Engineering Commons^™

High Temperature Diffraction From Aerodynamically Levitated Materials, Chris J. Benmore, Stephen K. Wilke, David Lipke, Richard Weber

Materials Science and Engineering Faculty Research & Creative Works

Aerodynamic levitation combined with laser beam heating has become an established technique for studying the structure of materials at ultra-high temperatures and under non-equilibrium conditions. This article briefly highlights some recent technical and scientific advancements in understanding the relationships between a material's behavior and its structure, investigated using diffraction methods. It focuses on three evolving frontiers: sophisticated sample environments for accessing metastable states and reactive chemistries, high-flux photon and neutron probes to reveal atomic structure, and advanced computational modeling frameworks. Free from contamination, containerless processing (levitation) can minimize heterogeneous nucleation at the interface, enabling access to deeply supercooled melts or …

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 …

A Combined Stochastic And Physical Framework For Alloys And Metal Casting Processes Modeling, Simon N. Lekakh, Oleg Neroslavsky

Materials Science and Engineering Faculty Research & Creative Works

High temperature metal casting processes have dualistic nature and conceptually consist of two parts of distinct processes: the first type is deterministic, strictly obeying the physical law, while the second type is stochastic. Therefore, the metal casting processes are not precisely predictable, and deterministic considerations cannot provide exact outcomes. To solve this problem, the combined stochastic and deterministic framework was suggested. The local processes were described using deterministic models for several parameter arrangements, while the distribution of these arrangements on macro level was calculated using stochastic approaches. The approach was used for cast alloy design, investment casting process optimization, and …

Thermal Transformations And Mechanical Properties Of All-D-Metal Mn2fecu Heusler-Type Shape Memory Alloy, Choji J. Daches, Joseph W. Newkirk, Mario Buchely

Materials Science and Engineering Faculty Research & Creative Works

All-d-metal Heusler alloys are emerging functional materials in which magnetic ordering, lattice distortion, and mechanical behavior are strongly coupled through d–d electronic interactions. This study systematically investigates the structural, thermal, magnetic, and mechanical properties of Mn₂FeCu synthesized within a Heusler-type compositional framework. SEM/EDS revealed a dual-phase FCC-based microstructure consisting of Mn–Fe–rich and Mn–Cu–rich domains, while XRD confirmed FCC symmetry with compositional partitioning rather than full L2₁ ordering. Differential scanning calorimetry identified partial melting of the Cu-rich phase near ~ 900 °C. Dilatometry showed a thermoelastic FCC → FCT transformation at ~ 770–780 °C with a recoverable strain of ~ 0.067%. …

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 …

Design Of Novel Gating Systems For Steel Castings, K. Balasubramanian, Laura Bartlett, M. Xu

Materials Science and Engineering Faculty Research & Creative Works

Gating systems play an important role in determining the quality and mechanical properties of castings. To understand the efficiency of gating systems, four systems, namely pressurized system, 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. Parameters like velocity of metal flow, air entrapment, microporosity and Niyama criterion were considered, and a design was developed with a common pouring basin. 8630 alloy was poured into two molds using a teapot ladle. The inclusion analysis revealed …

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 …

Microstructure And Properties Of Oxide Dispersion-Strengthened Alloys, Ertugrul Demir, Seung Min Ha, Anish Ranjan, Xingshuo Zhang, Aaron Penders, Mukesh Bachhav, Xiaochun Li, Lin Shao, Alexander Demblon, Haiming Wen, Enrique Lavernia

Materials Science and Engineering Faculty Research & Creative Works

Oxide dispersion-strengthened (ODS) alloys are a critical class of structural materials for extreme environments, owing to their unique combination of high-temperature strength, thermal stability, and radiation tolerance, enabled by a very high density of nanoscale oxide dispersoids. These features make ODS alloys attractive for advanced nuclear systems, aerospace applications, and other harsh-service conditions where conventional alloys rapidly degrade. Despite decades of development, key challenges remain in understanding how nanoscale oxides interact with matrix microstructures, alloy chemistry, and irradiation-induced defects to control macroscopic performance. This review provides a focused, mechanism-based synthesis of the microstructural features that govern the properties of ODS …

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 …

Evaluation Of A Novel Re-Crosslinkable Preformed Particle Gel For Conformance Control In Ultra-High Temperature Reservoirs, Yanbo Liu, Tao Song, Caleb Kwasi Darko, Thomas P. Schuman, Mingzhen Wei, Baojun Bai

Chemistry Faculty Research & Creative Works

Preferential fluid flow remains a major challenge in subsurface energy production and gas storage operations, resulting in excessive water production in mature oil fields, reduced heat extraction in geothermal reservoirs, and low sweep and storage efficiency in CO₂-EOR projects. Polymer gels are widely used to mitigate high-permeability channels; however, conventional systems exhibit limited plugging efficiency and short lifetimes in ultra-high-temperature reservoirs due to poor thermal stability. This study presents a novel ultra-high-temperature-resistant preformed particle gel (UHT-PPG) developed for conformance control in reservoirs with temperatures of 150–275 °C and severe super-K or channeling problems. The material was evaluated in …

Convergence Of High Throughput Experimentation And Machine Learning To Rapidly Advance Application-Specific Polymer Development, Mashrafee Aryan, Daniel Struble, Felix Campbell, Saroj Upreti, S. M.Ashik Abedin, Aahil Khambawla, Jeetain Mittal, Michael S. Dimitriyev, Emily B. Pentzer, Svetlana A. Sukhishvili, Xiaodan Gu, Boran Ma

Faculty Publications

Machine learning (ML) has heavily influenced the way scientific study is done with demonstrated successes in nearly every field. However, furthering performance and explainability of ML models in increasingly complex systems and with increasingly demanding outcomes requires a significant influx of high-quality data. To that end, this Review covers some of the techniques, instrumentation, and methodologies that have shown promise for significantly accelerating the discovery of polymer materials, optimization of their properties, and elucidation of property–application relationships through high throughput (HT) experimentation, characterization, and analysis. Attention is given to not only ML, but also to hardware advancements and their synergy …

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 …

Atomized Oxidative Polymerization As A 3d Printing Platform For Binder-Free, Bulk Conductive Polymer Architectures, Tazdik Patwary Plateau, Hiep Pham, Jonghyun Park

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Translating the ultrahigh intrinsic conductivity of conjugated polymers into bulk 3D architectures remains a formidable challenge due to the fundamental dichotomy between rheological printability and electronic purity. Existing strategies necessitate a compromise: solution-processing requires insulating binders that degrade charge transport, while binder-free vapor-phase polymerization (VPP) is kinetically confined to surface-limited thin films by diffusion constraints. Here, we introduce atomized oxidative polymerization (AOP), a manufacturing paradigm that overcomes these kinetic barriers via active, layer-by-layer monomer atomization. This approach ensures stoichiometric reaction conditions throughout the printed volume, driving a structural transition toward highly conductive quinoid-dominant chains with enhanced π-π stacking. The resulting …

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 …