bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of Insect Locomotion to Control the Transparent Omnidirectional Locomotion Compensator (TOLC)
Authors: Rahman Kaushik , Ehme Daniel , Ackerman Matthew , Penick Clint , Kim Dal Hyung 
Published: February 2024

Abstract
This paper presents prediction schemes of a walking insect for model predictive control (MPC) method for the Transparent Omnidirectional Locomotion Compensator (TOLC). The MPC method uses an average velocity vector or moving average (MV) of the previous gaiting cycle to estimate the future trajectory of the walking insect. Integration of the current heading angle (MCH) of the insect or the mean of the heading angles (MMH) of previous gaiting cycle with the existing MV scheme improves the overall prediction of insect locomotion to control the TOLC. The results of the experiment and simulation demonstrate that when the MMH is integrated with the MV in predicting the future insect trajectory, it yielded the lowest average distance error of 0.28mm. Additionally, the proposed methods effectively compensated the small error that occurred due to the oscillation of the insect body while gaiting. This claim was verified when the average distance errors for MCH and MMH were 0.28mm and 0.25mm respectively in a straight locomotion. In contrast, the average distance error for MV scheme was 0.34mm for a straight motion. The method proposed in this study provides a highly accurate and precise approach to tracking insect behavior, with potential applications in areas such as insect behavior research and the design of insect-inspired robots. The adoption of this method may lead to the development of novel control strategies for complex locomotion systems, with a wide range of potential uses across various fields.
Excavators Using Adjustable Linkages
Authors: Kotte Manoj Kumar , Zhou Hong 
Published: February 2024

Abstract
Excavators or backhoes are construction machines that are employed to create foundations, holes or trenches by moving or digging dirt through their attached end buckets. Excavators have been widely used for various construction or other projects. Tracked excavators are suitable for heavy-duty projects or on harsh terrain conditions because of their outstanding traction, excellent stability and high digging depth. Wheeled ones are preferred for inner-city or urban projects due to their dexterous maneuverability in narrow space and low impact to the contact ground. An excavator arm consists of bucket, stick and boom that are connected serially by R joints. The arm is pivoted to the excavator’s house that rotates with respect to its undercarriage. An excavator performs its tasks through its arm motion together with its rotatable house and locomotive undercarriage. The three R joints of an excavator arm have parallel axes and form its arm motion plane. They are driven by their corresponding hydraulic cylinders. The moving trajectories and orientations of the bucket of an excavator for digging or other tasks are generated from the three driving cylinder linkages of its arm. The reachable workspace of the bucket on its arm motion plane depend on the dimensions of the three arm linkages. The workspace has no flexibility if the dimensions of the three arm linkages of an excavator are fixed, which limits the applications of the excavator. In order for an excavating machine to have workspace flexibility, one or more motion related parameters of its three arm linkages have to be adjustable. This research aims at improving operation flexibility of excavators through using adjustable arm linkages. Excavators without and with adjustable parameters are analyzed and simulated. Their performances are evaluated and compared. The results from this research will provide some useful guidelines for developing excavating machines.
Electric and Pneumatic Regulation of a Dual Planetary Gearing System Using a Programmable Logic Controller
Authors: Achord Gillian , Hackett Kyle , Burlton Cahil , Azzouz Salim 
Published: February 2024

Abstract
The purpose of this project is to create a new lab apparatus for the Machine Element Design course at the McCoy School of Engineering at Midwestern State University. The apparatus is designed so that future students can visualize and understand how a car transmission system works, specifically in regards to the concepts of mechanical advantage, gear ratios and efficiency. The transmission control system utilizes pneumatic-mechanical clutches and electro-mechanical brakes to realize one of the six possible gear ratios. The system is automated by a Programmable Logic Controller (PLC) that is able to shift the transmission into the different gear configurations and allow the students to determine the mechanical advantage and the efficiency of each configuration.
To achieve the stated goals, necessary modifications have been made to a transmission built and modified by previous senior design groups. The current team of senior design students used the SolidWorks CAD software to design a new clutching and braking system that works more effectively. The team also created a new PLC program. The PLC controls the pneumatic cylinders for the clutch system, the linear actuators for the braking system, and it reads and displays the torque readings from two transducers. The PLC is used in conjunction with a Human Machine Interface (HMI). The HMI has been programmed so that the user may select a gear configuration simply by tapping a digital button on the touch screen.
Implementation of an Artificial Intelligence (AI) Instructional Support System in a Virtual Reality (VR) Thermal-Fluids Laboratory
Authors: Ayre Dennis , Dougherty Carolyn , Zhao Yitong 
Published: February 2024

Abstract
Physical laboratory experiments have long been the cornerstone of higher education, providing future engineers practical real-life experience invaluable to their careers. However, demand for laboratory time has exceeded physical capabilities. Virtual reality (VR) labs have proven to retain many benefits of attending physical labs while also providing significant advantages only available in a VR environment. Previously, our group had developed a pilot VR lab that replicated six (6) unique thermal-fluids lab experiments developed using the Unity game engine. One of the VR labs was tested in a thermal-fluid mechanics laboratory class with favorable results, but students highlighted the need for additional assistance within the VR simulation.
In response to this testing, we have incorporated an artificial intelligence (AI) assistant to aid students within the VR environment by developing an interaction model. Utilizing the Generative Pre-trained Transformer 4 (GPT-4) large language model (LLM) and augmented context retrieval, the AI assistant can provide reliable instruction and troubleshoot errors while students conduct the lab procedure to provide an experience similar to a real-life lab assistant. The updated VR lab was tested in two laboratory classes and while the overall tone of student response to an AI-powered assistant was excitement and enthusiasm, observations and other recorded data show that students are currently unsure of how to utilize this new technology, which will help guide future refinement of AI components within the VR environment.
Multiscale Surface Force Models for Adhesive Metasurfaces
Authors: Heyes Corrisa R. , Brown Joseph J. 
Published: February 2024

Abstract
This work advances small-scale surface adhesion modeling, motivated by recent advancements in adhesive metamaterial surfaces, also known as metasurfaces. Specifically, with microfabrication of Mechanical Interlocking Structure (MIS) metasurfaces onto a substrate, micro and nano-scale interlocking features can be used to produce mechanical bonding. This allows two similarly fabricated surfaces to form a press-fit mechanical connection in the absence of chemical adhesives. Design and optimization of nano-scale MIS for application in 2nd level electronics packaging could replace current techniques integrating chips and chiplets for improvements in assembly processing, temperature tolerance, and accommodation of thermal expansion mismatch. Robust modeling of the physical contact behavior of MIS surfaces allows for investigation the importance of scaling effects in contact performance by modeling interaction behavior prior to subcomponent assembly.
Improvement of Screw Compressor Performance by Rotor Profile Modification to Reduce Mechanical Losses
Authors: Patil Sumit , Abdan Suraj , Asati Neeraj , Stosic Nikola , Kovacevic Ahmed 
Published: February 2024

Abstract
A mathematical model has been developed to increase the efficiency of oil injected twin screw compressors by improving their rotor profiles. Unlike those currently in use, based purely on geometric considerations, it includes estimates of mechanical losses, mainly due to oil drag, with the aim of minimising them, by use of homotopy procedures. The manufacture of such rotors is only minimally more expensive than those with a conventional N Profile and it has been experimentally demonstrated that by their use, compressor efficiencies can be improved by 1.5–2.5%. Moreover, the scope of these procedures may possibly have a wider range of use in applications concerned with the optimisation of rotor profile shape and size.
A Three-Dimensional Numerical Investigation of Taylor Cone Jets Instabilities Using VOF Method
Authors: Cândido Sílvio , Páscoa José Carlos 
Published: February 2024

Abstract
Taylor cone liquid jets occurs when a conductive liquid is placed on a capillary nozzle and a strong electric field is applied. The electric field causes the surface of the droplet to deform into a conical shape, and a liquid jet is ejected from the tip of the cone. This phenomenon has a wide range of applications, such as in inkjet printing, drug delivery, and electrohydrodynamic propulsion. An understanding of the underlying physics of the Taylor cone jet is essential for optimizing the performance of devices that utilize this phenomenon. Computational fluid dynamics (CFD) has become a powerful tool for studying the Taylor cone jet, and in this paper, we propose the utilization of a full three-dimensional model to study the complete dynamics of the Taylor cone jet. These electrohydrodynamic jets are a method to accomplish the controlled emission of microdroplets, with applications from constructing nanofibers to micro-propulsion. For the numerical computations, we use the interIsoFoam solver on OpenFOAM, which resolves an immiscible two-phase flow, and coupled it with a transport equation for the electric charges as well the simplified version of the Maxwell equations for an electrostatic field. The advection equation of the phase fraction is solved by a geometric Volume-Of-Fluid (VOF). Moreover, the hydrody-namic momentum equation incorporates electrically generated body forces using the Maxwell Stress Tensor (MST). While axisymmetric simulations are computationally less expensive, they fail to capture an important behavior of this type of jet, such as the whipping effect and the tiny droplets emitted during the receding of the jet emission cycle. In contrast, the three-dimensional simulations used in this study offer a more accurate representation of the physics involved in the jet formation process, including the formation of instabilities and the resulting complex jet shapes. As we show in our results the droplets are radially scattered on the target collector due to the formation of the ionic wind, which we also show the three-dimensional structures. The current study begins with the numerical validation of the Taylor cone formation, by comparing the cone shape with the experimental results of the literature. Then simulations were performed for different electric potentials and inlet flow rates, which showed that the stable window is narrowed by the applied electric potential. The results revealed that the instability of the jet is due to the concentration of the electric charges, which led to a breakup of the jet into droplets, in the direction of the electric field. Overall, this study emphasizes the value of using three-dimensional numerical simulations to study Taylor cone jet instabilities because they provide a more accurate depiction of the physics at play and can offer useful information for optimizing Taylor cones jet-using equipment like inkjet printers and electrospray systems.
Graphics Processing Units’ Accelerated Navier-Stokes Solvers for Unstructured Meshes: A Literature Review
Authors: Morris Christopher , Mwaura Njiru , Schneider David , Tabish FNU , Carpenter Duncan , Clark Nathan , Sandip Anjali 
Published: February 2024

Abstract
Recent advances in graphics processing units (GPUs) computational hardware have provided opportunities to develop large-scale numerical models with complex geometric configurations at reduced run time for wide-ranging applications, including computational fluid dynamics. However, utilizing the GPU hardware at its maximum capacity remains challenging. There is a need to develop numerical solution algorithms to alleviate the above-mentioned bottleneck. This study reviews recent developments in GPU-based numerical solution algorithms for incompressible Navier-Stokes equations and unstructured meshes. This literature review aims to promote the creation and development of robust large-scale complex geometry numerical models with applications, including but not limited to computational fluid dynamics.
Design Optimization Framework for Uniform Stress Distribution of Mechanical Metamaterials
Authors: Dutta Shammo , Patiballa Sree Kalyan 
Published: February 2024

Abstract
Mechanical metamaterials have gained considerable interest because of their enhanced mechanical properties, such as being lightweight, having high energy absorption, and having high resistance to fracture and indentation. The macroscopic elastic properties of mechanical materials are governed by their microstructural geometry. Despite their advantages, attaining microstructures with evenly distributed stresses for improved load-bearing ability remains a challenge. Furthermore, employing stress constraints in tandem with numerical homogenization in structural optimization schemes has been time-intensive and complex. This paper presents a design optimization framework for metamaterial designs with uniformly distributed stresses using a bioinspired maximum material utilization (MMU) metric. The material microstructures can be size optimized by maximizing the MMU metric to attain designs with uniform stress distributions. The proposed design optimization involves two sequential steps. The first step involves the conceptual design, using a load flow technique and insights from the strain energy-based homogenization method to design material microstructures. Once we obtain a conceptual solution, we perform size optimization on the material microstructures to maximize the MMU metric. We test our optimization method on two planar auxetic metamaterials — (a) negative Poisson’s ratio microstructures with low shear (NPLS) and (b) negative Poisson’s ratio microstructures with high shear (NPHS). The optimized designs attained uniformly distributed stress levels throughout their topology at the microstructural and material levels. We showcase the efficacy of the proposed design methodology with numerical simulations and experiments. This study paves the way for computationally inexpensive, insightful, stress-based design optimization of metamaterials.
Peridynamic Micromechanics of Composites: Opportunities and Prospects
Authors: Buryachenko Valeriy A. 
Published: February 2024

Abstract
Due to the identical operator form of the linear general integral equation (GIE) proposed for both local micromechanics (LM) and peridynamic micromechanics (PM) of composite materials (CM), the methods of LM have easily recast into the following PM methods:
• Fast Fourier transform (FFT) method,
• Transformation field analysis (TFA),
• Estimation of effective energy-based criteria,
• Effective behavior of CM due to the body force with a compact support,
• Laminate theory.
Experimental Comparison of Model-Free Vibration Control Based on Virtual Controlled Object and Model-Based Control: Robustness to Characteristic Changes in Actual Controlled Object
Authors: Yonezawa Ansei , Yonezawa Heisei , Kajiwara Itsuro 
Published: February 2024

Abstract
Model-free active vibration control based on a virtual controlled object (VCO) has attracted a great deal of attention due to its simplicity. This study experimentally compares VCO-based model-free vibration control with model-based control in terms of the robustness to characteristic changes in an actual controlled object. The VCO is designed so as to achieve model-free vibration suppression in the designated frequency band. A state equation for designing a model-free vibration controller is constructed using only the actuator model and the VCO. The VCO-based model-free controller is designed based on the mixed H2/H∞ synthesis for the state equation. The model-based mixed H2/H∞ controller is designed based on the mathematical model of a both ends supported plate (BESP). The VCO-based and model-based controllers are tuned through vibration control experiment so that both controllers provide the same vibration reduction effects for the BESP. Then these controllers are applied to a vibration control experiment for a cantilever plate which is totally different from the BESP. As a result, the VCO-controller exhibits a good vibration suppression for the cantilever while the model-based one totally fails, revealing the advantage of the VCO-approach over the model-based strategy in the viewpoint of the robustness.
Experiment and Characterization of Temperature Dependent Dynamic Properties of Graphite Magnetorheological Grease
Authors: Dong Jiqiang , Mao Runsong , Wang Huixing , Wang Jiong 
Published: February 2024

Abstract
Magnetorheological grease (MRG) is an intelligent material with continuous, rapid, and reversible changes in rheological properties under the action of an applied magnetic field. Graphite is often incorporated into magnetorheological (MR) materials as an additive to increase their shear yield stress. However, the effect of temperature effects on GMRG has not been reported yet, which is a fundamental step for engineering applications. To investigate the effect of graphite additive proportion and temperature on graphite magnetorheological grease (GMRG), GMRGs with five different ratios of graphite were prepared. Through strain amplitude experiments and frequency experiments, the present work investigates the dynamic properties of graphite magnetorheological grease at different temperatures and magnetic field strengths. The results of strain experiments show that the relative MR effect of GMRG increases with the increase in temperature, which proves that GMRG has good dynamic properties under high-temperature working conditions. The frequency experiments show that GMRG exhibits more elasticity than viscosity. Finally, a modified model for the variation of storage modulus with temperature is proposed by combining the magnetically coupled polariton model with the classical Arrhenius equation. The relationship between the storage modulus and the temperature is predicted. This paper is of generalized significance for the application of graphite magnetorheological grease.
Feature Importance and Uncertainty Quantification of Machine Learning Model in Materials Science
Authors: Liu Zhichen , Singh Akash , Li Yumeng 
Published: February 2024

Abstract
Machine learning has emerged as a powerful tool in material science for novel materials discovery and development. Specifically, interatomic force field potentials have been developed using machine learning to perform reliable molecular dynamics (MD) simulations with comparable accuracy to first principle calculations but a fraction of computational cost. However, there is lack of systematic study to evaluate the uncertainty and computational efficiency of the machine learning potentials. Adopting the Behler-Parrinello approach and artificial neutral network, this paper presents a study to investigate how the features, i.e. the descriptors of the atomic environments, impact the fidelity of machine learning potentials through Shapley value analysis, enables us to design atomic features for developing machine learning potentials with balanced accuracy and efficiency. Through Shapley value analysis, feature importance is evaluated, and an informed feature dropping strategy is developed to understand how the dimension of features affect the performance of machine learning potentials, providing insights into the design and development of machine learning potentials for reliable and efficient MD simulations.
An Innovative and Novel Aluminum Metal Microsphere Production and Deposition Method Using a Pulsed DC Cold Plasma Process
Authors: Almandoz Rebecca , Fletcher Robert W. , Ziegelbauer Joseph 
Published: February 2024

Abstract
Metal microspheres have numerous applications including sintering, heat transfer fluids, electromagnetic fluids, catalysis and electrical components. We have now successfully produced aluminum metal microspheres using a novel method by means of a pulsed DC cold plasma process. There are two types of plasmas: hot plasma, 10,000–100,000 K, and cold plasmas with temperatures slightly above ambient room temperature. Cold plasma temperature is as high as hot plasmas, but the temperature of the neutral species is approximately ambient temperature. Cold plasma can operate in a vacuum, partial vacuum, or atmospheric conditions and can be used for surface modifications and material depositions applications. Its application to metal microsphere production, however, prior to our efforts presented here, has been undocumented. In this primarily experimental work, we review a new, innovative, and novel metal microsphere production method leveraging cold (atmospheric pressure) plasma. Nitrogen was the ionized gas and a high-purity aluminum wire source was used to produce the aluminum metal microspheres, which were simultaneously deposited onto a copper foil substrate. Repeatable depositions of discreet microspheres on to the substrate are possible. Particle adhesion occurs from the molten metal cooling on the substrate surface. Optimal process parameters were found at a pulse cycle time value of 40% using deposition durations of two minutes. Although the particle deposition was not uniform, partial size distributions using this process are repeatable with over 50% of the deposited particles between 0–0.8 μm in diameter. The primary advantage of this deposition process is that it can be performed in open-air at atmospheric pressures, lending itself to a continuous deposition process.