bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic Response of Soft Artificial Fabric Muscle Actuators for Launch and Recovery Systems
Authors: Smith Michael P. , Gamel Kaelyn , Redington Allison , Warner Eric , Cavallaro Paul V. 
Published: January 2025

Abstract
This research investigated the kinematics and vibrational performance of McKibben-type artificial soft fabric muscles (ASFMs). The ASFMs are constructed of High-Performance Fibers (HPF) encompassing an oversized, pleated, nonstructural fluid bladder. These ASFMs have potential applications for the launch, recovery, positioning and control of undersea and surface vehicles and interface platforms. The vibrational characteristics of ASFMs constructed of both glass and aramid braid materials were evaluated experimentally by exposing a fluid-pressurized ASFM to flow-induced vibration (FIV) and measuring the response.
Bi-Directional Locomotion of Asymmetric Curved Soft Millirobot Under Magnetic Fields in Different Frequencies
Authors: Bulang Christophe , Trinh Jessica , Scurry Jordan , Na Suk Joon , Park Jungkyu , Kim Dal Hyung 
Published: January 2025

Abstract
This paper presents the bi-directional swimming locomotion exhibited by both asymmetrical and symmetrical curved soft millirobots (SMR) and their characterization. Also, the controllability of these curved SMR is demonstrated via feedback control. The various curvatures of the robots are achieved by subjecting the robot to high temperatures while they are constrained using a circular mold containing a variety of hole sizes. When subjected to sweeping magnetic fields, the curved SMRs engage in distinctive swimming behavior, propelled forward within the low-frequency regime of magnetic fields while reversing their swimming direction at higher frequencies with the frequency ranges being determined by the thickness and curvature of the specific robot. The mathematical model of their locomotion is developed based on Taylor’s model but includes both forward and backward velocity terms and is validated with experimental data. The presented findings afford a profound insight into the complex locomotion dynamics of the curved SMR, thereby engendering a pivotal foundation for the prospective evolution of this robotic system.
Self-Excited Vibration Analysis of a Reduced-Order Model of a Braked Wheel With Tyre, Including Suspension Mechanism
Authors: Gualdi Daniele , Sorrentino Silvio , De Felice Alessandro 
Published: January 2025

Abstract
This study is aimed at deepening the stability analysis of a braked wheel of a road car, including suspension mechanism, and focusing on the interaction effects between the friction characteristic of the brake and the force characteristic of the tyre. It is well known that both contact forces can independently lead to instability in their respective rotation dofs. However, it is of practical interest to understand their combined effects on stability regions, which hasn’t been investigated in literature yet.
A minimal model with 5 dofs is proposed for the analysis, including the 2 dofs of the standard quarter car model (bounce of sprung and unsprung masses), plus rotation of the wheel rim and compliance of the suspension mechanism in both torsional and longitudinal directions. Stability analysis of the linearized model is performed with the aid of stability maps, highlighting sensitivity with respect to the governing parameters. In addition, the system’s modal behaviour is investigated as well.
Mechanical Failure Mode of Spinal Dura Mater Under Pressurized Loading Conditions
Authors: Tamura Atsutaka , Sakaue Chikano , Hongu Jun-ichi 
Published: January 2025

Abstract
It is believed that mechanical damage to the meninges protecting the spinal cord in case of blunt external forces can cause idiopathic cerebrospinal fluid leakage. This is probably because even a small meningeal failure leads to the leakage of cerebrospinal fluid (CSF) that fills the subarachnoid space. However, the dura mater, the outermost layer of the three-layered meninges, is especially resilient and is unlikely to be easily damaged. On the other hand, it is also known that CSF leakage can be caused by daily activities such as coughing, sneezing, and falling. Because of these contradicting facts, it is difficult to understand the essential mechanism of CSF leakage.
In recent years, extensive efforts have been made to elucidate the mechanism of traumatic and impact-related injuries through computational simulations. In order to enhance injury prediction accuracy, it is crucial to comprehend the actual failure mode of biological materials under injurious loading conditions.
Therefore, in this study, we focused on the relationship between the intrinsic wrinkle shape formed on the dural surface and its mechanical failure mode. We measured the surface profile of the porcine dura mater and performed a pressurization test until dural mechanical failure occurred using a custom experimental test apparatus.
An Additively Manufactured and Optimized Bicycle Saddle Prototype for Low Weight
Authors: Yeole Shivraj Narayan , Kode Jaya Prakash , Maddineni Poojit , Bolisetti Lakshmi Mounika , Vajah Jyothi Bharadwaj 
Published: January 2025

Abstract
The world is transitioning from using conventional sources of energy to using renewable sources. As the transportation industry has a relatively large carbon footprint, people are opting for more sustainable modes of transport, such as bicycles for shorter distances. Bicycles not only are good for the environment but are also advantageous to humans in terms of health. Although the conventional bicycle saddle provides comfort to the rider, for longer distances or uneven terrain, the saddle can cause discomfort and health problems to the rider such as erectile dysfunction, soreness, and chafing on the inner thighs. These issues can be completely avoided by using a saddle that provides a good fit and right cushioning. The current study proposed an improved design of a bicycle saddle for a male rider of 100 kg weight and a sit bone distance of 125 mm. The objective was to reduce the saddle weight and improving the comfort. Material was determined by the stress exerted on it, as well as the material’s behavior under stress. TPU 95A was selected as the material due to its excellent mechanical and thermal properties. Cubic and hexagonal lattice structures were studied to determine the optimum structure. The saddle was also analysed by applying a range of loads from 700 N to 1400 N on TPU 95A material. The final design of the saddle was 3D printed to achieve a light weight prototype of 128 g.
Effect of Soaking Time on the Thermomechanical Response of Sintered NiTi Shape Memory Alloy
Authors: Alawwa Fares , Abu Al-Rub Rashid K. , El-Khasawneh Bashar , Zaki Wael 
Published: January 2025

Abstract
Out of all the several metal systems that can exhibit shape memory behavior, nickel-titanium (NiTi or nitinol) is still the most commonly used. An effective method for manufacturing nitinol components is by the process of sintering, which entails compressing elemental or pre-alloyed metal powder and using a suitable mold. Recent studies show that pressureless sintering of uncompacted pre-alloyed powder is a feasible method for fabricating nitinol. Using this technique omits the need to compress the powder into a green part prior to sintering. This study investigates the impact of soaking time on the production of nitinol by pressureless sintering of pre-alloyed NiTi shape memory alloy powder. The process entails heating and compacting nitinol at a specific rate and duration in a vacuum to facilitate its sintering. The material’s shape memory capability is evident from the phase transition peaks observed in the differential scanning calorimetry (DSC) thermograms obtained. It is shown that as the soaking time increases, the peak intensity decreases because of Ni rich area formation of Ni3Ti. In addition, energy dispersive spectroscopy (EDS) is conducted using scanning electron microscopy (SEM) to show that the phases present in the samples are mainly NiTi and Ni3Ti. Vickers hardness test indicated that the sample exhibits a hardness value that is similar to the values published in the literature. Using optical microscopy, the grain pattern of the polished samples shows a correlation between the sintering time and grain size. Overall, the results of this work show that the soaking time affects the grain size, and shape memory performance much more than it does to the hardness exhibited by the samples. furthermore, the process of pressureless sintering of pre-alloyed NiTi shape memory alloy powder can be an effective and efficient method for the fabrication of functional nitinol.
Numerical Investigation on Wave Energy Harvesting Based on the Vibration of a Membrane
Authors: Raihan Gazi Abu , Chakravarty Uttam 
Published: January 2025

Abstract
Wave energy harvesting has emerged as a promising sustainable energy resource in recent years, offering huge potential for future energy solutions. However, technological advancement in developing wave energy converters (WECs) is still insignificant due to several unsolved challenges. In recent years, rubber-like elastomeric composite topologies, that can streamline the PTO of WEC design, are becoming increasingly popular. This study presents a comprehensive numerical investigation into the potential of wave energy harvesting based on the vibration of dielectric elastomer membranes using frequency-based hydrodynamics modeling. The research aims to explore an innovative approach to energy by capitalizing on the vibrational energy of membranes in response to oscillation. The study employs hydrodynamics modeling techniques to simulate the interactions between ocean waves and designed floating membrane structures. The hydrodynamics data are mapped and calculated for the power generation of the wave energy converter in a specific time domain. The membrane, when subjected to wave action, exhibits specific vibrational patterns, which are then converted into usable electrical energy through an integrated energy conversion system. This research underlines the understanding of the mathematical modeling of wave energy converted using dielectric elastomer generators (DEGs) and provides value insights to design and optimize the wave energy converter using DEGs.
Optimised Design of Acoustic Black Hole for Broadband Noise Attenuation in Ducts
Authors: Pradhan Biren Kumar , Mohanty Amiya Ranjan 
Published: January 2025

Abstract
Broadband noise attenuation remains a challenging problem in ducts. The development of acoustic metamaterials in recent times has made it possible to control and manipulate sound waves in novel ways. Acoustic black holes (ABH) are passive type absorbers. The two major parameters affecting the sound absorption characteristics of ABH are known as power-law decay of duct radius and tailored wall admittance. In theory, the tailored geometry induces power-law decay of wave propagation velocity, and the incident wave gets trapped inside the geometry without any reflections. The current study aims to develop an optimised ABH design targeting broadband frequency. The transfer matrix method (TMM) approach is used to characterise the reflection coefficient and validated using numerical approach considering thermoviscous effect along the thin walls. The developed basic design is further optimised for the influencing parameters and validated using numerical analysis. The result shows a broadband noise attenuation for the optimised design of the black hole.
Cavity Wall Undulations to Manage Unsteady Airflow
Authors: Gabel Matthew , Lee Peter C. , Sarigul-Klijn Nesrin 
Published: January 2025

Abstract
We investigate the use of cavity wall features to delay cavity transition from the shear mode to the wake mode and obtain more favorable cavity conditions across the flight envelope. Undulations referred to as “juts” are added to the cavity wall to catch internal cavity vortices and delay their growth and shedding into the freestream. We use Large Eddy Simulation (LES) to model the flow over the cavity for compressible flow conditions. The frequencies of the undulations are adjusted with an optional trailing edge lip to investigate an optimum configuration. The juts are compared based on their complexity, noise profile, drag, and flow unsteadiness inside the bay. We also propose possible applications of these juts to real world cavities used on existing aircraft.
Optimized Sizing of Solar PV Cells, Battery, and Aircraft Design of PV-Powered Surveillance UAV
Authors: Almheiri Salama , Alhammadi Abrar , Khan Aijaz , Zafar Sayem , Dos Santos Gustavo 
Published: January 2025

Abstract
The scope of this paper is to optimize the design of a fully solar-powered surveillance Unmanned Aerial Vehicle (UAV). Iterative modifications of the Photovoltaic (PV) power system design and the UAV airframe design were adopted to ensure optimal results. ANSYS Fluent was used to run Computational Fluid Dynamics (CFD) simulations on the UAV to obtain results of aerodynamic forces. These results were used to estimate the weight of the UAV and the thrust which were found to be 12.6 kg and 7 N, respectively. Contours of the velocity, pressure, wall y+, and turbulence intermittency, were produced to study the flow regime around the UAV. A MATLAB script was programmed to obtain irradiance data specific to Abu Dhabi and validate it with actual irradiance data to ensure accuracy. A comprehensive calculation of the UAV’s power consumption of 113W throughout its forward-flight was conducted and led to the decision to use 80 SunPower C60 solar cells, 2 Lithium-Polymer 3S batteries, and a Maximum Power Point Tracking (MPPT) system. MATLAB Simulink was used to model the MPPT using the incremental conductance method for the effective extraction and tracking of the maximum power point under the varying irradiance conditions obtained in Abu Dhabi.
Enhancing Water Leakage Detection in Transmission Lines Through Deep Learning-Analyzed Ground Penetrating Radar Images
Authors: Alnaqbi Mariam , Rezk Mahmoud , Almaeeni Khuloud , Ebisi Fahed 
Published: January 2025

Abstract
Underground water leakage is a critical problem that water utilities are facing. Efficient and timely detection of water leaks is necessary to mitigate consequences like operational cost loss and infrastructure damage and ensure water systems sustainability. This paper introduces a novel approach to detecting water leaks in transmission lines, utilizing deep learning algorithms to analyze Ground Penetrating Radar (GPR) images. Conventional leak detection methods often lack precision and early detection capabilities. The proposed method automates GPR image analysis, enhancing detection speed and accuracy through Convolutional Neural Networks (CNNs). The researchers collected the data from controlled leakage setups, augmented them, and used them to train a CNN model optimized for GPR image features. Results demonstrate superior detection performance compared to traditional methods, offering early leak discovery and potential cost savings.
Research on the Influence of Characteristics of Secondary Suspension on Vehicle Vertical Vibration in High-Speed Maglev Vehicle
Authors: Xue Zhao , Zhang Jimin 
Published: January 2025

Abstract
Aiming at the phenomenon that the vertical vibration acceleration amplitude of the vehicle body of a certain type of EMS high-speed maglev train increased significantly after being put into operation for a long time, theoretically analysis and numeral calculation were carried out about the influencing factors of the vertical vibration characteristics of the vehicle body in this type of high-speed maglev train, determining that the secondary suspension device in the form of symmetrical closed-chain six-linkage this type of vehicle had obvious influence on the vertical vibration characteristics of the vehicle body. Then with the vehicle system dynamics model considering the dynamic characteristics of the symmetrical closed-chain six-bar linkage mechanism in the secondary suspension, the influence of the slewing resistance in the rotating pair of the mechanism on the vertical vibration of the vehicle body was deeply studied. The research results show that: the operating speed of the vehicle and the vertical stiffness of the primary suspension have little influence on the vertical vibration of the vehicle body; the vertical stiffness of the air spring in the secondary suspension and the slewing resistance at the rotating pair of the symmetrical closed-chain six-link mechanism both affect the vertical vibration characteristics of the vehicle body, but the latter has a more obvious impact, whose influence on the vertical acceleration amplitude of the vehicle body is up to more than 50%, compared with the test results; in order to improve the vertical dynamic performance of this type of maglev train, it is suggested to keep the slewing resistance at each rotating pair of the symmetrical closed-chain six-link mechanism in the secondary suspension at a low level during daily operation and maintenance of the vehicle.
Vibration-Induced Degasification of Trapped Gas From the Liquids: Low-Cost Solution
Authors: Karim Saad , Haider Syed Mustafa , Hussain Abbas , Najib Antash , Majeed Syed Umer 
Published: January 2025

Abstract
During the processing, transferring, and handling of liquids, a lot of changes occur such as pressure change, temperature change, and chemical reactivities. These changes often result in the formulation or detachment of gas which remains stuck inside the liquid in the form of bubbles. The formation of bubbles in liquids causes variations in pressure and volume resulting in poor processing and are difficult to remove. This bubble formation phenomenon is widespread during the processing of water, wax of candles, aluminum castings, epoxy adhesives, lubricants, coatings, drinks, polymers, emulsions, and suspension products. Moreover, medical applications such as droplet digital polymerase chain reaction require the precise removal of trapped bubbles for its successful completion. This current work investigated the effectiveness of a low-cost bubble removal method (degasification) from water through vibrations. Two metal plates, each with distinct surface roughness values (Ra = 0.89μm & Ra = 1.6μm), were immersed in a boiling water beaker. They were then subjected to various vibration frequencies to investigate the removal of gas bubbles. During boiling, gas trapped inside the water separated into bubbles, adhering to the metal plates similar to heat exchangers or vessels. These bubbles are removed using vibrations applied to the plates. From experimentation, it has been found that the metallic plate with lower surface roughness removed bubbles more rapidly than the other. Furthermore, among the seven vibration frequencies tested (20, 50, 70, 100, 150, 200, & 250Hz), a frequency of 150Hz proved most effective for both plates. This concluded that for efficient degasification, a lower surface roughness area coupled with a vibration frequency of 150Hz is optimal.
Synthesis of Large Stroke Constant Torque Mechanisms via Iterative Structural Optimization and Nonsymmetric Design for Enhanced Strain Relief
Authors: Bi Shun , Rehman Tanzeel Ur , Johnson Shane 
Published: January 2025

Abstract
Compliant constant torque mechanisms (CTMs) offer a novel approach to maintain torque levels with their nonlinear torque rotation relation in a monolithic design. Current CTM designs have limited stroke (20–70 degrees) and coefficient of variance (COV) (±4%). It is hypothesized that both complex geometry and ineffective compliant members together increase computational cost and reduce strain relief capacity. In this study, an iterative optimization approach to address ineffective members in CTMs is proposed, aiming to enhance stroke range while minimizing complexity. Leveraging design methods related to strain relief from constant force mechanisms (CFMs), our methodology employs the graph method with nodal perturbation to introduce more slenderness and tortuosity efficiently into the geometry. Through iterative optimization with FEA models for CTMs achieved extended stroke ranges of 20–130 and maintained COV to about ± 2%, overcoming limitations of traditional CTMs. The experimental results show 40–120 stroke ranges and around ± 3% COV. This study offers a new methodology to efficiently design CTM while overcoming certain limitations existing in current methods. Such method may further be utilized in surgical and robotics applications.
Geometry Prediction Simulation for Metal Additive Manufacturing: a Calibration-Free Approach
Authors: Lorin Samuel , Sagar Vaishak Ramesh , Cromvik Christoffer , Edelvik Fredrik , Wärmefjord Kristina , Söderberg Rikard 
Published: January 2025

Abstract
Metal additive manufacturing has significantly impacted the manufacturing industry, yet ensuring geometric quality remains a challenge during the design phase, with geometric distortion proving difficult to alleviate through post-treatment methods. In numerous manufacturing processes, simulations have proven effective; however, accurately simulating geometric outcomes in metal additive manufacturing necessitates the mathematical representation of various physical scales, spanning from the microscopic intricacies of powder and laser melting to the macroscopic deformation of components. Notably, existing simulation methods often fall short in accounting for the fluctuations in thermal history resulting from the cyclical heating and cooling inherent in layer-by-layer manufacturing processes. Also, as a design tool, there is a need for simple yet accurate simulations to aid the designer. This paper delves into the incorporation of thermal history variations and their influence on the accuracy of geometry predictions. This research introduces a new approach for using the inherent strain method. By employing micro-scale simulations, we conduct meso-scale simulations to estimate the plastic strain changes resulting from repeated heating-cooling cycles. The calculated plastic strain values are then used to determine inherent strains, which are applied layer by layer within block structures. This method considers the shrinkage experienced in previous layers, enabling accurate deformation simulations at the part scale. Validation of this approach involved a comparative analysis with five strain bridges, each featuring varying bridge thicknesses, fabricated through the Selective Laser Melting process. It is noted that the printed parts undergo a rotation after the support structure is cut off. When compensating for this rotation, the prediction of geometric distortion exhibited exceptional accuracy after cut-off. Consequently, the result suggests this method facilitates precise geometry simulation for components produced using the Selective Laser Melting process without the need for extensive inherent strain parameter tuning. The authors believe that this approach holds great promise as an aid for designers in the additive manufacturing industry.