bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiscale Modeling of the Uptake of Hydrogen Chloride on Anodized Aluminum in Relevance to Spacecraft Fire Safety
Authors: Niehaus Justin , Mazumder Sandip 
Published: February 2023

Abstract
Fire safety is a critical component of space missions. An electrical fire within the spacecraft often produces gaseous hydrogen chloride (HCl) from the smoldering of wire insulation. These gases tend to stick to the interior materials of the spacecraft, which is often comprised of treated aluminum. Determining the rate of uptake for HCl by aluminum helps the safe design of the spacecraft to reduce catastrophic mission risk. Our previous studies showed that a one-step global reaction model for adsorption of HCl on aluminum is incapable of predicting the experimentally measured HCl uptake of anodized aluminum, compared to other treatments with thinner oxide layers. X-ray photoelectron spectroscopy revealed that aluminum chloride is found deep in the oxide layer of the anodized aluminum, implying that the transport of HCl within the oxide layer covering the aluminum surface must be considered. This work uses a multiscale modeling approach to predict the uptake of HCl. A pore model is developed wherein the HCl reacts with the aluminum oxide pore walls to create an aluminum chloride layer. The HCl then diffuses through that layer for further reaction, until the diffusion resistance grows too large, and the surface is said to be saturated. The pore model is then coupled with the reactor-scale model to predict overall HCl uptake. Results show that this new multiscale approach predicts the uptake of HCl far more accurately than previously used single-scale models.
Electrical Power Generation From Biogas Upgrading
Authors: Smith Morgan , Musgrove Zachary , Song Yuxin , Hu Hao , Duan Shawn 
Published: February 2023

Abstract
Great interest has been expressed in the harnessing of methane biogas from the decomposition of biowaste to combust in an electric generator to produce electricity. Biogas produced in this way is a mixture of methane gas, carbon dioxide, and hydrogen sulfide. To use this gas as a fuel for an electric generator, the gas mixture needs to be purified and dried to create a purer methane fuel in a process called upgrading. The application of such a technology has been posed as most effective in a situation where biowaste in the form of excrement, whether human or animal, is plentiful, and where conventional reliance on electric infrastructure is difficult. The Washington State Department of Transportation (WSDOT) has proposed one such application lies in the 47 safety rest areas possessed by the state. The goal of this project is to design and prototype a system which will take biowaste, in this case cow manure, and create a self-contained system which will collect and filter biogas to create methane fuel and supply this fuel to a generator modified to run on methane to produce electricity. This project successfully produced 8.5 pounds-per-square-inch of mixed biogas in an anaerobic digester and has created a filtration system to upgrade the gas for fuel in the electric generator. The mixed biogas is at a methane concentration of 100% of the lower-explosive-limit.
Nanosecond Laser Modification of Nickel-Titanium Based Shape Memory Alloys
Authors: Ma Jianfeng , Karim Mahmud Anjir , Jahan Muhammud P. , Shim Sally Jee Hyun , Lei Shuting 
Published: February 2023

Abstract
Nickel-Titanium based Shape Memory Alloys (Ni-Ti SMAs), a group of special advanced engineering materials, are gaining popularity in industrial engineering and biomedical engineering for their superior properties. for example, amazing shape memory effects (SME), high strength, excellent corrosion and wear resistance, pseudoelasticity, outstanding biocompatibility and biodegradability. Industrial applications of Nickel-Titanium based SMAs include phone antennas, sensors and actuators in aerospace industry, automotive industries, and robotics. Biomedical engineering applications of this group of SMAs include cardiovascular field, neurosurgical field, orthodontic and orthopedic field. The fact that this group of SMAs are very sensitive to stress and mechanical tension makes it very difficult to be machined using conventional manufacturing processes. As a result, many research studies have focused on improving the machinability of this SMA using non-traditional manufacturing processes. In this study, the Continuum Surelite Class III nanosecond laser system with 1064 nm wavelength and 5 nanosecond pulse width is used to modify the surface of a Nickel-Titanium based SMA. The effects of laser pulse energy level and lens-to-samples distance on the crater and slot forming are evaluated. Single shot mode of the laser system is used to generate craters, and totally six laser pulse energy levels are used. In addition, three lens-to-sample distance values are selected. These six energy levels are 0.053 J, 0.122 J, 0.296 J, 0.415 J, 0.526 J, and 0.662 J, respectively. The three different lens-to-sample distance values are 150 mm, 170 mm, and 190 mm, respectively. The focal length of the lens is 150 mm. Continuous shot mode of the laser system is used to machine slots on the Ni-Ti based SMA. For slot forming, two energy levels (0.296 J and 0.662 J) and two lens-to-sample distance values (150 mm and 190 mm) along with two different overlapping ratios (0.75 and 0.95) are used. A 3D surface profilometer is used to study the variation of crater depth with laser parameters. The scanning electron microscope (SEM) and energy dispersive X-ray spectroscopy (EDS) analyses are used to investigate surface topography, surface modification, and laser-induced elemental composition on the Ni-Ti based SMA surfaces. The crater diameter and depth were found to vary with the laser energy levels and lens-to-sample distances. The surface finish and topography were also found to be influenced by the laser parameters. Finally, a suitable range of parameters for improved surface finish and targeted surface modification have been identified for nanosecond laser processing of Nickel-Titanium based SMA.
In-Process Intelligent Inspection of the Specimen Using Machine Vision
Authors: Mahor Adarsh , Yadav Ram Singar 
Published: February 2023

Abstract
Quality control is a crucial component of every manufacturing process. Quality production can be done by removing the defective pieces before reaching the packaging line. Several innovative systems have proven the use of visual input and advanced computer processing to fulfill various production goals during the last several years. Product inspection technologies based on machine vision are extensively researched to increase the quality of the product and save expenses. Computer vision and Deep learning have recently evolved, resulting in powerful data analysis tools with excellent scanning quality and resilience. Authors have attempted in this direction using such a method to detect flaws present in the dimensions of the bottles, which are traveling continually on the conveyor belt. Using pictures collected from the camera, the Yolov5 object detection method is used to localize the bottle in the image. Then, the image is passed for pre-processing, such as image cropping, image gray scaling, and smoothening of the image. The next step of this algorithm uses canny edge detection to detect edges present in the image. The image with detected edges is in the form of a binary image. All the pixels are extracted from this binary image in the form of an array. After performing some mathematical calculations on the output array, the dimensions of the bottle can be determined. The bottles were inspected for any faults in the dimensions in the manufacturing. Any bottles with flaws in the dimensions are discarded and separated from the manufactured bottles. The first step of the algorithm is object detection; here, the model has achieved the mean average precision of nearly 99.5 percent for the confidence threshold set to 50 percent to 95 percent. The following entire algorithm runs in less than 847 milliseconds. Such a high-speed algorithm allows manufacturers to increase and decrease the manufacturing speed according to their needs. This algorithm can check any shape of bottle, and this algorithm is not limited to bottles, but it can also work for any shape of object. As this model is only trained on the images of the bottles, the model cannot instantly work on the other objects, but one can use transfer learning to use this model on different object. This algorithm can also detect defects in multiple objects in the production line containing the manufacturing of multiple objects in the same line. The model can classify the objects from the production line and can also be used to classify them wherever required.
Impact of Rotor-Stator Rub-Impact on Post-Resonance Backward Whirl Excitation
Authors: Abdul Nasar Rafath , A. AL-Shudeifat Mohammad 
Published: February 2023

Abstract
It has been indicated in the literature to many factors that contribute to faults in rotor dynamical systems such as rubbing impact at stator-rotor contact. Accordingly, the appearance of rubbing impact is investigated here as one of the major factors that could excite the post-resonance backward whirl (Po-BW) phenomena in rotors. Therefore, the effect of rotor-stator rub impact on Po-BW excitation is numerically studied here with a Jeffcott rotor model. Accordingly, vertical and horizontal rotor configurations are considered here with rub-impact. The rubbing between the stator and the rotor is modeled by using both Heaviside function and the exact time calculation during the numerical simulation for comparison and to guarantee whirl results convergence. It is found that at a time step of order 10−6 in the numerical integration both Heaviside function and exact contact time calculations produce similar convergent results. In addition, the obtained numerical simulation results show that the stator-rotor rub-impact is found to excite the Po-BW and affects their recurrence and intensity. Accordingly, the current study provides a more insight to the impact of rotor-stator rubbing on Po-BW excitation. Therefore, the rotor-stator rub-impact is found to be one of the main factors that lead to excite the Po-BW during the rotor transient operation.
Numerical Simulation of Aggregation and Deformation of Red Blood Cells in Microchannels With Different Stenosis Severities
Authors: Elhanafy Ahmed , Abuouf Yasser , Elsagheer Samir , Ookawara Shinichi , Ahmed Mahmoud 
Published: February 2023

Abstract
Numerical simulation of cellular blood flow modeling has attracted many studies in the few recent years due to its importance in determining many macroscopic properties of blood. Additionally, the accurate modeling of blood flow, and hence the diagnosing of many cardiovascular diseases requires a detailed description of the dynamical behavior of individual cells. The aim of this study is to simulate the blood flow in the cellular level to have a better understanding and accurate modeling of blood flow in some cases that are not intensively examined in literature such as the dense suspension of flowing RBCs in microvessel with different degrees of stenosis. The present study is based on an open-source code, Hemocell for modeling blood flow in the cellular level. The lattice Boltzmann method coupled with the immersed boundary method are used to capture the cell deformation and the interaction between plasma forces and cell membrane. The distributions of the RBCs in both radial and axial directions are obtained. The deformation of the cells due to passing through the vessel especially the throat is studied for two cases of stenosis. It is found that the deformation of the cells at the center of the stenosis is higher than the deformation in other regions. Additionally, the increase of the stenosis degree increases the average deformation of the cells. It is observed that a longer time is required for the simulation in the case of 80 % reduction in the diameter.
Detection and Classification of Robotic Manipulator Anomalies Using MLSTM-FCN Models
Authors: Ma Yuliang , Grimmeisen Philipp , Morozov Andrey 
Published: February 2023

Abstract
Errors and failures occur inevitably in modern Cyber-Physical Systems (CPS) due to their structural variability and internal heterogeneity. This can cause economic losses or even hazardous accidents. Currently, deep learning-based anomaly detection methods, e.g., Transformer or LSTM-based detectors, have shown tremendous results in terms of anomaly detection and prevention. However, focusing solely on improving detection performance without classification and interpretation of the detected anomalies is not enough for many industrial scenarios. Instead of only reporting an anomaly, the detection results should be understandable and transparent for the users. The interpretability can provide some guidance and help to identify suitable countermeasures for different types of anomalies.
In this paper, we introduce a Multivariate Long Short Term Memory Fully Convolutional Network (MLSTM-FCN) for anomaly classification based on multivariate time-series data generated from industrial robotic manipulators. Specifically, we investigate several scenarios: no collision, collision with another manipulator, and manually injected sensor faults. We collect time-series data from the simulations of robotics arms using CoppeliaSim software. We feed these data into the MLSTM-FCN model and train it to be a multivariate time-series classifier. The paper presents the simulative case study results that show that the MLSTM-FCN model can efficiently classify different types of anomalies.
Combustion Characteristics of Single Isolated Fuel Droplets of Different Diesel-Biodiesel Blends Derived From Waste Vegetables Oil and Animal Fat
Authors: Parveg A. S. M. Sazzad , Ratner Albert 
Published: February 2023

Abstract
Increasing energy demands due to rapid industrialization and urbanization, stringent emission limits, and depleting sources of conventional fossil fuels urges the scientific community in search of renewable, reliable, cost-effective, and environmentally friendly alternative and sustainable options. Biodiesel has become a center of research initiatives to address these issues as a replacement or a supplement to conventional petroleum-based fossil fuels. Biodiesel derived from waste vegetables oil and animal fat is an interesting solution to face the concerns regarding fossil fuels as well as an effective and environmentally friendly way for the disposal of waste vegetable oil in addition to reusing it for energy production. In the transportation sector, typically biodiesel is used in blends with petroleum-based diesel, and the most common blends are B5 (up to 5% biodiesel) and B20 (up to 20% biodiesel). In this regard, current manuscripts report an experimental study on the combustion characteristics of single isolated fuel droplets of different diesel-biodiesel blends. Five different diesel-biodiesel blends named B5, B10, B15, B20, and B25 were used for the droplet combustion study. Neat diesel (B0) and biodiesel (B100) followed the d2-law of combustion while the blended fuel droplets deviate from the d2-law due to puffing and micro-explosion. Increased combustion rates were observed in blended fuel droplets and the highest increase of around 7% was observed for B15 droplets compared to B0 droplets. There were no significant differences in ignition delay between B0 and blended fuel droplets while B100 fuel droplets showed an increase in ignition delay up to 38% compared to B0 droplets. B10 and B15 fuel droplets showed significant decrease in droplet burning time. Highest decrease in droplet burning time was observed for B15 which was around 8% compared to B0 droplets.
Quantitative Detection of Delaminations in CFRP Composite Plate by Spatial-Frequency-Wavenumber Analysis Based on Laser Ultrasonic Guided Waves
Authors: Liu Zenghua , Liu Xiaoyu , Tian Jiuzhou 
Published: February 2023

Abstract
To comprehensively quantitative assessment of delamination location in CFRP composite plates, a Lamb wave spatial frequency wavenumber imaging method based on laser ultrasonic full-wavefield scanning inspection is proposed in this paper. For a CFRP composite plate specimen containing a delamination, a piezoelectric sensor is arranged to excite a sinusoidal modulation tone-burst signal. A laser transducer is used for pointwise reception to obtain Lamb waves full-wavefield data. Frequency domain filtering were performed on the wavefield signal to obtain single-mode wavefield. Short-space Fourier transform and instantaneous wavenumber analysis were applied to single-mode wavefield signal to obtain a distribution image of Lamb wave spatial wavenumber respectively. At the same time, the Lamb wave dispersion relation in CFRP composite plate is analyzed, and the delamination location is calculated based on this relationship. Finally, it can be seen from the imaging results that instantaneous wavenumber analysis can accurately locate the distance between the delamination and the laser scanning detection surface, but the short-space Fourier transform technology cannot identify the location of defects under the experimental parameters set in this paper.
Exploration in Using the Weibull Distribution for Characterizing Trends in Bearing Failure Operational Changes
Authors: Wescoat Ethan , Bradford Joshua D. , Krugh Matthew , Mears Laine 
Published: February 2023

Abstract
Remaining Useful Life (RUL) is critical to optimizing part life and reducing maintenance costs in a predictive maintenance strategy. Current methods of remaining useful life predictions are significantly dependent on operating conditions and time as input features. However, these features do not fully encompass the variability of real-world operating conditions and notably as the bearing nears failure. This work provides an improved failure representation by exploring the underlying data distribution parameters of a bearing failure dataset generated using the Purposeful Failure Methodology under varying operating conditions and then provides a comparison to the widely used NASA/IMS bearing run-to-failure dataset. Laboratory experiments utilized a bearing test stand to capture failure states for fatigue and contamination failure mode. The fatigue and contamination failure procession is compared to the failed bearings from the NASA Bearing dataset to examine similarities in the underlying data distribution between either dataset. A Weibull distribution is then fitted to both datasets. The resulting distributions exhibit similar trends, dependent on the damage stage. Based on the fitted parameters, a decreasing trend for the Weibull parameters was influenced by the changing speed in the engraving test case with similar trends to the NASA bearing dataset. The resulting understanding of the data distribution parameters will be used to improve the end of RUL calculation by describing the distribution fit that best determines the bearing life modification numbers.
Auxetic Metamaterial Development With Commercial Finite Element Tools
Authors: Corrado Casey , Skelton William , Angilella Alexander , Rosfjord Kristine 
Published: February 2023

Abstract
Metamaterials exhibit unique properties that are often not found in nature, making them advantageous in challenging engineering applications. These materials, however, are extremely difficult and time consuming to design, typically requiring custom algorithm development for a specific application. For metamaterials to be more readily created and implemented, an easily accessible design method that uses commercially available tools is needed. With the integration of optimization packages, commercially available finite element analysis software now presents an opportunity for the constrained design of metamaterials. This work investigates using topology optimization (TO) capabilities within commercial finite element analysis (FEA) software to create a methodology for targeted metamaterial design. This study focuses on auxetic materials, those exhibiting negative Poisson’s ratio, as an example case. An overview of the design process and topology optimization objectives, constraints, and boundary conditions will be provided, as well as a description of the challenges associated with utilizing a commercial FEA method.
Novel Thermal Coating for High-Speed Airplanes
Authors: Satapathy Abinash , Battu Lakshay , Watson Liam , Rajabi Nazanin , Park Jungkyu 
Published: February 2023

Abstract
In comparison to various other materials, carbon fiber, specifically carbon fiber reinforced polymers (CFRP) remains pre-eminent amongst other materials for use on aeronautical systems. Due to its high specific strength (strength-to-weight ratio), CFRP has been able to carry heavy loads while maintaining a lightweight build. This strength and weight efficiency has allowed for commercial airplanes such as the Airbus A350 and the Boeing-787 Dreamliner to greatly outperform common aluminum frame airplanes. Despite its extraordinary strength and light weight efficiency, when influenced by heat resulting from air resistance, CFRP is known to undergo serious degradation that would significantly decrease the effectiveness of the polymers. To prevent this degradation and maintain the strength of the CFRP, thermal protective layers (TPLs) are designed to shield the CFRP from heat exposure. This research is focused on the examination of the effectiveness of TPLs, that are hybrid compositions of epoxy resins and buckypaper (carbon nanotubes) for 3K 2 × 2 twill carbon-fiber, through experimental methods. Experimental thermal analysis of the CFRP is performed at 225 °C for hot plate testing and 650 °C for heat gun testing. The results show that the addition of buckypaper in the thermal protective layer seemed to detect nearly 48°C less heat on average of the four measured intervals in hot plate tests. From heat gun tests, moreover, it was clearly seen that the carbon fiber TPL that contains the epoxy and buckypaper is dominant in terms of heat dispersion. The anisotropic thermal transport property of nanostructured carbon is expected to spread heat accumulated in hot spots efficiently, preventing the heat from being propagated into the CFRP body material. In the near future, the authors will use analytical method and FEA simulations to explain this heat dissipation phenomena.
Preparing Generation Z: Beyond Technologies
Authors: Leão Celina , Alves Anabela C. , Soares Filomena , Silva Vinicius 
Published: February 2023

Abstract
Personal skills such as communication, leadership, teamwork, can be the key factor for differentiation in a technological career. Attending to this, the authors of this paper were motivated to propose a different course (or Curricular Unit, CU) to students of Higher Education level. In this way, this paper describes the aim, objectives, methodology in the creation of an elective CU, called “Preparing Generation Z: beyond technologies (Z-Tec)”. Z-Tec, lectured for the first time in the academic year of 2021–2022, allows student to acquire skills that promote a conscious and reflective transition to the job market, namely: to recognize the importance of career preparation and the skills needed for this preparation, to integrate enhancing strategies as a starting point for career management, to recognize such strategies as facilitators for personal, professional and social success, and to identify and critically apply tools that allow to objectively analyze and decide the professional future. Z-Tec puts on active learning methodologies based on practical exercises, debates, seminars and reflective activities. The results discussed are based on the students’ perceptions gathered at the beginning of each semester, on the several activities that students developed and on the students’ feedback gathered at the end of each semester. A total of 62 students from different areas of knowledge (Engineering, Economy, to Sociology and Public Administration) were positively engaged.