bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional Requirements of Data Analytic Tools and Software for Metal Additive Manufacturing
Authors: Feng Shaw C. , Moges Tesfaye , Witherell Paul W. 
Published: February 2021

Abstract
Additive manufacturing’s (AM’s) transition to an accepted production technology has led to increasing demands on data requirements. Many of these advances have been made possible by an increase in in-situ sensing and ex-situ measurement devices. These new devices are rapidly increasing the volume, variety, and value of AM data. The number of software tools used to measure, model, simulate, and manage AM material, part, and process is increasing to take advantage of emerging customer needs and market opportunities. However, the capabilities and accessibility of these tools, which are being used by both practitioners and researchers, vary greatly. Software tools for AM users should be able to handle ex-situ needs as well as address emerging in-situ requirements, including 1) process the different types of measured data, 2) understand defect formation, geometric variation, surface roughness, and 3) run fast enough for the layer-by-layer, scanning process. To better understand both the current capabilities and future needs, this paper provides an AM product-lifecycle landscape of software tools. The landscape includes tools for product design, design analysis, process planning, process monitoring, process modeling, process simulation, and production management. A preliminary set of functional requirements are identified, and requirements that if supported will further data analytics capabilities in AM. Furthermore, this paper identifies opportunities to develop new data-analytics tools that can improve product quality and reduce production time.
Three-Dimensional Crystal Plasticity Modelling of High-Strength Tool Steels Using Fourier Based Spectral Solver
Authors: Ibrahim Youssef , Khafagy Khaled H. , Hatem Tarek M. , Hegazi Hesham A. 
Published: February 2021

Abstract
Tool steels are essential for any industry, being used to cut, drill, form, shear, and shape ferrous and non-ferrous materials in bulk or powder forms. Due to the harsh service environment, tool steels are engineered with superior properties that include high wear, corrosion, and impact resistance. The macro properties of tool steel alloys are acknowledged to depend upon their fine martensitic microstructure. Therefore, accurate representation of its microstructures will help to further study its behavior which shall lead in advancing and improving their properties. In the current research, a novel microstructure generator for tool steel alloys will be used to precisely simulate complex microstructures of tool steels. The novel generating algorithm along with multiple-slip crystal plasticity based model and specialize spectral solver formulations are used to investigate high-speed tools steels behavior. The spectral method for elastoviscoplastic boundary value problems implicitly uses fast Fourier transformation algorithm (FFT) by applying periodic BCs. Both quasi-static and dynamic uniaxial tensile loading in the [010] direction is applied on a RVE of AISI H11 martensitic tool steel. Validating the numerical results with the experimental results of tool steels is presented.
Assessment of Mobile Elevating Work Platforms Risks and Review of Changes Introduced in New Industry Standards to Address These Hazards
Authors: Kennedy Eugenia , Guttag Mark , Bress Thomas 
Published: February 2021

Abstract
Three new industry standards, American National Standard/Scaffold & Access Industry Association, Inc. (ANSI/SAIA) A92.20, A92.22 and A92.24, were introduced in December 2018 to address the safe design, use and training associated with mobile elevating work platforms (MEWPs). MEWPs are defined in the new Standards as “machine/device intended for moving persons, tools and material to working positions, consisting of at least a work platform with controls, an extending structure and a chassis.”2 This definition encompasses certain types and sizes of MEWPs such as scissor lifts, articulating boom lifts, telescopic boom lifts and straight mast boom lifts. Replacing product-specific industry standards, these three new Standards significantly change the design, testing, rental, use and training requirements associated with MEWPs. The Standards also offer greater clarity to the assigned responsibilities associated with these functions to various entities including manufacturer, dealer, owner, user, supervisors, operator, occupants, lessor, lessee and brokers. Compliance with these voluntary standards became effective June 1, 2020.3
Recognized hazards associated with MEWPs include: tip overs associated with wind loads and contact with other obstacles, contact with power lines leading to electrocutions, caught-between the lift and other objects, falls from platform and equipment collapse.4 This effort will analyze injury data including both fatal and nonfatal incidents associated with MEWPs to better understand the trends and quantifying many of the risks associated with the operation and maintenance of MEWPs. Injury data from the U.S. Bureau of Labor and Statistics (BLS) will be reviewed. The effort will also identify and explore how the design, use and training requirements introduced in the new industry standards address the hazards and risk associated with MEWPs.
Blood Flow Velocimetry in a Microchannel During Coagulation Using PIV and wOFV
Authors: Kucukal E. , Man Y. , Gurkan U. A. , Schmidt B. E. 
Published: February 2021

Abstract
This article describes novel measurements of the velocity of whole blood flow in a microchannel during coagulation. The blood is imaged volumetrically using a simple optical setup involving a white light source and a microscope camera. The images are processed using PIV and wavelet-based optical flow velocimetry (wOFV), both of which use images of individual blood cells as flow tracers. Measurements of several clinically relevant parameters such as the clotting time, decay rate, and blockage ratio are computed. The high-resolution wOFV results yield highly detailed information regarding thrombus formation and corresponding flow evolution that is the first of its kind.
An Artificial Intelligence Approach to Real-Time Energy System Performance Monitoring Using Acoustic Signals
Authors: Aliati Valdir , Metghalchi Hameed , Wallace Jon 
Published: February 2021

Abstract
Global warming has caused an increase for more energy efficient combustion engines. Measuring the energy performance at real time may require many sensors that increase the final cost of the energy system. This paper describes the feasibility of using deep learning Artificial Intelligence (A.I.) methods to estimate energy system performance using acoustical signals. First, an audio recorder was set up to measure the acoustic signals, while taking direct measurements of an aircraft propulsion system. Then, an energy balance equation for the aircraft was calibrated, and transformed into an algorithm that calculates the Specific Total Energy (STE) in real-time by using the direct measurements recorded. The acoustic signatures were filtered out and their statistical features were used to train and test an artificial neural network that outputs the aircraft’s energy state. This process showed that it is possible to create and train models with an R2 as high as 0.99854, while avoiding overfitting; proving that it is feasible to monitor an energy system performance by using acoustic signals.
A Physics-Informed Neural Network Constitutive Model for Cross-Linked Polymers
Authors: Ghaderi Aref , Morovati Vahid , Bahrololoumi Amir , Dargazany Roozbeh 
Published: February 2021

Abstract
The behavior of Cross-linked Polymers in finite deformations is often characterized by nonlinear behaviour. In this paper, we propose to embed an artificial neural network (ANN) within a micro-mechanical platform and thus to enforce certain physical restrictions of an amorphous network such as directional dependency and history-dependency of the constitutive behavior of rubber-like materials during loading and unloading. Accordingly, a strain energy density function is assumed for a set of chains in each direction based on ANN and trained with experimental data set. Summation of the energies provided by ANNs in different directions can determine the strain energy density function of the matrix. Stress-strain relation is derived from strain energy density function. Polyconvexity is enforced to assure minimized potential energy, a global solution for an optimization problem, and thermodynamic consistency that show the model cannot generate energy. The model is validated against multiple sets of experimental data, e.g. uniaxial, shear, and biaxial deformation available in the literature. This model captures not only the loading and unloading paths but also the inelastic response of these materials, such as the Mullins effect and permanent set. The model can be generalized to other materials and other inelastic effects as well.
Effect of Friction on Residual Stress Distribution Induced by Split Sleeve Cold Expansion Process
Authors: Dey Mithun K. , Kim Dave , Tan Hua 
Published: February 2021

Abstract
Residual Stress distribution and parametric influence of friction are studied for the split sleeve cold expanded holes in Al 2024 T351 alloy, by developing a three-dimensional finite element model of the process. Fastener holes in the alloy are necessary for the manufacturing process, but they create a potential area for stress concentration, which eventually leads to fatigue under cyclic loading. Beneficial compressive residual stress distribution as a result of the split sleeve cold expansion process provides retardation against crack initiation and propagation at the critical zones near hole edges. In this parametric study, the influence of friction between contact surfaces of the split sleeve and mandrel is numerically investigated. Hole reaming process after split sleeve cold expansion is often not discussed. Without this post-processing procedure, split sleeve cold expansion is incomplete in practice, and its purpose of providing better fatigue performance is invalidated. This study presents results and an overview of the significance of friction with the consideration of the postprocessing of split sleeve cold expansion. The numerical results show that with increasing friction coefficient, compressive residual stress reduces significantly at the mandrel entry side, which makes the hole edge more vulnerable to fatigue. The different aspects of finite element modeling approaches are also discussed to present the accuracy of the prediction. Experimental residual stress observation or visual validation is expensive and time-consuming. So better numerical prediction with the transparency of the analysis design can provide critical information on the process.
Systematic Integration of Topology Optimization Techniques in Design for Additive Manufacturing Methodologies Applied to Automotive Settings
Authors: Dalpadulo Enrico , Pini Fabio , Leali Francesco 
Published: February 2021

Abstract
Additive Manufacturing is having a great trend since its implementation possible benefits have been widely discussed and efforts in technology improvements are having impact on process reliability and industrial application. The aims of this work are to analyze the current and forthcoming scenario of methods for the specific development of parts to be produced by metal AM including topology optimization as a basic design step and to demonstrate that systematical design approaches can be introduced in order to better exploit potentials offered by AM implementation. The general framework composed by the main tasks is introduced and discussed. Key factors such as advance in different design solutions exploration, product-related and process-related design constraint implementation in the design phase and method effectiveness in product development lead time minimization are presented. Linear and iterative workflows are described, considering features, decision making points, pros and cons, possible variants and research hints. A strong connection between methods and actual means is highlighted and workflow implementation using standard and integrated commercial tools is considered. Such methods are related to several automotive case studies presented in order to demonstrate their applicability and to show actual results and possible further development.
A Study on the Tip-Based Nanomachining of Silicon Wafer Using Atomic Force Microscopy (AFM)
Authors: Okwuashi Chionye , Ma J. , Jahan M. P. 
Published: February 2021

Abstract
In this work, the principles of nanoindentation and nanoscratching processes (tip-based nanomachining processes) are applied in the computational study of relevant material behaviors of single crystalline silicon wafer. Molecular dynamics (MD) simulations are carried out to model the tip-based nanomachining process of a silicon substrate by employing LAMMPS, a free MD simulation software. A spherical diamond tool tip with a radius of 8Å is considered. In the MD simulation, a single diamond indenter is treated as a rigid body. The dimensions of the silicon workpiece in the MD simulations are 500Å × 500Å × 350Å, containing 2,207,698 Si atoms. A diamond cubic lattice structure is employed to arrange these Si atoms from the very beginning at 293 K (room temperature) and a lattice constant of 5.43Å is employed. The lowest layer of the Si workpiece model is fixed and this fixed layer is one atom thick i.e. its thickness is 5.43Å. Immediately above the fixed layer is another layer of equal thickness (5.43Å), which is called thermostat layer. This layer serves the purpose of maintaining constant temperature of the system. The force-controlled approach is employed for this study. Essentially, this research evaluates the influence of three parameters: exerted force on indenter, workpiece temperature (room temperature and several higher workpiece temperatures), and indenter size on the depth of indentation, length of scratch, and coordination number of the atoms. Verlet -Velocity algorithm is used to compute the velocities and positions of the atoms. Since we desired to maintain consistency in volume, energy, and the number of particles, the constant-energy ensemble (NVE), also known as microcanonical ensemble is applied in the simulations. Both the Si-Si and C-C interactions are computed using the Tersoff potential throughout the simulations while the Si-C interactions are computed with the Morse potential. The MDS results are visualized and analyzed using OVITO, a free and commonly use visualizing tool. It is found that these parameters (exerted force on indenter, operating temperature of the silicon substrate, and size of the indenter) have substantial influence on the behavior of the silicon substrate.
Towards Deep Learning Approaches for Quantitative Analysis of High-Throughput DLD
Authors: Gioe Eric A. , Chen Xiaolin , Kim Jong-Hoon 
Published: February 2021

Abstract
Microfluidics has shown great promise for the sorting or separation of biological cells such as circulating tumor cells since the first studies came out a few decades ago. With recent advances in high-throughput microfluidics, analysis of massive amounts of data needs to be completed in an iterative, timely manner. However, the majority of analysis is either performed manually or through the use of superimposing multiple images to define the flow of the particles, taking a significant amount of time to complete. The objective of the work is to increase the efficiency and repeatability of particle detection in a high-throughput deterministic lateral displacement (DLD) device.
The program proposed is in the early stages of development, but shows promise. The average time it takes to analyze over a gigabyte of video is 24.21 seconds. The average percent error of the total particle detection was 21.42%. The assumptions made for the initial version of the program affect the accuracy of the particle in wall detection, so new techniques that do not follow the assumptions will need to be investigated. More work will be completed to implement machine learning or deep learning to assist in the development of DLD devices.
Ambient Temperature Effects on Battery Electric Vehicle
Authors: Liu Yiqun , Liao Y. Gene , Lai Ming-Chia 
Published: February 2021

Abstract
The driving range of an electric vehicle depends on the vehicle weight, road load conditions, battery capacity, and battery performance. The battery rated capacity and its characteristics could be heavily affected by the ambient temperature. This paper investigates the effects of ambient temperature on the electric vehicle driving range, equivalent fuel economy, and performance. A production-type battery electric vehicle is modeled and simulated in the AVL-Cruise platform using semi-empirical data. The modeled vehicle battery pack consists of 20Ah Lithium-Nickel-Manganese-Cobalt-Oxide (LiNiMnCoO2) cells. The battery cell characteristics are experimentally measured to build the battery pack model. The simulated driving range and equivalent fuel economy are correlated with the published information as vehicle model validation. Series of simulations on driving cycles (UDDS, HWFET, US06, and WLTP) with across a broad range of ambient temperatures are conducted to investigate the quantified effects of ambient temperature on driving range, equivalent fuel economy, and vehicle performance. Simulation results show that driving range and fuel economy are much reduced to 70% at low ambient temperature. Driving range and fuel economy are almost not affected by high ambient temperature, such as 50 C, since this model does not include accessory load of thermal management. The vehicle performance is almost not affected by the ambient temperature.
Information Model for A-UGV Performance Measurement Standard
Authors: Yoon Soocheol , Bostelman Roger 
Published: February 2021

Abstract
Automatic through autonomous - Unmanned Ground Vehicles (A-UGVs) have the potential to be applied over a wide range of manufacturing systems under industry 4.0 paradigm. In order to use A-UGVs efficiently in a manufacturing system, it is necessary to select the A-UGV suitable for each factory or workplace. A framework for evaluating the A-UGV performance under a specific manufacturing environment is needed. ASTM International Committee F45 has been developing standards2 providing a basis for A-UGV manufacturers and users to compare tasks to the A-UGV capabilities. This paper proposes information models for A-UGV performance measurement along the standards development. The standard needs are analyzed to show how the standard and information model can be used for the introduction of A-UGVs into factories. The information model in this paper provides a structured way to describe the factory elements affecting the A-UGV performance, and the measured A-UGV performances against the factory elements. To validate the proposed information model, an A-UGV performance testbed was built and the information model instance is developed to describe the testbed elements. An A-UGV is tested against the testbed elements and the measured performance is described by the other instance. This paper contributes to mutual understanding, between A-UGV makers and users, to deliver A-UGV performance information efficiently and to provide basis for A-UGVs to be tested under the same conditions.
Overall Temperature-Dependent Elastic Properties of Carbon Fiber Polymer Matrix Composites at High Temperatures
Authors: Konduri Teja G. K. , Zhupanska Olesya I. 
Published: February 2021

Abstract
In this paper we discuss the effect of volumetric ablation on the overall elastic properties of the carbon fiber reinforced polymer matrix composite. An Arrhenius type equation describing polymer decomposition was used to determine volume fractions of evolving polymer matrix phases (i.e. polymer, growing pores filled with pyrolysis gases, and char). The effect of the pressure exerted by pyrolysis gases trapped inside the pores was analyzed. Microstructures consisting of carbon fibers (circular inclusions) in the matrix and pores (elliptic inclusions) in the polymer were generated. Temperature dependency was addressed by generating microstructures with different volume fraction of pores, which were calculated from the mass loss model. Two-step numerical homogenization of representative volume elements (RVEs) was performed using finite element analysis (FEA). The developed procedures were applied to calculate temperature dependent (up to 700 K) effective elastic properties of the AS4/3501-6 composite. The results are compared to the existing experimental data and show good agreement.
Evaluation of Automotive Hood and Bumper Performance With Composite Material by Pedestrian Impactor Systems
Authors: Mohammed Obaidur Rahman , Suresh D. V. , Lankarani Hamid M. 
Published: February 2021

Abstract
The quality and reliability of vehicle safety in the automotive industry has greatly improved over the last years. Automotive manufacturers are constantly investigating the potential for enhancing rigidity for passenger car components and reducing the vehicle’s weight costs. Frontal elements such as the hood and bumper are more complex to analyze during the frontal collisions for weight reduction with the same rigidity and shape design. The objective of this study is to examine the crash efficiency of a vehicle’s hood and bumper with additive composite materials for enhancement of the design. The system is evaluated with the FE upper legform and adult headform impactor sub-system models. Under EEVC WG17 regulations, finite element simulations are performed with a sedan vehicle model. Analysis of the head impact on the car hood, subsequent head acceleration and HIC values were analyzed using pedestrian impactor. Differences in simulation results are examined for steel and composite material for better material selection. To estimate the weight reduction and pedestrian protection, a comparison between the composite material and the steel material is performed for the sedan vehicle. The study, thus, examines safety issues regarding the new material Carbon fiber-reinforced plastic (CFRP) for vehicle front-end and whether it would be less safe to use during frontal collision for weight reduction and comprehension behavior on pedestrian injuries.
Manufacturing and Characterization of Continuous Carbon Fiber Reinforced Polymer Composites
Authors: Choi Hongbin , Honarmandi Peyman 
Published: February 2021

Abstract
Additive manufacturing (AM), also popularly known as 3D-printing technology, is innovative as it manufactures a part by adding small portions of materials layer by layer, instead of removing materials from a larger bulk. This technology allows designers to create and manufacture many complex geometries. There are several AM techniques but this research focuses on fused deposition modeling (FDM) technique due to its relatively cheaper price tag and robustness. Although FDM is great at manufacturing complex geometries, the produced parts are weaker compared to the ones manufactured by the traditional techniques due to the weak layer adhesion, porous inner structure and poor surface finish. To overcome the limitations of the technology, this research was focused on reinforcing 3D-printed parts with continuous fibrous materials. In composite materials, previous studies show that among the numerous ways to inserting carbon fibers, direct insertion method yields the best results. Since none of the prior studies present standardized manufacturing and post-processing protocol, this research seeks to address this issue by developing and presenting the detailed protocols for both processes and fully characterize the created composite material experimentally. The result shows that heat-treated carbon fiber reinforced sample has exceptional increases in mechanical properties. Most notably, yield strength and resilience compared to the stock sample, increase by whopping 60% and 64% respectively.