bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Learning-Based Super-Resolution for the Finite Element Analysis of Additive Manufacturing Process
Authors: Zhang Yi , Freeman Elton 
Published: September 2022

Abstract
Finite element analysis (FEA) of fused deposition modeling (FDM) has recently been recognized in additive manufacturing (AM) for predictions in temperature gradient of three-dimensions (3D) printed components. These predictions can be invaluable for making corrections to the printing process to improve quality of printed components. However, FEA has its limitations. For example, models with fine mesh (small element size) yield more accurate results than ones with coarse mesh (large element size). Comparing with the coarse mesh model, a fine mesh model can take considerably longer computational times and discourages most manufacturers from using FEA. In this work, an innovative deep-learning (DL) based super-resolution approach is used to improve the result accuracy of a coarse mesh model to the higher accuracy level of a fine mesh model and reduce the computational time. The element in the FEA was treated as the physical pixel in an image, so the fine temperature grid and coarse temperature grid in the FEA were analogous to high resolution (HR) images and low resolution (LR) images, respectively. The result shows that the difference value HS between HR image and super resolution (SR) image is much smaller than the one HL between HR image and LR image, which demonstrated that our proposed DL-based super-resolution approach was effective to enhance the result accuracy of the coarse mesh model. Besides, both the increased Peak Signal-to-Nosie Ratio (PSNR) value and Structural Similarity Index (SSIM) value indicated that the quality of the images was also improved through the super-resolution approach.
A Crystal Plasticity Finite Element Method Modeling of Zircaloy With Hydride Phases Based on Scanning Electron Micrographs
Authors: Kulkarni Shank S. , Truster Timothy , Senor David J. , Devanathan Ram 
Published: September 2022

Abstract
This work developed a microstructure-based finite element model to predict the stress state of alloys with second phase inclusions. Quantitative microstructural details were extracted from scanning electron microscopy (SEM) images and were used to generate heterogeneous microstructures. Generation of digital microstructure was achieved through two steps of tessellations using software Neper and Matlab. This digital microstructure can be further used to perform multiple structural simulations as per the need. Such simulations are very useful in many applications as the manufacturing process can be altered to obtain the morphology resulting in desired overall material properties. The process is demonstrated using an example of Zircaloy material with secondary phases of hydrides dispersed within and stress-strain response of Zircaloy containing hydrides was predicted. Crystal plasticity based constitutive material model was used for Zircaloy whereas the hydrides were modeled as isotropic elasto-plastic material. A parametric study was conducted to understand the effect of volume fraction, and lamellae thickness of the hydride phase on the mechanical properties of the overall material. The introduction of the hydride phase was found to increase the yield stress of Zircaloy with an almost linear relationship between yield stress and hydride volume fraction. On the other hand, the width of hydride lamina was found to have a negligible effect on the yield stress of Zircaloy. These results can help designers to alter the manufacturing process to obtain the enhanced mechanical properties for components used in nuclear applications made by Zircaloy material.
Coupled Diffusion-Deformation-Damage Model for Polymers Used in Hydrogen Infrastructure
Authors: Kulkarni Shank S. , Choi Kyoo Sil , Simmons Kevin 
Published: September 2022

Abstract
The soft materials used in the infrastructure of hydrogen storage and distribution systems are vulnerable because exposure to high-pressure hydrogen can lead to mechanical damage and property degradation. Polymers are one of the widely used classes of soft materials within hydrogen infrastructure. Many small cavities exist within the polymer material due to their long molecular chains. When exposed to high-pressure hydrogen gas, the gas diffuses through the polymer material and occupies these cavities. When outside hydrogen pressure reduces suddenly, the hydrogen gas inside the cavities does not get enough time to diffuse out as diffusion is a much slower process. Instead, this trapped gas causes blistering or in extreme cases rapture of polymer material. This phenomenon is also known as rapid decompression failure.
In this study, a continuum mechanics-based fully coupled diffusion-deformation model with damage is developed to predict the stress distribution and damage propagation while the polymer undergoes rapid decompression failure. The hyperelastic material model, along with the maximum principal strain failure theory, was chosen for this study as it represents the nonlinear material response with sudden failure observed in uniaxial tensile tests perfectly. EPDM polymer was chosen for this study because of its commercial availability and common use in hydrogen storage and distribution system. It has superior mechanical properties, high and low-temperature resistance, and certain compounds work well in hydrogen gas. Stress concentration was observed on the periphery of the cavity at the point closest to the outside surface which lead to damage initiation at the same location. Also, this work showed that the coefficient of diffusion plays an important role in damage initiation. As the value of the coefficient of diffusion increases, the amount of damage decreases due to the higher coefficient of diffusion ensures a safe passage for trapped hydrogen to escape to the atmosphere. This work is useful for design engineers to alter the parameters while manufacturing polymer composites to increase their performance in a high-pressure hydrogen environment.
Analysis of Conduction Cooling Strategies for Wire Arc Additive Manufacturing
Authors: Heinrich Lauren , Feldhausen Thomas , Saleeby Kyle S. , Saldana Christopher , Kurfess Thomas R. 
Published: September 2022

Abstract
Metal additive manufacturing (AM) processing consists of numerous parameters which take time to optimize for various geometries. One aspect of the metal AM process that continues to be explored is the control of thermal energy accumulation during component manufacturing due to the melting and solidification of the feedstock. Excessive energy accumulation causes thermal failure of the component while minimal energy accumulation causes lack of fusion with the build plate or previous layer. The ability to simulate the thermal response of an AM component can increase research efficiency by reducing the time to optimize thermal energy accumulation. This paper presents an effective implementation of finite element analysis to determine the thermal response of a wire arc additive manufactured component with various build plate sizes and cooling methods including, integral build plate cooling, oversized build plates with passive cooling, and non-integral build plate cooling. The use of integral build plate cooling channels was shown to decrease the interpass temperature at the conclusion of the build process by 55% and build plate temperature by 96% compared to the conventionally deposited sample with 20 second dwell time. The use of a tall build plate with passive cooling was shown to reduce the interpass temperature by 32% as compared to the conventionally deposited sample with 20 second dwell time. Each cooling strategy evaluated decreased the interpass temperature within a range of 20–55% which enables higher deposition rates and decreased dwell times during depositions. The cooling strategies are designed to be implemented in a hybrid or retrofit AM platform to mitigate concerns of the thermal input from the additive process having detrimental effects on the precision of the machining process. This paper shows that accurate simulations of all strategies can be used to accurately predict the thermal response of the various strategies discussed. These cooling strategies will allow for increased deposition rates with comparable interpass temperature and decreased dwell time, increasing deposition efficiency. This model and these simulations are verified by experimental results. It is concluded that passive strategies, such as the over-sized tall build plate, can be used when liquid coolant in the AM environment could negatively affect the deposition process. Active cooling strategies, such as the integral build plate cooling could be used if low thermal conductivity materials are deposited or higher material deposition rates are desired. This paper discusses the use of active and passive cooling used during AM and shows how a simulation model can be used to make design choices for cooling strategies. The model also enables verification of select critical process parameters such as dwell times for a desired interpass temperature.
Solving the Open Route Capacitated Periodic Vehicle Routing Problem With Time Windows to Service Microgrids Powered by Uncertain Renewable Generation
Authors: Shawky Waleed , Azab Ahmed , Kassem Sally 
Published: September 2022

Abstract
Supply Chain and logistics operations are high-cost operations that require planning to keep costs minimum. One of the most crucial supply chain stages is the distribution stage, including delivering products to retailers and/or customers. The problem of products’ distribution consumes considerable amounts of time and money and is modeled in many situations as a Vehicle Routing Problem (VRP). In this paper, servicing and provision of power transactions to an electric micro-grid using a fleet of mobile energy storage systems (MESSs) during a specific time horizon is targeted using the developed model for the well-known Capacitated VRP with Time Windows (CVRPTW). The process of servicing power transactions of an electric micro-grid is repeated for each station periodically, which results in a problem known as periodic VRP (PVRP). The MESSs in the developed model do not necessarily return back to their original trip starting point (depot); hence, the problem at hand is considered as Open-Route as well. Therefore, the Open Route Capacitated Periodic VRP with Time Windows (OCPVRPTW) is studied in this paper. The model is formulated and solved using commercial software to obtain exact solutions to the tackled problem instances. For future work and due to the combinatorial nature of the problem, Ant Colony Optimization will be used to solve larger instances of the problem.
Laser Micro Machining Using an Oblique Photonic Nanojet With Focused Laser Beam Irradiation
Authors: Uenohara Tsutomu , Yasuda Makoto , Yamamoto Kosei , Mizutani Yasuhiro , Takaya Yasuhiro 
Published: September 2022

Abstract
Three-dimensional microstructures in the sub-micrometer scale exhibit unique properties. A flexible machining method to fabricate such structures is desired. Photonic nanojet (PNJ) is high intensity laser beam with sub-micrometer scale beam diameter and micrometer scale depth of focus. PNJs have a longer depth of focus than tightly focused laser beams with a high numerical aperture. In this study, we investigate the angular control of PNJs by controlling the propagation direction of incident light in order to realize flexible laser micro machining using PNJs. By controlling the position of the microsphere in the focused laser beam with a large defocus, the propagation direction of the laser beam incident on the microsphere is changed, and the angle of the PNJ can be controlled. Laser machining experiments on a silicon substrate showed that the PNJ angle can be controlled by incident laser angle. Furthermore, sub-micrometer scale laser machining was achieved even when using an oblique PNJ. The simulation results and experimental results are in good agreement. In conclusion, the angle control of the photonic nanojet can be applied to flexible multi-axis laser micro machining.
Fabrication of Nanowires Using Glancing Angle Deposition
Authors: Qu Chuang , McNamara Shamus , Walsh Kevin 
Published: September 2022

Abstract
This paper introduces the fabrication of wafer-long nanowires using glancing angle deposition (GLAD). GLAD is an advanced physical vapor deposition technique, and it has the unique advantage of creating three-dimensional nanofeature arrays, compared to conventional top-down nanofabrication techniques. Various nanofeatures created by GLAD have been reported, including pillars, springs, chevrons, ribbons, and those structures as templates for creating nanoporous membranes; this paper fills the gap by presenting the creation of nanowires by GLAD. This paper describes the fabrication process by introducing the seeding scheme of corrals. The seed design for GLAD adopts the design rules of corrals of line seeds, and the GLAD parameters are determined by the design of the corrals of line seeds. In the experiment, conventional photolithography is used for creating micro-level widths and heights and wafer-length of line seed corrals. Two GLAD sessions with the target material for the nanowires and the mask material are deposited on the substrate in sequence with different azimuth angles; the nanowires are obtainable by anisotropic etching and removal of the sacrificial layer of corrals of line seeds. The design of the corrals of line seeds and the control of the size of the nanowires are discussed. The nanowires created are potentially applied in sensing applications, for example, the palladium or platinum nanowires can be used for hydrogen sensing.
Establishment of Mode Shape Database for Machine Tool and its Application in Estimating System Dynamics
Authors: Liu Jiahui , Kizaki Toru , Yamaura Shogo , Sugita Naohiko 
Published: September 2022

Abstract
Machine tool dynamics has an important role in machine health monitoring, chatter prevention, machining process control, and improvement of manufacturing accuracy. For industrial applications, system dynamics vary with the machining process. To achieve this information during operation, the operational modal analysis (OMA) method, which can observe dynamic performance with output only, has rapidly developed and evolved into transmissibility function-based operational modal analysis (TOMA), with the ratio of outputs used for the estimation of system dynamics. However, this analysis is limited by excitation variance and nature of coherence deformation for the entire system when machining position or posture change. To precisely estimate machine dynamics in process, this study proposes the use of feature fitting from a mode shape database after collection by TOMA. By segmenting the continuous machining process, the variation in system dynamics during operation can be separated into domains under the requirement of machining accuracy. A numerical experiment was performed with a no-damping finite element model of one machining center to verify the feasibility and accuracy of the proposed method. Subsequently, the experimental performance of the mode shape with several accelerometers was evaluated, and the differences with finite element results were discussed with further consideration of application in practice.
Embrace the Imperfection: How Intrinsic Variability of Roll-to-Roll Manufactured Environmental Sensors Enable Self-Calibrating, High-Precision Quorum Sensing
Authors: Saha Ajanta , Gopalakrishnan Sarath , Waimin Jose , Sedaghat Sotoudeh , Mi Ye , Glassmaker Nicholas , Cakmak Mukkerem , Shakouri Ali , Rahimi Rahim , A. Alam Muhammad 
Published: September 2022

Abstract
Roll-to-Roll (R2R) process is well suited for manufacturing low cost, miniaturized, solid contact Ion-selective electrodes (ISEs) of potentiometric sensors to be used for continuous monitoring of various analytes in environmental, industrial, and health-care applications. It is presumed that the intrinsic thickness variability of the R2R process would limit the accuracy of the ISE-based sensors and would make them inferior to sensors fabricated by higher precision manufacturing processes. Instead, in this paper we propose to use the intrinsic variability of R2R process as a “resource” to achieve high-accuracy sensing even when the sensors are operated in uncontrolled field conditions. This is achieved by applying a fundamentally new physics-guided statistical approach involving: (i) ‘Self calibration’ where we calculate temperature from differential measurement of the ISEs induced by R2R variability to calibrate the sensors in uncontrolled temperature condition, and (ii) ‘Quorum sensing’ where we use a collection of R2R manufactured sensors to estimate the true concentration considering credibility of each sensor calculated by Bayesian Maximum Likelihood Estimation method. With these two new techniques, we demonstrate the use of “low-precision” R2R sensors to measure nitrate concentration of an agricultural field continuously over a period of 15 days within 10% of the ground-truth measured by the traditional high-precision commercial nitrate sensor.
3D Printed Pelvic Organ Prolapse (POP) Tissue Scaffolds
Authors: Zhu Yuxiang , Ravichandran Dharneedar , Song Kenan 
Published: September 2022

Abstract
Nearly 1 in 4 women undergo surgery for pelvic organ prolapse or urinary incontinence in the US. The weakened pelvic floor, which could be caused by childbirth injury, aging, or obesity, fails to support the pelvic organs, resulting in urinary incontinence, sexual difficulties, and pelvic organ prolapse (POP). Polypropylene (PP) meshes are often used in reconstructive surgeries as a reinforcement to provide long-term, durable support. However, commercial polypropylene meshes have a risk of complications, such as pain, mesh erosion, and infection. The United States Food and Drug Administration (FDA) has consequently re-classified the polypropylene mesh as a high-risk device. Therefore, the need for new meshes to cure POP with a rapid prototyping technique is urgent, especially for personalized medicine.
Therefore, we developed a new implantable mesh using biocompatible polymers (e.g., gelatin, polyvinyl alcohol (PVA), chitosan) with controlled bonding strength and tunable lifetime. Our group has leveraged additive manufacturing for porous scaffold structures beneficial for cell attachment and nutrition transmission. Our POP scaffold mesh has demonstrated high biocompatibility and controlled biodegradability. We will also leverage our manufacturing expertise and clinical partnerships to examine cell proliferation and differentiation for tissue regeneration. Our advanced manufacturing method is compatible with other materials and has potential use in layered structures for dental, heart, or bone engineering applications.
Estimating Milling Forces From Vibration Measurements
Authors: Joddar Manish , Ahmadi Keivan 
Published: September 2022

Abstract
Machining force and vibration signals are commonly used for process monitoring. While low-cost accelerometers are conveniently installed in machining setups, the direct measurement of machining forces in industrial applications is challenging. As an alternative to direct measurement, cutting forces can be estimated indirectly from vibration measurements, enabling the simultaneous monitoring of vibrations and forces from vibration signals only. In this paper, we two methods for estimating the dynamic milling forces from acceleration measurements during milling processes. The first method applies offline regularized deconvolution to the measured acceleration data to extract the forces causing them. The second method designs an online Augmented Kalman Filter to observe the forces as the augmented system states. The efficiency and performance of both methods are studied experimentally. The comparison between the indirectly estimated forces and the directly measured ones confirms the feasibility of using acceleration sensors to monitor the machining forces and the resulting vibrations simultaneously. Nevertheless, because the low-frequency contents of the forces are filtered in the resulting accelerations, only the dynamic component of the forces can be recovered. Experimental comparison of regularized deconvolution and augmented Kalman filter methods shows that the latter is more effective in recovering a larger portion of low-frequency content of the forces. Despite missing the low-frequency content, the reconstructed dynamic forces can still be used for process monitoring in applications where force sensors cannot be installed.
Exploring the Role of Mechanochemical Effects in Cutting of Aluminum Alloys With Alcohols
Authors: Sugihara Tatsuya , Nomura Takuma , Enomoto Toshiyuki , Udupa Anirudh , Viswanathan Koushik , Mann James 
Published: September 2022

Abstract
In metal cutting processes, a chemical ambient environment in the cutting zone can be a useful variable for process control and process performance improvement. In this work, we study how mechanochemical effects influence the chip formation process, especially focusing on a specific chemical reaction between aluminum alloys and alcohols as a model system. Using high speed in-situ imaging and particle image velocimetry, we demonstrate that the mechanochemical effect in cutting of annealed Al with use of isopropyl alcohol (IPA) is manifest in two different ways: a lubricating effect at the tool-chip interface and an embrittlement effect at the workpiece free-surface, depending on the undeformed chip thickness and cutting speed. Consequently, the highly unsteady chip flow seen in dry cutting of annealed Al, which is typically seen in cutting of ductile “gummy” metals, transitions to a laminar-type (smooth) chip-flow mode or a segmented, fracture-controlled chip flow, due to the Al-IPA reaction. In both cases, the modified chip flow modes lead to significant reduction in cutting forces and improvement of finished surface quality. The specific manifestation of the mechanochemical effect is found to be principally determined by the penetration capability of the alcohols into the tool-chip interface and the time required for the chemical reaction between aluminum and the alcohols. Also, we discuss some implications for improving the performance of practical Al cutting operations using alcohols as a fluid medium.
Effect of Alloying Elements of Al Alloy on the Interfacial Microstructure and Fracture Behaviour of Al Alloy/Steel Inertia Friction Welded Joint: A Comparative Study
Authors: Ma Hong , Geng Peihao , Qin Guoliang 
Published: September 2022

Abstract
The present study highlighted the effect of alloying elements in Al alloy on the interfacial microstructure, and the corresponding fracture behaviour of the Al alloy/steel inertia friction welded joint by selectively adopting two types of Al alloys. A strong texture of &lt;111&gt;//radial direction was formed on the Al alloy side in both types of joints, while no obvious changes were identified on the steel side. Different types of intermetallic compounds (IMCs) were formed at the weld interface. In the Al-Mg-Si alloy/steel joint produced at a low heat input, the interfacial microstructure was composed of a nanoscale amorphous layer and partially crystallised layer, while it turned into a fully crystallised Fe2Al5 phase with Si enriched when the heat input was enhanced. In the Al-Cu alloy/steel joint, Cu was enriched at the weld interface, with the possible formation of Fe-Al-Cu based IMCs. Moreover, a two-layered structure of IMC with different compositions of Cu appeared when the joint was prepared at a high heat input. Such distinct interfacial microstructure caused different fracture behaviours of joints. An interfacial reaction layer less than 130 nm thick led to the failure of Al alloy rather than the weld interface which easily happened at a thicker IMC.