bluuebunny/crossref_metadata_2025_split huggingface dataset:
Potential Localized Impacts of Autonomous-Capable Electric Aircraft Tugs
Authors: Stone Brett , Jensen Matthew 
Published: November 2024

Abstract
Electrically powered, autonomous-capable aircraft tugs have the potential to reduce emissions, save fuel, reduce noise, and improve safety at airports. The demographic composition of populations living near major airports in the U.S. was investigated to determine what groups of people might benefit from such changes. Results, based off data aggregated from the U.S Census, other government agencies, and computer modeling, suggest that implementing the use of autonomous-capable electric aircraft tugs could reduce risks faced by significant numbers of members of vulnerable populations, such as those with levels of health insurance, education, income, and poverty that are worse than the median for the state in which they live.
Controlling Chaos in Rotating Systems Applying the OGY Control Method in Active Sliding Bearing Configurations
Authors: Polyzos Ioannis , Chasalevris Athanasios 
Published: November 2024

Abstract
Chaotic dynamics occur in rotating shafts mounted on sliding bearings under specific design and operating conditions. Despite the fact that chaos does not definitely prevent the operation of rotating machines, it may result to higher frictional power loss and temperature rise in bearings, compared to the case when periodic or quasi-periodic motions evolve in the operation; it is also likely to compromise the integrity of the system when whirling orbits evolve in a large extent. A rotor-bearing system consisting of a rigid rotor mounted on two journal bearings is used in this work to produce chaotic dynamics. The chaotic operation regimes of the system are first detected estimating Lyapunov exponents, 0-1 test for chaos, and Poincaré maps. Sliding bearings of active geometry are included in the physical model to enable the Ott-Grebogi-Yorke (OGY) control method as a reference solution to convert chaotic oscillations to periodic. The benefits from controlling chaos in the rotating system are investigated for a set of designs, considering frictional power loss, together with further aspects of integrity and operability of the system, like journal eccentricity. It is found that the OGY method is able to control the chaotic response and produce periodic motions of desired period, with low control effort. The results create a potential for smooth periodic motions in high-speed rotating systems.
Risk Factor Quantification for Motion Prediction in a Three-Dimensional Collision Avoidance Manual Reaching Task
Authors: Baus Juan , Yang James 
Published: November 2024

Abstract
Manual tasks like grasping and aiming require complex coordination between sensory capabilities and motor control. In the presence of obstacles, humans often overestimate the risk associated with collision due to the uncertainty of external stimuli. We present a quantification of the risk factor in multiple manual tasks on the premise that humans can adapt their motion to minimize the loss associated with collision. This study presents data collected for a reaching task around a three-dimensional obstacle chosen from five different obstacles, each with its characteristics. The empirical kinematic data and an optimization-based motion prediction algorithm provide experimental and optimal clearance distances around each obstacle. Based on the statistical decision theory, we define a loss function that will model the human risk perception, and using the collected data, we get an individual loss function depending on human performance around each obstacle. The risk factor is directly related to the clearance distance around an obstacle. It shows that the obstacle’s shape, size, and orientation are defining factors in the trajectory selection by the subjects. The risk factor quantification is the first step towards a comprehensive motion prediction model that could account for obstacle characterization and define trajectories based on what a human would do in similar situations.
A Novel Sandwich Flexure Blade With Improved Out-of-Plane Stiffness
Authors: Radgolchin Moeen , Rath Siddharth , Awtar Shorya 
Published: November 2024

Abstract
High out-of-plane stiffness is crucial in flexure-based motion stages that offer in-plane Degrees of Freedom (DoF). High out-of-plane stiffness helps support large payloads, suppress parasitic motions, and mitigate the adverse effects of out-of-plane vibration modes. Low in-plane stiffness is also essential because it increases the DoF range of motion and reduces the actuation effort. Increasing the out-of-plane stiffness and decreasing the in-plane stiffness simultaneously in flexure mechanisms is challenging because both these stiffness arise from the same flexible elements leading to an inherent tradeoff. This paper resolves this tradeoff by proposing a novel sandwich flexure blade architecture that improves the out-of-plane stiffness without affecting the in-plane stiffness. Closed-form analytical models are presented for the out-of-plane translational and rotational stiffness of the single-layer (or conventional) flexure blade and the novel sandwich flexure blade based on Timoshenko beam theory that closely match with Finite Element Analysis (FEA) results. Superior performance of the sandwich flexure blade over the conventional flexure blades is demonstrated and several design insights into the performance of the sandwich flexure blades are discussed based on the analytical stiffness models.
Optimizing Design and Control of Running Robots Abstracted as a Torque Driven Spring Loaded Inverted Pendulum
Authors: Truax Reed , Liu Feng , Chowdhury Souma , St. Pierre Ryan 
Published: November 2024

Abstract
Legged locomotion shows promise for running in complex, unstructured environments. Designing such legged robots requires considering heterogeneous, multi-domain constraints and variables, from mechanical hardware and geometry choices to controller profiles. However, very few formal or systematic (as opposed to ad hoc) design formulations and frameworks exist to identify feasible and robust running platforms, especially at the small (sub 500 g) scale. This critical gap in running legged robot design is addressed here by abstracting the motion of legged robots through a torque driven spring-loaded inverted pendulum (TD-SLIP) model, and deriving constraints that result in stable cyclic forward locomotion in the presence of system noise. Synthetic noise is added to the initial state in candidate design evaluation to simulate accumulated errors in an open-loop control. The design space was defined in terms of morphological parameters, such as the leg properties and system mass, actuator selection, and an open loop voltage profile. These attributes were optimized with a well-known particle swarm optimization solver that can handle mixed-discrete variables. Two separate case studies minimized the difference in touchdown angle from stride to stride and the actuation energy, respectively. Both cases resulted in legged robot designs with relatively repeatable and stable dynamics, while presenting distinct geometry and controller profile choices.
3D Capsule Compliant Gripper Based on Shape Optimization for Surgical Manipulation: Enhancing Precision in Lymph Node Isolation
Authors: Hermoza Llanos Estefania , Choi Myung-Jin , Sauer Roger A. , Corves Burkhard , Huesing Mathias , Klinkel Sven , Saxena Anupam 
Published: November 2024

Abstract
Compliant grippers hold great promise in improving precision and safety in Minimally Invasive Surgery (MIS), offering versatile solutions for tissue manipulation while minimizing trauma. A novel focus on a capsule-shaped compliant gripper introduces innovative design methodologies, including shape optimization and consideration of axillary lymph node dimensions. By integrating compliant beams internally and optimizing their shape and size, this gripper offers enhanced precision and adaptability in tissue manipulation, addressing specific challenges in delicate surgical interventions such as lymph node dissection in breast cancer surgery. An isogeometric approach for the analysis of geometrically nonlinear beam structures enables a seamless integration of exact geometry in CAD (Computer-Aided Design) into the analysis framework. It incorporates frictionless beam contact conditions based on a regularized penalty law, which enables an efficient and accurate simulation of the compliant grippers. Optimization results demonstrate the efficacy of the methodology in shape optimizing a set of compliant beams tailored for delicate tissue manipulation. Continued research and refinement of these methodologies are essential for furthering the field of compliant gripper design and their application in medical and surgical contexts.
Chitosan-Collagen Composite Scaffolds for Growth Direction Guidance of PC12 Axons
Authors: Tsai Po-Yu , Lin Ying-Ting , Wang Gou-Jen 
Published: November 2024

Abstract
In this study, nerve conduits of chitosan and collagen composites with biocompatibility and biodegradability were fabricated. The effects of material composition and surface morphology on the axonal growth and directionality of rat epinephric pheochromocytoma PC12 were investigated. The cells were separated by a PDMS structure to simulate nerve injury, and the growth of axons of PC12 cells was observed under the separation of large gaps. At the same time, mitochondria extracted from osteosarcoma cybrid cells (C2-GFP) were added to the culture to investigate the effect of healthy mitochondria on axon differentiation and growth. The experimental results showed that the chitosan-collagen composite film can promote the growth of PC12 axons more effectively than the pure chitosan film. Cell culture results at different groove widths also showed that smaller grooves resulted in more axon numbers and longer axon lengths. Nerve injury simulation experiments showed that the nerve repair could be almost completed after 12 days of culture.
A Digital Twin Framework Utilizing Machine Learning for Robust Predictive Maintenance: Enhancing Tire Health Monitoring
Authors: Karkaria Vispi , Chen Jie , Luey Christopher , Siuta Chase , Lim Damien , Radulescu Robert , Chen Wei 
Published: November 2024

Abstract
We introduce a novel digital twin framework for predictive maintenance of physical systems with long term operations. Using monitoring tire health as an application, we show how the digital twin framework is used to enhance automotive safety and efficiency, while overcoming technical challenges using a three-step approach. Firstly, for managing the data complexity over a long operation span, we employ data reduction techniques to concisely represent physical tires using historical performance and usage data. Relying on this data, for fast real-time prediction, we train a transformer-based model offline on our concise dataset to predict future tire health over time, represented as Remaining Casing Potential (RCP). Based on our architecture, our model quantifies both epistemic and aleatoric uncertainty, providing reliable confidence intervals around predicted RCP. Secondly, we incorporate real-time data by updating the predictive model in the digital twin framework, ensuring its accuracy throughout its life span with the aid of hybrid modeling and the use of a discrepancy function. Thirdly, to assist decision making in predictive maintenance, we implement a Tire State Decision Algorithm, which strategically determines the optimal timing for tire replacement based on RCP forecasted by our transformer model. This three-step approach ensures that our digital twin not only accurately predicts the health of a system, but also continually refines its digital representation and makes predictive maintenance decisions for removal from service. Our proposed digital twin framework embodies a physical system accurately and leverages big data and machine learning for predictive maintenance, model update and decision making.
Measuring the U. S. Biomanufacturing Economy
Authors: Thomas Douglas 
Published: November 2024

Abstract
This paper estimates biomanufacturing (manufactured products made of biomaterials) and advanced biomanufacturing (products manufactured using activities that grow biological molecules and materials along with activities that alter biological material using non-mechanical means) value added in ways that make it consistent with estimates of U.S. GDP. Direct advanced biomanufacturing is estimated as being $94.6 billion annually while total direct biomanufacturing is $438.8 billion annually. When including supply chain and other indirect value added, the total biomanufacturing industry is $1,363.8 billion and advanced biomanufacturing is $259.9 billion. These estimates include biomanufacturing products that are excluded from estimates of the bioeconomy made by other organizations and/or individuals. For instance, a report by the National Academy of Sciences defines the bioeconomy as that being “driven by research and innovation in the life sciences and biotechnology,” which tends to exclude production of many food items that are included in this paper’s estimates. Other U.S. estimates differ from estimates of GDP and value added. This paper uses the EPA TRACI measures to evaluate the environmental impact associated with the production of products in the bioeconomy. As calculated using NIST’s Manufacturing Cost Guide, the production of biomanufacturing goods accounts for 43 % of the total environmental impact resulting from economic activity in all U.S. industries while the production of advanced biomanufacturing goods is 6.4 %. This paper also examines the assets and material flow time.
Social Network Influence on Residential Solar Photovoltaic Adoption in an Agent-Based Electricity System Model
Authors: Dello Russo Gina , Wu Lei , Lytle Ashley , Odonkor Philip 
Published: November 2024

Abstract
As the United States phases out traditional fossil fuels in favor of renewable energy sources, it is important to capitalize on all available avenues to increase renewable penetration. In the last decade, the costs associated with residential solar photovoltaic (PV) installations have decreased significantly, providing more homeowners with the opportunity to generate their own clean electricity. Research has found that the decision to invest in a residential solar PV system is guided by economic, social, and personal factors. Accounting for such complexities, the joint power of agent-based modeling and social network analysis is leveraged in this study to evaluate the effect of social influence on solar PV adoption. Featuring residential consumer agents with data-driven attributes, a logistic regression function to predict solar adoption, and random and small-world social network implementations, this work simulates residential solar PV adoption in New Jersey. Results indicate that including social influence in an agent-based electricity system model leads to increased installed residential solar capacity, but not necessarily higher adoption rates. These findings suggest that, with an understanding of the intricacies of consumer social networks, there are potential opportunities to bolster residential solar installations through low-cost social campaigns that motivate individuals to adopt home solar through their social ties.
Application of Munich Agile Concept for MBSE for a Holistic Approach To Collect Vehicle Data Based on Board Diagnostic System
Authors: Salehi Vahid 
Published: November 2024

Abstract
This paper is based on four different steps. In the first step, a literature review is provided on the topic of the application of on-board diagnostic systems and their connection to digital twins in a virtual environment. In the second step, some important research questions are addressed, which are dealt with in the following sections. Based on the research questions, this paper applies a systematic method to use generated data such as GPS position, gasoline engine parameters such as speed/revs, and the vehicle’s gasoline battery to enrich a digital data environment for virtualization and simulation. This technical paper explores the use of On-Board Diagnostic II (OBD-II) interfaces to collect data from gasoline vehicles and the subsequent analysis of this data using systems engineering methods. The paper will present the results of gasoline vehicle testing based on OBD-II data and Model Based Systems Engineering (MBSE) using the Munich Agile Concept for Systems Engineering (MAGIC) to design a system-of-systems approach based on Digital Twin Data. This paper and the corresponding research project will develop a consistent, traceable, holistic system-of-systems engineering approach for digital twins. MBSE is based on three important core pillars: 1) Methods/Processes, 2) Language and 3) Systems. The purpose of the newly developed Munich Agile Concept Approach is to manage complexity throughout the data collection, data processing and data virtualization process from a real environment to a virtual Digital Twin environment. The Munich Agile Concept contains six different levels: System Requirement, System Function, System Architecture, System Validation, System Test and System Usage Level. A graphical language called System Modeling Language (SysML) was used to define the first three levels. In the final step, this paper will report on the experiences made and the results of the applied MAGIC approach in Model Based Systems Engineering.
Development of an Optimal Variable-Pitch Controller for Floating Axial-Flow Marine Hydrokinetic Turbines
Authors: Sundarrajan Athul Krishna , Tran Thanh Toan , Wiley Will , Ross Hannah , Zalkind Daniel , Herber Daniel R. 
Published: November 2024

Abstract
This article discusses the development of an optimal variable-pitch controller for floating, axial-flow marine turbines. Recently, OpenFAST, an open-source wind turbine modeling tool, has been extended to model marine turbines. A controller is necessary to simulate marine turbines for different load cases using OpenFAST, which greatly impacts the performance of the energy system. Previous studies have designed controllers using a linearized model of the marine turbine, which can be time-consuming and require the expertise of a control engineer. In this study, we use an automated approach that uses generic models of the marine turbine to identify the controller gains, which can expedite the process of designing a controller. Using an optimizer to identify the control system parameters can additionally improve the controller’s performance. The optimal controller tuned using such an approach results in a 20% reduction in the tower-base damage equivalent loading and better tracking of the rated generator speed and power.
Operating Behavior and Performance of Polymer Gears in Pulsator Tests
Authors: Reitschuster Stefan , Tobie Thomas , Stahl Karsten 
Published: November 2024

Abstract
For designing gears reliable strength values are essential. The determination of strength values for the tooth root load-carrying capacity is usually based on experimental fatigue tests in a pulsator due to various advantages compared to back-to-back tests. In contrast to steel gears, it is currently unclear how polymer gears perform in the pulsator test and whether the pulsator test is suitable for determining the tooth root load-carrying capacity of such gears. Against this background, theoretical and experimental investigations on the operating behavior and fatigue life of POM gears were conducted and evaluated. Measurements on the tooth temperature under dynamic load provide insights into the thermal behavior of polymer gears, which must be considered due to the high-temperature dependency of the mechanical properties. Based on theoretical studies on the tooth root stress in the pulsator, S-N curves are determined and evaluated for different tooth temperatures revealing comparable tendencies to results from the back-to-back test in terms of damage pattern as well as service life.
Characterizing Model Fidelity Through a Set-Based Approach
Authors: Taylor Evan , Louis Ed , Mocko Gregory , Li Gang , Hybl Evan 
Published: November 2024

Abstract
Simulation models are often used in design to predict system performance for several use cases including trade space exploration, decision-making, and validation and verification. Models are abstractions of reality and do not contain all the phenomena and details in the real world. This fact brings many concerns, such as “How can I trust this model?” or “How should I choose between models?”. In modeling and simulation (M&S), the concept of fidelity explains how a model differs from reality. This paper proposes a set-based definition of fidelity based on the reduction of information throughout the model development process. An example of a ground vehicle conducting a gradeability test demonstrates the reduction in information from reality, the known world, testing, modeling, and simulation. Overall, this set-based approach to fidelity bridges disparate definitions of fidelity and creates a greater understanding of how models reflect reality.
Walking Gait, Energy Efficiency, and Energy Harvesting of a Simple Biped Robot
Authors: Wang Fengxia 
Published: November 2024

Abstract
To design energy efficient robots, researchers have dedicated themselves to examining the locomotion dynamics and walking pattern generation of passive bipeds. As the walking environment or system parameter changes, an energy use efficient robot may become inefficient, a possible approach to increase the energy efficiency is through the ability to harvest the energy used during the locomotion. The goal of the paper is to investigate the relations of a biped’s walking speed, locomotion energy consumption, as well as the ability to retrieve the lost energy as system parameter varying. Piezoelectric bimorphs were attached to the feet of the biped to harvest energy via exploiting the acceleration excitations induced vibrations at the instant foot lift and heel strike. As the incline angle of the ramp slope increases, the stable periodic-1 (P1) walking gait becomes faster and more energy costing. Also means more available energy to harvest, although the retrieved energy is much smaller compared to the locomotive energy. As the slope angle continues growth, the stable walking experiences sequence of period doubling (PD) bifurcations, becomes P2, P4, P8, and Chaos walking. As the walking gaits change, the walking speed, locomotion energy consumption, as well as the harvested energy grows as the slope becomes deeper.
Human Assembly Action Recognition Framework for Real-World Assembly Operation
Authors: Yang Chao-Lung , Kao Tzu-Ching , Lin Po Ting , Fu Pin-Cheng 
Published: November 2024

Abstract
In recent years, significant progress has been proceeded in human action recognition (HAR) technology. When applying HAR to practical scenarios, especially in the task of recognizing Standard Operating Procedures (SOP) for factory operators, some challenges such as resource requirements, differentiation of diverse movements, and difficulties in manual annotation exist. In this research, an assembly action recognition framework (AARF) was proposed to recognize the assembly operation conducted at the station level using the SlowFast video understanding model. First, the pre-trained YOLOv7 model is employed as a non-assembly action filter to detect the main operator, and then the irrelevant background is masked for a refined region of interest. Then, the preprocessed data is fed into SlowFast for action recognition through both temporal and spatial features. Finally, the confidence calibration strategy is implemented to enhance the robustness of results. A series of ablative experiments were conducted to study for optimizing the selection of model parameters, incorporating attention mechanism, non-assembly action filtering, and recognition result filter. Multiple assembly motion videos were collected from two similar product lines at a real-world production line. According to experimental results, the proposed method can improve the accuracy of human motion recognition on real factory production lines by up to 86.3%.