explores the behavior of confined flow. The seepage flow governing equation is solved numerically to estimate the uplift pressure underneath the hydraulic structures and the exit gradient.The Gauss–Lobatto–Legendre (GLL) type is used as nodal and integration points. Several models were solved to validate the applied numerical method. The obtained results are compared with theoretical and preceding numerical solutions mentioned in the literature. The system of equations generated from applying the WFQEM …

Reliability-Oriented Spatiotemporal Machine Learning For High-Impact Power Outage Event Prediction, Marwa Gamal

Mansoura Engineering Journal

Power outages have become an increasing concern for modern power systems due to their impact on infrastructure reliability, economic activities, and public safety. The growing frequency of extreme weather events and the rising demand for electricity have made it more difficult to anticipate high-impact outage events. One of the main challenges in this context is the complex interaction between temporal patterns and geographic variations, which traditional methods often fail to capture effectively. This study develops a machine learning framework that combines temporal characteristics with geographic information to improve the prediction of high-impact power outages. Temporal features such as seasonal patterns, …

Optimal Design Of Concrete Canal Section For Minimizing Overall Costs Using Artificial Ecosystem Optimization, Aya M. Elkhouly, Hamdy A. El-Ghandour, Tharwat Sarhan, Mahmoud E. Abd-Elmaboud

Mansoura Engineering Journal

The optimal design of concrete-lined canals represents a critical challenge in hydraulic engineering, requiring simultaneous minimization of construction and operational costs while satisfying hydraulic performance constraints. This study presents a novel optimization framework that utilizes the Artificial Ecosystem-based Optimization (AEO) algorithm for determining optimal canal cross-sectional dimensions. The proposed methodology comprehensively considers excavation costs, lining expenses, and water losses due to seepage and evaporation while ensuring hydraulic efficiency through velocity and Froude number constraints. The AEO algorithm mimics natural ecosystem processes through production, consumption, and decomposition phases to efficiently explore the design space and converge to global optima. The framework …

Comparative Evaluation Of Gating Systems In Femnal Castings, K. Balasubramanian, Laura Bartlett, M. Xu

Materials Science and Engineering Faculty Research & Creative Works

To understand the efficiency of gating systems, four systems, namely AFS styled pressurized system, AFS styled non-pressurized system, naturally pressurized system with a side riser and a naturally pressurized system with a top riser, were studied. The naturally pressurized systems were provided with overflows which collected the incoming metal swirl while the pressurized and non-pressurized systems had runner wells. Parameters like velocity of metal flow, air entrapment, microporosity and Niyama criterion were considered, and a design was developed with a common pouring basin using solidification software. Two molds were 3D printed using carbonitride sand, and steel of composition Fe-29Mn-8.2Al-0.91C-0.88Si-0.49Mo was …

Overcoming Resolution Vs. Throughput Trade-Offs In Ceramic Material Extrusion Additive Manufacturing Via Viscoelastic Filament Stretching, Abid H. Rafi, David W. Lipke, Jeremy L. Watts, Gregory E. Hilmas, Ming C. Leu

Materials Science and Engineering Faculty Research & Creative Works

Fabricating large, monolithic ceramic parts using material-extrusion additive manufacturing remains challenging due to difficulty maintaining uniform moisture content during printing, which can lead to drying-induced defects such as warping and cracking, especially as part size and print time increase. Fabricated parts have trade-offs among print resolution, high throughput, and structural fidelity. Our study has shown that increasing the ratio of nozzle traverse speed vs. material extrusion speed increases filament stretching in viscoelastic ceramic paste, helping to overcome the trade-offs between resolution and throughput. Using aqueous ZrB2–SiC (70/30 vol.%) as a representative ultra-high temperature ceramic paste, rheological characterisation revealed viscoelastic yield-stress …

Design And Fabrication Of A Scaled Automated Dairy Farm Model: A Report, Md Towfiqur Rahman

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Summary

This study investigates how ventilation systems work in dairy barns and builds a scaled model to support education and research. The project is designed to help students from the University of Nebraska–Lincoln (UNL), K-12 learners, and researchers in animal science, veterinary medicine, and engineering gain visual experience with dairy facility components and processes. Different ventilation methods were studied, leading to the design of a 1/64-scale tunnel-ventilated dairy barn meant for 60 Holstein Friesian cows. Barn dimensions were set based on real Holstein cow measurements to ensure proper cow comfort, while airflow requirements were calculated and scaled down. Miniature fans …

A Computational Approach To Graduated Centrifuge Profiles For Partial Gravity Planetary Environments, Cabell W. Jones

Mechanical & Aerospace Engineering Faculty Publications

Missions such as NASA’s Artemis and SpaceX’s Starship aspire towards creating permanent settlements beyond Earth. In order to achieve this goal, it must be considered that the gravity present on planetary surfaces such as the Moon (0.165 g) and Mars (0.378 g) may be insufficient to support human physiology for long term habitation. On near-Earth missions, issues such as muscular atrophy, neuro-ocular changes, cardiopulmonary variations, and bone mineral density loss have been observed proportional to the duration spent in microgravity. Further studies have suggested that the severity of these conditions scales linearly with decreasing gravity, meaning that astronaut health can …

Automated Object Detection And Change Quantification In Underground Mines Using Lidar Point Clouds And 360◦ Image Processing, Ana Fabiola Patricia Tejada Peralta, Roya Bakzadeh, Sina Siahidouzazar, Pedram Roghanchi

Mining Engineering Faculty Publications

Underground mining environments pose significant challenges for automated hazard detection due to low illumination, restricted visibility, and the absence of Global Navigation Satellite System (GNSS) coverage. These factors limit situational awareness and delay inspection efforts, particularly after disruptive events when rapid assessment is essential for safety. This study addresses this problem by developing a dual-pipeline framework for 2D–3D detection that uses 360° imaging and LiDAR-based machine learning to identify people, vehicles, and positional changes in underground settings without requiring personnel to re-enter hazardous areas. The objective was to create a system capable of recognizing objects and monitoring spatial changes under …

Utilizing Digital Twins To Model And Optimize Hydraulic Excavator Operator Performance Through Arena Simulation, Mateo Fernando Montenegro Defaz, Kwame Awuah-Offei

Mining Engineering Faculty Research & Creative Works

This study aims to provide a digital twin tool for mining and construction companies to evaluate the effect of operator behaviors on the truck-loading process, focusing on swing and bucket rotation. While equipment performance estimators are available, there are few tools to assess the influence of operators. The aim is to create a discrete event simulation (DES) model in Arena® to evaluate how variations in swing and bucket angles affect hydraulic excavator production rates. We validated the DES model using real-world data from a case study to assess the differences in behavior among four operators. Results showed that Operator 1 …

Stall Detection In Hydraulic Excavator Operations Using Heuristics And Machine Learning: A Case Study, Mateo Fernando Montenegro Defaz, Kwame Awuah-Offei, Yixiang Gao

Mining Engineering Faculty Research & Creative Works

This work aims to develop a reliable algorithm for stall detection during excavator digging by analyzing key operational variables such as velocity and angular displacements from machine monitoring data. The work develops and validates a heuristic algorithm to detect stalling events and trains a support vector machine classification algorithm to distinguish between "normal" digging cycles and cycles with stalling. This work is a novel attempt at using a classification algorithm to categorize digging cycles into normal and those with stalling events based on machine monitoring data alone. The developed classification algorithm achieved a sensitivity of 100%, indicating it correctly identified …

Triangulating Primary Sources, Professional Judgement, And Llm-Generated Summaries: Educating Nurses In An Ai-First World, Sarah Oerther, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Multi-User Collaboration In Augmented Reality For Beyond-Visual-Line-Of-Sight Bridge Inspection, Joel Murithi Runji, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Bridge inspection traditionally relies on scaffolds, snooper trucks, and aerial robots for hard-to-reach areas beyond the visual line of sight of inspectors. This study automates the collaborative inspection workflow for multiple users when inspecting hard-to-reach bridge sections by interfacing low-cost multimodal sensors mounted on a magnetically wheeled climbing robot with augmented reality devices in a cyber-physical system. Non-destructive and visual sensors provide near real-time information of automated steel thickness measurements and visual observations of corrosive regions, respectively. The visual sensors also support robot teleoperation. The cyber-physical system is evaluated for its user-friendliness and performance. The system performance is quantified by …

Heat-Related Injuries And Fatalities In Roofing: Osha Investigations From 2003-2024, Kenneth S. Sands Ii, Benjamin Marshall

The Professional Constructor

This study examines 52 heat-related roofing incidents recorded by the Occupational Safety and Health Administration (OSHA) between 2003-2024 to describe patterns in outcomes and identify trade-specific prevention opportunities. Researchers built a structured dataset from OSHA investigation summaries and analysed frequencies of the incidents and their associations with month, time of day, project type, end use, and age to complement a thematic review of narrative abstracts. Fifty-eight percent of cases were fatalities, with the remainder split between hospitalized and non-hospitalized injuries; these statistics underscore the consequences of heat events that trigger OSHA reporting. There was a clear relationship between number of …

Raw Data For The Manuscript "Silicon-Stabilized Three-Dimensional Covalent Networks In High Entropy Diborides", Michael Yeung, Reza Mohammadi

Chemistry Department Faculty Scholarship

Abstract for data:

Raw data for the journal publication, Silicon-stabilized three-dimensional covalent networks in high entropy diborides. ReadMe file provided.

Abstract for Journal publication: 

High entropy ceramics offer a pathway to stabilize unconventional chemistries beyond traditional alloying rules. We report the incorporation of silicon into an AlB₂-type high entropy diboride, Cr_0.2Nb_0.2Si_0.2Ta_0.2Ti_0.2B₂, despite silicon violating classical Hume-Rothery rules for alloying. Arc melting produced a phase-pure, chemically homogeneous structure, as confirmed by powder X-ray diffraction (pXRD) and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM–EDS). Silicon occupies …

Managing Green And Sustainable Construction Projects: A Computational Analysis Of Associated Risks And Challenges For Improved Performance, Bahaa Chammout, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Green and sustainable building practices have emerged as effective strategies to address the environmental challenges posed by the construction industry. This includes unsustainable resource utilization, excessive waste production, greenhouse gas emissions, and high energy consumption. However, the integration of green and sustainable initiatives in construction introduces distinct risks and challenges that affect project management and may lead to claims and disputes. To this end, and while previous research examined dispute causation across various aspects of the construction industry, there is limited investigation of the unique and complex nature of risks and challenges - and consequently conflicts, claims, and disputes - …

Evaluation Of Two-Group Iate Coupling With Pbe For Beyond Bubbly Flows In A Large Diameter Pipe, Sungje Hong, Joshua P. Schlegel, Subash L. Sharma

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

This study evaluates the two-group interfacial area transport equation (2G IATE) coupled with the S-Gamma (Sγ) population balance equation (PBE) model for beyond bubbly flow regimes in a vertical large-diameter pipe. The 2G IATE framework incorporates intergroup mass transfer mechanisms and is implemented within the Sγ model, which assumes a log-normal bubble size distribution. The numerical approach is validated against experimental data from Schlegel et al. (2012), with a focus on the void fraction and interfacial area concentration (IAC) distributions. The results show that 2G IATE improves the predictions of the void fraction and IAC, although its accuracy varies with …

Experimental Investigation Of Subcritical Neutron And Gamma Noise Methods At The Seven Percent Critical Experiment (7upcx), Cole Kostelac, Jesson Hutchinson, George Mckenzie, Robert Weldon, Nicholas Whitman, Ayodeji Babatunde Alajo

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

As part of a collaborative international effort organized by Lawrence Livermore National Laboratory (LLNL), with key participants from L'Institut de radioprotection et de s ˆuret´e nucl´eaire (IRSN), Los Alamos National Laboratory (LANL), and Sandia National Laboratories (SNL), a series of high-multiplication subcritical neutron and gamma noise measurements were planned and executed. The primary aim of this research was to advance detector technology, assess the validity of gamma noise for subcriticality measurements, and nuclear criticality safety, focusing on collecting list-mode or time-series data from various reactor configurations with multiplication values ranging from 20 to 310. This comprehensive dataset enabled a detailed …

A Framework For Enhanced Circular Product Development With Total Life Cycle Considerations, Gisele Bortolaz Guedes, Fazleena Badurdeen, Ibrahim S. Jawahir

Mechanical Engineering Faculty Publications

Advancing circular product development (CPD) requires design decisions that account for the entire product life cycle, from material sourcing and manufacturing to use and end-of-use (EoU) stages, to ensure enhanced sustainability performance. Existing Product Development Process (PDP) models tend to emphasize isolated phases or perspectives with limited explicit consideration of the total product life cycle. This hinders the systematic embedding of various Circular Economy (CE) strategies during product development. Thus, designers and engineers lack a unified framework to determine when and where critical decisions should be made to effectively incorporate CE strategies such as effective resource selection, extending product use-life, …

Students For The Exploration And Development Of Space (Seds) Air Brake Subsystem: High-Altitude Autonomous Apogee Modulator System For High-Powered Rockets (Haamshr), Camden J. Maclean, Matthew Wharton, Nick Revis, Colin Guido

Honors Theses and Capstones

The objective of this project was to research, design, fabricate, and analyze an autonomous apogee modulation air brake system for the University of New Hampshire (UNH) Students for Exploration and Development of Space (SEDS) high-powered rocket as competitors in the Friends of Amateur Rocketry – Oxidizers Uninhibited Tournament (FAR-OUT) competition.

This air brake system would be developed with considerations for full autonomy, structural reliability, and repeatable deployment. The design would also be easily integrated into the existing high-powered rocket airframe and mechanically simple to increase reliability and practical functionality. The final design would be evaluated using finite element analysis simulation …

Μmodules: A Low-Cost, Eurorack-Compatible Modular Audio Synthesis System, Nolan K. Juneau

Honors Theses and Capstones

The modular audio synthesizer is one of the fastest-growing industries in contemporary music technology. Unlike a traditional audio synthesizer, a modular synthesizer allows for the user to directly control the signal path and effects of the synthesized sound, allowing for a workflow that is completely customizable to an individual musician and their creative vision. However, the modules and cases currently in production for the common “Eurorack” design standard can be prohibitively expensive to new users, often costing thousands of dollars for even a small system. The µModules project aims to eliminate this financial barrier to modular synthesis by using inexpensive …