Engineering Commons^™

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 …

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. …

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 …

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, …

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 …

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 …

Polystyrene Nanoplastics As Pfas Carriers And Their Interactions With Zwitterionic Phospholipid Membranes, Jiahuiyu Fang, Tongxuan Qiao, Pranab Sarker, Xiaoxue Qin, Size Zheng, Mark J. Uline, Tao Wei

Faculty Publications

The co-occurrence of per- and polyfluoroalkyl substances (PFAS) and nanoplastics (NPs) poses a synergistic threat to environmental and human health, yet the molecular mechanisms governing PFAS–NP complexation and membrane interactions remain unclear. Using atomistic molecular dynamics simulations, we investigated the adsorption of neutral polytetrafluoroethylene (PTFE) and anionic perfluorinated compounds (perfluorooctanoic acid, PFOA, and perfluorooctanesulfonic acid, PFOS) on polystyrene NPs (3.1 and 6.7 nm) and their interactions with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) membranes. Polystyrene NPs act as carriers, transporting PFAS molecules to the lipid/water interface, where PFAS attachment modifies NP interfacial behavior. PFAS adsorption on the NP surface is driven by …

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 …

Distributed Model Predictive Control-Based Power Management Scheme For Grid-Integrated Microgrids, Sergio Escareno, Sijo Augustine, Liang Sun, Sathishkumar J. Ranade, Olga Lavrava, Enrico Pontelli, John Hedengren

Faculty Publications

Transitioning from traditional electrical grids to smart grids is currently an ongoing process that many nations are striving for due to their access to renewable resources. Energy management is one of the key parameters that decides the performance of such complex systems. Distributed Model Predictive Control (DMPC) is a promising technique that can be used to improve the energy management of grid-connected systems. This paper analyzes a grid-connected inverter system with DMPC that exchanges key operating parameters with the grid to optimize coordinated power sharing between its respective loads. The state-space model for the inverter is derived and verified to …

Molecular Survival Strategies Against Kidney Filtration: Implications For Therapeutic Protein Engineering, William Heaps, Anna Elise Packard, Kristina M. Mccammon, Tyler P. Green, Joseph P. Talley, Bradley C. Bundy, Dennis Della Corte

Faculty Publications

The glomerular filtration barrier poses a significant challenge for circulating proteins, with molecules below ~60–70 kDa facing rapid renal clearance. Endogenous proteins have evolved sophisticated evasion mechanisms including oligomerization, carrier binding, electrostatic repulsion, and FcRn-mediated recycling. Understanding these natural strategies provides blueprints for engineering therapeutic proteins with improved pharmacokinetics. This review examines how endogenous proteins resist filtration, evaluates their application in protein engineering, and discusses clinical translation including established technologies (PEGylation, Fc-fusion) and emerging strategies (albumin-binding domains, glycoengineering). We address critical challenges of balancing half-life extension with tissue penetration, biological activity, and immunogenicity—essential considerations for the rational design of next-generation …

Tuning Oxygen Reduction Kinetics In Lasrcoo4 With Strained Epitaxial Thin Films And Wrinkled Freestanding Membranes, Habib Rostaghi Chalaki, Ebenezer Sessi, Mohammad El Loubani, Dongkyu Lee

Faculty Publications

Sluggish oxygen reduction reaction (ORR) remains a critical barrier to advancing intermediate-temperature electrochemical energy devices. Here, we demonstrate that strain engineering in two platforms, epitaxial thin films and freestanding membranes, systematically tunes ORR kinetics in Ruddlesden-Popper LaSrCoO4. In epitaxial films, film thickness is varied to control in-plane tensile strain, whereas in freestanding membranes strain relaxation during the release step using water-soluble sacrificial layers produces flat or wrinkled architectures. Electrochemical impedance spectroscopy analysis reveals more than an order of magnitude increase in the oxygen surface exchange coefficient for tensile-strained films relative to relaxed films, together with a larger oxygen vacancy concentration. …

Reformulation Of The Protein Databank For Real-Time Search Of Geometrical Attributes Of Protein Structures, Musa Azeem, Christopher Lee, Aaron Hein, Christopher Ott, Homayoun Valafar

Faculty Publications

Introduction:

In this study, we introduce the design and implementation of PDBMine, a large-scale, queryable platform for mining sequence-structure statistics from the Protein Data Bank (PDB). PDBMine enables rapid analysis of local conformational trends across proteins by extracting dihedral angles and sequence patterns at scale. In addition to the design and implementation of PDBMine, we also present results validating its ability to return structurally meaningful information.

Methods:

We first assess the accuracy of its dihedral angle distributions by comparing them to established Ramachandran space and verifying expected behaviors of residues such as glycine and proline. We then use PDBMine to …

Temperature Dependent High Frequency Performance Of A 62% Algan Channel Hemt, Jiahao Chen, Abdullah Al Mamun Mazumder, Parthasarathy Seshadri, Dheekshinn Nandakumar, Ruixin Bai, Rafael Andrew Choudhury, M. Asif Khan, Chirag Gupta

Faculty Publications

This article reports on the temperature dependent performance of a HEMT with an Al_0.62Ga_0.38N channel layer and an Al_0.84Ga_0.16N barrier layer grown by metal–organic chemical vapor deposition. The device in this report was measured at room temperature and elevated temperatures of 100–150 °C. The sheet resistance increased from 3.5 kΩ/sq (25 °C) to 5.4 kΩ/sq (150 °C), while the contact resistance remained nominally similar. For a device with 160 nm gate length and 2 µm source-to-drain length, excellent electrical characteristics have been achieved when the device was operated at 150 °C with …

Optimal Placement Of Electric Vehicle Chargers: A Mixed-Integer Linear Programming Model, Joubin Zahiri Khameneh, Emmanuel Fagbenle

Faculty Publications

Electric vehicle adoption is growing, but New Hampshire lags in public charging infrastructure, especially in rural areas. This gap increases range anxiety and economic inefficiencies. In this study, we developed a mixed-integer linear programming (MILP) model to optimally locate new electric vehicle chargers statewide, maximizing coverage and equity under budget constraints. The model includes geographic coverage requirements, population-weighted equity, capacity limits, and a $28 million budget. Moreover, the model recommends 855 Level 2 chargers and 149 Direct Current Fast Chargers (DCFCs) across 247 ZIP Codes, nearly doubling public charging capacity and achieving 98.8% coverage within defined service radii. The plan …

Precision Acoustofluidics For High-Throughput Mechanobiology In Suspension Cells, Kaichun Yang, Ruoyu Zhong, Ke Li, John Mai, Pengzhan Liu, Ye He, Joseph Rich, Ying Chen, Janna Wang, Zhiteng Ma, Zhiteng Ma, Xianchen Xu, Qian Wu, Tony Jun Huang

Faculty Publications

Mechanomodulation, the process of altering cellular behavior through applied mechanical forces, plays a critical role in physiological processes and has substantial implications for cancer therapy, immunology, and drug development. However, precise and efficient stimulation of nonadherent cells remains a major challenge, limiting the investigation of mechanotransduction pathways and the development of targeted therapeutics. Here, we developed an acoustofluidic platform named Suspension-cell Targeted Response to Excitation via Acoustofluidic Mechanomodulation (STREAM) to enable precise, high-throughput stimulation of suspension cells. STREAM accomplishes this using 101.14-megahertz high-frequency surface acoustic waves to deliver controlled mechanical stimulation at a throughput of 500,000 cells per minute. STREAM …

Stoichiometry-Controlled Surface Reconstructions In Epitaxial Abo3 Perovskites For Sustainable Energy Applications, Habib Rostaghi Chalaki, Ebenezer Seesi, Gene Yang, Mohammad El Loubani, Dongkyu Lee

Faculty Publications

ABO₃ perovskite oxides are a versatile class of materials whose surfaces and interfaces play essential roles in sustainable energy technologies, including catalysis, solid oxide fuel and electrolysis cells, thermoelectrics, and energy-relevant oxide electronics. The interplay between point defects and surface reconstructions strongly affects interfacial stability, charge transport, and catalytic activity under operating conditions. This review summarizes recent progress in understanding how oxygen vacancies, cation nonstoichiometry, and electronic defects couple to atomic-scale surface rearrangements in representative perovskite systems. We first revisit Tasker’s classification of ionic surfaces and clarify how defect chemistry provides compensation mechanisms that stabilize otherwise polar or metastable …

Mission-Focused Multidisciplinary Design Optimization Of Tilt-Rotor Evtol Propulsion System, Tyler Critchfield, Andrew Ning

Faculty Publications

Tilt-rotor propulsion system design requires a multidisciplinary approach to tackle important challenges and competing tradeoffs between disciplines. In this paper, we model rotor aerodynamics, blade structures, vehicle drag, electric propulsion, and tonal/broadband acoustics for a tilt-rotor, electric vertical takeoff and landing aircraft using low-to-mid fidelity tools. We use gradient-based design optimization with automatic differentiation and parameter sensitivity analyses to explore the design space and complex tradeoffs of tilt-rotor distributed electric propulsion systems, exploring effects of variations in payload/empty weight, battery specific energy, and blade tip speed. This framework models multiple operating points with a mission-focused objective to account for the …

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 …

Using Network Models To Understand Biological Signaling Architecture, Russ White, Emily Brown Reeves, Gerald L. Fudge

Faculty Publications

Engineers have developed abstract network models to better understand the recurring problems faced by communication systems. This paper argues that these models can be generalized to describe biological communications systems given that they share many requirements with human-designed systems, including functional requirements and physical constraints. Leveraging collaboration, biologists and engineers can work together to use well-understood communication systems, designed to carry data across a computer network, as a model for analyzing less well-understood biological communication systems in order to make predictions and uncover previously unknown functionalities. To illustrate this approach, we apply the Recursive Internet Network Architecture model (RINA) to …

Performance Of Shcc Brick Infill And Nsm Reinforcement Systems For Strengthening Rc Deep Beams With Large Openings, Ahmed Badr El-Din, Mohamed Ghalla, Galal Elsamak, Ayman El-Zohairy

Faculty Publications

The presence of large web openings in reinforced concrete (RC) deep beams often disrupts the natural load-transfer mechanism, leading to severe reductions in shear strength and premature failure. This study introduces a novel hybrid strengthening system incorporating strain-hardening cementitious composite (SHCC) bricks, stainless-steel and galvanized-steel sheets, and near-surface-mounted (NSM) steel reinforcements to restore and enhance the shear performance of RC deep beams with large openings. A comprehensive experimental program was conducted on sixteen beams under concentrated loading to evaluate the influence of different infill and strengthening configurations on load capacity, stiffness, ductility, and energy absorption. The results revealed that the …

Workshop Outcomes Report: 2nd International Workshop On Seismic Resilience Of Arctic Infrastructure And Social Systems, Majid Ghayoomi, Daniela Morganti

Faculty Publications

The report provides an overview of the second international workshop on Seismic Resilience of Arctic Infrastructure and Social Systems. The report discusses agenda, workshop activities, interdisciplinary working groups, and results. It ends with several strategic questions and investigation plans that were developed as part of the workshop activities.

Influence Of Surface Features On Heat Transfer During Dropwise Condensation Over Superhydrophobic Surfaces In Shear Flow, Shaur Humayun, R. Daniel Maynes, Julie Crocket, Brian D. Iverson

Faculty Publications

This study investigates heat transfer during dropwise condensation (DWC) on superhydrophobic (SH) surfaces in humid air shear flow, emphasizing the effect of increased drop mobility and the influence of surface micro/nanostructure on heat transfer rates. Experiments were conducted on smooth hydrophobic, microstructured SH, nanostructured carbon-infiltrated carbon nanotube (CICNT) surfaces, and two-tiered SH surfaces with both micro and nanostructures. Heat transfer rates were measured under humid air flow rates in the range of 2–4 CFM. Experimental results demonstrate that surfaces with nanostructure (including two-tiered structures) exhibit increased drop mobility and coalescence-induced drop jumping, enhancing drop removal rates and overall heat transfer …

The Composition Of Gases From A Diffusion Flame Above Longleaf Pine Needle Fuel Beds, David R. Weise, Thomas H. Fletcher, Timothy J. Johnson, Weimin Hao, Russell G. Tonkyn, Catherine A. Banach, Javier Palarea-Albaladejo, Mahsa Alizadeh, Stephen Baker

Faculty Publications

The gas and tar composition of a wildland fire diffusion flame from longleaf pine needles is currently relatively unmeasured and more data are needed to fill in the gap between pyrolysis data and smoke plume data, thus improving physical and chemical modeling of wildland smoke formation. A pilot experiment to measure light gas and tar composition of such a flame is described for three flame zones: persistent flame (flame base), intermittent flame, and smoke plume. Flame gases from 24 experimental fires were collected in canisters and analyzed for CO2, CO, H2, CH4, and C2 to C7 hydrocarbon gases. Other light …

Efficiently Stowed Flashers With Uniform-Thickness Panels Based On Non-Developable Origami, Larry L. Howell, Robert J. Lang, Specer P. Magleby, Davis Wing

Faculty Publications

We present the mathematical construction of a deployable flasher pattern with near-uniform nonzero thickness in the deployed form and efficient face-to-face packing in the stowed form. We demonstrate its fabrication, deployment, and stowage. The results facilitate the design and manufacture of deployable systems with panels whose substantial thickness is dictated by the end application, with particular utility for space systems.

Optimal Sizing Of Battery Energy Storage Systems For Peak Shaving And Demand Response Using A Degradation-Aware Bayesian Optimization-Mixed-Integer Linear Programming Framework, Jiwei Yao, Blake Billings, Tao Gao, John Hedengren, Kody M. Powell

Faculty Publications

The increasing integration of renewable energy and rising electricity demand highlight the importance of battery energy storage systems for peak shaving and demand response. Unlike prior approaches that overlook operational impacts on degradation, this study proposes a Bayesian Optimization–Mixed Integer Linear Programming framework for optimal battery energy storage system sizing. In this framework, Mixed Integer Linear Programming determines short-term scheduling while a calibrated electrochemical model iteratively evaluates degradation. The central hypothesis is that the framework can efficiently identify optimal sizes that yield realistic and economically robust outcomes. The method is tested across three scenarios: peak shaving, peak shaving with energy-reduction …

Amp: Single-Shot Ultra-Wide Fisheye-To-Cubemap Pnp Pose Estimation, Ryan M. Raettig, Richard R. Nyquist, Scott L. Nykl, Clark N. Taylor, Christine M. Schubert Kabban

Faculty Publications

Estimating the position and orientation of a rigid object from an image is critical for situational awareness in robotics and autonomous systems. This study explores relative pose estimation using an ultra-wide fisheye camera for unmanned aircraft inspection vehicles. Ultra-wide fisheye lenses introduce radial distortion and capture features beyond the rectilinear image plane, rendering rectilinear Perspective-n-Point (PnP) algorithms inadequate. Designing a bespoke ultra-wide fisheye localization algorithm requires consideration of both the feature detection method and the pose estimator itself. This study proposes a novel method that combines (1) a fisheye-to-cubemap reprojection, (2) a You Only Look Once (YOLO) convolutional neural network …