bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling and Simulation of Convective Heat Transfer Caused by a Rotating Disk
Authors: Ruiz David , Mueller Donald , Abu-Mulaweh Hosni 
Published: January 2022

Abstract
In this study, computational fluid dynamics (CFD) software is used to model and simulate a smooth disk rotating in a still fluid. The primary quantity of interest is the convective heat transfer coefficient. Laminar, transition, and turbulent flow regimes are considered. To ensure that the physical characteristics of the situation are properly captured, the velocity and temperature profiles of the fluid are qualitatively and quantitatively compared to results reported in the literature. By analyzing the velocity and temperature profiles, an estimate for the proper size of the computational domain within the CFD software is obtained. If the computational domain is too small, the velocity and temperature profiles are affected; hence, the calculation of the convective heat transfer coefficient is influenced by the size of the computational domain.
Two methods — the global rotation method (GRM) and the local rotation (or sliding) method (LRM) — are used to obtain results for the convective heat transfer coefficient. The global rotation method involves conversion of the specified angular velocity into a mass-distributed force. The local rotation method involves the creation of a secondary body that rotates. The secondary body can cause inaccuracies to appear when discretizing the domain. These inaccuracies cause the local rotation method to be less predictable than the global rotation method.
An extensive and systematic verification and validation study of the two methods is performed with validation achieved by comparing the calculated values to published correlations and measured results. Both methods demonstrate agreement with the expected heat transfer coefficient value by maintaining a difference of less than 3% for low angular velocities. At higher angular speeds, the global rotation method maintains less than a 3% difference, once an appropriate mesh is established and the turbulent parameters are set correctly.
Over the entire range of parameters considered, the global rotation method is best suited to model and simulate a singular disk rotating in still air. The global rotation method does not require the introduction of a secondary body and yields predictable and uniform convergence to published values as the mesh size is reduced.
Relationships between accuracy, grid size, and computational effort are reported. Recommended laminar and turbulent parameter settings are discussed. The results of this fundamental study provide insight and guidance into the proper modeling and simulation of both low-speed and high-speed rotating machinery and equipment.
Constitutive Modeling of Viscoelastic Photo-Adaptable Thermally Activated Shape Memory Polymers
Authors: Prasad Aayush , Moon Swapnil , Cui Fangda , Rao I. J. 
Published: January 2022

Abstract
Shape memory polymer (SMPs) are a class of smart materials that have the ability to retain multiple temporary shapes and recover original shapes as they exhibit deformation in response to external stimuli. The shape change in these polymers can be triggered using different stimuli like temperature, light, water, pH, magnetism, and their mechanisms can be easily altered. SMPs are capable of displaying multiple temporary and one permanent shape by either creating a multiphase system or by undergoing a very broad thermal transition. SMPs and their composites are also easy to manufacture, and complex structures can be 3D printed with multimaterials by controlling various geometric parameters. Their applications are diverse and found in various fields such as transportation, energy generation, deployable structures, clothing, healthcare, etc. It is therefore important to model the behavior of such a material. This work discusses the behavior of a thermally activated subclass of SMPs in which the temporary shape is fixed by a crystalline phase and a light activated subclass of SMPs in which the temporary shape is fixed by photo-reversible covalent crosslinks. Light activated SMPs (LASMPs) ease the temperature limitations faced by thermally activated SMPs while making remote activation possible, which opens an even wider range of applications. The thermo-mechanical behavior of such copolymers is simulated using a framework based on the theory of multiple natural configurations while incorporating the viscoelastic effects in a rate type model. The model is applied to different boundary value problems related to homogeneous deformations such as uniaxial extension of dual and triple shape memory polymers under controlled stress and strain conditions. The results are consistent with experimental observations and show how the complicated thermo-mechanical behavior and shape memory effect (SME) are influenced by parameters like temperature, external stress, crystallinity and bond formation.
High Strain Rate Impact on Carbon Nanostructures Using Molecular Dynamics Simulations
Authors: Prates Matheus , Durr Ian , Park Jungkyu , Espitia Giovanny , Peterson Braden 
Published: January 2022

Abstract
In the present study, we researched the behavior of graphene experiencing high strain rate impacts by employing molecular dynamics simulations. Graphene with various thicknesses are selected for the study. A silver particle is designed to impact these carbon nanostructures with pre-specified speeds. The amount of energy absorbed during impacting graphene is calculated from the change in the kinetic energy of the silver particle before and after the impact. Graphene is shown to have excellent flexibility and its structural integrity is retained under a high strain rate impact. At an impact velocity of 4 km/s, a single layer of graphene absorbed 6.5 keV without any damage in the structure. The impact energy used to fracture graphene is shown to increase linearly with an increase in the thickness of graphene; the absorbed energy during breaking seven layers of graphene was 23 keV when the impact velocity was 10 km/s. It was also found that temperature does not affect the impact energy required to break a graphene sheet. The results obtained in the present research study will be used to accelerate the development of futuristic strong light-weight materials for military applications.
Applied Machine Learning Method to Predict Crack Propagation Path in Polycrystalline Graphene Sheet
Authors: Elapolu Mohan S. R. , Shishir Md. Imrul Reza , Tabarraei Alireza 
Published: January 2022

Abstract
A machine learning model is developed to predict the crack propagation path in polycrystalline graphene sheets. The dataset used for training the machine learning (ML) model is obtained from the molecular dynamics (MD) simulations. A training set of 700 samples has been used to train the ML model. Each training sample consists of an input image which contains the information of the initial configuration of precracked polycrystalline graphene sheet and an output image which contains the information of crack path. After training, the ML model can predict the crack propagation path in polycrystalline graphene sheet instantaneously, thus avoiding the computational costs involved with MD simulations.
Stochastic Analysis of the Interphase Thickness and Modulus in Carbon Fiber Reinforced Polymer Matrix Composites
Authors: Yekani Fard Masoud , Raji Brian 
Published: January 2022

Abstract
Atomic Force Microscopy based Peak Force Quantitative Nanomechanics Mapping (PFQNM) technique with the high lateral resolution was used for the characterization of the interphase in polymer matrix composites (PMC) at the nanoscale. Details of the calibration parameters include probe stiffness, real spring constant, tip radius, tapping force, deformation level, synchronous distance, drive3 amplitude sensitivity (DDS3), and deflection sensitivity for heterogeneous PMC, were discussed. Reduced modulus, adhesion, and deformation results were used to examine the interphase zone thickness and properties. The symmetric composite laminate plates have a thickness of ∼8mm. Specimens from the subsurface (∼400 μm from the surface) and the depth (∼ 4mm from the surface) were considered. The polymer matrix composite samples have been exposed to heat and humidity. AFM Multimode 8, scanner type J with a maximum scanning window of 125μm × 125μm, was used. The Derjaguin, Muller, Toropov (DMT) equation was applied to the retract curve to calculate the elastic modulus. The Weibull model was used to examine material properties’ statistical distribution. The scale parameter and the Weibull modulus (shape parameter) of the distribution characterize the data’s scattering. A higher Weibull modulus means a steeper function and a lower dispersion. The Weibull analysis results illustrated the effects of the local moisture content on the interphase thickness and the reduced modulus.
Additive Manufacturing With Ceramics
Authors: Campanella Jesse , Figueroa-Cecco Ivan , Fujinaka Ian , Sasek Adam , Nowicki Margaret , Vargas-Gonzalez Lionel , Ku Nicholas 
Published: January 2022

Abstract
The purpose of this project was to modify and improve an off-the-shelf 3D printer, previously modified by Army Research Laboratory, to print a ceramic slurry of B4C and SiC. Initial iterations suggest improvement in mixedness of the ceramic composite is desirable to create a more homogenous blended microstructure. The initial design utilized a basic auger shape designed to move the slurry along, but it did not effectively mix the two slurries while printing. Various auger designs were also modeled in SolidWorks, matching the rheological properties of the ceramic slurries engaged in the print, to determine influence of geometric modifications on auger performance. Experimental augers were printed using a Formlabs 2 stereolithography printer, with clear photopolymer resin, and tested on the modified 3D printer. Modeling predictions were verified through the experimental print allowing for rapid analysis of geometric modifications without requiring an experimental print for each iteration. The group examined the homogeneity of the mixture under a 10x and then 40x microscope. A point counting method, like that used in traditional volume fraction analysis, was employed to evaluate mixedness.
Deriving Thermal Model From Data by Sparse Identification Based on Physical Laws
Authors: Suzuki Tomoyuki , Kano Akira , Hirohata Kenji 
Published: January 2022

Abstract
In this paper, we propose a method for creating a reduced-order model (ROM) for temperature prediction that can be applied to nonlinear time-variant systems. Our nonlinear time-variant ROM is an extension of sparse identification of nonlinear dynamical systems, first proposed in 2016. Three machine learning methods are developed for automatically deriving a thermal network model from time series data. Link relationships between temperature nodes and parameter settings, such as thermal resistance and heat capacity, are automatically inferred by machine learning. Because the proposed model targets phenomena that can be represented as a thermal network model, it can deal with forced convection with velocity as a variable. The model can also handle natural convection and radiation, where thermal resistance is a function of temperature. The model can be created using a very small amount of time series data. Unlike black-box AI, the proposed model is easy to interpret; in other words, it enables us to understand the heat transfer process. Furthermore, because it is based on a physical model, it has high prediction accuracy when extrapolated. The effectiveness of the proposed method is demonstrated using the results of thermo-fluid analysis for an air-cooled power module. In addition, because the proposed method can be created using a very small amount of time series data, has high extrapolation accuracy, and is easy to interpret, it is expected not only that design parameters can be fine-tuned and actual loads can be taken into account, but also that condition-based maintenance can be realized through real-time simulation.
Fluid-Structure Interaction of Slender Biofilaments at Low Reynolds Numbers
Authors: Mortazavi Mehrad , Ayyaswamy Venkattraman , Gopinath Arvind , Goyal Sachin 
Published: January 2022

Abstract
Active filamentous organelles such as cilia and flagella oscillate due to the interplay between activity, elasticity, and viscous hydrodynamic drag. The presence of no-slip boundaries also impacts the viscous drag forces on the filament. Recent efforts to develop low Reynolds numbers synthetic swimmers and mixers that mimic the ciliary dynamics have used effective elastic filaments that are animated. The instabilities underlying the spatiotemporal dynamics of such biomimetic filaments are dominated equally by elasticity and fluid-solid viscous interactions. Predicting ensuing patterns requires robust computational models that can capture both large-amplitude elastic deformation of the filaments and associated long-ranged hydrodynamic interactions. To address this coupled elastohydrodynamic problem, we develop a composite framework that combines a computational rod model valid for slender filaments and slender body theory (SBT) that accounts for hydrodynamic interactions. The presence of no-slip boundaries is accounted for by using a wall-corrected slender body theory (W-SBT). We analyze the accuracy of the slender body formulations and compare them to solutions obtained via computational fluid dynamic solvers. SBT and W-SBT are found to be computationally faster than other hydrodynamic models; however, they may not provide accurate solutions for small aspect ratio filaments. The fluid-structure interaction model we present here, provides a starting point to computationally investigate the movements of natural and biomimetic cilia and flagella in the vicinity of plane walls.
Research on the Application of Acoustic Emission Technology in the Health Monitoring of the Reducers on Amusement Devices
Authors: Zhang Junjiao , Shen Gongtian , Shen Yongna , Yuan Yilin , Zhang Wenjun , Li Juanjuan 
Published: January 2022

Abstract
The reducer is a very important mechanical part of large-scale rotating amusement devices such as the popular big pendulum. It constantly adjusts the speed during the operation of the device and bears different loads. Due to it is difficult to disassemble after its installation, there is no effective method for the detection or online monitoring. Acoustic emission (AE) technology is an effective tool for condition monitoring and fault diagnosis of rotating machinery. AE tests for the reducer were studied in the lab. The effects of speed change and load change on the AE signals of the reducer are respectively obtained. The filed test on reducers of a big pendulum in the amusement park was carried out. The AE characteristics of the reducer with the movement of the pendulum were analyzed. The results show that AE technology will play an important role in the health monitoring of the reducer on amusement devices.
Finite Element Analysis on Plastic Collapse Behavior of Topology-Optimized Cellular Structure Subject to Compressive Loading
Authors: Takase Yuta , Kawano Takahiro , Kojima Tomohisa , Tsuji Tomoaki 
Published: January 2022

Abstract
The cellular structure is an assembly of cells. It may have excellent properties such as lightweight, high rigidity, and high energy absorption capacity with artificially manufactured cellular structure. However, guidelines for designing cellular structures with desired properties have not been established. This study aims to present the design guidelines for cellular structures with high energy absorption capacity. The unit cell was designed by topology optimization with the objective function of stiffness maximization. The compressive behaviors of the topology-optimized cellular structure and BCC, FCC lattice structures were investigated by carrying out the compression analysis by finite element method (FEM). A full model and a simplified model with a reduced number of cells with periodic boundary conditions were built for the analysis. It was confirmed that the use of the simplified model could significantly reduce the analysis cost. From the analysis results, it was shown that the deformation modes of the struts of the cell were different in optimized structure and BCC, FCC lattice structures. Finally, the specific energy absorption and the specific strength of each structure were evaluated. The optimized shape had high energy absorption capacity and specific strength compared with the BCC and FCC lattice structures. Further study is necessary to examine the objective function and boundary conditions in topology optimization to design cellular structures with larger energy absorption capacity by controlling the stress-strain relationships.
Use of LiDAR for Negative Obstacle Detection: A Thorough Review
Authors: Guerrero-Bañales Luis Daniel , Hernández-Bautista Ignacio , López-Parra Marcelo , Ricardo-Torres Osiris 
Published: January 2022

Abstract
Negative obstacles for field autonomous land vehicles refer to potholes, ditches, cliffs, pits, or any type of obstacles that are on the road but not in a visible way, which bring risks both to the vehicles or potential passengers and even to the environments where autonomous land vehicles are moving along. These negative obstacles can cause severe damage to autonomous land vehicles, from damage to the vehicle’s suspension, rollovers, or even loss of the autonomous vehicle. Obstacle detection is the first step to avoid any risk, and it is extremely important to be able to warn of nearby obstacles, to avoid any type of danger that may arise. In recent years several articles have been published on the different types of hazards or obstacles and different methods of avoiding them. The authors report on ways to better understand the environment so that autonomous land vehicles stay out of harm’s way. Some of the dangers could be, the collision with another vehicle, hitting a pedestrian, not recognizing the traffic signs on the road, leaving the planned routes or lanes, or not braking when they detect an obstacle. The use of image recognition using different types of cameras, as well as the use of ultrasonic sensors and Light Detection and Ranging (LiDAR) sensors, or the combination of some or all of the sensors is widely used in the field of autonomous land vehicles. Most of this research work has been carried out in positive obstacle detection; that is, obstacles that are above the road. However, the detection of negative obstacles and their avoidance remains less explored. Due to this, an exhaustive review is made of the state of the art of use of LiDAR sensors in the detection of negative obstacles applied in autonomous land vehicles and the different techniques that have been used to recognize and classify the different types of potholes, ditches, pits.
Tolerance Analysis of Contacting Assembly Parts Based on Parametric Space Envelope
Authors: Nie Jiaqi , Luo Chen , Zhou Yijun 
Published: January 2022

Abstract
Tolerance is an important part of design and manufacturing. Applying right level of tolerance is vital for manufacturers to gain a competitive edge. This paper proposes a new method to analyze the geometric tolerance for two mating parts for compliant assembly. Under proposal, the two mating parts are represented in a purpose-built parametric space and the manufacturing deviation of the two parts is linked to movements of a compact set of control points. The contact state of the two parts is formulated as an optimization problem by minimizing the distance between the two parts under non-negative constraints (i.e. the two parts are not embedded during the assembly process). By solving the optimization problem, the translation distance along the assembly direction can be obtained to ensure that the two parts are in non-penetration contacts. The assembly tolerance is analyzed in the contact state with the idea of selective assembly. The effectiveness of the method is verified through a case study on assembling two plane metal sheets. The proposed method has significance on formulating geometric tolerances for compliant assembly.
Design and Energy Flow Management of Hybrid Renewable Energy System
Authors: Amini Reza , Davani Abbasali A. , Pourgol Mohamad Mohammad 
Published: January 2022

Abstract
Wind and solar energies are promising renewable energy technologies, in which hybrid renewable energy systems are gained much attention in remote area locations. The present study proposes the design and energy flow management of stand-alone hybrid wind and solar energy systems. Fuel cells and batteries are used as backup resources, so it ensures the load is unceasingly provided. An electrolyzer is used to generate hydrogen from excess energy requirements. First, Mathematical modeling of hybrid system components, including photovoltaics, wind turbines, fuel cells, batteries, and electrolyzers, is provided. Hence, we have developed a novel energy flow management algorithm, which intelligently controls the energy flow management system using a fuzzy logic control system. We have compared the performance of the novel energy management system with the conventional approach. Our novel approach will prevent these systems from being hit, and system upgrades will be enhanced during startup. In the conventional power management system, the voltage overshoot of the on-off controller is 425 V. At the same time, the fuzzy logic control reaches 405 V. The controller’s on-off time is 31.1 seconds, but this is 0.041 for the fuzzy logic controller, which is much more stable.
Fostering Student Engagement and Learning in Online and Flex Delivered Thermodynamics Courses via Two-Stage Concept Inventory Quizzes in Time of COVID
Authors: Sadeghizadeh Zahra 
Published: January 2022

Abstract
The COVID-19 pandemic has required many engineering programs to design and deliver their courses in more flexible formats, including courses that involve teaching students who are participating remotely and face-to-face at the same time (flex courses). However, in the meantime, it is essential to ensure that students are remaining actively engaged in the learning process and that their remote presence is not negatively affecting their conceptual understating of the course materials. The objective of this study was to use concept inventory in the format of a two-stage quiz to investigate how this format impacts students’ performance and engagement in both online and flex delivery modes. During two-stage quizzes, students first work on conceptual problems individually and then collaborates in groups that are remote or hybrid. This approach applied for two sections of an Engineering Thermodynamics class, one delivered in flex dual-mode format and one fully online. It was interesting to see how the level of confidence and students’ perception to answer conceptual questions including misconceptions, change as they interact in different forms of teams. The statistical analysis shows there is no significant difference between online and flex mode results, however students confidence level in answering concept-based questions increases significantly in group answers for both modalities. Additionally, an anonymous survey was developed to receive student’s perceptions and feedback about their learning experience.