bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Influence of Magnetic Vector Potential in Electroplasticity
Authors: Grimm Tyler J. , Mears Laine 
Published: February 2023

Abstract
The application of an electric current in situ with plastic deformation has been shown to produce non-thermal effects, which often present as a reduction in flow stress. This phenomenon is known as electroplasticity. Despite over 60 years of research, the mechanism(s) responsible for this behavior remains unknown.
The magnetic vector potential is explored herein as a possible mechanism that may contribute towards electroplasticity. This effect is explored experimentally by isolating the potentials experienced during a common electrically-assisted tension/compression test through use of a solenoid. It was discovered that the vector potential does not affect the flow stress or elongation in several materials that were tested. This conclusions eliminates one possible mechanism of the electroplastic effect.
Acoustically Induced Vibration Mitigation
Authors: Arjunan Raj , Swindell Rob , Ghosh Arindam , Karczub Denis , Horder Nick , Mann J. Adin 
Published: February 2023

Abstract
Reduction of the fatigue risk presented by acoustically induced vibration in flare header systems using mitigations that either reduce dynamic stress concentration effects or the level of vibration are of considerable interest to designers and plant operators. Assessments of the relative performance of different types of pipe fittings in reducing dynamic stress levels are presented based on the evaluation of data from full-scale laboratory tests of a pressure-relief system. A modal-analysis based finite-element methodology is also developed so that predictions may be extended to other piping arrangements that vary in thickness, size or connection type. The pipe fittings considered in the test are Pipet®, fabricated tee (Stub-on arrangement), sockolet (small-bore branch connections only), full-wrap reinforced fabricated Tee and Sweepolet®. For the finite-element method reducing tee connection is considered in addition. The test system produced significant levels of both turbulent-induced vibration (FIV) and acoustically induced vibration (AIV), which required differentiation of stress evaluations for the low-frequency FIV region and the mid-to-high frequency AIV region. The relative performance of mitigations (through selection of the type of pipe fitting) was found to be particularly relevant in the low-frequency FIV region. The reductions in dynamic stress and vibration of small-bore branch connections from installation of clamped bracing are also presented. The results show that the use of reducing Tees and full-wrap reinforcements for Stub-on connections for tailpipe and sub-header branch connections provide significant mitigation of dynamic stress and improvement of fatigue life over the use of Pipet® and Stub-on fittings. However, for the Sweepolet® connection which was expected to provide similar improvement the benefits are not fully realized in the 10S configuration.
Recovering From Cyber-Manufacturing Attacks by Reinforcement Learning
Authors: Prasad Romesh , Swanson Matthew K. , Moon Young 
Published: February 2023

Abstract
A Cyber-Manufacturing systems (CMS) is an integration of informational and operational entities that are synchronized with manufacturing processes to increase productivity. However, this integration enlarges the scope for cyber attackers to intrude manufacturing processes, which are called cyber-manufacturing attacks. They can have significant impacts on physical operations within a CMS, such as shutting down plants, production interruption, premature failure of products, and fatal accidents. Although research activities in this emerging problem have been increased recently, existing research has been limited to detection and prevention solutions. However, these strategies cannot ensure a continuous function of an attacked CMS. To ensure continuous functioning of a CMS, a robust recovery strategy must be developed and employed. Current research in recovery has been limited to feedback controllers with an assumption of a complete knowledge of a system model. To overcome this limitation, a recovery agent augmented by reinforcement learning was developed. This is to utilize the ability of reinforcement learning to handle sequential decisions and to proceed even without a complete knowledge of a system model. A virtual environment for recovery agents has been developed to assist efforts needed to obtain sample data, experiment various scenarios, and explore with reinforcement learning. Two cyber-manufacturing attack scenarios have been developed: (i) spoofing a stepper motor controlling additive manufacturing processes, (ii) disrupting the sequence of the pick and place robot. The recovery agent takes random actions by exploring its environment and receives rewards from the actions. After many iterations, it learns proper actions to take.
Model Predictive Control of the Transparent Omnidirectional Locomotion Compensator With a Simple Prediction of a Walking Fire Ant
Authors: Le Kevin , Morgan Todd , Plank Riley , Penick Clint , Kim Dal Hyung 
Published: February 2023

Abstract
Automation in studying the behavior of small animals or insects is a key to finding behavior stereotypes. In this paper, we have demonstrated the Model Predictive Control (MPC) for locomotion compensator for a walking fire ant to reduce error based on the prediction of an ant’s movement. We have implemented the MPC with the simple trajectory prediction of a walking ant, which generates optimal control input to minimize the error on current and future positions. In our Transparent Omnidirectional Locomotion Compensator (TOLC), the ant freely walks without tethering atop a transparent acrylic sphere. Using the near-infrared (NIR) camera underneath the transparent sphere and a motorized omnidirectional wheel system, we can reorient the sphere to maintain the ant’s position on top of the sphere. The adaptive MPC method was implemented in the TOLC, while the reference trajectory is predicted using the moving average of the past history movement. The results show significantly reduced error with the predicted ant positions, and compared to the method without prediction of future positions of the walking ant. The average position error using the MPC methods with prediction is 0.413 mm, improved 48.0% from that without prediction (0.794 mm). Furthermore, the average position while tracking moves toward the target center using the MPC control with prediction.
Development of an Artificial Neural Network (ANN) Constitutive Model for Mechanical Metamaterials
Authors: Hussain Arif , Sakhaei Amir Hosein , Shafiee Mahmood 
Published: February 2023

Abstract
Metamaterials are a group of materials with artificial engineered structures that exhibits customized properties which are not naturally available in other materials. To accelerate the computational analysis of components made from metamaterials that helps novel engineering product design process, it is crucial to develop an accurate and robust model for these materials in macroscale. The classical approach to drive a material model in continuum level is based on development of a phenomenological model to represent the physical behaviour of the material. However, this approach has specific limitations in including the effect of tailoring design parameters in the model which is a key element for metamaterials. In this study, we have proposed an artificial neural network (ANN) constitutive model to represent the macroscale mechanical behaviour of metamaterials in three-dimensional domain. Because of its extraordinary capabilities to stimulate computational performance in identifying and constructing prospective microstructure model for mechanical metamaterials, the proposed ANN constitutive model provides intriguing advantages over conventional models. The ANN constitutive model has been trained based on strain-stress data which is obtained from microscale simulation of 3D cubic lattice structure under various loading conditions. The trained material model is then validated by measuring the accuracy of material behaviour prediction.
Selective Patterns for Circular Dimples Distribution As a Means to Enhance Structural Mechanical Response of Tubular Components
Authors: Sakonder Cuneyt , Paredes Marcelo 
Published: February 2023

Abstract
Bioinspired materials and structures subjected to external loads tend to exhibit unprecedented mechanical behavior, especially impact loads and extreme quasi-static forces. It has been observed that certain bioinspired structures may withstand excessive compressive loads with little or moderately inelastic response due to their complex materials’ architecture that extends at various length scales. On the other hand, nature inspired patterns may be an alternative to improve mechanical response, especially in the form of selective notches/dimples distribution over the surface of tubular members. The main goal behind this idea seeks to overturn the deleterious effects of circular notches or dimples on tubular components’ strength due to interaction of stress concentration fields generated at the hole’edges. By selecting an optimized pattern of dimples distribution along the tubular component, an interesting behavior can be observed, as the interaction of stress concentrations tend to cancel out each other rather than add them up and bring the structural component to premature failure. In this exploratory study, a numerical investigation is carried out on notched tubular members models with surface circular dimples, strategically distributed following bioinspired patterns typically observed in nature such as hexagonal, honeycomb and net patterns. Additionally, this study pursues to gain understanding on the possible beneficial effects that this type of selective dimples distribution might bring in stressed components not only made of metallic alloys, but also biological materials such as blood vessels replacement nonsynthetic, decellularized graft whose mechanical response can be greatly enhanced.
Performance of Flat-Tube Louvered-Fin Automotive Evaporator With R1234yf
Authors: Gurudatt H. M. , Narasimham G. S. V. L. , Sadashive Gowda B. 
Published: February 2023

Abstract
Following the Kyoto Protocol and the more recent Kigali agreement, Hydrofluoroolefins (HFOs) are considered as the low global warming drop-in or substitute refrigerants for hydrofluorocarbons (HFCs) which have high global warming potential. The HFO R1234yf gained significant importance as a replacement for R134a in automobile air conditioning. In this context, the performance of a two-slab automotive evaporator with R1234yf numerical simulation is reported in this paper. The simulation is conducted by considering the heat transfer from air to the outside wetted surface consisting of louvered fins and tube wall, from there to the inside tube wall, and from there to the bulk of the boiling refrigerant inside the tube. The combined effect of heat and mass transfer from air to the wetted surface is described by the enthalpy potential method. For the two-phase and superheating regions suitable heat transfer correlations are employed. The results show that the refrigerant side heat transfer coefficient increases with increase in vapour quality up to around 80% and then decreases with further increase in the vapour quality. The major contribution to the cooling capacity is the latent heat abstraction during the flow boiling process occurring inside the tube. The temperatures of the condensate water film surface and the inner and outer tube wall surfaces are nearer to the bulk temperature of the refrigerant because of the high heat transfer coefficient on the refrigerant side. Results are also presented for the refrigerant side pressure drop and the evaporator exit air temperature and humidity ratio.
Estimating Combined Impact of Urban Heat Island Effect and Climate Change on Cooling Requirements of Tall Residential Buildings in Hot-Humid Locations
Authors: Kamal Athar , Hassan Ibrahim , Wang Liangzhou (Leon) , Rahman Mohammad Azizur 
Published: February 2023

Abstract
Climate change estimates are critical in developing long-term solutions to the dwelling problems that we currently face. This study combines the impact of climate change and the urban heat island effect to study the outcomes of future weather conditions on the cooling of tall residential buildings in hot and humid climates. For the year 2050, we calculate the impact of urban characteristics through the urban weather generator and climate change through the world weather gen tool on the micro-climatic condition of a district in a newly constructed city near Doha, Qatar, the Lusail City. A total of four weather files are compared to the weather data gathered from the established weather station in the city (two for the year 2020 and three for the year 2050). Results reveal that once the open weather map file has been processed through the urban weather generator (UWG) first and then the climate change model, the MAE increases to 3.30, and the RMSE goes to 3.8 with a maximum deviation of 11.4°c occurring. If the process is done the other way around, the climate change model is applied first, and then the UWG file is applied, the MAE of 3.46 is with RMSE of 3.94 with a maximum deviation of 11.3°c occurring. The impact of these weather files is then assessed on a tall residential building in Lusail. A significant increase of 777197 kwh or 20% is seen in the openweather map file that has been processed first through the climate change model and then through the urban weather generator (as compared to the rural weather file); an increase of 739983 kwh or 19% is seen in the openweather map file that has been processed first through the UWG and then through the climate change model; finally close to 22.6 percent increase or 874088 kwh is seen in the openweather map file that has been processed first through the climate change model and then through the climate change model.
Variable Kinematic Shell Finite Elements for Dynamic Analyses of Rotating Structures
Authors: Filippi Matteo , Azzara Rodolfo , Carrera Erasmo 
Published: February 2023

Abstract
This paper makes use of low- and high-fidelity finite plate and shell elements for vibrational analyses of various rotating structures. The two-dimensional models, developed with the Carrera Unified Formulation (CUF), are obtained by adopting two different kinematics expansions, namely the Lagrange-like (LE) and Taylor-like (TE) polynomials. The possibility of selecting different kinematic expansions enables various configurations such as composite, reinforced and sandwich structures to be considered. The equations of motion of rotors with arbitrarily shaped cross-sections are derived with respect to a co-rotating reference system. All contributions induced by the rotational speed (the Coriolis force, the spin-softening and the stress-stiffening terms) for both spinning and blade-like configurations are included in the equations of motion. Furthermore, the linearized and geometrically nonlinear approaches are presented to compute the speed-induced stiffening effect. Numerical simulations are performed on a swept-tip blade and a shallow shell to validate the formulation. Comparisons with solutions available in the literature demonstrated the accuracy of the approach.
Video Verification of an Instrumented Mouthguard in American Collegiate Men’s Rugby
Authors: Fetchko Travis , Boudreau Grace , Roach Megan , Cameron Kenneth , Rooks Tyler 
Published: February 2023

Abstract
There are few published studies investigating wearable head impact sensors which focus on rugby. Devices mounted externally on the head can shift or be fully removed during normal play. Investigation into the use of instrumented mouthguards in rugby has recently begun. However, different devices and their associated software have varying reliability in helmeted vs. non-helmeted sports which must be verified. This study implemented the Impact Monitor Mouthguard device in male American collegiate rugby players, and used video-verification to assess the reliability of the device’s validity software. We found a Positive Predictive Value of 97.0%, which compares favorably to previously published values for this device. We believe this is the first study to analyze the accuracy of sensor events rejected by the software, which resulted in a Negative Predictive Value of 97.0%.
An Investigation on the Aerodynamics, Vibrations, and Control of an Electroactive Membrane
Authors: Ojo Oluwatosin , Pulok Mohammed Khairul Habib , Su Ji , Chakravarty Uttam K. 
Published: February 2023

Abstract
Dielectric elastomer membrane(s) are smart material(s) that produce large actuation strains. They are also a class of electroactive polymers that function as actuators and sensors to convert and sense electrical signals to mechanical deformation and vice versa. Unique properties, such as flexibility, lightweight, and the ability to have an electrical field-induced deformation, make the dielectric elastomer membrane an ideal solution to the challenges faced by many applications, including the wings of unmanned aerial vehicles. This study aims to analyze the modal characteristics and aerodynamics of the dielectric elastomer membrane both computationally and experimentally. An electroactive membrane, VHB 4910, is considered the specimen, and the conductive material of carbon grease is used as an insulator on both surfaces of the membrane. Finite element models are developed to compute the resonance frequencies and mode shapes. The computational results of the modal analysis are validated using a closed-loop vibration testing experimental arrangement and digital image correlation system. Aerodynamic analyses are conducted using a wind-tunnel setup with a data acquisition system. A shape sensitivity study is also performed to see how five different shapes of a constant area affect the aerodynamics and vibrations of the membrane. The modal characteristics are controlled by adjusting the prestretch, true stress, and applied voltages. The natural frequencies decrease as the applied voltage increases. The aerodynamic coefficients increase with the angle of attack up to a particular range.
Books Trimmer Industrial Machine Knives Diagnosis: A Condition-Based Maintenance Strategy Through Vibration Monitoring via Novelty Detection
Authors: Viale Luca , Daga Alessandro Paolo , Garibaldi Luigi , Caronia Salvatore , Ronchi Ilaria 
Published: February 2023

Abstract
In recent years, Artificial Intelligence (AI) is ever more exploited in all the scientific and industrial fields and is allowing significant developments in mechanical engineering too. An emblematic contribution was given in terms of safety and reliability since Machine Learning (ML) techniques permitted the monitoring and the prediction of the state of health of machinery, allowing the adoption of predictive maintenance strategies. In fact, data-driven models — based on acquisitions — attract considerable interest both thanks to its theoretical and application development. The evolution of diagnostic techniques is oriented towards Condition-Based Maintenance (CBM) strategies, thus allowing improvements in terms of safety enhancement, cost reduction and increased performances. This paper proposes the development and implementation of a diagnostic/prognostic tool applied to an automated books trimmer industrial machine, implementing condition monitoring by means of accelerometers which can be integrated into a Supervisory Control And Data Acquisition (SCADA) system. Given its use, the core components of this production line are three knives, subjected to significant impulsive forces. Therefore, the target of the work is to infer the wear of these three knives, as they are critical elements of the machinery and have a high impact on the quality of the final product. The project was carried out in collaboration with Tecnau — an industry-leading company — which made it possible to conduct experimentation and data acquisition on their machinery. An appropriate Design Of Experiments (DOE) and the use of inferential statistical techniques — such as the ANalysis Of VAriance (ANOVA) and the identification of significant effects — applied to the multivariate dataset allowed recognizing the most relevant features for Novelty Detection (ND). Both the Linear Discriminant Analysis (LDA) and the k-Nearest Neighbors (kNN) method permitted to correctly distinguish the patterns representing the health conditions of the machinery, classifying the data in the reduced multidimensional space according to the final product quality. The results obtained in terms of accuracy are very positive and promising. This means that the developed method is able to successfully identify the state of health of the blade in spite of varying functioning parameters (book thickness and size, paper type and characteristics) and operating conditions. The algorithm speed and its integration into the industrial line make a real-time condition-based maintenance strategy possible. This diagnostic method is suitable for applications oriented to the paradigm of Industry 4.0 and the digitalization of the industrial sector, which can be integrated with the Internet of Things (IoT) and cloud systems.
Hybrid Solver for the Radiative Transport Equation in Nongray Combustion Gases
Authors: Jajal Nehal , Mazumder Sandip 
Published: February 2023

Abstract
The absorption coefficient of molecular gases exhibits strong oscillations with wavelength. Thus, solution of the Radiative Transfer Equation (RTE) in a medium comprised of combustion gases require repeated solution of the gray RTE, rendering such calculations computationally very expensive. Popular methods to solve the RTE include the Finite Angle Method (FAM) and the Spherical Harmonics Method (PN). FAM, the finite-angle variant of the discrete ordinates method, produces accurate solutions when used with sufficient angular resolution. However, it has high computational cost. The lowest order Spherical Harmonics Method (P1) requires solution of a single elliptic partial differential equation and is very efficient in comparison to FAM. It yields accurate solutions for fairly isotropic intensity fields. In this study, a Hybrid solver for the nongray RTE is proposed that capitalizes upon the efficiency of the P1 method and the accuracy of the FAM. Depending on the spectral (or band) optical thickness, an appropriate solution method is chosen. The objective is to determine optimal parameters for selecting the solution method that can provide the best compromise between accuracy and computational cost. Using the statistical narrow band (SNB) model for carbon dioxide and water vapor, the nongray radiative transfer equation is solved in inhomogeneous media enclosed in multidimensional enclosures. Two different approaches — cut-off and filter optical thickness — are investigated for selecting the solution method. Several problems, both two-dimensional and three-dimensional, and with and without coupling to other modes of heat transfer are considered. The filter approach was found to be the best choice for prediction of the radiative source, while the cut-off approach was found to be the best for prediction of wall radiative heat fluxes.