bluuebunny/crossref_metadata_2025_split huggingface dataset:
Process Mapping of Additively-Manufactured Metallic Wicks Through Surrogate Modeling
Authors: Borumand Mohammad , Esfandiarpour Borujeni Sima , Nannapaneni Saideep , Ausherman Moriah , Madiraddy Guru , Sealy Michael , Hwang Gisuk 
Published: January 2022

Abstract
Tailored wick structures are essential to develop efficient two-phase thermal management systems in various engineering applications, however, manufacturing a geometrically-complex wick is challenging using conventional manufacturing processes due to limited manufacturability and poor cost effectiveness. Additive manufacturing is an ideal alternative, however, the state-of-the-art metal three-dimensional printers have poor manufacturability when depositing pre-designed porous wicks with pore sizes below 100 μm. In this paper, a powder bed fusion 3D printer (Matsuura Lumex Avance-25) was employed to fabricate metallic wicks through partial sintering for pore sizes below 100 μm with data-driven control of process parameters. Hatch spacing and scan speed were selected as the two main AM process parameters to adjust. Due to the unavailability of process maps between the process parameters and properties of printed metallic wick structures, different surrogate-based models were employed to identify the combinations of the two process parameters that result in improved manufacturability of wick structures. Since the generation of training points for surrogate model training through experimentation is expensive and time-consuming, Bayesian optimization was used for sequential and intelligent selection of training points that provide maximum information gain regarding the relationships between the process parameters and the manufacturability of a 3D printed wick structure. The relationship between the required number of training points and model prediction accuracy was investigated. The AM parameters’ ranges were discretized using six values of hatch spacing and seven values of scan speed, which resulted in a total of 42 combinations across the two parameters. Preliminary results conclude that 80% prediction accuracy is achievable with approximately forty training points (only 10% of total combinations). This study provides insights into the selection of optimal process parameters for the desired additively-manufactured wick structure performance.
Effect of Heat Treatment on Microstructure and Hardness of Graphene Nanoplatelets Reinforced Al-Zn-Mg-Cu Alloy Composite
Authors: Sharma Ankit , Pratyush Akula Sai , M. Srinitesh , Gupta Amit Kumar , Sujith Ravindran 
Published: January 2022

Abstract
Excellent mechanical, electrical, and thermal properties of the sp2 hybridized carbon allotrope derivative of graphene nanoplatelets (GNP) make it a suitable reinforcement candidate for the metal matrix composite. Due to the superior properties of Al – Zn – Mg – Cu alloy, it is used as an armor material for decades in defense industries. In this study, Al – Zn – Mg – Cu alloy/GNP reinforced composite with varying weight fraction of 0, 0.5% & 1% GNP was fabricated via hot-pressing sintering. Initial investigation shows that the composites were densified, and the relative density was 99.64% after the fabrication process. Two-stage heat treatment was performed on the Al alloy, forming a stable η (MgZn2) phase. The DSC plots show the dissolution of the unstable η´ (Mg4Zn7) phase into the stable η (MgZn2) phase in between 450 °C – 480 °C and homogenized due to artificial aging process with the α-Al phase. Investigation showed an increment in the hardness of the heat-treated 0.5% GNP reinforced composite by 15.44%, and 8.92% in the heat-treated 1% GNP reinforced composite compared to their non-heat treated composites. The Field Emission Scanning Electron Microscopic images of samples before heat treatment show agglomeration of GNP and heterogeneous nucleation, and images after heat treatment show that GNP has been dispersed into the grains and grain boundaries alongside the eutectic phases, which restrict the dislocation motion and strengthen the matrix by grain boundary strengthening.
Framework for Automated Robotic Arm Manipulation in Variable Industrial Environments
Authors: Pradhan Anvay A. , Martin Will C. , Danesi Ruiz Juliana , Deierling Phillip E. 
Published: January 2022

Abstract
In this paper, we present a generalized, holistic method for automated robotic arm handling of manufactured components in an industrial setting using computer vision. In particular, we address scenarios in which a high volume of manufactured parts are moving along a conveyor belt at random locations and orientations with multiple robotic arms available for manipulation. We also present specific, tested solutions to all stages of the framework as well as some alternative methods based on the literature review. The framework consists of three stages: (1) visual data capture, (2) data interpretation, and (3) command generation and output to robotic arms. In the visual data capture stage, a multi-component computer vision system takes in a live camera feed and exports it to an external processor. In the data interpretation stage, this video feed is interpreted using tools like 3D point clouds and object detection/tracking models to provide useful information such as object number, location, velocity, and orientation. Lastly, the command generation and output to the robotic arms stage takes the information acquired from the analysis in the data interpretation stage and turns it into instructions for robot control. While a full-scale, cohesive system has yet to be tested, our solutions to each stage show the feasibility of implementing such a system in an industrial setting.
Damage Quantification of High-Rate Impacts Using Hybrid Deep Learning Models
Authors: Todisco Mark , Mao Zhu 
Published: January 2022

Abstract
The ability to classify the damage of a structure caused by high-rate, high-acceleration impacts has been of scientific interest for many years. These dynamic events are often nonstationary with broadband spectral energy, making damage classification in this setting significantly more challenging. Recently, structural health monitoring (SHM) has benefitted from data-driven techniques, such as deep learning, that can overcome unclear system dynamics. This paper presents a hybrid damage classification method that fuses deep, shallow, unsupervised, and supervised machine learning (ML) algorithms, and classifies the damage levels of a structure. A deep unsupervised Convolutional Variational Autoencoder (CVAE) first extracts features containing the structure’s damage information. A shallow supervised support vector machine (SVM) classifier then uses the extracted damage information to predict the structure’s damage level. This hybrid damage classification method is applied to a highly instrumented electronic assembly subjected to high-rate high-acceleration drop tower impacts. Using the extremely limited and sparse data collected from these experiments, the hybrid SHM method infers the electronic assembly’s damage level with an accuracy of 73.0% and an F1 score of 72.9%. This technique can also be extended to remaining useful life (RUL) prediction.
Derivation of Loading Surfaces for a Nitinol Triply Periodic Minimal Surface Unit Cell Subjected to Cyclic Loading
Authors: Carcavilla Adriano Cebrián , Zaki Wael 
Published: January 2022

Abstract
This paper intends to describe the process of derivation of loading surfaces with respect to phase transformation, when a structure is subjected to cyclic loading. This structure is realized as a Schwarz Primitive unit cell, for which only 1/16th part is considered, due to the symmetry conditions. Displacement boundary conditions are applied to realize the periodicity of the unit cell, thus simulating the presence of adjacent unit cells. A homogenization of the stress fields is done, so as to obtain volume-averaged values that represent the whole domain. One limitation of the employed constitutive model is not considering plasticity. The large stresses observed in the results would be alleviate in a real application by plastic deformation. Another limitation of the model is not considering a thermomechanical coupling. Therefore, the heat that would be generated depending on the frequency employed is not taken into account. Thus, the frequency of the applied displacements only plays a role in the simulation time. One hypothesis is that the curves in a stress space will shrink as more cycles are performed, due to a higher martensite volume fraction. This is a consequence of functional fatigue. The curves are indeed observed to shrink in an axisymmetric way, due to the lack of phenomena to shift the curves along any of the axis.
A New Approach to Develop an Intelligent Manufacturing System Using Virtual Tools
Authors: Guerra-Zubiaga David , Morton Corey , Stacey Derrick , Peach Virginia , Ham Chan , Escobar Escobar Diego , Hitchcock Noah 
Published: January 2022

Abstract
Intelligent automation could be applied to continuous processes and discrete manufacturing. This research is presenting a new approach exploring intelligent automation on discrete manufacturing. A degree of smart integrated manufacturing is presented according to industry 4.0 trends. In this research a digital twin is explored incorporating some new manufacturing paradigms such as Industrial Internet of Things (IIoT), Cloud Manufacturing (CM) and Machine Learning (ML) in the creation of new intelligent manufacturing systems. A virtual simulation of B&R’s SuperTrak with magnetic shuttle technology is presented as a digital twin concept and specific aspects of IIoT, CM and ML are connected to extend smart manufacturing aspects providing the intelligent automation on discrete manufacturing. The aim of this research is to present a new approach to develop an intelligent manufacturing system using virtual tools.
Computational Fluid Dynamics to Study the Origin of Secondary Flows in Square Ducts With Straightened Elbow Concept Governed by Artificial Body Force
Authors: Ayala Orlando , Humphries Thurston , Youells Tyler , Thomas Jahshawn , Ayala Manuel 
Published: January 2022

Abstract
The 90° pipe bend is perhaps the most frequently used fitting in piping systems. The secondary flow and associated losses occurring in such bends are therefore of considerable engineering importance. However, although many investigators have studied the problem, it is still unclear how secondary flows develop, and get triggered. The curvature of the 90-degree elbow induces centrifugal force, causing the development of such secondary flow. The intensity of the secondary flow is dependent on the radius of the bend curvature (R) and Reynolds number (Re). The objective of this study is to gain an understanding of how of the triggering mechanism and development of this flow which should depend on R and Re. A commercial tool, COMSOL Multiphysics, is used to model the flow in a fully straight duct under the action of a “centrifugal” body force was studied. The domain of study was divided in three duct sections, the inlet duct, the “elbow” duct (where the “centrifugal” body force was applied), and the outlet duct. Special attention was paid to the secondary flows in the “elbow” duct near the elbow inlet. The study is conducted for different laminar Reynolds numbers (Re = 10 and 100), and different radius of curvatures (R/D = 2 and 5). It was found both the pressure gradient in the flow transversal direction and the flow “radial” advection appear to be responsible for the initiation of secondary flow phenomena and its propagation. When using slip wall conditions, the secondary flow gets weaker, or even its swirling motion disappears. It also appears to be that the full formation of the secondary flow of the vortex type occurs at the same “arc length” distance, regardless of the representative “radius of curvature.”
Characterization of the Leading-Edge Erosion of Wind Turbine Blades by Sand Particles Impingement
Authors: Alajmi Abdullah F. , Ramulu M. 
Published: January 2022

Abstract
Solid particle erosion experiments have been conducted on the leading-edge of a wind turbine blade with silica sand as the abrasive material. Two variables have been investigated in this experiment: the angle of attack at which particles impact the leading-edge and the erosion duration. For the angle of attack, four angles of attack have been used, namely: −5°, 0°, 5°, and 10°, and for erosion duration, 180 seconds and 360 seconds were used. Two parameters have been used to analyze the erosion behavior: the amount of material removed and the erosion scars’ depth. Then, to record the change in the airfoil profile, a 3-D scanner was used before and after the erosion experiments. It has been found that, on average, the highest erosion rate and depth of erosion scars occurred at 0°, which resulted in the most alteration in the 2D profile of the airfoil, while the least damage observed was caused by 10° angle of attack. The erosion scars created by the four angles of attack were superposed to create an erosion scar similar to that created by sandstorms, extrapolated along the blade, and the total mass loss was calculated. Then, a model to estimate the amount of material removed from the leading edge of wind turbine blades using the depth of erosion scars was proposed. Finally, a preliminary aerodynamic analysis has been conducted in terms of lift and drag coefficients before and after erosion. It has been found that with the increase of intensity in erosion, the change in the aerodynamic performance increases.
Bioreactor Temperature Control System Using PID Controller
Authors: Alimberti Richard , Chauhan Vedang , Jaiswal Devina 
Published: January 2022

Abstract
Bioreactors are engineered physiological environment that can be used to study and grow tissue and organ systems in vitro. They are used to subject the cells to physiologically relevant stimulus such as tensile or compressive stress, bending, torsion or fluid flow. An optimal internal environment of a bioreactor should remain sterile while maintaining the viability of tissue, cells and biomolecules at 37°C (normal body temperature) with a tolerance of + or −0.1 °C. This study presents an Arduino microcontroller-based temperature-controlled system using an autotuning proportional integral derivative (PID) control for a small-scale bioreactor. A table top bioreactor temperature control system was designed, fabricated and assembled with laser cut acrylic enclosure. The closed-loop control system maintained the set temperature of 37°C using a tuned PID controller that used a high precision TMP117 sensor for feedback, and controlled the heating element accordingly. The system achieved the desired performance characteristics such as a fast rise time, settling time, low overshoot and low steady state error. Once the system achieved the steady state, it maintained the temperature at 37 ± 0.1 °C. Since the temperature control can vary and monitor fine changes in the environment, the system can be used to study an impact of temperature variations on cell response such as growth and differentiation.
Analysis of Process Physics in Electron Beam Melting
Authors: Hedreen Mark , Doyle Curtis , Bol Eric , Kelley Garrett , Ramulu M. 
Published: January 2022

Abstract
Electron Beam Melting (EBM) is a novel additive manufacturing process capable of producing production-quality metal components. The physics of EBM are complex, involving highly non-linear heat and mass transfer effects. Understanding these physical phenomena is key to producing quality components.
In this study, a variety of analytical and numerical models are demonstrated to characterize the relationship between material properties, process parameters, and the resulting physical behavior during printing, with Ti-6Al-4V and Inconel 718 as test cases. The thermal and fluid flow behaviors are analyzed with several dimensionless numbers and the sensitivity to various factors is discussed. Radiative and evaporative heat loss are calculated, taking into account the effects of activity coefficient on vapor pressures in an alloy system. Compositional losses during printing are calculated and a method to optimize composition is discussed.
Verification and Validation of a Small Wind Tunnel Data Acquisition System
Authors: Doom Alex J. , Hollingsworth Elena , Bishop Riley , Fisher Wesley , Mazzoni Brian , Manohar Chidurala 
Published: January 2022

Abstract
This paper discusses the design, validation, and verification of a wind tunnel data acquisition system that measures the pressure distribution around a cylinder and airfoil and calculates the resulting lift and drag forces acting on the object in cross flow. Typical aerodynamic research is conducted using wind tunnels with large test sections and high air speeds, which can be expensive and unattainable for many universities. A traceable path of validation can improve the results of experimentation on small test section and low speed wind tunnels by providing important information on the accuracy, uncertainty, and error involved in the system. It is concluded that CFD verification and validation not only improves experimentation but is the key to conducting quality research with limited resources.
The High Cycle Fatigue Behavior of Surface Treated Electron Beam Melted Titanium Ti6Al4V
Authors: Mojib Melody , Soyama Hitoshi , Sanders Daniel , Arola Dwayne , Ramulu M. 
Published: January 2022

Abstract
With the growth of Additive Manufacturing (AM) or 3D printing, the need for long lasting metal components for high-stress applications is becoming increasingly crucial. One of the biggest limitations is the low fatigue life of AM components due to a variety of factors including build orientation, surface roughness, and internal defects. To address the low fatigue behavior of metal AM components, there is an increase in interest in performing surface treatments such as machining or polishing on additive manufactured components. With AM’s unique potential to produce complex shapes, the ability to perform conventional surface processes on printed parts becomes difficult and limited. Preliminary effects of tool-less post processing techniques on fatigue life titanium Ti6Al4V specimens has been explored in this study with specimens undergoing hot isostatic pressing (HIP), in addition to a surface treatment process including cavitation peen, laser peen, shot peen or cavitation abrasive surface finishing. Uniaxial high cycle fatigue testing has been performed on untreated, HIP, and HIP + surface treated cylindrical electron beam melting (EBM) specimens. The location of crack initiation has been determined under high magnification and the location of internal defects are evaluated using micro-Computer Tomography (μCT). The location of crack initiation in all specimens was attributed to the sharp voids due to the rough surface or the subsurface defects which remained after post processing. The shot peen and polished titanium specimens exhibited the greatest increase in fatigue life due to the improvement in roughness and introduction of high compressive stresses.
Robotic-Based Repair of Concrete Structures: A Surface Crack Filler Robot
Authors: Stevens Melinda , Arellano Samuel , Rodriguez Diego , Wilson James , Gutierrez Zady , Trudell Noah , Momeni Hamed , Ebrahimkhanlou Arvin 
Published: January 2022

Abstract
Surface cracks in concrete structures are often indicators of more substantial damage and may negatively affect the durability of a structure. To ensure the soundness of these structures, surface cracks should be quickly detected; this project proposes a robot with the ability to detect, map, and fill surface cracks. The robot will use a Bayesian network to fuse the multi-sensor data provided via an RGB camera, a stereo infrared depth sensor, and a LIDAR sensor. It will also be fitted with a newly designed piston-driven syringe system to inject a concrete filler material in a controlled manner. A non-captive lead screw and stepper motor drive the piston along with the syringe, and an arm with two degrees of freedom will allow the robot to position the injector along a crack accurately. To control the arm, the Bayesian network and sensor systems will work in unison to determine when a crack has been filled in a satisfying manner, ensuring a degree of uniformity and consistency in the repaired concrete surface.
A Novel Image-Based Method for In Situ Characterization of the Pore Size Distribution and Dimensional Accuracy of Bone Tissue Scaffolds
Authors: Abdelgaber Yousef , Klemstine Cole , Lawrence Logan , Day James B. , Claudio Pier Paolo , Salary Roozbeh (Ross) 
Published: January 2022

Abstract
Pneumatic micro-extrusion (PME) is a high-resolution direct-write additive manufacturing method, which has been widely utilized for the fabrication of biological tissues, structures, and organs. The PME process allows for non-contact, multi-material deposition of a wide range of functional bio-inks for tissue engineering applications. However, the PME process is inherently complex, governed by complex multi-physics phenomena. Consequently, investigation of the effects of significant process parameters and their interactions on scaffold functional properties would be inevitable.
The overarching goal of this research work is to fabricate defect-free, porous bone scaffolds for the treatment of large osseous fractures. In pursuit of this goal, the objective of the work is to forward an image-based method for the characterization of the pore size distribution as well as the dimensional properties of bone tissue scaffolds, fabricated using the PME process. The developed method will allow for detection of scaffold pores, thus quantification of pore size distribution, and ultimately assessment of the dimensional accuracy of bone tissue scaffolds. The method was validated based on specimens obtained from a single factor experiment. The specimens were composed of PCL, fabricated using the PME process. The results of this study pave the way for fabrication of complex bone scaffolds with accurate dimensional properties for the treatment of bone fractures and defects.
Study of Flow Field Configuration Effect in Cooling Systems
Authors: Carbajal Gerardo 
Published: January 2022

Abstract
A three-dimensional numerical simulation was performed to increase a cooling system’s performance using different flow field configurations. In this study, the cooling system consists of three fluid configurations and contains ten batteries and eleven channels. The fluid flow configurations are the U-configuration, the Z-configuration, and the I-configuration. The battery was modeled assuming a solid material with constant physical properties, and the air is the working fluid in the cooling system. The numerical simulation results showed a better uniform temperature distribution with the I-configuration than the other two configurations. The numerical solution of the coupled fluid-energy equations corresponding to the three configurations indicates a significant effect of the relative flow distribution in the local transfer of energy from the batteries to the airflow: therefore, affecting the temperature distribution of the system’s components. This study assumed four heat inputs and mainly focused on the effect of fluid flow in evaluating the core temperature of the batteries. The worst performance in terms of temperature rise in the system corresponded to the U-configuration. The I-configuration presented the lowest average temperature in the battery’s core; the temperature field was also more uniform than the other two configurations. The U-configuration delivered the lowest pressure drop, and the Z-configuration the highest pressure drop. The results confirmed that it is possible to improve the cooling process by selecting the suitable flow field configuration of the system.