Engineering Commons^™

Improving Hydrogen Storage Kinetics Of Polymeric Composites Via Additions Of La0.6Ce0.4Ni5 And Carbon Particles, Muhammad M. Rahman, Fenil J. Desai, Ramazan Asmatulu, Md. Nizam Uddin, Karina Suarez-Alcantara

Faculty Publications

Nanostructured metal hydrides have garnered interest in their potential to store hydrogen safely and effectively as an energy carrier. By partially substituting lanthanum (La) with cerium (Ce), the structure of lanthanum pentanickel (LaNi₅) was maintained to create a novel encapsulated La–Ce–Ni-based metal hydride (La_0.6Ce_0.4Ni₅). The incorporation of metal-polymer composites can protect metal hydrides from oxidation and enhance cyclic stability. Carbon-based materials such as graphene and multi-walled carbon nanotubes (MWCNTs) not only store hydrogen but also improve the reaction kinetics and address thermal management issues. This study presents La_0.6Ce_0.4Ni …

Roadmap: Integrating Artificial Intelligence In Structural Health Monitoring Systems, Simon Laflamme, Erik Blasch, Flippo Ubertini, Zheng Liu, John Wertz, Christine Knott, Matthew Cherry, Eric Lindgren, Fu-Kuo Chang, Amrita Kumar, Jack Poole, Keith Worden, Austin Downey, Jie Wei, Patrick F. Musgrave, Adrian S. Wong, Guiseppe Quaranta, Marco Martino Rosso, Giuseppe Carlo Marano, Yu Chen, Et. Al.

Faculty Publications

Advances in computing and machine learning (ML) methods have led to a rapid rise in artificial intelligence (AI) research and applications in many fields. AI research benefitted from advances in computation hardware, collection and distribution of large data sets, and proliferation of software techniques. AI techniques include ML for provable results, deep learning for data exploration, reinforcement learning for control, and active learning for adaptive systems. Likewise, AI algorithms can handle large amounts of data, construct unknown representations, and provide a direct link between data and classification for decision making. These unmatched capabilities have been seen as a path to …

Towards Sustainable Energy Storage: Evaluating The Performance Of Three Polymer Electrolytes For Zinc-Ion Batteries, Roya Rajabi, Shichen Sun, Buke Sun, Jamil A. Khan, Kevin Huang

Faculty Publications

Polymer electrolytes have been explored as an alternative to conventional aqueous electrolytes in zinc-ion batteries, particularly for flexible and wearable applications. Despite the increasing interest in polymer electrolyte-based zinc-ion batteries (ZIBs), their development is still in its early stages due to various challenges. In this study, we investigated three promising polymer electrolytes: CSAM (carboxyl methyl chitosan with acrylamide monomer), PAM (polyacrylamide monomer hydrogel electrolyte), and p-PBI (phosphate-doped polybenzimidazole solid electrolyte) with Zn(ClO₄)₂ and Zn(OTf)₂, as electrolytes for zinc-ion batteries. The p-PBI solid electrolyte showed high mechanical stability and improved resistance to short-circuiting during cycling. The …

Towards Sustainable Energy Storage: Evaluating The Performance Of Three Polymer Electrolytes For Zinc-Ion Batteries, Roya Rajabi, Shichen Sun, Buke Wu, Jamil A. Khan, Kevin Huang

Faculty Publications

Polymer electrolytes have been explored as an alternative to conventional aqueous electrolytes in zinc-ion batteries, particularly for flexible and wearable applications. Despite the increasing interest in polymer electrolyte-based zinc-ion batteries (ZIBs), their development is still in its early stages due to various challenges. In this study, we investigated three promising polymer electrolytes: CSAM (carboxyl methyl chitosan with acrylamide monomer), PAM (polyacrylamide monomer hydrogel electrolyte), and p-PBI (phosphate-doped polybenzimidazole solid electrolyte) with Zn(ClO4)2 and Zn(OTf)2, as electrolytes for zinc-ion batteries. The p-PBI solid electrolyte showed high mechanical stability and improved resistance to short-circuiting during cycling. The presence of carboxyl groups in …

Characterizing Atmospheric Turbulence With The Lunar Step Response Method, Patrick D. Carattini, Caleb J. Stilp, Katelyn M. Atkinson, Stephen C. Cain

Faculty Publications

Most methods that astronomers use to characterize the strength of atmospheric turbulence in and around their observatories use differential image motion monitors observing a star to provide the necessary data for the measurement. With the Moon becoming a greater national priority, the need to characterize atmospheric paths between observatories on Earth and the Moon is potentially going to grow in the future. To this end, the differential image motion monitor is not an ideal instrument for characterizing turbulence along paths between observatories and the Moon as the bright Moon makes it difficult to detect and locate stars in its vicinity. …

Beyond Catalysts And Membranes: Using Cell Assembly And Operating Strategies To Significantly Improve The Performance Of Aem Electrolyzers, Mahmoud Amirsalehi, Venkata Sai Sriram Mosali, Mohammed Al-Murisi, Shaghayegh Bashiri, Hari Gopi, Pongsarun Satjaritanun, Benjamin Britton, Karen Swider-Lyons, Mustain E. William

Faculty Publications

Green hydrogen, produced through water electrolysis, is a key enabler of a low-carbon energy future, and anion exchange membrane electrolyzers (AEMELs) have emerged as a promising technology due to their potential for ultra-low-cost operation. However, achieving low cell voltage at high current densities and maintaining long-term durability remain key AEMEL challenges. To address these issues, most research efforts to date have focused on developing advanced catalysts and membranes. In contrast, the influence of non-material factors, such as cell assembly parameters and operating conditions, remains underexplored, even though they can significantly impact performance. This study investigates how such variables affect AEMEL …

Impediments To Transforming The Healthcare Delivery System: Shifting The Paradigm From Provider Centric To Patient Centric, Elizabeth A. Regan, Manasa Devi Chinta

Faculty Publications

Introduction: 

Stated aims for digital healthcare transformation frequently cite goals for better coordinated patient-centric systems. However, despite advances in medical science, digital technologies, health policies, and billions of dollars invested over the past 25 years, most healthcare providers are far from fully realizing the demonstrated benefits of today's digital technologies for improving patient care. Sharing information across healthcare systems remains challenging. Problems with fragmentation, quality, inequities, and rising costs of care delivery persist. A recent study of 1,026 U.S. hospital systems found that only 15.8 percent achieved a digital maturity level needed to provide digitally enabled healthcare services to better …

Influence Of Pulse Width On Energy Deposition And Temperature In Nanosecond-Pulsed Discharges, Christopher B. Reuter, Joshua B. Sinrud, Tanvir I. Farouk, Nicholas S. Dewey, Dmitri Kaganovich

Faculty Publications

Nanosecond-pulsed discharges are a promising method to enhance combustion but can generate significant levels of electromagnetic interference (EMI). Modifying the discharge pulse width is an unexplored option to reduce EMI, but few studies have examined how changing the pulse width affects discharge parameters such as energy and temperature. This study addresses this issue by systematically investigating how the pulse width affects the energy per pulse, breakdown time, rotational temperature, and vibrational temperature in air across different frequencies, flow velocities, and gap distances in a plasma-assisted flow tube. It is observed that the pulse width has a substantial impact on the …

Hybrid Cnn–Gru-Based Demand–Supply Forecasting To Enhance Sustainability In Renewable-Integrated Smart Grids, Süleyman Emre Eyimaya, Necmi Altin

Faculty Publications

The rapid integration of renewable energy sources in smart grids has introduced significant uncertainty in both power generation and consumption patterns, posing challenges to environmental, economic, and operational sustainability. Accurate short-term forecasting of energy demand and supply is essential for achieving optimal scheduling, grid stability, and resilient operation in renewable-integrated power systems. This study proposes a hybrid deep learning framework combining Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU) for intelligent joint demand–supply forecasting in smart grids. The model was developed and implemented in MATLAB using real-world datasets comprising electricity consumption, photovoltaic (PV) generation, temperature, and irradiance variables. Comparative …

Bridging 2d And 3d Computational Modeling Of Vacuum Arc Remelting: Capturing Rotating Arc Dynamics In Axisymmetric Simulations, Zilong Zhang, Elaheh Dorari, Ramesh Minisandram, Shakarjee Krishnamoorthi, Lang Yuan

Faculty Publications

Computational modeling of the Vacuum Arc Remelting (VAR) process has been developed to provide a deeper physical and metallurgical understanding and assist in the manufacture of defect-free ingots. While fully 3D, time-resolved arc models capture arc–melt interactions with high fidelity, their high computational cost makes 2D steady arc models still the preferred option in industrial applications. In this study, a multi-physics VAR model, which accounts for magnetohydrodynamics, heat transfer, fluid dynamics, and melting/solidification, was established in ANSYS Fluent for Alloy 718 in 3D with a rotating arc. It was validated against measured melt pool morphology. A new 2D axisymmetric oscillating …

Rapid-Response Reconnaissance Architecture Design For Planetary Defense With Nested Trajectory Optimization, Adam P. Wilmer, Justin A. Atchison, Marcus J. Holzinger, Robert A. Bettinger

Faculty Publications

Reconnaissance is a vital component in a comprehensive planetary defense mitigation strategy—aimed at preventing or reducing the impact threat posed by celestial objects on close-approach trajectories to Earth. It provides decision-makers with critical information on the physical and orbital properties of a near-Earth object (NEO), enabling better assessment of size, composition, and trajectory. This study investigates how to optimally pre-position a fleet of reconnaissance spacecraft prior to the discovery of a specific hazardous NEO. It evaluates response timelines and mission success rates for combinations of spacecraft launched from Earth and those maneuvering from pre-deployed locations within the Sun-Earth system. A …

Rapid Single-Cell Measurement Of Transient Transmembrane Water Flow Under Osmotic Gradient, Hong Jiang, Jinnawat Jongkhumkrong, Y. J. Chao, Qian Wang, Guiren Wang

Faculty Publications

Aquaporins (AQPs) are critical for transmembrane water transport in response to osmotic gradients, but their gating and regulatory mechanisms remain poorly understood. A central challenge is the lack of methods to measure water flow across AQPs from individual cells with the spatiotemporal resolution and sensitivity equivalent to patch-clamp recordings of ion fluxes—a limitation stemming from the electrically silent nature of water flow. Here, we present a novel optical technique—Flow-Induced Fluorescence Increase Velocimetry (FIFIV) based on Laser-Induced Fluorescence Photobleaching Anemometry (LIFPA)—that enables direct, real-time monitoring of cytoplasmic flow induced by transmembrane water transport under osmotic pressure gradients. Using small molecular fluorescent …

Discovery Of Dynamical Structures Mapping Chaotic Transport Pathways In The Earth–Moon Cr3bp, Tyler J. Kapolka, Christina E. Paljug, Robert A. Bettinger, Rachel Oliver, Bruce A. Cox, Jeremiah A. Specht

Faculty Publications

Chaos; Deterministic chaos; Earth–Moon system; Poincaré map; Quasi-chaotic; Surface of section /// For the Circular Restricted 3-Body Problem (CR3BP), the topologies present within a Poincaré map enable the extraction of useful information regarding periodic, quasi-periodic, and chaotic trajectory behavior. Aside from the prominent topologies that follow distinct concentric patterns around fixed points, indicative of the periodic and quasi-periodic motion that is often the central focus of CR3BP research, there are also many “dusty” regions on the Poincaré map that appear random without an apparent structure and are indicative of chaotic motion. This paper, for the first time in literature, identifies …

Post-Fire Inspection, Material Testing, Repair, And Field Load Testing Of A Full-Scale Concrete Box Girder Bridge: Delta Bridge Case Study, Ahmed S. Eisa, Hilal Hassan, Mohamed A. Badran, Ayman El-Zohairy

Faculty Publications

Bridges are critical components of transportation networks, and fire accidents can significantly impair their structural integrity, leading to safety risks and major economic losses. This study presents a comprehensive inspection, materials testing, repair, and field load testing program for a full-scale concrete box girder bridge (Delta Bridge, Alexandria, Egypt) following a fire exposure on two spans. A total of 28 concrete core samples were extracted and tested, revealing average compressive strengths of 48.50 MPa (slab), 53.90 MPa (web), and 45.88 MPa (columns), representing moderate reductions of approximately 8.5%, 7.9%, and 10.8%, respectively, relative to the original in situ concrete strength …

A New Highly Oxygen-Deficient And Cubic Pr3Zro8-Δ For Intermediate-Temperature Thermochemical Production Of Oxygen And Hydrogen, Jiaxin Lu, Yongliang Zhang, Luhong Chen, Yan Chen, Ke An, Yasser Shoukry, Xinfang Jin, Zhi-Hao Wang, Sai Mu, Kevin Huang

Faculty Publications

Two-step thermochemical cycles offer a clean route for hydrogen and oxygen production but are typically limited to high temperatures exceeding 1500 °C. Lowering operating temperatures would enable the use of alternative heat sources such as industrial waste heat. Here, we report Pr₃ZrO₈ as a new enabling material for efficient intermediate-temperature redox cycling, with thermal reduction at 900 °C in argon and steam oxidation at 400 °C. Pr₃ZrO₈ adopts a face-centered cubic structure similar to CeO₂ but exhibits significantly greater oxygen deficiency, achieving average oxygen and hydrogen fluxes of 331.7 and 70.3 µmol·g-1, respectively, …

Digital Twin Enabled Robot Collision Detection Using Time Series Forecasting, Fadi El Kalach, Mojaba A. Farahani, Philip Samaha, Thorsten Wuest, Ramy Harik

Faculty Publications

The advent of Industry 4.0 has reshaped modern manufacturing, driven by breakthroughs in cutting-edge technologies. A key example is the widespread deployment of sensors, which capture and transmit large volumes of operational data. This data surge has fueled the development of advanced Artificial Intelligence (AI) applications, enhancing manufacturing intelligence and efficiency. A key enabler of such intelligence is Time-Series Forecasting (TSF), which leverages historical data to predict future trends and events, thereby providing actionable insights for proactive decision-making. In parallel, Digital Twin (DT) technology has gained significant prominence due to its capacity for bidirectional communication with physical manufacturing systems, enabling …

Approaching Lower Bound Of Lattice Thermal Conductivity By Simultaneously Suppressing Diagonal And Off-Diagonal Phonon Contributions, Alejandro David Rodriguez, Riccardo Rurali, Changpeng Lin, Joshua Ojih, Mohammed Al-Fahdi, G. Jeffrey Snyder, Ming Hu

Faculty Publications

Pushing the intrinsic lattice thermal conductivity (LTC) in crystalline materials to lower bounds is crucial for fundamental materials research towards emerging technologies including thermoelectric energy conversion and thermal management in both hypersonic aircraft and next-generation turbine systems. However, in the ultralow LTC regime ( <  1 Wm-1K-1), the competition between propagative (particle-like) and coherent phonons—arising from off-diagonal components—poses a significant challenge in further reducing LTC. We perform quantitative analysis of 4700 materials using density functional theory (DFT), spanning all crystallographic groups, to elucidate the interplay between diagonal and off-diagonal phonon contributions. We identify a critical balance between these transport mechanisms, where intermediate phonon lifetimes ( ~ 1 ps) and slow group velocities ( ~ 1 km/s) collectively suppress both contributions, enabling ultralow LTC. Results from a large dataset of 31,058 structures by machine learning models strongly resemble the DFT trends of two-channel phonon transport. Leveraging these models, we screen 25,882 additional materials and confirm their properties with DFT, identifying 12 candidates with ultralow room-temperature LTC—including a record-low value of 0.132 Wm-1K-1. Our large-scale analysis reveals fundamental insights into dual-channel phonon transport, enabling rational design of ultralow LTC materials and accelerating the discovery of advanced phononic crystals with tailored thermal transport properties.

Intravascular Ultrasound Is More Accurate Than Angiography In Arteriovenous Vascular Access Lesions, James W. Decker, Dima Banihani, Curtis Honshideler, Saran Lotfollahzadeh, David Jasen Wu Wong, Alik Farber, Jeffrey J. Siracuse, Najia Idrees, Laura Dember, Mohammad Bader, Suvranu Ganguli, Vijaya Kolachalama, Tarek Shazly

Faculty Publications

Background:

Conventional angiography remains the standard diagnostic modality for arteriovenous (AV) access dysfunction in hemodialysis patients, but its geometric accuracy is limited. Intravascular ultrasound (IVUS) offers superior lesion detection, yet its absolute measurement accuracy remains uncertain. Using three-dimensional (3D) printed vascular conduits as reference standards, we assessed the accuracy of IVUS versus angiography, hypothesizing that complex conduit geometry, quantified by Gaussian curvature, would exacerbate angiographic error.

Methods

Clinically relevant AV access geometries were modeled with computer-aided design (CAD) and fabricated using 3D printing. Lumen diameters were measured by contrast angiography and IVUS and compared with CAD dimensions. Conduit geometry was …

Uav-Deployable Open-Source Sensor Nodes For Spatial And Temporal In Situ Water Quality Monitoring And Mapping, Matthew Burnett, Mohamed Abdelwahab, Joud N. Satme, Austin Downey, Gabriel Barahona Smith, Antonio Fonce, Jasim Imran

Faculty Publications

Cost efficient, spatially resolved water quality monitoring is essential for managing pollution and protecting aquatic ecosystems. This study presents a low-cost (approximately USD 200), open-source, unmanned aerial vehicle (UAV)-deployable in situ sensor node for real-time assessment of surface-water conditions. The system integrates sensors for pH, turbidity, temperature, and total dissolved solids (TDSs), with onboard data logging and real-time clock (RTC) synchronization. Bench validation of the sensor package yielded mean absolute percentage errors of 1.34% for pH, 5.23% for TDS, and 0.81% for temperature, and the device operated continuously for 42 h. Field deployment demonstrated its ability to resolve spatial gradients, …

Structural And Mechanical Properties Facilitate Shock Wave Damping By Helmet-Like Orbital Hoods In Snapping Shrimp, Mia Kazel, Rebekah E. Cammack, Alexandra C.N. Kingston, Ahmed A. Alshareef, Tarek Shazly, Daniel Isaac Speiser

Faculty Publications

Snapping shrimp damp the shock waves they produce and use as weapons with a helmet-like structure termed the orbital hood. Here, we ask how structural and material properties contribute to shock wave damping by orbital hoods in Alpheus heterochaelis. Using tensile mechanical testing, we find orbital hoods are approximately half as stiff as carapace and have twice the capacity for viscous energy dissipation. Microstructural features probably contribute to tissue-specific mechanical properties: the endocuticles of orbital hoods have almost twice as many lamellae as those of carapaces despite being half as thick, suggesting a mechanism for enhanced material mobility underlying …

Striation Characteristics In Atmospheric Pressure Ac-Driven Glow Discharge Operating In Monoatomic Gas, Ayuob K. Alwahaibi, Sang Hee Won, Tanvir Farouk

Faculty Publications

Striation in an atmospheric pressure AC-driven helium glow discharge operating at 25 kHz is experimentally characterized. Striation behavior is characterized by the visualization of discharges and voltage–current measurements over a range of plasma power. Voltage–current characteris tics reveal that striations form in the “normal” glow regime of operation, with a higher number of strata at low current, diminishing as dis charge current increases. The relative differences and similarities in the striation patterns during the positive and negative cycles are identified. High-speed imaging shows the striations to be traveling in time—“moving striations.” The spatial luminosity of the striations is tracked over …

Construction Project Performance Research: A Bibliometric, Scientometric, And Qualitative Review (1989–2023), Abdelnaser Abdelhameed, Mohamed S. Yamany, Ahmed Abdelaty, Emad Elbeltagi

Faculty Publications

Despite the significant increase in publications on construction project performance (CPP), there is a deficiency of research that rigorously assesses and synthesizes previous studies to delineate the field’s development, themes, and research gaps. This article employs quantitative and qualitative methodologies to critically evaluate studies on CPP published over the last three decades and indexed in the Scopus database. The quantitative approach includes bibliometric searches and scientometric analyses to assess the extent of research interest and achievements. The qualitative methodology aims to conduct thorough content analysis to classify existing material based on prevalent themes. The results demonstrate an exponential growth of …

Influence Of Superhydrophobic Surface Microstructure On Transient Jet Impingement Cooling, D. Jacob Butterfield, Brian D. Iverson, Daniel Maynes, Julie Crockett

Faculty Publications

Water jet impingement is an effective method of rapidly cooling a surface, but heat transfer from the surface is highly dependent on the surface condition and properties. Here, the impact of a superhydrophobic (SH) surface on heat transfer to an impinging, axisymmetric, room-temperature water jet with Re=6 x 10³to 18 x 103 is explored. SH surfaces are created by etching thin silicon wafers to form different micropatterns (posts or holes). Surfaces are heated to between 200 and 320°C, and the local surface temperature is measured with a thermal camera. The time resolved heat transfer from the surface and …

Rapid Flood Inundation Mapping For Dam Failure And Operations, Shivakumar Balachandran, Parvaneh Nikrou, Ayman Mokhtar Nemnem, Reza Saleh Alipour, Sagy Cohen, Xingong Li, Erfan Goharian, Jasim Imran

Faculty Publications

Dam failure often causes catastrophic flooding. Although conventional hydrodynamic models are available for generating flood inundation maps, there is a need for low-complexity models that can provide rapid inundation estimates during emergency situations. Operational releases of large volumes may also lead to downstream flooding. This study utilizes two DEM-based models, OWP HAND-FIM and FLDPLN, to produce flood inundation maps for near-real-time operational applications. Three dam-related scenarios, including failures and controlled operations, are examined using these simplified models for the Fall River Dam in Kansas. Breach flows are estimated using empirical relationships, and discharge attenuation is calculated using an analytical approach. …

Spline-Based Factor-Graph Optimization With High-Grade Inertial Sensors, Kyle Leland, Clark N. Taylor, David Woodburn, Randal Beard

Faculty Publications

Inertial measurement units (IMUs) are central to global navigation satellite system-based and alternative navigation solutions. This paper combines three lines of research to explore a novel methodology for using inertial sensors: factor graphs, spline-based trajectory estimation, and high-grade inertial sensing. Spline-based factor-graph trajectory estimation is increasingly used in the literature, especially for asynchronous or high-rate sensors. However, prior models neglect the impact of the Earth’s rotation, which is significant for high-grade IMUs. We extend spline-based factor graphs to incorporate accelerometer and gyroscope models that account for the Earth’s rotation. We apply this approach to simulated data from high-grade inertial sensors …

When Disasters Trigger Cyber Vulnerabilities: Mapping Physical-Digital Interdependencies In Critical Infrastructure Systems, Dikshya Panta, Sicheng Wang, Aditya Sapkota, Prakash Ranganathan

Faculty Publications

Critical infrastructure (CI) systems such as power, water, communications, and emergency services are increasingly exposed to compound risks in which natural disasters and cyber incidents interact and amplify one another. Traditional risk assessments often isolate physical and digital threats, overlooking the cascading dependencies that emerge when operational stress, emergency reconfiguration, and adversarial exploitation coincide. This study conducts a 2019–2025 scoping review and introduces a Geographic Information System (GIS) driven six-stage disaster cyber compounding framework that characterizes, maps, and operationalizes compound risk across interdependent CI sectors. The framework integrates a common operating picture, analytic situational understanding, exposure mapping, threat-fingerprint encoding, detection …

Crystal Structures, Optical Behavior, And Magnetic Properties In Hydrated Lanthanide Iron Sulfates, Chole Jones, Silu Huang, Tyler L. Spano, Eric A. Gabilondo, Mohammed Al-Fahdi, Kara Trim, Mary Douglas, Rongying Jin, Andrew Miskowiec, P. Shiv Halasyamani, Ming Hu, Jie Ling

Faculty Publications

Single crystals of LnFe(SO₄)₃(H₂O)₂ (Ln = La, Ce, Pr, Nd, Sm, Eu, Gd, Dy, Ho, Er, Tm; compounds 1–11) and LnFe(SO₄)₃(H₂O) (Ln = Tm, Yb, Lu; compounds 12–14) were synthesized under hydrothermal conditions. Single-crystal X-ray diffraction (SCXRD) analysis revealed that the dihydrated compounds (1–11) crystallize in centrosymmetric (CS) structures, with the lanthanide ions adopting eight-coordinate geometries. In contrast, the monohydrated compounds (12–14) exhibit noncentrosymmetric (NCS) structures, where the lanthanide ions are seven-coordinated. Vibrating sample magnetometry (VSM) confirmed that compounds 2, …

Pdr-Stgcn: An Enhanced Stgcn With Multi-Scale Periodic Fusion And A Dynamic Relational Graph For Traffic Forecasting, Jie Hu, Bingbing Tang, Langsha Zhu, Yiting Li, Jianjun Hu, Guanci Yang

Faculty Publications

Accurate traffic flow prediction is a core component of intelligent transportation systems, supporting proactive traffic management, resource optimization, and sustainable urban mobility. However, urban traffic networks exhibit heterogeneous multi-scale periodic patterns and time-varying spatial interactions among road segments, which are not sufficiently captured by many existing spatio-temporal forecasting models. To address this limitation, this paper proposes PDR-STGCN (Periodicity-Aware Dynamic Relational Spatio-Temporal Graph Convolutional Network), an enhanced STGCN framework that jointly models multi-scale periodicity and dynamically evolving spatial dependencies for traffic flow prediction. Specifically, a periodicity-aware embedding module is designed to capture heterogeneous temporal cycles (e.g., daily and weekly patterns) and …

Fatigue Crack Length Estimation Using Acoustic Emissions Technique-Based Convolutional Neural Networks, Asaad Migot, Ahmed Saaudi, Roshan Joseph, Victor Giurgiutiu

Faculty Publications

Fatigue crack propagation is a critical failure mechanism in engineering structures, requiring meticulous monitoring for timely maintenance. This research introduces a deep learning framework for estimating fatigue fracture length in metallic plates through acoustic emission (AE) signals. AE waveforms recorded during crack growth are transformed into time-frequency images using the Choi–Williams distribution. First, a clustering system is developed to analyze the distribution of the AE image-based dataset. This system employs a CNN-based model to extract features from the input images. The AE dataset is then divided into three categories according to fatigue lengths using the K-means algorithm. Principal Component Analysis …

Proposed Methodology For Correcting Fourier-Transform Infrared Spectroscopy Field-Of-View Scene-Change Artifacts, Kody A. Wilson, Michael L. Dexter, Benjamin F. Akers, Anthony L. Franz

Faculty Publications

Fourier-transform spectrometers are widely used for spectral measurements. Changes in the field of view during measurement introduce oscillations into the measured spectra known as scene-change artifacts. Field-of-view changes also introduce uncertainty about which target the measured spectrum represents. Though scene-change artifacts are often present in dynamic data, their significance is disputed in the current literature. This work presents a theoretical framework and experimental validation for scene-change artifacts. Field-of-view changes introduce variable interferogram offsets, which standard processing techniques assume are constant. The error between the interferogram offset and its estimate is Fourier-transformed, yielding scene-change artifacts, often confused with noise, in the …