bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Physics-Based Data-Driven Approach for Modeling of Environmental Degradation in Elastomers
Authors: Ghaderi Aref , Chen Yang , Dargazany Roozbeh 
Published: February 2023

Abstract
Elastomers are now commonly used in a number of industries, including aerospace, structure, transportation, shipbuilding, and automotive, due to their excellent workability, formability, and flexibility. During their activity, elastomers are subjected to harsh environmental conditions, which decreases their resilience. False predictions made early in their lives can have major financial and environmental implications. Elastomers’ performance and properties, such as strength, durability, and density, are influenced by chemical changes in these materials, known as degradation, which occurs over time. This process can alter the morphology of a polymer matrix as well as cause chain scission and cross-linking, resulting in different behaviors than that of the unaged material. To demonstrate the effect of thermaloxidative aging on the mechanical behavior of elastomers, several experimental and theoretical models have been proposed. In view of the large volume of experimental data available on micro-structural evolution in the course of aging, we propose a physics-based data-driven approach to overcome the shortcomings of both phenomenological and micro-mechanical models. This work presents a novel thermodynamically consistent, multiagent machine-learned model for predicting the constitutive behavior of cross-linked elastomers during environmental aging, such as thermo-oxidative and hydrolytic aging for various states of deformation. Single mechanism degradation changes the polymer matrix over time where it is causing chain scission, reduction of cross-links, and morphology change. To capture the idealized Mullins effect and permanent set due to the effect of single aging mechanisms on nonlinear mechanical responses of elastomers, we propose a data-driven model for simulating inelastic elements in a polymer matrix. By using a sequential order reduction, we were able to reduce the 3D stress-strain tensor mapping problem to a small number of super-constrained 1D mapping problems. To systematically classify such mapping problems into a few categories, an assembly of multiple replicated conditional neural network learning agents (L-agents) is used based on our recent work. Each category is represented by a different type of agent. The effect of deformation history, aging time, and aging temperature is captured by this model. The model is validated using a broad collection of data, ranging from our experimental results to data from the literature. In addition, thermodynamic consistency and frame independence are investigated. The most significant achievements of this model are its precision, simplicity, and prediction of inelasticity under various states of deformation. The model’s accuracy and simplicity make it a good option for commercial and industrial applications. Conveniently, due to the model modular nature, it can be expanded in the future to include viscoelasticity and non-isotropic formation for better precision.
Improving the Yield of Biodiesel Production Using Waste Vegetable Oil Considering the Free Fatty Acid Content
Authors: Ityokumbul Igbax Saanyol , Swartling Daniel , ElSawy Ahmed , Idem Stephen 
Published: February 2023

Abstract
This paper investigates the use of waste vegetable oil (WVO) for production of biodiesel. The goal of this study was to explore the improvement of biodiesel production to achieve high yields. Different oil streams, including virgin canola oil and WVO, were used as the raw material for the transesterification processes. These oils had different fatty acid contents as a result of environmental or previous processing conditions. The main objective of this study was to assess the impact of free fatty acid (FFA) content on the resulting yield. In addition, the yield was influenced by production parameters such as reaction time, reaction temperature, molar/volume ratios of oil to alcohol, catalyst amount, and mechanical mixing. This was accomplished by automating the biodiesel production from WVO, thereby achieving improved processing and requiring minimal direct human involvement. A biodiesel production apparatus was developed with a Raspberry Pi 3 microcomputer to control the process. It was shown that the particular choice of these process parameters depended on the particular oil type. This research used mixtures of virgin and waste vegetable oils at different volume ratios (oil to alcohol) of 4:1, 6:1, and 8:1, which was determined by the FFA content of the oil. In addition to mechanical mixing, ultrasonication rated at 500W, 20kHz was used to enhance mixing by adding 450 kJ to the process, thereby reducing both the processing time and the amount of methoxide needed to perform a base-catalyzed transesterification. The production temperature was held within the range of 50–65°C. This research demonstrated that optimal yield depends on temperature, catalyst concentration, FFA content of the oil, and the energy introduced by sonication. A 96% yield was achieved with the following parameters: an oil to methanol volume ratio of 6:1, 0.6% weight concentration of catalyst (NaOH) at 6.25 g, and FFA values of approximately 5%. It was determined that the proposed system can produce acceptable quality biodiesel.
A Green and Sustainable Approach for Carbon Steel Acidic Corrosion Inhibition Using Agricultural Waste: Experimental and Theoretical Studies
Authors: Sanni Omotayo , Ren Jianwei , Jen Tien-Chien 
Published: February 2023

Abstract
Carbon steel corrosion in hydrochloric acid media is a huge challenge in the chemical industry; hence, creating green and more efficient inhibitors is an urgent task. Furthermore, the increasing amount of solid wastes arising from the municipality and other sources and its disposal consequence has been a major economic and environmental problem. Hence, in this research, the effect of agricultural waste as a natural inhibitor on the carbon steel dissolution in one molar hydrochloric acid solution was studied using electrochemical and surface techniques. The obtained results showed that the corrosion protection potential of the agricultural waste increases with the agricultural waste concentration and an optimum value of 95.92% was achieved at 500 ppm concentration. The waste adsorption on the metallic surface followed the Langmuir adsorption isotherm. The electrochemical impedance spectroscopy test shows that the inhibitor inhibits the metal against corrosion by getting adhered to the carbon steel surface. The scanning electron microscopy analysis proves that in the presence of the inhibitor, the surface of the carbon steel becomes smooth owing to the inhibitive films formed on the metal surface. The results demonstrated that the agricultural waste extract is an excellent green and eco-friendly corrosion inhibitor.
Modeling and Verification of Firing Dynamics of a Multiple Launch Rocket System
Authors: Aydın Berk , Ünver Hakkı Özgür 
Published: February 2023

Abstract
Multiple rocket launcher systems have great strategic importance in today’s defense systems. Therefore, the development and the quality of these strategically important systems are among the priorities of defense industry companies. The quality of the multiple launcher rocket systems is twofold. 1) Firing the ammunition with the appropriate time interval within the correct trajectories, 2) leaving the firing location quickly after completing the mission. In this study, stabilizer support legs were not used to increase vehicle mobility. The dynamics of a multiple rocket launch vehicle are modeled using rigid bodies and elastic elements with eight degrees of freedom in total. Since a 90-degree firing was performed relative to the longitudinal direction, half-vehicle modeling has been developed in the lateral direction of the vehicle. Firing tests had been executed without a support leg over a Multiple Launch Rocket System. During the firing, measurements were taken with a 3-axis accelerometer and gyroscope over the elevation and azimuth platforms. In addition, LPTs in vertical and lateral directions are placed on the superstructure. With these LPTs, the data obtained from the 3-axis accelerometer and gyroscope on the azimuth platform have been confirmed. The model parameters, stiffness/damping parameters of tires, suspensions, and hydraulic actuator, have been obtained using initial test results with MATLAB™ Parameter Estimator toolbox. The model’s accuracy has been verified with a second firing test result.
Control of Flight Vehicles From the Perspective of Non-Holonomic Constraint Manifold Dynamics: Quadrotor Application
Authors: Dahal Ambika P. , Barhorst Alan A. 
Published: February 2023

Abstract
In this paper, we address the problem of flight path planning and control. We approach the problem from the perspective of non-holonomic generalized momenta. We first build a desired minimum Jerk trajectory that we use as a momentum manifold constraint for the vehicle. We then develop a trajectory reference model of the flight vehicle that evolves exactly on the flight path as a constraint, as if the vehicle were a bead on a wire in the generalized coordinate configuration space. This model uses non-holonomic generalized momenta and position and orientation variables as states, the model is of order 2N – M, where N is the full dimension of the vehicle model and M is the number of manifold constraints imposed. These momenta models are canonical without Lagrange Multipliers. Next, we build a full 2N order model of the flight vehicle and design an LQR controller linearized about nominal path independent flight. We then implement this control in the full flight model and use as the reference state trajectory the constrained momentum states computed on the desired flight path. We allow inflight disturbances. We demonstrate that this approach provides good performance for a Quadrotor flight vehicle.
Pipeline Leak Detection and Localization Based on Advanced Signal Processing and Negative Pressure Wave Analysis
Authors: Li Weiming 
Published: February 2023

Abstract
Pipeline monitoring and leak detection are critical for safe and economical operation as well as preventative maintenance in water and oil industry. They also provide environmental protection from crude oil emission or theft. Leak detection and localization play a key role in the overall integrity monitoring of a pipeline system especially for long residential water pipelines and midstream crude pipelines. Operational data such as fluid flow and pressure data are often utilized in many physics and computation-based leak detection and localization methods. However, noise in both flow and pressure affects recognition of actual leak pressure drop and results in false leak alarm and inaccurate leakage localization. In this paper a total variation regularized numerical differentiation (TVRegDiff) algorithm is used to estimate derivatives from noisy fluid flow and pressure data. Then possible leak events from both fluid flow data and pressure data are obtained by examining these derivatives against corresponding control limit lines. Customized parameter criteria of flow and operation activities are used to effectively filter flow and operation events from possible leak events. Therefore, earliest leak occurrence time and pressure meters can be identified. Finally, negative pressure wave (NPW) analysis is combined with the leak recognition to compute and locate leakage. Negative pressure wave methods are based on the principle that a leak will cause a sudden pressure alteration as well as a decrease in fluid flow speed which will result in an instantaneous pressure drop and speed variation along the pipeline. As the instantaneous pressure drop occurs, it generates a negative pressure wave starting at the leakage position and propagates with certain speeds towards both the upstream and downstream ends of the pipeline section. Depending on the leakage position from the two ends and actual negative pressure wave velocities towards upstream and downstream there are time sequence of the pressure wave arriving at both ends. The lapse of time arrival and negative pressure wave velocities are then used to calculate the actual leakage position within the pipeline section. A field leak case study indicates that actual leak pressure drop is correctly captured and pipeline leakage can be accurately located. The accuracy of leak localization is theoretically dependent on the pressure and flow meter frequency. With widely accepted industry standards for pressure devices used in industry applications it is proved to be a practical, efficient and accurate leak detection and localization method. This method can also be applied to not only residential water pipelines but crude oil pipelines.
Thermo-Mechanical Properties of SiC-Mineral Binder Composites for Space Applications
Authors: Chandrasekaran Sujithra , El-Ghannam Ahmed , Monroe James A. , Xu Chengying 
Published: February 2023

Abstract
Due to its excellent stiffness, thermal stability and low density, silicon carbide (SiC) is an excellent candidate for fabrication of lightweight substrates for space mirrors in telescopes and satellites. However, the strong Si-C covalent bond induces high thermal stability and mechanical strength which makes it difficult to manufacture dense SiC. Other ceramic mirror materials such as Cordierite (CO720) by Kyocera® and Spodumene (ZERODUR®) by Schott® are characterized by their light weight, near zero thermal expansion coefficient and excellent thermal properties. However, mirrors made of cordierite or spodumene have relatively low stiffness and unsatisfactory thermal conductivity. We hypothesize that composites made of SiC-Cordierite and SiC-Spodumene can serve as better mirror substrates characterized by high stiffness, high thermal conductivity and improved thermomechanical stability. The present study reports on the synthesis and characterization of SiC-Cordierite (SiC-Cord) and SiC-Spodumene (SiC-Spod) using powder metallurgy method. The densification and thermomechanical stability of the SiC-mineral composites are enhanced by a novel in situ mineralization mechanism at the interface between the SiC and mineral binders between 800 °C and 1200 °C. The densities of SiC-Cord and SiC-Spod composites were 2.74 g/cc and 2.61 g/cc, respectively, while the thermal conductivities were 6.737 W/m. K and 3.281 W/m. K, respectively. Polishing the SiC-Cord with SiC grit numbers 400–1200 and diamond/silica slurry resulted in a mirror surface with an average roughness of 2.32 nm on SiC particles. The nano indentation stiffness of the polished SiC-Cordierite composite measured 239.9 ± 20.6 GPa. The stiffness of the SiC-Cord composite is superior to that of pure cordierite (140 GPa) or Zerodur (80 GPa). The average Vickers hardness of SiC-Cordierite was 8.12 ± 4.5 GPa which was superior to that of Zerodur (6.08 GPa) and comparable to that of pure cordierite (8–8.5 GPa). The composite samples demonstrated high thermal shock resistance as indicated by their comparable compressive strength and dimensional stability before and after quenching from 1200 °C to room temperature in water. Taken altogether, the superior thermomechanical properties of SiC-Cordierite and SiC-Spodumene suggest their suitability for mirrors in space-based telescopes.
Research on Variation Law of Rolling Force of Three-Roll Skew Rolling Hollow Axle
Authors: Wang Jitai , Shu Xuedao , Xu Haijie , Ye Caoqi , Xia Yingxiang , Zhang Song 
Published: February 2023

Abstract
In the research of part forming, forming force is one of the most concerned factors. To explore the variation law of rolling force in the process of three-roll skew rolling (TRSR) hollow axle, the process of TRSR hollow axle is tested and simulated in this paper. First, the working principle of TRSR hollow axle is described; Second, taking the hollow axle of LZ50 steel as the research object, according to the actual performance of TRSR mill, the blank and rolling process parameters are selected, and the finite element model is established; Third, combined experiment and numerical simulation, the evolution laws of the rolling force are obtained by exploring the forming process of TRSR hollow axles; Fourth, the evaluation standard of rolling force is determined on the basis of the evolution law of rolling force, combined with the typical process parameters, and the orthogonal test was carried out. The results show that the simulated evolution law of rolling force is basically consistent with the experimental result. The evolution curve is opposite to the surface shape of the rolled piece. Besides, the rolling force increases gradually with time. Through orthogonal test, the influence subsequence of process parameters on rolling force and relationship between them are determined. In addition, the quantitative relationship between process parameters and rolling force is established.
Design and Fabrication of a Test Rig for a New Approach on Health Monitoring of Roller Bearings Using Acoustic Emission
Authors: Bjarkason Heimir Rafn , Asgeirsson Saethor , Unnthorsson Runar 
Published: February 2023

Abstract
This article presents the design, equipment selection and implementation of a test rig using non-destructive evaluation (NDE) for rolling element bearings used in Vertical Axis Wind Turbines (VAWT), designed and manufactured by Icewind in Iceland. The design is outlined along with the description and preliminary results of a pilot test of the rig. Features of Acoustic emission waves are used for the health monitoring and fault detection. The proposed method of using AE wave segments to construct a surface plot of features is presented. The usage of a high precision encoder to map the acoustic wave over the rotation of the bearing is proposed and demonstrated. Using surface feature plots and the mapped location in the rotation is an intuitive way to characterise the AE signal for condition monitoring, and allows for the possibility to locate defects in bearings effectively providing additional information to time frequency analysis such as Fourier transformations on the acoustic signal.
Part Metrology and Defect Detection Using Machine Vision
Authors: Granitto Anthony , Chauhan Vedang 
Published: February 2023

Abstract
This paper focuses on the detection, classification & sorting of good and defective blade/automotive fuses through the utilization of Machine Vision Inspection (MVI). Fuses are an electrical safety device found in most vehicles and serve to protect their wiring and electrical devices against overcurrent. These small-size components are produced in large quantities, through a process involving the encasing of two metal prongs connected by a thin metal strip inside a plastic housing. Due to the nature of working with delicate metals and plastic, during the manufacturing process multiple defects can occur. The purpose of the project was to detect, classify and sort good and defective fuses, while performing part metrology solely on good fuses. Using NI Vision Builder Software, an image acquisition algorithm was written to generate a database of images for all the fuse classes. With this database, further algorithms were constructed to identify each class of fuse as it progressed along the conveyor. Utilizing vision inspection techniques such as pattern matching and distance measurement, the system was able to properly classify the fuses in the database. If the system determined the fuse to be defective, an I/O signal from the smart camera activated a pneumatic system that would remove the fuse. However, when the system classified a good fuse, it was allowed to continue along the conveyor and be collected after part metrology was performed by another algorithm. A graphical user interface (GUI) displayed these inspection statistics in realtime. This project was successful in completing all the defined goals for the system and proved to have an object classification accuracy of over 90%. This MVI system has the proper algorithms to be used in tandem with a high-speed smart camera, for adaptation into a real-world manufacturing application.
Relations of Radial Vibration of the Arterial Wall to Pulsatile Parameters in Blood Flow for Extraction of Arterial Indices
Authors: Hao Zhili 
Published: February 2023

Abstract
In light of the utility of radial vibration of the arterial wall for clinical values, this paper presents a theoretical study on the relations of radial vibration of the arterial wall to pulsatile parameters in blood flow. Pulse wave propagation in an artery is formulated as a combination of the governing equations of blood flow and the arterial wall and no-slip conditions at the blood-wall interface. A free wave propagation analysis is conducted on the problem to obtain the wave velocity and the theoretical expressions for blood flow rate and arterial radial displacement in terms of pulsatile pressure. With the harmonics of a pulse signal, mathematical relations of radial vibration of the arterial wall to pulsatile parameters in blood flow are derived under two conditions: without and with wave reflection. These mathematical relations identify the assumptions for the simplified relations employed in the utility of radial vibration of the arterial wall for extraction of arterial indices. With the arterial wall treated as a unit-mass vibration system, these simplified relations are utilized for extraction of arterial indices from radial vibration of the arterial wall. Some other aspects of radial vibration of the arterial wall are further discussed.
Finite Element-Incorporated Multiscale Micromechanics Modelling of Vehicle Crashworthiness for 3-Phases Hybrid Fibres Reinforced Graphene Nano-Composite Materials
Authors: Elmasry Ahmed , Azoti Wiyao , Elmarakbi Ahmed 
Published: February 2023

Abstract
Crashworthiness focuses on the safety and protection of occupants. In addition, not only do energy absorbing members have to absorb sufficient collision energy, but the vehicle structure must be lightweight to improve power consumption. Nevertheless, estimating vehicle crashworthiness is experimentally expensive and time-consuming. Explicit nonlinear finite element analysis (FEA) is probably the most commonly used modelling technique to evaluate vehicle behaviour during a crash. However, commercial FE software still lacks efficient explicit modelling of lightweight graphene-based nano-composites. This work develops a simple approach to studying 3-phases hybrid fibres/graphene nanoplatelets-reinforced polymer matrix composites through multiscale modelling. Thermo-elasto-plastic response of composites is considered. The heterogeneous material problem is resolved through a kinematic integral equation. A linear spring model LSM is adopted to account for the interfacial behaviour in a modified Mori-Tanaka scheme The non-linear response is established in the framework of the J2 plasticity flow rule coupled with the “Lemaitre-Chaboche” ductile damage. The considered material is short glass -fibres/graphene nanoplatelet/Polyamide-Nylon 6 composite. The model is implemented as a UMAT within LS-DYNA® software for automotive crashworthiness applications. The results highlight the crash performance’s impact, incorporating the influence of the interfacial behaviour and material damage on the peak crash force and specific energy absorption SEA.