bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robotic Exoskeleton Glove System Design and Simulation for Patients With Brachial Plexus Injuries
Authors: Xu Wenda , Guo Yunfei , Ben-Tzvi Pinhas 
Published: November 2023

Abstract
This paper presents a novel robotic exoskeleton glove system for patients who suffer from brachial plexus injuries. The robotic exoskeleton glove systems takes advantage of our previously designed rigid coupling hybrid mechanism (RCHM) concept that was used for the index finger mechanism design of the exoskeleton glove. The finger mechanism utilizes the single degree of freedom case of the RCHM that combines a rack-and-pinion mechanism and offset-slider-crank mechanism as the rigid coupling mechanism. The serial and special arrangement enables the design of each finger mechanism of the glove with reduced degrees of freedom while more closely imitating the human hand motion. The exoskeleton glove is designed to assist patients with hand disabilities in daily activities, and as such, it is optimized to be compact, lightweight, and portable, and includes modulated electronics for everyday use. The control system contains low-level motor control and high-level human-machine interface components, which enable safe and intuitive control of the exoskeleton glove, thereby enhancing the user’s ability to perform various daily activities. A high-level user interface voice activation is also integrated into the system. The paper also describes a simulation environment that was developed using MATLAB Simscape and was designed to test out and optimize different control algorithms.
Coupling Simulated Annealing and Homogenization to Design Thermally Conductive Hybrid Lattice Support Structures for LPBF
Authors: White Lisha , Liang Xuan , Zhang Guanglu , Cagan Jonathan , Zhang Yongjie Jessica 
Published: November 2023

Abstract
When designed effectively, support structures for Laser Powder Bed Fusion (LPBF) quickly dissipate heat and mitigate part distortion without driving up excessive costs. Lattices, composed of individual unit cells strategically arranged to achieve a desired function, are a promising solution as support structure. Prior research utilizing gradient-based optimizers to design lattice support structures for heat dissipation pose challenges regarding limited design exploration and non-differentiable design variables. Non-gradient-based optimizers are an alternative solution but are known to be too slow compared to gradient-based optimizers and have not yet been applied to optimize the heat dissipation of lattice support structures. Thus, this paper presents a computational framework that facilitates the design of lattice support structures with stochastic optimization to maximize heat dissipation. Simulated annealing (SA) is utilized to quickly optimize the distribution of three commonly employed unit cells while adhering to user-defined manufacturing constraints. By incorporating both stage-dependent actions and homogenization approximation with SA, a broader exploration of the design space is accomplished without compromising computation time. The framework is validated through the case study of a cantilever beam by generating optimal hybrid lattice support structures with about 16% better heat dissipation than the uniformly distributed benchmark design with manufacturing constraints satisfied.
Frequency Response Based Optimization of an Aircraft Hydraulic Pump Support Structure
Authors: Kersten Simon T. , Mechefske Chris K. 
Published: November 2023

Abstract
Free-size optimization is an effective method for determining the optimal thickness of the elements in a finite element model given a set of constraints and objectives. This work aims to show that size optimization can be used as a tool to reduce the structural vibrations transmitted from non-structural components on-board an aircraft into the cabin. A test structure of a hydraulic pump support frame is analyzed using a frequency response analysis. The output velocity is measured for three independent dynamic input loads across a 20–4000 Hz bandwidth. The maximum frequency response velocity for each input load was used to define the upper bounds of the velocity for the optimized model. The design space had a minimum thickness equal to the original thickness and a maximum thickness of 1.5 times the original thickness. The objective was to determine the optimal locations for new material to be added, so that the original design was not significantly changed. This was done to ensure the structural integrity of the frame and increase the ease of implementing the design while still reducing the transmission of structural vibrations. The optimized model showed an average reduction of 6% in the maximum frequency response velocity for the three loading directions, while increasing the mass by 9%.
Study on Driver’s Preview Distance Based on Driving Simulator Tests
Authors: Gobbi Massimiliano , Mastinu Giampiero , Milivinti Massimiliano , Previati Giorgio , Ríos Hidalgo Daniel 
Published: November 2023

Abstract
Several simplified driving models used nowadays assume that the drivers’ preview distance is mainly dependent on the vehicle speed. The scope of this paper is to analyze the behavior of a sample of drivers during a lane change test, evaluating specifically the evolution of their preview distance.
In order to undergo this study, the tests are performed in a DiM400 dynamic driving simulator installed at Politecnico di Milano. The preview distance is measured while performing a specially designed test, divided in straight and double lane change sections, at a constant speed of 80 km/h. Furthermore, a wearable eye tracker is used to acquire the data from the drivers’ eyes. Finally, a simple method to estimate the preview distance under the testing conditions of this project is undergone.
Opposite to what it is mainly stated in the literature, it can be observed a clear variation of the preview distance along each of the tests performed in the simulator. Drivers seem to increase it when driving straight, while they reduce it considerably to perform the double lane change maneuver. The algorithm developed in this paper provides an easy estimation of this quantity, although several limitations must be taken into account.
Exploration of Building Clustering Potential With Energy Storage in New York City
Authors: Kaminski Gregory , Odonkor Philip 
Published: November 2023

Abstract
The adoption of distributed energy resources has increased in recent years due to decreasing implementation costs and increasing regulatory incentives to reduce energy consumption. This trend has been driven by a surge in energy consciousness and the availability of energy-saving products and technologies. Many energy consumers are also electing to use battery systems to store energy locally, further reducing reliance on the electrical grid and maximizing the benefits of distributed energy systems. For owners of multiple buildings, or multiple owners willing to share the operational cost, building clusters may be formed to more effectively take advantage of these distributed resources and storage systems. However, determining what makes a “good” building cluster when implementing these systems in existing buildings is a challenge. Additional challenges are presented when geographical proximity of these buildings is considered. Using metrics derived from comparison of unique five-building clusters from a population of sixteen stock buildings with a given distributed energy resource (in this case, a solar photovoltaic panel array) and energy storage system, we apply performance ranking information to a population of actual building data from New York City. In doing so, the authors aim to build upon the concept of logical building clusters with consideration of physical building location to develop an understanding of which geographic areas present the greatest opportunity for clustering.
Proposed Design for Electromechanical Telescoping Actuator to Replace Hydraulics in Extreme High Force and Long Stroke Applications
Authors: Sleight Crawford Carmen , Smyk Mariia , Cheung Sophia , Coughran Doug , Costello Jeffrey , Liang ZhiYi , Winter Amos G. 
Published: November 2023

Abstract
The increasing demand for electrification in various industries has led to the need for new technology to evolve and support this shift. Manufacturers in the industrial and military market are exploring the electrification of its hydraulic actuation devices in order to improve efficiency, sustainability, and maintenance. However, replacing hydraulic actuators with electromechanical alternatives presents a significant challenge, particularly in high force, high stroke applications that require a stroke length of 2.4 m (8 ft) to 6.7 m (22 ft) and the delivery of 150 kN of force. In this paper, we present the design and scaled-prototype of an electromechanical telescoping actuator architecture that can meet these demanding requirements. The proposed design relies on screw and nut mechanisms that are engaged simultaneously in a telescoping manner and is able to achieve more than double extension of its collapsed length. Our group was able to successfully develop and evaluate the design and build a scaled-down prototype that could likely serve as a direct replacement for currently used long-stroke high-force hydraulics. The prototype was able to achieve extension from 17 cm (7 in) to 49 cm (19.2 in) with 10 s cycle time, and is able to lift at least 28 N (6.3 lbf). This work was done in partnership with Oshkosh Corporation.
Animated Point Clouds Real-Time Rendering for Extended Reality
Authors: Piazzolla Pietro , Rossoni Marco , Pozzi Matteo , Colombo Giorgio , Gribaudo Marco 
Published: November 2023

Abstract
Point cloud 3D models are becoming more and more popular thanks to the spreading of scanning systems employed in many fields, like autonomous vehicles and robotics. When used for rendering purposes, point clouds are usually displayed with their original color acquired at scan time, without considering the lighting condition of the scene where the model is placed. This leads to a lack of realism in many contexts, especially in the case of animated point clouds employed in eXtended Reality applications where it would be desirable to have the model reacting to incoming light and integrating with the surrounding environment. This paper proposes the application of Physically Based Rendering (PBR), a rendering technique widely used in Real-Time Computer Graphics applications, to animated point cloud models for reproducing specular reflections, and achieving a photo-realistic and physically accurate look under any lighting condition. Firstly, we consider the extension of commonly used animated point cloud formats, to include normal vectors, and PBR parameters (such as roughness and Metalness), as well as the encoding of the animated environment maps required by the technique. Then, an animated point cloud model is rendered with a shader implementing the proposed PBR method. Finally, the proposed PBR pipeline is compared to traditional renderings of the same point cloud obtained with commonly used shaders, under different lighting conditions in different environments. It will be shown how, using the proposed PBR method, the point cloud better integrates visually with its surroundings. Moreover, it will be shown that using this rendering technique it is possible to render different materials, by exploiting the features of PBR and the encoding of the surrounding environment.
High-Speed Schlieren Imaging of Shock Waves for the Study of Tympanic Membrane’s Response
Authors: Oliveira Luiz Jonathan , Alipanahi Anahita , Cheng Jeffrey Tao , Rosowski John J. , Furlong-Vazquez Cosme 
Published: November 2023

Abstract
The mechanics of tympanic membrane (TM) fractures resulting from exposure to high-pressure blasts are not yet fully understood. To investigate TM responses to such events, shock tubes can be utilized as loading devices. The effective use of these devices requires proper characterization. One appropriate method for visualizing the shock waves produced by a shock tube is high-speed Schlieren imaging, which can provide both qualitative and quantitative information. In this paper, we present a shock tube integrated with a high-speed Schlieren system and high-speed dynamic pressure transducers. The highspeed Schlieren system allowed us to observe the shock waves emitted from the shock tube and characterize the Mach number of each wave. The flow structures generated from the tube exit were identified and synchronization between Schlieren images and pressure data was achieved. The shock tube showed good repeatability and generated supersonic blasts capable of rupturing TM samples, with a shock Mach number of up to 1.4. The versatile and cost-effective nature of the shock tube opens new possibilities for understanding the real-time mechanics of TM fractures and investigating their dynamic response in the future, when even more sophisticated quantitative optical techniques will be used to investigate the TM’s behavior in these conditions.
Automating Style Analysis and Visualization With Explainable AI - Case Studies on Brand Recognition
Authors: Chen Yu-Hsuan , Kara Levant Burak , Cagan Jonathan 
Published: November 2023

Abstract
Incorporating style-related objectives into shape design has been centrally important to maximize product appeal. However, stylistic features such as aesthetics and semantic attributes are hard to codify even for experts. As such, algorithmic style capture and reuse have not fully benefited from automated data-driven methodologies due to the challenging nature of design describability. This paper proposes an AI-driven method to fully automate the discovery of brand-related features. Our approach introduces BIGNet, a two-tier Brand Identification Graph Neural Network (GNN) to classify and analyze scalar vector graphics (SVG). First, to tackle the scarcity of vectorized product images, this research proposes two data acquisition workflows: parametric modeling from small curve-based datasets, and vectorization from large pixel-based datasets. Secondly, this study constructs a novel hierarchical GNN architecture to learn from both SVG’s curve-level and chunk-level parameters. In the first case study, BIGNet not only classifies phone brands but also captures brand-related features across multiple scales, such as the location of the lens, the height-width ratio, and the screen-frame gap, as confirmed by AI evaluation. In the second study, this paper showcases the generalizability of BIGNet learning from a vectorized car image dataset and validates the consistency and robustness of its predictions given four scenarios. The results match the difference commonly observed in luxury vs. economy brands in the automobile market. Finally, this paper also visualizes the activation maps generated from a convolutional neural network and shows BIGNet’s advantage of being a more human-friendly, explainable, and explicit style-capturing agent.
Finite Element Simulation of Gleeble Testing Toward Thermomechanical Analysis of Alloy Materials
Authors: Xu Dong , Zhang Kevin J. , Frame Lesley D. , Kim Jeongho , Tang Jiong 
Published: November 2023

Abstract
This study investigates the mechanical behavior of alloy materials at high temperature (750°C) by correlating finite element simulation with the experimental testing using Gleeble system. Traditionally, such characterization is challenging due to the measurement challenges in experimentation. In this research the Gleeble 3500 physical simulator is used to collect experimental data under specific temperatures and strain rates, providing necessary data for parameter identification. In order to accurately analyze the underlying physical process, the temperature gradient of the specimen during Gleeble testing needs to be considered. As such, a comprehensive finite element based analysis is established to study the temperature/stress distribution during the testing process. An empirical constitutive model, the Johnson-Cook constitutive relation, is adopted to characterize the mechanical behavior of metal materials at high temperatures and high strain rates. Parameters from reference material are used to facilitate initial analysis, which are subsequently modified empirically to examine the parametric influence. To reduce the computational cost, simulation simplification is explored. Through analyzing the predicted results of stress and force, this study provides insights to the importance of developing high fidelity finite element simulation that can authentically duplicate the actual physical process. The analysis formulation will play key role in facilitating optimized identification of material parameters utilizing Gleeble testing data.
An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization
Authors: Massoudi Soheyl , Picard Cyril , Schiffmann Jürg 
Published: November 2023

Abstract
Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocompressors supported on gas bearings, which utilizes surrogate models and ensemble learning with artificial neural networks. The proposed approach addresses the limitations of nominal and separate optimizations by integrating all relevant design aspects into a single optimization problem. A multi-objective optimization is carried out, considering four objectives and over twenty constraints, including robustness against manufacturing deviations of the radial and axial bearings in terms of stability, load capacity, and efficiency, as well as robustness against performance metric gradients. The proposed methodology maximizes the compressor’s range in speeds and mass flow, while also maximizing the signal-to-noise ratio of the isentropic efficiency over the compressor map. Additionally, the approach maximizes system efficiency, taking into account component losses and isentropic efficiency of the compressor. To enable rapid and automated integrated design, the methodology reduces the compressor representation to a fully cylindrical representation. The study finds that the proposed methodology has the potential to significantly enhance the overall performance of turbocompressors in terms of efficiency, stability, and robustness. The methodology eliminates the need for sequential and iterative design steps, providing an optimal starting point for higher representation of the system with CFD and finite elements study. Furthermore, the proposed methodology has broad applications, including the optimization of other complex and interdependent systems in various fields. This study highlights the crucial role of a comprehensive and integrated approach to turbocompressor design and provides a valuable framework for future research in this area.
Predicting Vehicle Motion in Shallow Water with Data-Driven Hydrodynamics Model
Authors: Yamashita Hiroki , Martin Juan E. , Sugiyama Hiroyuki , Tison Nathan , Grunin Arkady , Jayakumar Paramsothy 
Published: November 2023

Abstract
In this study, a numerical procedure for predicting vehicle mobility in shallow water is proposed with the data-driven hydrodynamic force and moment model. To this end, the high-fidelity coupled CFD-MBD model is developed to characterize the hydrodynamic loads exerted on the vehicle in shallow water and used to generate the training dataset for the proposed data-driven model. The neural networks are called from the MBD mobility solver every time step to determine the hydrodynamic loads, given the current vehicle motion states and water conditions, allowing for predicting the transient responses of the vehicle interacting with shallow water. It is demonstrated by several numerical examples that the complex vehicle-water interaction behavior was accurately predicted by the proposed data-driven hydrodynamics model while achieving a substantial computational speedup.
Let’s Chat If You Are Unhappy – The Effect of Emotions on Interaction Experience and Trust Toward Empathetic Chatbots
Authors: Liao Ting , Yan Bei 
Published: November 2023

Abstract
Chatbots are now prevalent in obtaining information and executing tasks on behalf of human users. While the design community has paid more attention to streamlining user-chatbot interactions, the existing literature has not thoroughly examined social elements such as emotions and understood how emotions influence user interaction and trust in chatbots. This study proposes to test how participants perceive an empathetic chatbot versus a non-empathetic one under various emotional states (i.e., positive, neutral, negative) when the chatbot facilitates conversations for student advising via an online platform. The study shows the importance of presenting empathetic cues in the design of chatbots or other intelligent agents. The empathetic behavior of the chatbot improves participants’ trust and perception of the chatbot’s performance. The improvement is more salient to people with negative emotions than people who feel neutral or positive. This interaction effect is explained by people’s perceived effort of the chatbot during the interaction with people, even though the chatbot is a technological agent that acts based on algorithms. The results suggest that people attribute human qualities to chatbots in social interaction and highlight the emotional needs of people who experience negative emotions. Therefore, design efforts need to be designated according to people’s dynamic emotional states.
Selectively Stiffened Integrated Composite Hinge
Authors: Klocke Philip , Skinner Mitchel , George Andy , Magleby Spencer 
Published: November 2023

Abstract
Fiber-reinforced composites have potential advantages for manufacturing origami arrays. However, methods for manufacturing large origami arrays using composite materials are complex, time-consuming, and expensive. This research proposes two processes for synthesizing origami-based arrays, each made using fiber-reinforced composites and requiring only a single layup. The overarching principle used in these processes is to selectively modify the stiffness in the composite array, thus forming both the panels and hinge lines of an origami array. The feasibility of using these processes to produce deployable carbon fiber arrays is then demonstrated.
Design of Unhinged Compliant Mechanism to Enable Bistable Segments in Continuum Robots
Authors: Niazi Muhammad Umer Khan , Mehmood Usman , Choi Jaesoon , Moon Youngjin 
Published: November 2023

Abstract
Continuum robots have seen increased utilization in various fields such as aerospace, rescue operations, human interaction, and especially medicine. More specifically, in medicine, continuum robots have enabled minimally invasive surgeries and faster patient recovery time. However, the design of continuum robots needs to be improved, especially by enhancing or incorporating characteristics that improve functionality across various applications. This paper explores different mechanisms, including bistable, compliant, and lamina emergent mechanisms, to achieve these design goals. Specifically compliant bistable mechanisms which can store energy when deformed and utilize this energy to transition from one state to another have shown significant promise for the design of continuum robots. In this paper we explore the characteristics and functions associated with compliant bistable mechanisms and their potential integration in device designs, we review the design process for adapting compliant bistable mechanisms to continuum robots, highlighting the challenges and considerations involved. We also present two examples of applications to continuum robot designs that demonstrate the potential of compliant mechanisms for creating varied functionality for a number of applications. By understanding the capabilities and limitations of compliant mechanisms, we can advance the design of continuum robots, which presents a significant opportunity for innovation and progress in the field of medical device design.