bluuebunny/crossref_metadata_2025_split huggingface dataset:
Navigating Complex Vascular Pathways With “Meet in the Middle” Magnetic Guidewire Navigation Technique
Authors: Nwankwo Chijioke Christopher , Kelly Damian , Srivastava Rupal 
Published: January 2025

Abstract
In interventional cardiology and endovascular surgery, navigating tortuous and occluded vascular pathways presents a significant challenge. The “meet in the middle” magnetic guidewire navigation technique is a promising strategy to address this challenge. This innovative approach leverages the principles of magnetic attraction and repulsion to guide a magnetic guidewire through intricate vascular networks, allowing for precise and controlled navigation. This study investigates the efficacy and feasibility of the “meet in the middle” magnetic guidewire navigation technique in navigating complex vascular lesions. The guidewire tip has a copper coil generates the magnetic field through electromagnetic induction. Through experiments, observations are made to understand the intensity of the electromagnetic induction guidewire system for varying cooper coil turns and wire diameters. Additionally, considerations such as magnetic field strength, guidewire design, and compatibility with existing interventional tools are explored to present a future framework to optimize the navigation process. The findings from this study hold significant implications for interventional cardiologists, endovascular surgeons, and medical device developers, offering a novel approach to enhance procedural success rates and patient outcomes in navigating challenging vascular lesions. By advancing our understanding of magnetic guidewire navigation techniques, this research contributes to the evolution of minimally invasive vascular interventions, ultimately improving patient care and clinical outcomes.
Numerical Assessment of a Partially Stirred Reactor-Based Combustion Model Using a High-Fidelity CFD Tool
Authors: Ruiz Sebastian , Valencia Sebastian , Illacanchi Fernando , Mendiburu Andres , Bravo Luis , Khare Prashant , Celis Cesar 
Published: January 2025

Abstract
In combustion systems such as those used in rotating detonation engines (RDE), turbulence chemistry interactions (TCI) play a key role. Accordingly, the main goal of this work is to assess a partially stirred reactor (PaSR) based combustion model that allows modeling the referred TCI interactions. PaSR-based models represent indeed a computationally affordable alternative compared to other combustion models, while still accounting for detailed finite-rate chemistry. The capabilities of a PaSR-based combustion model are assessed in this work accounting for a reactive Taylor-Green vortex (TGV) flow configuration. More specifically, all numerical simulations are performed using a high-fidelity computational fluid dynamics (CFD) tool known as PeleC. This CFD tool solves the Navier-Stokes transport equations accounting for a reactive compressible flow. Closure of the set of transport equations solved is achieved using a large eddy simulation (LES) based approach and a combustion model based on chemical reactors. The numerical results obtained in this work using the PaSR-based combustion model evaluated here are compared in terms of temperature, heat release, velocity, and species mass fractions against direct numerical simulations (DNS) related results. Overall, the numerical results obtained here using LES and the implemented PaSR-based combustion model highlight that they are comparable with the DNS ones accounted for as reference here.
Fault Parameter Quantification With a Bayesian Surrogate Model for Coupling Misalignment in a Rotor System
Authors: Belli Olympio , Fiori de Castro Helio , Ekwaro-Osire Stephen 
Published: January 2025

Abstract
The growing demand for efficiency in production chains has centered on the reliability of these systems. With the emergence of artificial intelligence models, several techniques for diagnosing rotating machinery have been developed and applied. Different qualitative diagnostic techniques have proved successful in industrial applications. However, some issues, such as the reliability and interpretability of the models, still need to be addressed. In addition, research into the quantification of failure parameters for estimating the useful life of machines still has gaps to be filled. To this end, this work aims to create a reliable, computationally inexpensive surrogate model for quantifying the failure parameters of a rotor coupling in a situation of angular and parallel misalignment. Using Bayesian DeepONets, two surrogate models were trained to be used with the search algorithm to quantify the failure parameters. This process was concluded with success.
Frequency Content and Related Flow Physics of Kelvin-Helmholtz and Rayleigh-Taylor Instabilities
Authors: Baird Hayden , Zhou Hao , Zheng Zhongquan Charlie 
Published: January 2025

Abstract
This study is to investigate the driving physics and related frequency contents in two elementary flow instabilities, Kelvin-Helmholtz (KHI) and Rayleigh-Taylor instability (RTI). Using computational simulation, each instability is simulated individually and then combined to generate flow field data for analysis to study flow structures and their related frequency contents. The results show KHI frequencies are related to inlet velocity perturbation and shear properties. RTI analyses reveal no apparent dominant frequencies. Combined KHRTI analyses exhibit apparent dominant frequency peaks which appear to result from interactions between KHI and RTI.
FEM-Based Prediction of Crater Dimension Formed During Single Discharge Micro-EDM
Authors: Kumar Rajiv , G. L. Samuel 
Published: January 2025

Abstract
Being stochastic and complex in nature, the fundamental of the micro EDM (μ-EDM) process has not been understood well yet. In this current work, an endeavor has been made to understand the μ-EDM process. A 2D axisymmetric FE model has been developed for single-spark considering all the realistic parameters such as Gaussian heat source, temperature-dependent material properties, spark radius as a function of discharge time, latent heat of melting and vaporization. The shape and size of the crater have been predicted based on the temperature distribution generated using this developed model. Further, this developed model’s result has been validated with the experimental result. The numerical model developed incorporating the latent heat predicted crater dimensions close to the experimental results. Additionally, the developed model has been used to predict the finishing process and it was found that the smallest crater of volume 408.45 μm3 was predicted.
Temperature and Energy Behaviours of Powder Fe/Al Mixtures in Friction Stir Processing
Authors: Store Rachel , Wagner Scott W. , Nguyen Vinh , Emblom William 
Published: January 2025

Abstract
The friction stir back extrusion process (FSBE) gained popularity as a process with potential to create cylindrical shapes without seams, a controlled wall thickness and use less energy than traditional methods for creating tubular structures. These tubular structures are desired because the tube walls can be tailored to specific applications and it was also noticed that tubes made using FSBE had microstructures that could be influenced by the swirling of the stir tool. Because the tubes created by using FSBE are seamless and have a uniform thickness, they are desired for tube hydroforming applications. Instead of using a traditional cylindrical billet, milling machine chips and then powders were also used to create the cylindrical components. As a result, Friction Stir Powder Processing (FSPP) has been studied. The use of powders as the friction stir materials allows for custom alloyed tubes to be created. Similar to FSBE, the FSPP method generates tubular structures with swirled grains. This is believed to be provide additional strength within the tube walls. This can be very desirable when strength is needed for thinner walled tubes. The swirled patterns are believed to influence the tubes’ abilities to withstand a higher internal pressure in tubular hydro forming for example. In this study, cylindrical structures are created using FSPP methods with varying the alloy composition.
In this study, a conventional CNC milling machine is used to drive the spin tool and incrementally plunge into an enclosed die loaded with powders. As the spin tool is plunged, attaining the necessary amount of friction can be difficult. Stirring the powder has an inherent tendency to disperse the particles in every direction and a top cap allows the mill to generate pressure against all the particles and create the required friction. Dwell time as the stir tool plunged was also monitored. The process temperature was observed to indicate when the spin tool needed further plunging. For this study, the heat and temperature process responses of two aluminum steel alloy powder compositions were tested during FSPP. The process temperature was monitored throughout the tests with thermocouples. These readings were then used in an energy model in a side-by-side comparison. The two alloys tested had similar temperature and heat generation behaviors during the start-up and end of the test. The alloy with a larger steel concentration experienced a more significant rise in temperature and thermal energy generation during the middle of the test as compared to the alloy with a smaller steel concentration based on a test for statistical difference with a 0.05 level of significance.
Understanding the relationship between alloy mixtures and the process energy consumption in FSPM may allow for the optimization of process parameters for production efficiency.
Analysing the Influence of Geometry and Tool Paths for a Laser-Based DED Application
Authors: Pazireh Syamak , Mirazimzadeh Seyedeh Elnaz , Urbanic Jill , Hedrick Bob 
Published: January 2025

Abstract
This study examines the coupled effects of geometry type and toolpath patterns on residual stresses and strains in parts manufactured using laser-based Directed Energy Deposition (DED). Finite Element Method (FEM) simulations were conducted for four distinct geometries, each subjected to three different tool-path strategies: one-way longitudinal, longitudinal zigzag, and one-way transverse. The plastic strain is highly correlated with the maximum temperature within the deposition. The longer walls also gain higher strains in the deposition direction. The highest tensile strains were observed in the upper layers of the structures, while the mid-layers exhibited the maximum principal residual stresses. Additionally, thin walls are more sensitive to deposition patterns than thick walls due to limited heat dissipation. These insights provide a foundation for optimizing toolpath strategies in laser-based DED processes, aiming at improved mechanical performance and reduced distortion in complex geometries.
Optimizing Propeller Efficiency Using AI / Machine Learning Techniques
Authors: Arya Advika , Zaidi Sohail 
Published: January 2025

Abstract
In recent years, the aerospace industry has placed increasing importance on enhancing propeller efficiency. However, traditional methods like computational fluid dynamics (CFD) simulations and empirical analysis demand substantial expertise and resources. Moreover, the intricate nature of propeller aerodynamics complicates accurate modeling requiring few other techniques that can develop predictive models based on the available data on existing propellers.
This paper addresses this challenge by utilizing experimental wind tunnel data from a UIUC repository to predict propeller efficiency using AI/ML models. Key design parameters, including number of blades, diameter, pitch, brand, alongside advanced ratio and RPM rotation inputs, are used. IMB Watson could-based AI platform was used to develop predictive models. Various algorithms including linear regression, decision tree and snap random forest were tested with and without enhancements (HPO-1, FE, HPO-2). Utilizing a diverse dataset, we achieved a notable 0.036 root mean squared error (RMSE), with significant features identified including thrust and power coefficients. A 10:90 test:train split ratio contributes to robust model performance.
While the application of advanced AI and machine learning techniques in aerospace engineering is still in its embryonic stage, this study lays a foundation for future advancements in propeller design and efficiency optimization through rigorous analysis of various predictive models that were employed in this work.
Integration of Digital Twins Into Virtual Commissioning Practices
Authors: Guerra-Zubiaga David A. , Richards Gershom , Forsberg Paul , Nwachukwu Kingsley , Burroughs Andrew , Sabula Eric , Kuts Vladimir 
Published: January 2025

Abstract
The demands of manufacturing equipment often led to operating the equipment most effectively to maximize productivity or profit. The need for maximized operating time for the equipment has made the maintenance aspect resort to more creative means to address the risk of equipment failure. The failure of equipment can range in effect from producing poor quality products, hindering the manufacturing process, or endangering the workers around them. Additionally, the damage done to equipment that has malfunctioned often causes a greater loss in profit as the equipment would need to be fixed or replaced. The knowledge gap is in how a manufacturing plant can balance good quality maintenance without hindering the operation of the equipment itself. The historical maintenance practice is to run scheduled maintenance breaks on the equipment, check for system variables that have been shown to correlate to a decaying system or wait for the equipment to fail. Virtual Commissioning (VC), which is the practice of using a simulated model of a system to explore the potential of a system without impeding the operation of the physical system, seems to be a sound resolution. This paper explores the potential of integrating Digital Twins, a real-time simulation of a system, into the practice of VC to gather real-time data from the manufacturing system. With the ability to collect and store complex data, the algorithms used to diagnose the system would enlighten the industry to various observations of the current practice of maintaining and operating certain equipment. While the effectiveness and potential of this new data have yet to be defined, the ability to obtain the data would prove to be a great step forward in optimizing the maintenance and operation practices within the manufacturing industry.
Viscoelectric Effects on the Electroosmotic Flow of Maxwell Fluids in a Rectangular Channel
Authors: Jimenez Edson M. , Gómez Juan R. , Escandón Juan P. , Hernández Clara G. 
Published: January 2025

Abstract
The present work analyzes the electroosmotic flow of Maxwell fluids in a rectangular channel with high and asymmetric zeta potentials on the walls. This theoretical study considers the viscoelectric effect because the fluid viscosity varies with the presence of high voltages within the electrical double layer. The problem is modeled by the Poisson-Boltzmann equation for the electric potential, the conservation equations of mass, momentum and Maxwell’s rheological model for the flow field, which are solved through numerical simulations. The results show that the relaxation time of the viscoelastic fluid controls the oscillatory behavior of the velocity and the time in which the fluid reaches the steady-state. On the other hand, the increase in zeta potentials produces a rise in the magnitude of the velocity, which is counteracted by the viscoelectric effect. Therefore, this study contributes to understanding the electroosmotic phenomenon of viscoelastic fluids in the presence of high zeta potentials, considering variations in viscosity that have not been reported in this type of fluids. Additionally, this research helps design electrokinetic devices in transport and pumping applications.
Evaluation of Flexural Strength, Compliance, and Vibration Characteristics of Fiber Reinforced Wood Composite Materials Used in Bike Frame Front Triangles
Authors: Agnew Jesse , Beaman Isaac , Gilchrist Ian , Gurule Alden , Oman Sarah 
Published: January 2025

Abstract
Specific material properties are desired for an ideal riding experience in the front triangle of a bike frame. The tubes in an optimal front triangle should be strong and able to dampen vibrations while maintaining relatively high compliance. Strength and compliance increase the impact energy the bike frame can absorb before failure, and vibration damping promotes a smoother riding experience. A common impact that can lead to catastrophic failure of a bike frame is a front tire direct strike that invokes a large bending moment into the downtube of the front triangle. The ability of the tube material in this region to comply while maintaining strength can lead to higher durability of the bike by increasing the impact energy required to break the frame. This study investigates the vibration and strength characteristics of several fiber reinforced wood composite materials through the use of a four-point loading test based on the ASTM C1161-18 standard and an impulse excitation of vibration test following ASTM E1876-15. The composite material samples tested included several common weaves of fiberglass, Kevlar, and carbon fibers. While fiberglass and Kevlar-carbon reinforced wood samples demonstrated the highest vibration damping characteristics, Kevlar-carbon reinforced material was selected for further testing due to its higher flexural strength. Pursuant to these tests, the different strength profiles of common bike frame materials, steel, aluminum, and titanium, were compared to the selected Kevlar-carbon reinforced wood composite material using a tube bending test inspired by loading that the downtube experiences during the ASTM F2711-19 falling mass test. Videos of the tube bending tests were analyzed using Vernier Video Analysis software to gather displacement data, and MATLAB was used for strength, energy, and compliance calculations as well as data representation. The results of the stated tests and analysis concluded that the fiber reinforced wood composite materials showed a higher yield strength, energy absorption, and compliance in the bike frame application compared to aluminum, steel, and titanium materials designed for the same purpose. The bending moment in the wood downtube reinforced with one layer of Kevlar-carbon fiber weave was 15.3% higher than aluminum, 11.9% higher than steel, and 32.9% higher than titanium while demonstrating at least twice the compliance during all of the tube bending tests. Wood reinforced with two and three layers of Kevlar-carbon fiber material demonstrated similar compliance results as well as even higher strength characteristics. Additionally, these fiber reinforced wood composite materials demonstrate desirable vibration damping characteristics.
Evaluation of a 3D Printed Single Layer Polyvinylidene Fluoride-Trifluoroethylene (PVDF-TrFE) Sensor as a Wall Shear Stress Measuring Device in High Frequency Oscillatory Flows
Authors: Akanji Sunday , Lalsen Dane , Marandi Mohammadrafi , Cavalline Tara , Smith Michael S. , Hewlin Rodward L. 
Published: January 2025

Abstract
This paper presents the first implementation of a novel class of dynamic time-resolved direct wall shear stress (WSS) measurement sensors based on active Polyvinylidene fluoride (PVDF-TrFE) piezoelectric materials. These piezoelectric sensors have the advantage that they contain no moving parts, perform a direct measurement of WSS, and can be mounted directly to the surface of an existing vessel with no modification to the sensor and produces minimal to zero flow disturbing effects to the surrounding flow environment. The design and development methodology and characterization of the sensor dynamic signal response are discussed. This work explores a double layer sensor configuration consisting of a single layer of printed PVDF with an additional layer of printed PVDF-TrFE with silver painted electrodes. Both sensor types were tested in an in-house developed Stokes plane wave tube, and the results demonstrate the potential for using PVDF-TrFE sensors to perform accurate, high frequency measurements of WSS in unsteady flow applications.
Comparative Study on Real-World Head and Neck Injuries With Regulations Defined for Helmet Safety in Motorcycle Accidents
Authors: Rahimnezhad Baghche Jooghi Shabnam 
Published: January 2025

Abstract
Motorcycle accidents are a global issue, occurring in both low- and middle-income countries and developed nations. Helmets stand as the primary safety gear against head injuries for motorcyclists. However, the effectiveness of helmet standards in reducing injury risks needs more investigation. This study aims to highlight this matter by initially examining injury patterns documented in papers and reports on motorcycle accidents, with a specific focus on head and neck injuries, and comparing these patterns with two main standards ECE 22.06 and DOT-FMVSS218, to assess their accuracy in describing real-world accident scenarios. In the second part, the performance of conventional motorcycle helmets based on ECE 22.06 and DOT-FMVSS218 standards, using rigid head models and finite element modeling for both frontal and oblique impacts was evaluated. The acceleration data obtained from these tests are then used as an input condition for THUMS (AM50, V6) and the Penn State Head (fine model). The study highlights differences in strain distribution estimated by different finite element models (FEM) human head models under the same test conditions. Moreover, the regions of maximum strain vary for the same test conditions across these two head models. These differences underscore the need for further exploration of the biofidelity of FEM human head models to better reflect real-world accident dynamics.
An Experimental Study Focused on the Impact of Manufacturing Process in the Mechanical Performance of Lattice Structures
Authors: Hamel Josh , Gutierrez-Amezquita Mauricio , Proctor Theodore , Rujoni Emmanuel 
Published: January 2025

Abstract
Digital manufacturing techniques, such as computer numerically controlled (CNC) machining and additive manufacturing (AM), have greatly increased the design space available to engineers with respect to both geometry and materials. Obviously, certain geometries cannot be realized by anything other than a layer-by-layer AM process, and certain materials can only be formed using traditional subtractive approaches, leaving designers with little choice. However, for the wide array of structures that could be realized in a variety of different ways, the choice of manufacturing process is just another faction in the overall design process. Planar lattice structures have complex repeating geometric features which are best designed using computer aided design (CAD) tools, and these structures can easily be manufactured using a variety of different digital manufacturing processes. For this study a set of planar lattice structures were designed and fabricated from acrylonitrile butadiene styrene (ABS) plastic using both a CNC milling machine and a material extrusion AM machine. All test lattices were then loaded in tension to failure to determine their mechanical performance. The determined properties were then compared to analytical predictions from the literature, and an analysis of the impact of a chosen manufacturing process was performed. The results obtained show good agreement with publish models for lattice performance, and additionally suggest that the choice of manufacturing process has a measurable effect on the mechanical performance of the resulting structures for this specific material and geometry combination, but it is important to note that this study is just an example of how to mitigate the uncertainties associated with the freedoms offered by advanced manufacturing processes, and more work in needed in this important area of study.