bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Statistical Shape Model of Femur of ACL-Injured Knee
Authors: Ghidotti Anna , Regazzoni Daniele , Weiss Cohen Miri , Condello Vincenzo 
Published: November 2024

Abstract
Injuries to the anterior cruciate ligament (ACL) are common among active populations. The shape and anatomical variations of the bones are directly related to the function of the ACL, and therefore are considered to be risk factors for injury. This research aims to delineate the key patterns of shape variation in femurs affected by ACL injuries through the application of Statistical Shape Modelling (SSM). SSM is applied to 50 distal femur models and their modes of variations are described. Ten morphologically significant parameters of the distal femur bone are selected and measured on a 3D model of the mean femur, as well as the −3SD and +3SD shapes of the first three principal components (PCs). The first principal component reflects the variation in size of the femur. The second principal component is mainly related to the width of the notch. A variation in the height of the medial posterior condyle is observed in the third principal component. Nevertheless, it is not as significant as with the first two PCs. The study presents a statistical shape model for characterizing the fundamental modes of geometric variation in femoral bones following an ACL injury. Knowing the bony morphological features associated with ACL injuries is crucial to tailoring treatment plans to each individual.
Automatic Kinematic Alignment of Flexures in Parallel Mechanisms
Authors: Piening Patrick V. L. , Nijenhuis Marijn , Aarts Ronald G. K. M. , Brouwer Dannis M. 
Published: November 2024

Abstract
Compliant mechanisms offer a number of benefits over sliding joint based mechanisms; however, their design is more complicated. As a result multiple design methods have been developed to assist with the design of compliant mechanisms. The kinematic FACT method assists in the manual design of mechanisms but has seen limited use in computational optimization. This research presents an alternative kinematics based computational optimization approach towards the automatic placement of a chosen set of flexures in 3D space such that a desired constraint space is obtained while minimizing the redundancy of constraints within a parallel spatial mechanism. A continuous measure for vector space misalignment is developed and utilized in a cost function optimization to manipulate the coordinate frame transformation of screws associated with flexural building blocks. This continuous measure is also used to formulate constraints for the cost function optimization. The approach is tested in three design cases within a limited design volume: a spherical hinge composed of wire flexures, a single rotation degree of freedom (DOF) hinge composed of leaf flexures and a parallel mechanism with three non-intersecting rotational DOFs consisting of wire flexures. The flexures are introduced and optimized sequentially and kinematically valid designs are obtained. This research is a stepping stone towards the development of a more general automatic 3D building block based synthesis approach for compliant mechanisms.
Development of a Comprehensive Linear Finite Element Model of the Human Wrist Joint
Authors: Mena Andres , Wollstein Ronit , Yang James 
Published: November 2024

Abstract
This study presents a linear finite element model for the human wrist, constructed from a CT scan of a 68-year-old male (type I wrist). This model intricately captures the bones, soft tissues, and ligaments to study the biomechanics of static grasping by applying pressure loads on the five metacarpals. The results show radial transmission of the load, consistent with findings from wrist finite element models conducted in the last decade and other experimental in vitro studies. Validation is explored through the assessment of carpal resultant displacement. Our preliminary results confirm the model’s efficacy in reproducing key biomechanical aspects, laying the groundwork for future investigations into ongoing wrist biomechanics challenges.
Automated Sub-Feature Labeling Using Prompt-Based Pretrained Language Model
Authors: Park Seyoung , Jiang Yilan , Kim Harrison 
Published: November 2024

Abstract
Many studies have been utilizing online user-generated data to draw product design implications via supervised and unsupervised approaches. While the supervised learning methods typically yield higher performance, they demand extensive data labeling tasks, consuming significant time and effort. This study proposes a framework that automatically labels online user data to address this limitation. The proposed framework consists of two pseudo-labeling mechanisms, keyword detection and prompting Pretraied Language Model (PLM). The first stage defines keywords for the target topic and then labels datasets by checking if the data contains these keywords. The second stage employs the PLM and labels datasets based on their context. Specifically, Prompting PLM adds a task-specific template at the end of the given text data (review) and predicts the masked token (label). This PLM-based approach serves as promising labeling candidates as they can make predictions without additional training data from the target domain. The suggested method was tested on a case study with real-world datasets. The study validates the effectiveness of this novel framework by comparing the pseudo-labeled results on smartphone sub-features to manual ground-truths. The results demonstrate that the new framework achieves F1 scores 28% and 14% higher than a baseline for screen and battery, respectively.
Techno-Economic Outlooks for the Operation of Zero-Emission Heavy-Duty Trucks: Their Implications on Fleet Operators, Cargo Shippers, and Vehicle Designers
Authors: Liang ZhiYi , Dupont Bryony L. , Winter Amos G. 
Published: November 2024

Abstract
Heavy-duty trucking is an essential economic sector and the logistical backbone of the American and global economy. However, heavy-duty vehicles (HDVs) contribute significant CO2 emissions to global warming. HDVs are hard to decarbonize due to the large amount of onboard energy storage required for the range and towing performance needed. Currently, there are two potential promising alternative drivetrain architectures to replace existing diesel fleets: lithium battery-electric vehicle (Li-BEV) and hydrogen fuel-cell-electric vehicle (H2 FCEV). While these alternative-fuel HDVs are on their way toward technical maturity and commercialization, the techno-economic implications of operating a zero-emission fleet remain largely uncertain to stakeholders in the trucking industry. In this study, we developed a multi-dimensional techno-economic model to evaluate the technical constraints of onboard energy storage in HDVs and compare the operational technoeconomics of zero-emission drivetrains against diesel vehicles, using the perspectives of fleet operators and cargo shippers. We have found that although Li-BEV drivetrains show promise in decarbonizing heavy-duty vehicles, they are limited to the short to medium range (&lt; 500 mi) and in applications where freight capacity is not a high priority. In the long-haul freight-carrying scenario above 750 miles, H2 FCEVs are shown to be a better candidate for replacing diesel heavy trucks than Li-BEVs, due to a higher cargo capacity. However, to make H2 FCEVs more competitive in the HDV sector, more proactive investments and infrastructure developments are necessary to establish a mature hydrogen supply chain and to further reduce the price of hydrogen fuel to 2 USD/kgH2. It is also apparent that the operational techno-economics and freight performance of the zero-emission options remain out-competed by existing diesel fleets. Governments would need to put forth aggressive fiscal and regulatory policies to promote the competitiveness of zero-emission drivetrains and limit the use of diesel vehicles.
Design and Fabrication of a Deployable Tensegrity Millirobot for Next-Generation Gastrointestinal Diagnostics and Treatment
Authors: Kazoleas Christian , Zhang Jiajun , Tan Na , Yuan Sichen 
Published: November 2024

Abstract
The advent of robotics in medicine has brought about a paradigm shift, enabling minimally invasive interventions for in-vivo practices. Pill-based robots, specifically designed at the millimeter scale, have emerged as a viable alternative to traditional endoscopic methods for gastrointestinal tract diagnostics and treatment. These millirobots, capable of navigating the complex and constrained environments of the human body, offer a significant advantage by enabling thorough visualization or targeted drug delivery in a single session without the need for sedation. We previously developed a novel deployable tensegrity robot, designed for gastrointestinal diagnostics and treatment, which addresses the limitations of conventional capsule endoscopes through its unique structure and locomotion mechanism. Tensegrity structures, characterized by a network of components in tension and compression, provide an innovative solution to the challenges of designing robots for in-vivo applications. Our millimeter-scale tensegrity robot leverages the inherent advantages of such structures — lightweight, high stiffness, and adaptability — to navigate through densely packed tissues and high-pressure environments within the GI tract. Inspired by the locomotion of earthworms, the movement mechanism of the robot enables efficient navigation and precise positioning, significantly reducing the risk of retention and ensuring patient safety. This paper investigates the design and fabrication process of the tensegrity robot, focusing on achieving a high folding ratio to facilitate its deployment as a pill-based robot. Through a comparison of the robot’s fabricated dimensions with the theoretical design, we evaluate the accuracy of the fabrication process, highlighting the potential of this innovative approach in transforming GI tract diagnostics and treatment. The deployment of such tensegrity-based millirobots marks a new era in medical devices, promising enhanced patient safety and comfort through non-invasive methods.
Swarm Inspired Path-Constrained Motion Planning for Maintaining Communication Within Multiple Robot Systems
Authors: Leong Jabez Kit , Lawrence Brandon J. , Soh Gim Song 
Published: November 2024

Abstract
The involvement of Multi-robot Systems (MRS) in a vast range of missions such as search and rescue, patrolling, exploration and mapping of environments has increased over the years. The working dynamics between MRS and human operators has also evolved to include more human-in-the-loop approaches where the MRS becomes an extension of the human operator(s) to accomplish complex tasks as human-robot teams. This advancement requires a higher frequency of information sharing among the MRS and with the human operator(s) to provide situational awareness so that more informed decisions can be made rapidly. Thus, maintaining communication between the various actors of the team is key to ensure mission success. This paper explores the dynamic challenge of swarm reconfiguration to maintain communication among a system of dynamic nodes — i.e. multiple robots or humans — navigating in an urban environment. Proposed is a hierarchical robotic system that utilises a swarm of Small Supporting Unmanned Ground Vehicles (SSUGVs) as mobile communication breadcrumbs. These SSUGVs dynamically reconfigure themselves through swarm-inspired, path-constrained motion planning to maintain communication within the main system during exploration. The presented solution is verified successfully with hybrid simulations — i.e. a combination of real experimental data with simulated components on a mapping exploration task. The system is studied based on three metrics namely the system connectivity that measures the network connectivity of the overall system, the system response that measures the response of the system to a changing environment, and the average distance travelled of the system that indicates the activity level of the system.
A Piecewise Linear Piezoelectric Energy Harvester With Controllable Gap Size
Authors: Guan Yuqin , D’Souza Kiran 
Published: November 2024

Abstract
Research in the field of vibration energy harvesting has been increasing over the past decade. Researchers have developed various methods to collect unused or wasted energy from physical systems, such as bridges. This paper presents and tests a piecewise-linear (PWL) piezoelectric energy harvester design. Similar studies have been conducted for an electromagnetic energy harvester and have shown the benefit of implementing a PWL energy harvester for some potential applications. This work investigates the performance of the PWL energy harvester using a piezoelectric cantilever beam as the energy generator, which is more suitable for smaller-scale harvesting applications. The design of the piezoelectric cantilever beam system uses a simple control algorithm to maintain the optimal gap size in the system. This design actively adjusts the resonance frequency to maximize power generation over a larger frequency range to make self-powered sensors more viable. The resonance frequency is optimized by adjusting the gap size between the piezoelectric cantilever beam and an elastic stopper using a combination of linear actuators, circuits and microprocessors. The design shows an increased performance in maintaining an optimized vibrating amplitude in the pre-computed frequency range. An experimental realization of the design is tested and compared with the computational prediction to validate the design’s effectiveness.
Parametric Analysis and Design of a Triple-Magnet System for Magnetic Gravity Compensation in Linear Motion
Authors: Li Shuojie , Zeng Xiangxian , Kuo Chin-Hsing 
Published: November 2024

Abstract
This paper introduces, analyzes, and designs a magnetic gravity compensation mechanism utilizing three aligned, parallel cylindrical magnets for balancing linear motion against gravity. Unlike traditional magnet-based designs that employ numerous permanent magnets, this triple-magnet approach offers structural simplicity and high adjustability, suggesting a practical solution concept for linear-type gravity compensation. First, to determine the theoretical magnetic forces, an approach based on Monte Carlo integration is described. Several dimensional factors affecting the interactive forces between the three magnets, such as the magnetic polarization as well as the magnet radius and thickness are thoroughly investigated. It was found that increasing the thicknesses of the magnets will enhance the synthesized magnetic force without affecting the stability of gravity compensation. On the other hand, enlarging the diameters of the magnets will improve the stability of gravity compensation, but there is a bound of maximum diameters for the improvement. Accordingly, a procedure for gravity compensation design of the triple-magnet mechanism is developed. The design philosophy is illustrated through two examples, in which the design results were validated by finite-element simulation. As a result, the presented design concept holds great potential for applications, offering a reliable and efficient solution for magnetic gravity compensation in translational motion.
A Matrix-Based Approach to Unified Synthesis of Planar Four-Bar Mechanisms for Motion Generation With Position, Velocity, and Acceleration Constraints
Authors: Deng Xueting , Purwar Anurag 
Published: November 2024

Abstract
This paper introduces a novel matrix-based approach for the simultaneous type and dimensional synthesis of planar four-bar linkage mechanisms, accommodating various practical constraints, including position, velocity, acceleration, and joint placements. Traditional design processes segregate type synthesis, the determination of joint and link configurations, from dimensional synthesis, which involves specifying link sizes and pivot locations. This segregation often leads to complexities in addressing the complete design challenge. The novel methodology proposed in this paper departs from the conventional sequential design approach by concurrently evaluating type and dimensional parameters using a data-driven matrix formulation. The crux of the paper’s methodology involves formulating a singular design equation through a transformation matrix, parameterized by the Cartesian parameters of the mechanism’s dyads. This formulation linearly expresses a broad range of constraints, facilitating the identification of viable solutions through Singular Value Decomposition (SVD) and Null space analysis. This integrated approach not only simplifies the synthesis process but also provides direct insights into the mechanism’s parameters, encompassing both type and dimensions, thereby obviating the need for further interpretative steps common to the use of quaternions and kinematic mapping. In essence, the paper presents two main contributions: the development of a unified design equation capable of encompassing a wide array of constraints within the mechanism synthesis process, and the introduction of an algorithm that effectively identifies all potential planar four-bar linkage mechanisms by accurately satisfying up to five constraints. This approach promises to enhance the design and optimization of mechanical systems by offering a more holistic and efficient pathway to mechanism synthesis.
Design and Control of a Prosthetic Wrist Mechanism
Authors: Epp Jonas G. E. , Ours Madison K. , Chaplinski Payton A. , Pesch Alexander H. 
Published: November 2024

Abstract
Amputees, whether due to congenital conditions, accidents, or health issues, encounter the daily challenge of navigating life with heightened difficulty in performing essential tasks compared to the general population. While technology has made significant strides in addressing this challenge, there remains a noticeable gap in the availability of high functioning prosthetics for individuals with limited financial resources. Specifically, in the realm of upper extremities, such as the hand and forearm, the need for precise fine motor control adds a layer of complexity to the design considerations for restoring meaningful functionality to patients. Prosthetic options, such as body-powered and electromyography devices, present diverse choices for patients. While body-powered prosthetics rely on cable systems activated by body movements, electromyography prosthetics harness electrical muscle activation for precise control. This paper delves into the intricate design process of an advanced prosthetic arm, with a focus in replicating the pronation and supination of the wrist and forearm. In exploring the intricate problems associated with upper extremity amputations, this studies’ attention centers on Trans-radial amputations, among the most prevalent and complicated cases. The classification system outlines three levels: Hand, Partial Hand and Digits; Trans-radial and Wrist Disarticulation; and Trans-humeral, Elbow Disarticulation, and Shoulder Disarticulation. This research and design aims to restore functionality to Trans-radial amputees, recognizing the pivotal role hand and wrist movements play in daily activities.
Extracting Design Knowledge From Optimization Data: Application to Multi-Split Thermal Management System Configuration
Authors: Bayat Saeid , Shahmansouri Nastaran , Peddada Satya R. T. , Tessier Alex , Butscher Adrian , Allison James T. 
Published: November 2024

Abstract
As engineering systems become more complex, the traditional sources of design knowledge face limits in the rate and complexity of design knowledge generation. Additional sources of knowledge are needed to guide future design efforts, especially for unprecedented engineering systems that have no design heritage. One promising avenue lies in the analysis of design optimization data, which has the potential to offer valuable insights into unprecedented system design, and to break free from incremental improvements over heritage designs. This paper presents a step toward extracting knowledge from design optimization data. The resulting design knowledge can be used as a basis for successfully synthesizing engineering system configurations that are more complex than those the knowledge was derived from. These methods are studied here using the combined system topology and optimal control design of multi-split fluid-based thermal management systems. This knowledge generation approach offers several advantages over traditional strategies, including applicability in cases where there is no design heritage and the ability to provide normative guidance as opposed to descriptive (i.e., how should systems be designed vs. how have they been designed). Four significant case studies with varying levels of complexity are presented that demonstrate the effectiveness of using knowledge extracted from design optimization data in enhancing the design of complex thermal management systems. Our results show that the knowledge extracted in this way provides a good basis for more general design of complex thermal management systems. It is shown that the objective function value of the estimated optimal configuration closely approximates the true optimal configuration with less than 1 percent error, achieved using basic features based on the system heat loads without involving the corresponding optimal open loop control (OLOC) features. This eliminates the need to solve the OLOC problem, leading to reduced computation costs.
FE-Analytical Contact Modeling for the 3D Simulation of Bevel Gear Dynamics
Authors: Vivet Mathijs 
Published: November 2024

Abstract
The numerical prediction of spiral bevel gear contact dynamics is often hampered by the complexity of the gear tooth geometry and the three-dimensional (3D) nature of the motion transfer, which forms a major challenge for efficient contact detection and accurate contact force calculation. This works proposes a novel spiral bevel gear contact force element that enables the accurate prediction of 3D bevel gear contact force distributions in flexible multibody system dynamics simulations (MBDS). An efficient contact detection strategy, based on the surface of action, is used, while the accurate contact force calculation is obtained by inclusion of a new semi-analytical bevel gear contact stiffness model. This stiffness model relies on model order reduction (MOR) of finite element method (FEM)-based models to describe the bevel gear tooth and blank deformation, and analytical modeling to predict the tooth contact deformation. The solution can be used to model and analyze lightweight bevel gear dynamics. The method is validated against high-fidelity nonlinear finite element analysis-based contact simulations to evaluate the predicted transmission error, contact pattern, and contact pressure distribution. Finally, a use case is presented to demonstrate how the methodology enables detailed insights in spiral bevel gearbox dynamics, and noise and vibration (NVH) performance.