bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nonlinear Energy Sink and Targeted Energy Transfer in Smart Structures
Authors: Dekemele Kevin , Van Torre Patrick , Loccufier Mia 
Published: November 2022

Abstract
Nonlinear energy sinks (NESs) are strongly nonlinear mechanical oscillators that are weakly coupled to a mechanical primary system. Through targeted energy transfer (TET), vibration energy is irreversibly transferred from the primary system to the NES, making the NES an attractive passive vibration control device. Furthermore, because of the NES’ strong nonlinearity, the NES has a variable natural frequency, unlike linear vibration control devices. This enables a self-tuning property where the NES adapts to the primary system’s vibration frequency, making the NES a broadband vibration absorber. This self-tuning extends to multi-frequency vibrations through resonance capture cascade (RCC), where the NES tunes itself to the different frequencies in sequential order. Recently, some works have discussed the piezoelectric NES, a nonlinear electrical circuit that interfaces with a mechanical system through a piezoelectric transducer. This paper will show for the first time that by using an electromagnetic transducer instead of a piezoelectrical transducer, an electromagnetic NES is obtained. Furthermore, this work will show that dynamics of mechanical, piezoelectric and electromagnetic NESs can be generalized under a universal NES in a slow flow expression and that resonance capture cascade occurs for all the NES types. The performance of the NES configurations are compared and their physical components are discussed.
Modeling Large Deformable Terrain With Material Point Method for Off-Road Mobility Simulation
Authors: Chen Guanchu , Yamashita Hiroki , Sugiyama Hiroyuki , Ruan Yeefeng , Jayakumar Paramsothy , Gorsich David , Leiter Kenneth W. , Knap Jaroslaw , Yang Xiaobo 
Published: November 2022

Abstract
In this study, a computational framework for the material point method (MPM) terrain model is developed for off-road mobility simulations to account for large granular terrain deformation in high-fidelity off-road mobility simulations. The Lagrangian finite element (FE) approach is not suited for modeling very large soil deformation due to mesh distortion, which causes element instability. Whereas the discrete element (DE) approach has gained acceptance in modeling complex granular material behavior, the computational cost is, in general, prohibitively high due to a large number of particles needed to describe not only the grain-scale material behavior, but also the macro-scale large soil deformation. Therefore, this study examines the use of MPM to model large deformable granular terrain in the context of off-road mobility prediction. To this end, MPM terrain models are developed and integrated into the off-road mobility simulation framework, leveraging high-performance computing. Furthermore, a contact modeling procedure for the FE tire and MPM terrain is developed, along with the moving soil patch technique generalized for the MPM terrain with the background grid. The MPM soil model is validated against test data, and its large deformation modeling capabilities are examined with several numerical examples.
Flexible Multibody Model of a Complete Tiltrotor for Aeroservoelastic Analysis
Authors: Cocco Alessandro , Savino Alberto , Masarati Pierangelo 
Published: November 2022

Abstract
This work presents a numerical validation and capability demonstration of the solver MBDyn when applied to a complex tiltrotor model. The Bell XV-15 tiltrotor equipped with Advanced Technology Blades (ATB) is chosen since a considerable amount of data is publicly available. The multibody modeling of each sub-component, i.e. the rotor, blades, yoke, drive system, and the airframe is illustrated and validated considering experimental and numerical results. This work is a first step towards further, more complex analyses, such as whirl-flutter stability assessment, transient maneuvers, and pilot-vehicle interaction.
Self-Aligning Rotational Latching Mechanisms
Authors: Fernandez Gabriel I. , Gessow Samuel , Quan Justin , Hong Dennis 
Published: November 2022

Abstract
In concurrent work, we introduced a novel robotic package delivery system LIMMS (Latching Intelligent Modular Mobility System). Each of LIMMS’ end effectors requires a small, lightweight latching mechanism for pre-manufactured containers such as cardboard boxes. In order to effectively process a high volume of packages, aligning the latching mechanism quickly and reliably becomes critical. Instead of depending on highly accurate controllers for alignment, we propose a novel self-aligning rotational mechanism to increase the system’s tolerance to misalignment. The latching design consists of evenly spaced blades that rotate into slots cut into the box. When misaligned, the blades contact the edges of the engagement slots, generating a self-correcting force that passively centers the blades with the slot pattern. This paper introduces a mathematical framework with closed form expressions to quantify error tolerance for for these mechanisms. Through our mathematical and optimization analyses, it is shown that a 2-blade design can tolerate a maximum misalignment: 5 ≈ 2.236 times the radius of the blade tips. Our approach can be generalized for a class of rotational latching mechanisms with any number of blades. Utilizing this theory, a design process is laid out for developing an optimal self-aligning rotational latching mechanism given desired parameters and task constraints. With this methodology, we designed, manufactured, and verified the effectiveness of both 2-blade and 3-blade self-aligning latches in practical experiments.
Disassembly Analysis of Gas Cooktops: Towards Eco-Design Rules for Product Repairability
Authors: Boix Rodríguez Núria , Favi Claudio 
Published: November 2022

Abstract
The ease of disassembly and the application of repairability metrics are important in determining the ability to repair industrial products and goods (e.g., ease of Disassembly Method, Repair Scoring System, French repairability index, etc.). Increasing product repairability is a key aspect to tackle during the product development process aiming at the product lifetime extension and the reduction of industrial waste. The purpose of this work is to find eco-design actions by examining the ability to disassemble key components in different types of gas hobs. After the definition of target components, several disassembly tests were performed following the method proposed by the Joint Research Centre’s report (Analysis and development of a scoring system for repair and upgrade of products) and the European standard EN 45554 (General methods for the assessment of the ability to repair, reuse and upgrade energy-related products). The Disassemblability Index of each priority part has been calculated, being able to verify that one of the factors that affect the most is the number of steps needed to remove the component. The outcomes offer interesting insights into the characterization of disassembly issues as well as for the identification of possible eco-design actions making the product repairability efficient and less costly.
Phononic Metamaterial Design via Transfer Learning-Based Topology Optimization Framework
Authors: Wang Zihan , Zhuang Ran , Xian Weikang , Tian Jiawei , Li Ying , Chen Shikui , Xu Hongyi 
Published: November 2022

Abstract
Phononic metamaterials are widely used to attenuate wave propagation. However, designing the structure of phononic metamaterial remains a challenge. In this work, we proposed a transfer learning-based design framework to accelerate the design of phononic metamaterials with wide bandgaps. First, we establish a transfer learning model with convolutional layers. This model leverages the knowledge learned from the structure-elasticity dataset to predict the structure-phononic property relationship. We demonstrate that the transfer learning model achieves good prediction accuracy with limited training data. We also discuss the feasibility of using the structure-elasticity model to benefit the design optimization of phononic metamaterials. Then we propose a transfer learning-based design framework for the topology optimization of cellular metamaterial for optimal phononic properties (bandgap width). Parametric optimization is conducted to find the optimal structure features that lead to the widest bandgap. The structure features are represented by an embedding layer shared by the structure-elasticity and the structure-phononic property models. Next, the corresponding elastic stiffness constants are obtained via the structure-elasticity model. Then topology optimization is employed to generate the metamaterial structural images corresponding to the target elastic stiffness constant values. The effectiveness of the proposed design framework is validated by comparing the performances of design candidates with existing designs.
A Comparison of Graph-Theoretic Approaches for Resilient System of Systems Design
Authors: Chatterjee Abheek , Helbig Cade , Malak Richard , Layton Astrid 
Published: November 2022

Abstract
System of Systems (SoS) are networked integration of constituent systems that together achieve new capabilities not possible through the operation of any single system. SoS can be found across all aspects of modern life such as power grids, supply chains, and aerospace operations. Their resilience (being able to withstand and recover from disruptions) is a critical attribute whose evaluation is nontrivial and requires detailed disruption models. Engineers rely on heuristics (such as redundancy and localized capacity) for achieving resilience that often result in unacceptable operation costs, erosion of profits, over-consumption of natural resources, or unacceptable levels of waste or emissions. Graph-theoretic approaches provide a potential solution to this challenge as they can evaluate architectural characteristics without needing detailed performance simulations, supporting their use in early-stage SoS architecture selection. However, no consensus exists as to which graph-theoretic metrics are most valuable for SoS design and how they should be included in the design process. In this work, multiple graph-theoretic approaches are analyzed and compared, on a common platform, for their use as design tools for resilient SoS. The metrics Density, Total Degree Heterogeneity, Modularity, Specialized Predator Ratio, Generalization, Vulnerability, and Ecological Fitness are found to be viable options for the development of early stage resilient SoS design tools and operation-specific applications.
Human Hand Motion Prediction in Disassembly Operations
Authors: Liao Hao-yu , Zheng Minghui , Hu Boyi , Behdad Sara 
Published: November 2022

Abstract
The remanufacturing workforce can benefit from the capabilities of robotic technology, where robots can alleviate the labor-intensive nature of disassembly operations and help with handling toxic and hazardous materials. However, operators’ safety is an important aspect of human-robot collaboration in disassembly operations. This study focuses on predicting human hand motion to provide advanced information to disassembly robots when collaborating with humans. A prediction framework is proposed, which consists of two deep learning models, including convolutional long short-term memory (ConvLSTM) and You Only Look Once (YOLO). ConvLSTM forecasts the next-frame image using images from the disassembly process, and then the YOLO model identifies the human hand object on the predicted image resulting from ConvLSTM. The disassembly images collected from four desktop computers are used to train the ConvLSTM and YOLO. The results reveal that the combined framework of ConvLSTM and YOLO performs well in predicting human hand motion and locating the hand object. The outcomes highlight the need for developing deep learning models capable of recognizing human motion when working with different designs as often remanufacturing workforce have to deal with a wide range of products from different brands, models, and conditions.
Application Oriented Modelling and Simulation of an Innovative Parallel Robot for Single Incision Laparoscopic Surgery
Authors: Pisla Doina , Gherman Bogdan , Tucan Paul , Birlescu Iosif , Pusca Alexandru , Rus Gabriela , Pisla Adrian , Vaida Calin 
Published: November 2022

Abstract
Single-incision laparoscopic surgery (SILS) is on the path of becoming a standard procedure in minimally invasive surgery due to the outstanding results obtained both during and after the medical act, these being defined by the reduced hospitalization time, the reduced recovery time, and the reduced visibility of the incision. The paper presents the modeling and simulation of a new parallel robot concept with 6 Degrees of Freedom (DOF), called PARA-SILSROB used for the single incision laparoscopic surgery. The paper focuses on the inverse kinematics, the preliminary design, and the robot control system architecture of PARA-SILSROB. A CAD motion simulation validates the mathematical model using Siemens NX.
Identifying the Effects of Immersion on Design for Additive Manufacturing Evaluation of Designs of Varying Manufacturability
Authors: Mathur Jayant , Miller Scarlett R. , Simpson Timothy W. , Meisel Nicholas A. 
Published: November 2022

Abstract
The demand for additive manufacturing (AM) continues to grow as more industries look to integrate the technology into their product development. However, there is a deficit of designers skilled to innovate with this technology due to challenges in supporting designers with tools and education for their development in design for AM (DfAM). There is a need to introduce intuitive tools and knowledge to enable future designers to DfAM. Immersive virtual reality (VR) shows promise to serve as an intuitive tool for DfAM to aid designers during design evaluation. The goal of this research is to, therefore, identify the effects of immersion in design evaluation and study how evaluating designs for DfAM between mediums that vary in immersion, affects the results of the DfAM evaluation and the mental effort experienced from evaluating the designs. Our findings suggest that designers can use immersive and non-immersive mediums for DfAM evaluation without experiencing significant differences in the outcomes of the evaluation and the cognitive load experienced from conducting the evaluation. The findings from this work thus have implications for how industries can customize product and designer-talent development using modular design evaluation systems that leverage capabilities in immersive and non-immersive DfAM evaluation.
Finding Optimal Sequence of Mobile Manipulator Placements for Automated Coverage Planning of Large Complex Parts
Authors: Malhan Rishi , Gupta Satyandra K. 
Published: November 2022

Abstract
Sensors are widely used in the industry to collect information about a physical object. Operational range of the sensor is limited and therefore the sensor needs to be moved around a large complex part in order to capture complete information. Robot arm or manipulators can provide the degrees of freedom needed to maneuver the sensor through the complex geometry. However, a robotic arm has a limited workspace as well and cannot cover large parts. Mobile base can enhance the capability of the robotic arm by adding mobility to the arm and carrying the arm around the part. Mobile base will need to relocate around the part during the process. Relocating the mobile base increases execution time and also introduces uncertainty in the localization as mobile base moves inaccurately. It is important to reduce the number of mobile base repositioning and reduce execution time and uncertainty. In this paper, we develop a motion planner that finds the minimum number of mobile base placements in order to find robotic arm trajectories that can cover a large complex part using a RGB-D camera sensor. The planning problem, also known as optimal base sequencing, is challenging due to the immensity of the search space. The computation costs involved in inverse kinematics calculations also adds to the search time. A branch and bound search algorithm is developed with efficient branch guiding and pruning heuristics that quickly explores the search space. A capability map based method is developed to improve the search space construction time. Output of our method is an optimal sequence of base placements for the mobile base that will lead to minimum number of placements and execution time required for the process.
A Finite Element Model of an Electric Scooter for Simulating Traffic Accidents
Authors: Chontos Rafael , Grindle Daniel , Untaroiu Alexandrina , Doerzaph Zachary , Untaroiu Costin 
Published: November 2022

Abstract
In the past several years, injuries caused by electric scooter accidents have significantly increased in areas serviced by scooter ride-share companies. The majority of injuries observed are mild to moderate in severity. In this study, a FE model of an electric scooter accident was created to observe the effect that impact speed and the type of ground have on the risk of severe injury to the rider. A FE standing Hybrid III dummy was calibrated against the certification test data using optimization techniques. To model a scooter-bump accident, the calibrated HIII FE model was placed on the scooter to mimic how a rider would stand on an electric scooter. Three scooter-bump impact simulations were run where the impact speeds were either 4.48 m/s or 3.2 m/s. The ground was similarly switched between soil and concrete. The simulation where the dummy fell on a concrete surface resulted in the highest risk of severe injury to the rider. Furthermore, the results concurred with previous literature that the head/neck region presented one of the biggest risks of severe injury. It is believed that the models developed in this study could be used in future to improve the e-scooter riders’ safety by development of new safety.
Deep Learning of Cross-Modal Tasks for Conceptual Design of Engineered Products: A Review
Authors: Li Xingang , Wang Ye , Sha Zhenghui 
Published: November 2022

Abstract
Conceptual design is the foundational stage of a design process, translating ill-defined design problems to low-fidelity design concepts and prototypes. While deep learning approaches are widely applied in later design stages for design automation, we see fewer attempts in conceptual design for three reasons: 1) the data in this stage exhibit multiple modalities: natural language, sketches, and 3D shapes, and these modalities are challenging to represent in deep learning methods; 2) it requires knowledge from a larger source of inspiration instead of focusing on a single design task; and 3) it requires translating designers’ intent and feedback, and hence needs more interaction with designers and/or users. With recent advances in deep learning of cross-modal tasks (DLCMT) and the availability of large cross-modal datasets, we see opportunities to apply these learning methods to the conceptual design of product shapes. In this paper, we review 30 recent journal articles and conference papers across computer graphics, computer vision, and engineering design fields that involve DLCMT of three modalities: natural language, sketches, and 3D shapes. Based on the review, we identify the challenges and opportunities of utilizing DLCMT in 3D shape concepts generation, from which we propose a list of research questions pointing to future research directions.
Va

riable

R

esistance

S

uit (VARS) for Enhancing Resistance Training
Authors: Kadhim Ibrahim Falih , Aracena Alvial Alvaro Andres , Frankle Eric , Rios Carbonell Gabriel , Hosseini Saba M. , Fukuda David , Stout Jeffrey , Park Joon-Hyuk 
Published: November 2022

Abstract
Muscle disorders and induced muscle atrophy impose critical risks to the well-being of an individual, limiting normal activities of daily living. Several resistance training methods exist that have effectively reversed the progression of muscle atrophy. Weightlifting and hydrotherapy are the two widely practiced schemes for resistance training; however, there is the potential risk of excessive loads exerted on the muscles during weightlifting, and limited accessibility and cost are barriers to hydrotherapy. An alternative is using a resistance band. Some limitations include engaging multiple muscles/joints while only unidirectional resistance is feasible. To address these limitations, a VAriable Resistance Suit (VARS) is designed to provide speed-dependent, bi-directional, and variable resistance at a single joint. As a proof of concept, an elbow module of VARS is developed and validated experimentally. A pilot study shows the changes in flexor and extensor muscle activations in response to eight different levels of resistance modulated by VARS. The clinical implications of VARS remain as future work, but the functionalities implemented in the presented VARS prototype and preliminary results suggest that VARS could be a viable solution and complementary to existing tools and techniques utilized in resistance training.
A Synthetic Tradespace Model for Tradespace Analysis and Exploration
Authors: Turner Cameron J. , Masoudi Nafiseh , Stewart Hannah , Daniels Julia , Gorsich David , Rizzo Denise , Hartman Greg , Agusti Rachel , Skowronska Annette , Castanier Matt , Rapp Stephen H. 
Published: November 2022

Abstract
Tradespace analysis and exploration is used to frame a design problem. By taking stock of available technologies, predictions of the performance of a system defined from a combinatorial combination of technologies (from say a morphological matrix) can be made. Based on these assessments, tradeoffs between functional performance objectives (often termed simply Functional Objectives or FOs) can be made. The result of these performance tradeoffs or Trades, can then be used to define a target design space for a problem. That design space can then be characterized with criteria to determine the viability of the tradespace and the design problem.
However, the cost to develop the morphological matrix for the tradespace can be prohibitive. The tradespace at the US Army DEVCOM Ground Vehicle Systems Center (GVSC) took more than 2 years of effort by multiple staff and technical experts to develop and allows for the consideration of more than 1021 vehicles. To develop enhanced approaches to tradespace analysis and exploration to enhance programmatic decision-making, a simulated tradespace based on “synthetic data” is necessary. For tradespace studies within the Clemson University Virtual Prototyping of Ground Systems (VIPR-GS) it was necessary to develop a synthetic tradespace model to serve as a basis for evaluating improved approaches to tradespace analysis, exploration and decision-making methods.
Within this work, we describe the state-of-the-art for developing models of the tradespace, formulations of functional objectives and defined models to represent different synthetic variable types to produce a synthetic tradespace with far less effort. Using this approach, we demonstrate the development of an example of a synthetic tradespace for small semi-autonomous ground vehicles developed within the VIPR Center that can be used to evaluate vehicle designs for the Clemson Deep Orange Project Vehicle and at GVSC. Finally, we will explore how this tradespace model can be used to facilitate decision-making surrounding the tradespace in the future.