bluuebunny/crossref_metadata_2025 huggingface dataset:
A Three-Dimensional Numerical Investigation of Taylor Cone Jets Instabilities Using VOF Method
Authors: Cândido Sílvio , Páscoa José Carlos
Published: February 2024

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

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

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

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

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

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

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

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.
The Impact of Indoor Environment on Engineering Students’ Inhibition Control Ability
Authors: Mobaraki-Omoumi Mehri , Ahad Md Tanvir , Kittur Javeed , Siddique Zahed
Published: February 2024

Inhibition control is one of the executive functions identified as the process by which goals influence prepotent response tendency. Most of the engineering courses include problem solving activities, and it has been proven that cognitive inhibition abilities improve students’ performance. So, understanding the factors that can enhance interference control skills is highly valuable in education.

The Stroop task was designed to investigate interference control by evaluating how incongruent conditions can increase response time (RT), called the Stroop effect. In this study, we investigate the impact of indoor temperature (20° C, 24.40° C, and 26° C) on interference control ability using Event-Related Potential (ERP) studies. Ten engineering students from the University of Oklahoma performed Stroop/reverse Stroop tasks using Neurobs’ Presentation (Neurobehavioral Systems, Inc., Albany, CA). The ERP components related to the Stroop effect and the anatomical location of the topographic scalp maps were evaluated.

The prefrontal network is active during the process, with one exception. N100-N200 components with higher amplitudes are related to the selective attention observed in this study in all three thermal conditions. The statistical analysis showed a significant impact of the thermal condition on response time in the incongruent condition presented by the Stroop test and general incongruent condition.
Design and Fabrication of Human Head and Neck Model for Concussion and TBI Experiment
Authors: Honarmandi Peyman , Reina Caitlin , Capiccioni George
Published: February 2024

Concussions in athletes can occur from slight bumps, blows, and jolts to the head. Helmets are used to protect the athlete’s head, often tested on artificial head forms. An artificial test dummy was created to accurately model the contents and mechanical properties of a 95th percentile male head. An artificial skull was created to mimic that of the human head with a center of gravity and motions of the brain to accurately simulate that of the human head. An artificial brain and cerebrospinal fluid were used that had similar properties to the contents of the head. A neck was manufactured to accurately model human extension and flexion. An angular accelerometer was placed in a compartment inside the brain in order to read the values needed to detect a concussion to determine efficacy of helmets. The behaviors of these materials were analyzed through SolidWorks simulations and were verified through experimentation. The accelerometers read the values needed to detect a concussion with success which allowed for efficient testing of potential headgear. The model was able to sustain 109 Gs on the skull and 190 Gs on the brain, which meets the standard of 100G acceleration for a concussion.
Optimizing a Manufacturing Pick-And-Place Operation on a Robotic Arm Using a Digital Twin
Authors: Perry LaShaundra , Guerra-Zubiaga David A. , Richards Gershom , Abidoye Cecil , Hantouli Fadi
Published: February 2024

Industry 4.0 is the ongoing evolution of manufacturing, characterized by implementing new technologies and methods to increase adaptability and efficiency. To realize the potential of Industry 4.0, integrating technological concepts is essential. This research combines process simulation, automation, and existing manufacturing infrastructure to develop a digital twin (DT) and implement it to drive visibility and innovation. This research seeks to optimize a live production system by developing a simulation to model a pick-and-place operation, creating a DT to reflect the real-world system environment. The simulation will allow for modifications to the process or system to better understand the impacts of changes to the operation.

The provided definition of a DT outlines a clear set of criteria that must be met for a virtual model to be considered a DT. According to this definition, the creation of a virtual, kinematic replica of a physical model is essential. Connecting this kinematic model to the physical model results in the automation of the kinematic model and the creation of a DT. The discussion also identifies potential opportunities for improving the performance of a physical robot cell through the use of statistical analysis and machine learning algorithms.
Parametric Optimization of Degradation Reduction of PEM Fuel Cell for Hydrogen Fuel Cell Heavy-Duty Truck
Authors: Nguyen Huu Linh , Kim Younghyeon , Han Jaesu , Yu Sangseok
Published: February 2024

A proton exchange membrane fuel cell (PEMFC) of heavy-duty truck is operated in very harsh conditions, but it requires more longevity than a passenger vehicle. The current durability strategy for vehicular fuel cells is geared towards passenger vehicles, hence this study employs response surface analysis to develop a durability strategy for heavy-duty fuel cell trucks. The study uses a physics-based model to predict the degradation of PEMFC under truck operation mode. The model is validated using experimental data from a 20-cell PEMFC stack, which is operated for 2000 hours under the world harmonized vehicle cycle (WHVC) mode. The study employs a response surface method (RSM) to select the power output and degradation rate as object functions. Results indicated that as the operating temperature increases, the power output increases, but the degradation is accelerated. By contrast, increasing gas inlet temperature decreases power output and degradation rate. Higher relative humidity at the cathode and anode leads to increase fuel cell and lower voltage degradation. Therefore, the optimal operating conditions for the fuel cell to minimize voltage degradation are high levels of humidity, moderate cell temperatures, and moderate gas inlet temperatures. The study suggests that the optimal operating conditions are anode and cathode relative humidity of 100%, a fuel cell temperature of 61°C, and a gas inlet temperature of 57°C.
Analysis of Hydrodynamic Loading on Shark Species to Inform Design of Low Drag Satellite Telemetry Tags
Authors: Aduviri Brooke , Hansen Bianca , Wettstein Cassandra , Piacenza Susan , Piacenza Joseph , Lomonaco Pedro
Published: February 2024

Sharks are pivotal apex predators in marine ecosystems and migrate up to thousands of miles throughout their lifetimes. Shark movement is studied using satellite tracking tags, which are typically attached to the dorsal fin. Tags either send a signal when the dorsal fin breaches or detach from the shark and float to surface to communicate with the satellite (Fig.1). While spatiotemporally resolved movement data is valuable to studying shark ecology and conservation, satellite tags impose hydrodynamic loading which produces a drag force on the shark, potentially influencing their behavior, leading to incorrect movement analysis. Since tags change the streamlined body shape of animals, they may influence swimming patterns, especially at high speeds since drag increases with velocity. In this study, we used existing 3D digital models of three shark species — the Great Hammerhead, Blacktip Reef, and Caribbean Reef — to assess the effects and influence future tag design. This paper explores flume testing at the OSU O.H. Hinsdale Wave Lab to improve CFD validation. A cart apparatus was glided across the flume at controlled velocities to simulate average cruising speeds of each shark species at angles of attack of 0°, 12°, and −12° degrees for neutral, rising, and diving movement patterns, respectively. We compared the output drag and lift coefficients to coefficients generated using CFD simulations in STAR-CCM+. Across the three species and angles of attack, the mean percent error was 47.3% ±34.1% standard deviation (SD) for the drag coefficient and 97.8% ±69.0% SD for the lift coefficient. Future work incorporates attaching scaled satellite tag models to shark models to compare to untagged data with the intent of informing subsequent tag designs.
A Robot Motion Planning Approach Based on Adaptive Multi-Tree Sampling
Authors: Feng Bohan , Jiang Xinting , Bi Youyi
Published: February 2024

Efficient motion planning methods are essential to ensure industrial robots to work properly and safely. Although sampling-based planning algorithms are viable ones, they often struggle to adapt to highly constrained and complex environments. This paper introduces a new robot motion planning approach for such environments, utilizing a multi rapidly-exploring random trees exploration structure. The approach combines the fast exploration property of RRT-based methods with the global exploration property of multi-tree structures. In the subtree generation, an information gain-based method is used to analyze the sampled information from multiple trees to compute the potential information gain at various subtree generation locations. By selecting the locations with higher information gain, our method can effectively improve the exploration quality of the environment. Furthermore, an adaptive local subtree planning method is developed, which relies on local structure information and dynamically updates the sampling distribution to maximize the possibility of forming feasible trajectories in narrow passages. The effectiveness of the proposed approach is tested in 2D, 4D, and 6D environments, along with a complex material picking scenario. These experiments demonstrate that the proposed approach surpasses the performance of other algorithms, particularly in those highly constrained and complex environments. Our study contributes to the development of advanced and highly-adaptive motion planning methods for robots in complex environments.
Improving Facility Energy Efficiency Through Energy Cost Analysis
Authors: Guo Qi , Courville Adam , Liu Qiu
Published: February 2024

This paper presents a comprehensive procedure for conducting an electricity cost analysis to promote energy savings, reduce operational costs, and improve sustainability for facilities. By analyzing utility bills, the majority of a facility’s electricity costs in the US can be broken down into energy charge, demand charge, power factor charge, and service charge, each of which is explained in detail. These findings contribute to the field of facility energy analysis by providing novel insights into the breakdown of complex energy charge items into their constituent parts. The case study of a university in Louisiana with an annual electricity cost of approximately $1.7 million is presented. The energy and demand consumption, as well as the corresponding cost, were calculated and plotted. The potential energy-saving opportunities are discussed. The paper’s framework can serve as a roadmap for facilities to optimize their energy consumption, reduce costs, and minimize their carbon footprint. By conducting an electricity cost analysis and following the suggested guidelines, facilities can enhance their sustainability and financial well-being.
Research on Optimization of Sampling Feature Points for On-Machine Measurement of Integral Impeller Blade Profile
Authors: Song Weishu , Li Bingran , Ye Peiqing , Chen Weihua
Published: February 2024

During the machining process of the integral impeller, on-machine measurement can be used to measure the profile of the blade surface before precision machining, evaluate the distribution of allowances, guide the adjustment and optimization of the precision machining tool path NC program, and improve the machining accuracy of the blade surface. To improve measurement efficiency, it is necessary to optimize the sampling algorithm for the feature points of the blade surface, to reflect the most geometric features of the blade surface with the minimum number of measurement points as much as possible. This study proposes an optimization strategy for on-machine measurement feature point sampling of blade profile based on an actual produced integral impeller. By analyzing the structural characteristics of the blade surface and using the B-spline approximation approach, the measurement section line extraction that meets the fitting accuracy threshold requirements was achieved. The sampling function was reconstructed to achieve adaptive adjustment of curvature chord height, and the maximum allowable step size was introduced, achieve adaptive extraction of measurement feature points under multiple constraints. A reliability evaluation process for on-machine measurement systems has also been proposed, which has been applied in practical production lines to verify whether the accuracy of the on-machine measurement system itself meets the requirements.
Design, Development, Analysis, and Preliminary Testing of a Compliant Knee for Bipedal Robots
Authors: Talley Connor , Tetrault Anthony , Woods Parker , Allah Majazz , Jones Nathan , Wilson Catherine , Tekes Coskun , Tekes Ayse
Published: February 2024

There is still an ongoing effort in the design and development of legged robots in the field of robotics. Bipedal robots can imitate the walking gait cycle, hopping, and jumping type locomotion. To accomplish the gait cycle, the four phases of the gait cycle as double support phase, the pre-swing phase, the single support phase, and the post-swing phase should be successfully alternated in a sequence. Compliant mechanisms have been utilized in biomimetic designs due to their inherent properties such as bending of their flexible members rather than joints when forced and their ability to be manufactured as a single piece. This work presents the design of a single-piece robotic knee consisting of upper and lower legs which are combined using a compliant rolling contact hinge to allow for vertical motion in the foot. The hip of the robot houses two stepper motors to actuate the legs, additional two stepper motors for the swing of the hip, and 4 propeller kits arranged in a standard quadcopter orientation to balance the robot. MATLAB Simscape model of the robot is created for rapid motion analysis.
Design and Development of Remote Operated and Soft Biomimetic Amphibious Mud Skipper
Authors: Juarez Rafael , Cho Sungchan , Tran Kevin , Lupercio Ulysses , Schwenck Lucas , Talley Connor , Tekes Ayse
Published: February 2024

In this study, an amphibious, remotely operated, soft biomimetic locomotive mechanism that can reliably travel over rough terrain and swim in water is presented. The design of this mechanism is inspired by the mudskipper and consists of two soft fins, two compliant arms, a central body, and a compliant tail, utilized to travel on both land and water surfaces. The parts of the biomimetic robot are 3D printed using thermoplastic polyurethane and polylactic acid to sustain its contact with the ground in a unique way. The robot utilizes four servo motors to consistently move two compliant arms and soft fins to overcome obstacles. While the fins swipe back and forth across the fluid surface to generate movement, the tail is utilized in a vertical swiping motion to propel the robot through the water and assist in turning. The mechanism is remotely operated by a Bluetooth controller and powered by onboard batteries. All the electronics are encased in a waterproof housing so that the robot can swim in water without the hazard of shorting. Additionally, the MATLAB Simscape model of the robot is created to optimize the link lengths and analyze the locomotion behavior.
Leveraging Virtual Laboratory Modules for Digital Engagement and Active Learning in Mechanical Engineering
Authors: Uysalel Can , Jain Anshal , Ghazinejad Maziar
Published: February 2024

Ongoing advancements in pedagogical technologies have prompted engineering educators to embrace digital platforms and interactive models. In this paper, we present a study of how incorporating engineering virtual laboratory modules can provide a valuable tool to bridge the gap between theoretical concepts and practical applications, enhancing students’ physical understanding of engineering topics. To address this issue, we are putting forth virtual laboratory modules that visualize the mechanical behavior of engineering materials. These modules include but are not limited to tensile test, Rockwell hardness measurement, and Vickers microhardness test. To provide a learner-centered environment, we utilize Python programming to create an interactive interface that enables users to select the engineering material and the type of tests. We employed Python programming to develop a student-oriented interface replicating a real lab environment, further enhancing the experiential learning process. Utilizing virtual learning modules in engineering education can significantly improve students’ engineering intuition and enhance their proficiency in characterizing and selecting engineering materials for various technical applications. Preliminary results indicate that virtual laboratories can supplement physical laboratories effectively due to their low costs, easy replication, and meeting substantial student demand. The virtual environment also enables students to view experiments repeatedly and at their own pace outside of the classroom. Integration of virtual learning modules can significantly improve the accessibility of advanced educational laboratories and setups, which may be unattainable for under-resourced facilities and student communities. When combined with hands-on experience in physical laboratory modules, our approach enhances the interaction between learners and instructors, fostering an experiential learning environment.
Passive Frequency Tuning Using Liquid Distributed Load
Authors: Adhikari Rahul , Karimi Vahid , Jackson Nathan
Published: February 2024

Creating self-sustaining wireless sensor networks to power the Internet of Things requires universal energy harvesting systems. MEMS energy harvesters are in particular demand as they can be batch fabricated to meet the large supply demands. However, currently silicon MEMS kinetic energy harvesters are fabricated with a narrow bandwidth of 1–2 Hz, so each application requires a custom designed device which limits the advantages of batch fabrication. This paper investigates the development of a passive tuning MEMS vibration energy harvesting method that is based on distributing the load to various locations along the proof mass using a liquid load. A 3D printed proof mass with an array of cavities was developed, where each cavity could be filled with liquid to alter the resonant frequency as desired. Cavities were filled with silicone oil to validate the concept. The results illustrate tuning of the frequency with a resolution of < 1 Hz and a range of approximately 50 Hz. This method represents a passive tuning method as no power is required and the tuning can be accomplished during manufacturing so that one single universal energy harvester could be made and then tuned to meet the end user’s frequency specification.
A Comparative Study on Conductive Polyimide Composite Thin Films Containing Indium-Tin-Oxide and Silver Nanoparticles
Authors: Guler Zeynel , Jackson Nathan
Published: February 2024

Polyimides (PI) have been broadly utilized in thin film processes and microelectromechanical systems (MEMS), because they have relatively high thermal and mechanical stability, high glass transition temperature and biocompatibility. This paper investigates the development of 0–3 flexible PI composite thin films containing electrically conducting silver (Ag) or indium-tin-oxide (ITO) nanoparticles via spin coating. Photodefinable PI was used in order to pattern the films without requiring a complex etching process. Resolution and conductivity of the films were analyzed with varying concentration of nanoparticles. A 10 wt% Ag-PI film demonstrated a conductivity value of 7.1 S/m, while ITO-PI films had a slightly lower conductivity of 3.7 S/m with the same wt%. Conductivity of 5 wt% was 4.2 S/m and 2.3 S/m for Ag-PI and ITO-PI samples. The resolution decreased with increasing wt% and ITO demonstrated better resolution than Ag due to transmission of UV light.
Thermal Performance of Dovetail Fins Under Dehumidifying Operating Conditions: Analytical and Numerical Solutions
Authors: Saiboonchan Pornphiphat , Pashah Sulaman
Published: February 2024

Extended surfaces or fins enhance the heat transfer rate between a solid and surrounding fluid. The first scenario is thermal management by dissipating heat from a hot surface. The application sizes range from heat loss through a car radiator to the thermal management of electronic appliances through extended surface heat sinks. The second category is heating, ventilating, and air conditioning (HVAC) applications. The purpose of refrigeration and air conditioning equipment is to cool the atmospheric air by passing it over an extended surface (or fin) at a temperature lower than the passing air. Moreover, if the fin surface temperature is below the dew point temperature of incoming moist air, then the condensation of water vapor occurs on the fin surface. Therefore, heat and mass transfer co-occur over the fin surface. The application is commonly termed a “wet fin.” Enhanced fin geometries (such as wavy, louver, slit, and convex louver) exist. However, simple fin geometries are adopted due to low manufacturing and maintenance costs. The most common fins are longitudinal (or plane) fins, annular (or radial) fins, and spines (or pin fins). A dovetail fin (i.e., variable thickness longitudinal fin) can enhance the performance of a double pipe heat exchanger due to its higher surface area than the rectangular profile fin. Literature shows that the performance of a dovetail fin has been studied for heat loss (or dry operating conditions) only, and no closed-form solution is available for air conditioning (i.e., wet fin) applications. The analysis of a wet fin is more challenging than the dry fin analysis because of the additional consideration of mass transfer due to vapor condensation from the moist air. The thermal performance of an extended surface is commonly described through a dimensionless parameter called fin efficiency. The current work presents a closed-form solution for a dovetail fin’s thermal efficiency and temperature profile that accounts for the combined heat and mass transfer under dehumidification operating conditions. The developed solution is a general case that covers rectangular, tapered, and triangular fins. The solution is validated through available closed-form rectangular and triangular fins solutions. Comparison of results with a two-dimensional finite element numerical solution provided a dovetail fin’s limit of a one-dimensional solution. Preliminary results show that the dovetail fin has higher thermal efficiency than the rectangular and triangular fins.
Nonlinear Dynamics Simulation of R-RTR Planar Mechanism
Authors: Yousuf Louay S.
Published: February 2024

The planar R-RTR mechanism with two moving links and guide is considered at different speeds. The R-RTR mechanism is consisted from driver link, slider, ground, and rocker link. The external moment is applied on the rocker link which is a function of angular velocity. The level of chaos is investigated using correlation dimension based on the value of time delay at different speeds for the driver link. Time delay is calculated using the algorithm of average mutual information of the dynamic tool. The motor torque is simulated at different speeds for the driver link in the presence of the inertia torque expression using SolidWorks program. Time delay, decorrelation time, and ‘bad’ predict time are used in the calculation of correlation dimension value with the aid of MatLab code. Moreover the chaos is detected using Fast Fourier Transform using power spectrum and autocorrelation analyses. The motor torque of the driver link against time is used in the calculation of time delay, correlation dimension, and Fast Fourier Transform (FFT). The higher value of correlation dimension, the higher level of chaotic complexity in the dynamic system.
Dynamic Simulations of a Cam Planar Mechanism With Impacts and Clearance
Authors: Yousuf Louay S. , Marghitu Dan B.
Published: February 2024

The dynamic simulation of flat-faced follower, spinning cam, and a slider with different clearances are analyzed at distinctive speeds. There is a concentric joint between the flat-faced follower and connecting rod. The follower impacts with friction the spinning cam at various contact points of the cam profile. The simulation is done using SolidWorks. The cause of the chaotic phenomenon is the impact and clearance. The impact parameters are the sliding contact velocity, kinetic coefficient of friction, contact stiffness, exponent, and coefficient of restitution. The nonlinear analysis of the midpoint of the connecting rod is considered in time delay, global, the local embedding dimensions, and Lyapunov exponent calculations. The system’s motion is examined for different coefficients of restitution and additional clearances of the slider. Phase plane and Poincaré maps are developed for nonlinear analysis.
Digital Twin Based Learning From Demonstration System for Industrial Robots
Authors: Bondarenko Yevhen , Pizzagalli Simone Luca , Kuts Vladimir , Petlenkov Eduard , Otto Tauno
Published: February 2024

Learning from Demonstration (LfD) is an approach to robot programming where the machine aims to replicate the task presented by a human without being explicitly programmed to execute this task. While being an effective way to create complex robot routines even for users without coding skills, most LfD implementations heavily rely on sensors for the robot to capture the state of the surrounding world and the task being demonstrated.

In this research paper we offer an alternative LfD approach based on a fully simulated 3D environment. We demonstreate how simulation can eliminate the need for real-life sensors on the robot, serve as a unified medium for recording demonstrated tasks, and facilitate sharing of the produced solutions between different types of robotic cells with minimal to no reconfiguration. A Virtual Reality interface allows the operator to interact with the LfD environment in a natural way when recording task demonstrations for the robot. The system is built on top of commonly available software such as Unity engine, Robot Operating System, ROS-Industrial and MoveIt motion planning framework. It will be published on the public GitHub page of TalTech IVAR Lab [1].

We also provide a simple experimental procedure to validate the system’s ability to generate programs for multiple robot models from a single task demonstration, demonstrating its flexibility and ease of use for the operator.
Fabrication of Ultra-High Aspect Ratio Array Structures Using Spontaneous Evolution in Multiport Lifted Hele-Shaw Cell
Authors: Rakshe Makrand A. , Gandhi Prasanna S.
Published: February 2024

High aspect ratio (HAR) micro/meso-well array structures are useful in biomedical devices such as spheroid formation, drug-releasing patches, and cell-trapping. Nature-inspired honeycomb structures with high aspect ratio walls have the potential for such applications. This paper demonstrates the lithography-less, spontaneous, scalable fabrication of an ultra-high aspect ratio structure in polymer by disciplining Saffman-Taylor fluid-fluid interface instability. The fabrication process includes (i) rearrangement of fluid in the array during the initial stage of the plate separation due to the evolution of air fingers without splitting because of controlled Saffman-Taylor instability, (ii) subsequent pinning of the fluid boundary due to evaporation of the solvent from the polymer solution (iii) stretching of fluid due to continuous increment in the viscosity of the volatile polymer solution, and finally (iv) solidification due to volatility of the fluid. With the proposed method, we successfully demonstrated the fabrication of ultra-high aspect ratio (in the range of 100–200) structures with less than 10-micron wall thickness.
Improved Six Rules-Based Fuzzy Compensation for Time-Varying Control Cycle in Active Powertrain Oscillation Reduction
Authors: Yonezawa Heisei , Yonezawa Ansei , Kajiwara Itsuro
Published: February 2024

To prevent the degradations of comfort and drivability, this research presents an improved fuzzy-logic-based active oscillation control algorithm for an automotive powertrain with a time-fluctuated control cycle limitation. A sampled-data controller is firstly employed as the base control, and a model-predictive algorithm is implemented to compute the optimal control signals at a periodic time interval. However, the update timing of the real control input fluctuates over time due to the powertrain actuator limitation. The fuzzy reasoning is applied to tackle the time-fluctuated control cycles. In the present method, the update timing is translated into some fuzzy sets. Moreover, the periodic control signals by the sampled-data controller are combined as fuzziness, resulting in linguistic fuzzy sets. Six fuzzy rules are created based on those fuzzy sets to derive feasible control inputs at the fluctuated updating timings. The control strategy is tested via simulations with a powertrain oscillation model. The compensation effect is observed for the two patterns of the fluctuated control cycles. In addition, the test results confirm the improvement of the oscillation reduction over a conventional control algorithm.
Robust Contact Modeling in Non-Rigid Variation Simulation
Authors: Sadeghi Tabar Roham , Lorin Samuel , Lindkvist Lars , Wärmefjord Kristina , Söderberg Rikard
Published: February 2024

Geometric variation is an inevitable element of any fabrication process. To secure the geometric quality of the assembled products, variation simulation is performed, approximating the statistical moments of the geometric variation, thereby controlling compliance with the set geometric requirements. Contact modeling involves describing the behavior of contacting bodies. In non-rigid variation simulation, contact modeling is used to avoid the virtual penetration of the components in the adjacent areas, enhancing the simulation accuracy. Variation simulation and contact modeling is based on the Method of Influence coefficients (MIC). Compared to the traditional MIC, the contact model imposes non-linear behavior on the deformation calculation. In this approach, the MIC matrix is utilized as the reduced stiffness matrix in the contact model. For frictionless contact models, numerical errors and convergence issues due to the deformation behavior of the interacting surfaces are still limiting the computational efficiency of solving this optimization problem. The optimization problem associated with a contact model is often large-scale, and in practice, fast and robust methods for achieving convergence are required. Previous implementations of contact modeling for non-rigid variation simulation have been prominently based on the Iterative or Penalty Methods, and Lagrangian Multipliers Method through Interior Point Solvers. In this paper, a quadratic programming approach has been introduced based on the Lagrangian multiplier method for robust contact modeling in non-rigid variation simulation, and the performance of the proposed approach has been compared to the previously applied Iterative and Interior Point Method. The methods have been compared on three industrial reference cases, and the convergence, and time-efficiency of each method are compared. The reference models have been chosen from different problem sizes, small, medium, and large-scale. The results show that robust optimization of the quadratic program associated with the contact model is highly dependent on the assemblies’ condition, composed of the reduced stiffness matrix condition. Furthermore, it has been shown that robust and efficient contact modeling in non-rigid variation simulation is achievable through the proposed quadratic programming method. Improvement in the convergence is achieved while maintaining the accuracy level to the predefined tolerance intervals.
Digital Twin Approach to Support Preventative Maintenance in a Robotic Application
Authors: Clounie Joshua , Guerra-Zubiaga David A. , Voicu Razvan Cristian
Published: February 2024

The cost-effectiveness and efficiency of any manufacturing system are now more critical than ever. Therefore the embracing of Industry 4.0 is underway. Interconnectedness and smart automation with the integration of the Manufacturing Execution System (MES) are the key concepts of Industry 4.0. The fast-paced industrialization 4.0 requires a good insight into existing concepts and methods. There are many ideas and concepts that are integrated into the advancement of Industry 4.0. This paper explores the integration of preventive maintenance concepts and methods used by the fourth industrial revolution, ideas like the Industrial Internet of Things (IIoT), Cloud Manufacturing (CM), Machine Learning (ML), Product Lifecycle Management (PLM), Digital Manufacturing (DM), and Digital Twins (DT). This paper will introduce additional concepts into the conference paper, Intelligent Process Control Following Industry 4.0 Trends, with Siemens PLM product, Tecnomatix.
Finite Element Analysis of Brain Damage Induced by the Impact of Hit-by-Pitch
Authors: Shimomura Kohei , Terai Motoharu , Sakuma Atsushi , Zhang Yuelin
Published: February 2024

Concussion due to hit-by-pitch can be life-threatening in baseball, and it requires effective countermeasures. Concussion lesions are microscopic and imaging diagnosis is generally difficult. Recently numerical modeling of brain injury mechanics has been proposed. This study aims to quantitatively analyze and evaluate the effect of helmets on head injury using numerical analysis of brain injury models. First, in the analysis under the condition of direct impact of the ball on the head, residual strain corresponding to damage occurred near the collision and center points of the brain. This result was used as a criterion for evaluation of brain injury. Then, the effect of ball rotation was observed, and the effect was relatively small. Furthermore, in case of impact with helmet on, residual strain was smaller near the collision point, larger near the center point when the helmet was fixed. The residual strain was smaller for impacts to temporal region than to parietal region under conditions of different collision positions. The residual strain was smaller than that of the fixed helmet regardless of collision position when the helmet was not fixed. The results indicate that the effect of the ball rotation on brain damage at hit-by-pitch is small, and that the impact position and fixation of the helmet have a relatively significant effect.