bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vision-Based Tool Wear Classification During End-Milling of Inconel 718 Using a Pre-Trained Convolutional Neural Network
Authors: Kumar Aitha Sudheer , Agarwal Ankit , Jansari Vinita Gangaram , Desai K. A. , Chattopadhyay Chiranjoy , Mears Laine 
Published: February 2024

Abstract
Nickel-Based Superalloys (NBSAs) are widely used for components subjected to high-temperature applications due to their excellent mechanical strength, toughness, and corrosion resistance. Despite favorable properties, NBSAs work-harden during machining, resulting in acute temperature rise at the cutting edge, severe plastic deformation, and rapid tool wear. The lower thermal conductivity, intense friction at the chip-tool interface, chemical affinity with tool material, and temperature gradients typically lead to abrupt crater formation or cutting-edge chipping in addition to rapid flank wear. Three distinct phenomena characterize tool wear during end milling of NBSAs; rapid flank wear, abrupt crater formation, and cutting-edge chipping. The continued use of worn or damaged cutting tools leads to poor surface finish and, eventually, catastrophic failures, resulting in significant machine downtime. As each tool wear condition has a unique mitigation strategy, timely identification and classification are imperative to implement solutions that minimize wear and guide tool replacement.
In recent years, the augmentation of vision-based systems with pre-trained Convolutional Neural Networks (CNNs) has shown great promise in failure identification and classification tasks. The present work develops an image-based classification model using a pre-trained CNN, Efficient-Net-b3, for identifying three tool wear conditions during end milling of Inconel 718 (IN718). The network training uses labeled image datasets that capture various tool wear characteristics generated using end-milling experiments. The extensive training dataset requirement of the CNN was met using image augmentation techniques by varying the brightness, contrast, and orientation of the captured images. The prediction abilities of the algorithm were corroborated by validating the model on a validation dataset and further testing on new unseen datasets. It has been shown that Efficient-Net-b3 demonstrates robust prediction accuracy for all three tool wear conditions. The proposed classification model can be further employed for developing an on-machine vision-based tool wear classification system.
Efficient Modeling of Blades via Beam Element in the Multi-Objective Optimization of Small Wind Turbine Blades
Authors: Kayran Altan , Çöker Demirkan , Muyan Can , Batmaz Onur Ali , Pourrajabian Abolfazl , Wood David 
Published: February 2024

Abstract
A study is conducted to propose an efficient structural analysis method to be included in the multi-objective optimization of small wind turbine (SWT) blades. For this purpose, initially aerodynamic optimization of a SWT blade is performed utilizing a multi-objective function including the power output and the starting time. Structural analyses of the aerodynamically optimized blade are performed utilizing different fidelity finite element models for justifying the use of the reduced-order finite element (FE) model with beam elements. As a reference, higher fidelity three-dimensional (3-D) FE analyses of the blade are performed and alternative 1-D beam-blade models are evaluated utilizing the results of 3-D FE solutions. In this respect, tapered and multi-section non-tapered 1-D beam-blade model alternatives are evaluated as potential lower fidelity reduced-order models to be employed as efficient structural solvers in a future multi-objective optimization of the small wind turbine (SWT) blade. It is shown that multi-section non-tapered beam-blade FE model of the SWT blade is a robust model which handles unsmooth section transitions, which are encountered in meta-heuristic optimization of blades, effectively unlike the tapered beam-blade model and it can be used in a future constrained optimization involving structural metrics as constraints and/or objective functions.
Part 1: Gyroscopic Control of Robotic Smart Vehicles Using SO(3)
Authors: Chen Jason , Kim Eunkyu , Leppitsch Calder , Meiner Benjamin , Zaretsky Daniel , Rykkje Thorstein Ravneberg , Luchtenburg Dirk M. , Impelluso Thomas J. 
Published: February 2024

Abstract
In response to challenges faced in engineering education, this paper presents the Moving Frame Method (MFM) as an alternative to the existing pedagogies. This paper, and a companion paper, present the MFM for the analysis of rigid single-bodies, in the context of an international collaborative senior design project between two engineering schools: The Cooper Union in New York, NY and The Western Norway University of Applied Sciences in Bergen, Norway.
Students at Cooper Union analyzed the smart vehicle as a single-body problem; a second team in Norway used the same method to model the problem as a multi-body. Both teams modeled the gyroscopic lift effect using the foundational theory of the MFM. This first paper presents the underlying theory of how the MFM uses the Special Orthogonal Group, SO(3), to model the problem of gyroscopic lift of a smart vehicle. It presents the underlying theory: motion of a reference frame in terms of the reference frame; and the various properties of SO(3) and its associated algebra as applied to a new, undergraduate approach to dynamics.
The paper presents two design alternatives to lift a vehicle, the first one uses two gyroscopes and the second a single reaction wheel. The modeling and analysis process led to the design that employs a single reaction wheel. Next, it examines the model-generated estimates for torque generated and subsequent motion of the car. After analysis using the initial model, the Cooper Union Team pivoted a design approach before entering the rapid prototyping phase of the project. Then, it discusses the manufacturing process for the final version of the car and the construction of a test enclosure for ensuring safety by containing the heavy reaction wheel spinning at high speeds. Finally, it describes the testing of the car, which involves measurement of angular impulse due to a braking event. The results from initial experiments on the prototype validate the model and confirm that the car can lift itself using the selected method.
Tensile and Fatigue Response of Steel Parts Fabricated by the Additive Friction-Stir Deposition Process
Authors: Alam Chowdhury Sadid , Ahmed Radif Uddin , Rahman M. Shafiqur 
Published: February 2024

Abstract
Additive Friction Stir Deposition (AFSD) is a relatively new solid-state additive manufacturing (AM) process that utilizes frictional heating and plastic deformation for the layer-by-layer deposition of materials (e.g., metals and alloys). This study characterizes the mechanical behavior of AFSD-processed AISI 4340 steel parts under various tensile and fatigue loading conditions. A distinct scale of AISI 4340 steel specimens, namely the standard ASTM rectangular dog bone specimen is considered for the analysis. A finite element (FE) model is developed to predict the tensile and fatigue behavior of AFSD-processed steel AISI 4340 parts under multiple loading circumstances. The FE model can generate results for the von-Mises stress, strain, total deformation, fatigue life, factor of safety, and fatigue limit under various loading conditions. Experimental data for the tensile and fatigue responses are compared with the mechanical behavior obtained from the FE model at room temperature. The modeling results for the maximum tensile stress, deformation, and fatigue life exhibit excellent agreement with the experimental findings, which successfully confirms the validation of the FE model. The FE modeling for the fatigue analyses is conducted for a unit load ratio and by applying zero-based cyclic loads at different frequencies. Results from the current study successfully lead to generating a stress-life curve for the AFSD-processed AISI 4340 steel parts. According to the findings, the AFSD-processed components show higher strength than that of the parts created by conventional manufacturing techniques. In all cases, the AFSD specimens show extended lifespan compared to the conventionally manufactured specimens.
A Heterogenous Hydrogel Brain Phantom for Convection-Enhanced Drug Delivery
Authors: Pineda Rose , Ryu Sangjin , Kim Seunghee , Zhang Chi 
Published: February 2024

Abstract
Hydrogel plays an important role in several biomedical engineering applications, one being convection enhanced drug delivery (CED). During CED, a drug is locally injected into the brain to attack diseased or cancerous cells via infusion under pressure. Predicting the flow path of the injected drug during CED has been challenging because fluid infiltration through brain tissue will cause the solid to deform, causing a change in the resultant flow pattern. To characterize the pharmacodynamics of the injected drug through brain tissue, an accurate in vitro engineering model that emulates material properties of brain tissue is highly demanded. We thus propose to develop and characterize a heterogenous hydrogel structure to replicate the soft, porous, and complex structure of the organ, for further exploration of how injected fluid affects deformation which in turn affects the flow. In this study, we created and characterized a heterogeneous gel brain phantom consisting of hydrogel gel beads and matrix of different Young’s moduli.
Agar gel beads were fabricated from the gel solution (1 or 2 w/v%) using a rotating-liquid-based drop generator. With needles of two different inner diameters (0.413 and 1.372 mm), 1 w/v% solution resulted in beads of a diameter of 1.17 mm and 1.47 mm, respectively, and 2 w/v% solution resulted in beads of a diameter of 1.70 mm and 1.99 mm, respectively. Through microscopic compression tests, the Young’s moduli of agar beads were measured to be 34.2 kPa and 100.8 kPa for 1 and 2 w/v% cases, respectively. For validation, homogeneous agar discs were fabricated and tested: macroscopic Young’s modulus values were 57.1 kPa and 143.2 kPa for 1 and 2 w/v%, respectively.
The heterogeneous brain phantom was fabricated by embedding prepared agar gel beads into agar matrix of different concentrations (1% beads in 2% matrix and vice versa). Fabricated heterogeneous gel discs were characterized via compression tests, and the overall Young’s modulus of the heterogenous phantom was found to be lower than that of the matrix. Discs made with 1% agar beads and 2% agar matrix resulted in a Young’s modulus of 45.24 kPa, whereas discs made with 2% agar beads and 1% agar matrix resulted in a Young’s modulus value of 18.95 kPa. Although simply binary, fabricated heterogenous agar discs demonstrate that their mechanical behavior differs from their homogeneous counterpart, which clearly supports urgent need for heterogenous gel phantom for advancing CED.
Utilizing Neural Networks to Assist in the Assessment and Predictive Measurement of Developmental Hip Dysplasia Radiographs
Authors: Perry Sheridan , Folkman Matthew , O’Brien Takara , Wilson Lauren , Coyle Eric , Liu Raymond W. , Price Charles T. , Huayamave Victor 
Published: February 2024

Abstract
Developmental dysplasia of the hip (DDH) is a condition in which the acetabular socket inadequately contains the femoral head. If left untreated, DDH can result in degenerative changes in the hip joint. Several imaging techniques are used for DDH assessment. In radiographs, the acetabular index, center-edge angle, Sharp’s angle, and migration percentage metrics are used to assess DDH. Determining these metrics is time-consuming and repetitive. This study uses a convolutional neural network (CNN) to identify physical metrics on radiographs and improve traditional methods of identifying DDH. The dataset consisted of 60 subject radiographs rotated along the craniocaudal and mediolateral axes 25 times, generating 1500 images. A CNN detection algorithm was used to identify DDH metrics. The algorithm was able to detect the metrics with reasonable accuracy in comparison to the blank metrics. The CNN performed well on images with high contrast margins between bone and soft tissues. In comparison, the CNN was not able to identify some critical points for metric calculation on a select few images that had poor definition due to low contrast between bone and soft tissues. This study shows that CNNs can efficiently measure clinical parameters to assess DDH on radiographs with high contrast margins between bone and soft tissues with purposeful rotation away from an ideal image. Results from this study could help inform and broaden the existing bank of information on using CNNs for radiographic measurement and medical condition prediction.
Flexible Surface Acoustic Wave (SAW) Sensors for Cryogenic Sensing Application
Authors: Kohler Michael , Zhang Andy , Moore Christopher , Voiculescu Ioana , Li Fang 
Published: February 2024

Abstract
Real-time monitoring of temperature and pressure, particularly in harsh environments such as extreme temperature and high electromagnetic radiation environments, has wide-ranging applications in the aerospace, civil infrastructure, and motor industries. Surface acoustic wave (SAW) technology has gained significant attention for harsh environment applications due to its ability to enable self-powered and wireless sensor devices that can operate in harsh environments. Our previous studies have demonstrated the effectiveness of 128° YX-cut LiNbO3-based SAW sensors for cryogenic sensing applications with no degradation in sensor signals at cryogenic temperatures of 80K. However, the high value of the temperature coefficient of delay (TCD) presents a major challenge in developing wireless SAW pressure sensors, as even small changes in temperature can induce significant changes in the signal, which may be greater than that due to the pressure change of interest. Therefore, there is a need to improve the thermal stability and pressure sensitivity of the 128° YX-cut LiNbO3-based SAW device. This paper reports on our simulation study of improving the thermal stability of the LiNbO3-based SAW sensor by applying an overlayer to compensate for the temperature effects. Additionally, we present our experimental study to develop a single crystalline thin-film-based SAW sensor, which has the potential to improve pressure sensitivity.
Development and Integration of Continuous Load and Position Measurement for Quasi-Steady Flows
Authors: Cockrell Quintin J. , Hiremath Nandeesh 
Published: February 2024

Abstract
Obtaining aerodynamic forces and moments about all three orthogonal axes for arbitrary shapes at arbitrary orientations in a fast manner via a measurement technique specific to Cal Poly’s low-speed wind tunnel to continually obtain the forces and moments under quasi-steady conditions is explored. A Continuous Rotation Technique (CR) uses a 6-DOF load cell and stepper motor to rotate an object about an axis for a complete rotation. The forces and moments acting upon the object pass through the stepper motor and interface plates and recorded by the load cell as the object is rotated continuously a finite number of rotations. An optical encoder installation tracks the progress of a rotation serving indicator between the subsequent rotations to determine starting angles and body slippage. Average loading of measurements at each timestep along the average time for rotation is found. This dataset along the average time is placed in 1-degree bins and averaged to a final dataset of load measurements at 1-degree intervals for a complete 360-degree load map. Testing of this technique is performed on aspect ratio 1 circular cylinder. This paper showcases the repeatability of the results in a different and smaller wind tunnel with improved certainty on angle measurements.
Design and Experiments Involving a Mechanism-Based Artificial Tongue Prosthesis
Authors: Holod Ace , Singh Nadia , Curney Xavier , Radhakrishnan Pradeep , Pahlavan Kaveh 
Published: February 2024

Abstract
Oral cancer can result in the loss of tongue through total glossectomy, and patients have difficulty with speech, deglutition, and mastication. Current tongue prostheses lack the ability to move for mastication and deglutition and are mainly for cosmetic purposes. The goal of this research was to investigate and develop a self-contained prosthetic tongue that could aid in deglutition by moving bolus from the front of the mouth to the back. A review of existing designs and alternatives led to the development of a linkage system mounted in a silicone cast to move the bolus. The development of this new prosthetic tongue design entailed creating silicone molds, 3D printing linkage systems and jaws, and developing new circuits. The circuit used a TinyDuino microcontroller and MOSFET. A functional mandibular Hawley retainer was added to hold the tongue to increase ease of use. The final circuit used an EMG sensor to trigger actuation and a single servo motor with a gear train to actuate the tongue. The prosthetic tongue succeeded in moving bolus from the front of the mouth to the back when lying at a 5-degree angle and actuating between 1.8–2.31cm in height. The paper will describe the development process, challenges, and future work.
Numerical Investigation of Broken V-Ribbed Turbulators in a Multi-Pass Turbine Channel Under Rotating Conditions
Authors: Thirumalai Madhusudan Pallikaranai , Ekkad Srinath V. 
Published: February 2024

Abstract
Rotation induces Coriolis and centrifugal forces resulting in a significant non-uniformity of heat transfer distribution on the pressure and suction side walls of turbine blade internal cooling channels. This nonuniformity in cooling creates asymmetric cooling resulting in significant thermal stresses and potential failure of the airfoil. In order to minimize this non-uniform distribution of heat flux, this study proposes a novel multi-pass channel configuration with a 45-deg angled V-Broken ribs. Numerical simulations were conducted under stationary and rotation conditions to calculate detailed heat transfer coefficients on the internal walls of these channels. Results indicate that the heat transfer characteristics on the pressure and suction side internal walls were very similar under both stationary and rotating conditions. The new design with the broken rib configuration does not significantly affect the pressure drop while providing the added benefit of heat transfer enhancement.
Performance Characteristics of Small-Scale Horizontal Axis Three Bladed Ocean Current Turbine: Computational Fluid Dynamics Investigation
Authors: Sadeqi Setare , Xiros Nikolaos I. , Rouhi Shahab , Ioup Juliette W. 
Published: February 2024

Abstract
The fundamental research described in this paper is a comprehensive numerical simulation (Blade Element Momentum Theory) for developing a small-scale three bladed horizontal axis underwater ocean current turbine (OCT), to be tested in a laboratory towing tank located at the University of New Orleans. A precise numerical simulation has been developed to generate hydrokinetic loads such as torque and power for the OCT based on the geometry and design characteristics of the small-scaled blades. Each blade is divided into 25 different cross sections from the FX77-W airfoil family based on the real size OCT. This method is an in-house blade element momentum theory (BEM) algorithm which considers each cross section of the blade as a two-dimensional hydrofoil to calculate the local drag and lift coefficients for each sub-section to obtain the maximum generated power of the OCT. Many different generated power estimates based on these simulations have been conducted for different in-coming flow speeds in the range of few cm/s to as much as 2 m/s, along with constant turbine circular speeds. The results of this numerical study are used as one of the main sources of initial information for ongoing research which is the design and implementation of an experimental small scale experimental underwater ocean current turbine. Also, the results of the numerical study are compared to the results of the experimental research. The aim of this research is to provide an accurate prediction of the nominal rotor speed for a given incoming flow current to optimize the capability of the small-scale OCT performance. The paper also highlights the need to develop new and reliable technologies to harness ocean currents and extract the maximum hydrokinetic energy from the ocean in order to convert it into reliable and usable energy.
Optimizing Material Properties for 3D Printing: A Study on Compressive Strength of Mixed Clear and Tough Resins
Authors: Javvaji Vijay K. , Angadi Santosh , Piovesan Davide 
Published: February 2024

Abstract
Most published review papers primarily discuss 3D printing techniques, the printing of pure materials and incorporating nano particles, but never looked at the possibility of mixing different resins with different mechanical properties to develop hybrid material. The main objective of the experiment was to explore the potential of mixing different resin materials and creating a hybrid material. The goal was to optimize the properties of the resin material by combining different components. By experimenting with different ratios and compositions, the aim was to achieve a hybrid material with enhanced characteristics, such as improved strength, durability, or other desirable properties. The experiment aimed to determine the feasibility of creating such hybrid materials and to optimize their properties for various applications in 3D printing or other fields.
Clear and tough resins provided by Anycubic were used for this experiment. The Clear is a multipurpose resin for 3D printing with good rigidity, low shrinkage, high success rates, and excellent detail performance. The Tough resin can withstand both compression and bending and is suitable for sections requiring durability. The two materials were mixed at different volume ratios to create three different samples. The samples were printed using the PRUSA SL1 speed printer and washed in isopropyl alcohol.
Samples were tested before and after post-processing to identify their compressive strength using the ASTM D695-15 standards. The results showed that mixed resin is stronger than regular resin and increasing the amount of clear resin in the mixture increases strength.
Overall, this experiment provides valuable insights into the properties of mixed Clear and Tough resins, and their potential uses in 3D printing applications where both resistance to creep and toughness are required. Along with pointing out the possibility of mixing materials it also points out that the hybrid material can withstand more compression load when compared to the standard materials which increases the use cases and potential of implementing in different industries and labs.