bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural Design Exploration for Product Architecture Design
Authors: Toi Masato , Nomaguchi Yutaka , Fujita Kikuo 
Published: November 2020

Abstract
This paper proposed a design support method based on structuralization and analysis of various design candidates of product architecture design. The product architecture is a basic scheme that assigns the function of the product to physical components. In the conventional modular design method, a concise model, i.e., a graph or a matrix, is used to express the interactions of the system’s components and aims to support the designer grasping the system behavior. The Design Structure Matrix (DSM) is a representative model of system architecture and enables quantitative evaluation of design candidates. While various design candidates are generated through mathematical operations, it is difficult to understand their relationships from simple comparisons because of discrete behavior and the size of the problem. It must be a critical issue at the stage of selecting and interpreting the design candidates. In the proposed method, the design candidates are classified and structuralized as a dendrogram by the hierarchical clustering method. The comparison of clusters of each branch of dendrogram clarifies the system leverage points. The information of the system is summarized into the hierarchical tree-shaped graph that corresponds to the dendrogram. The designer can explore the design candidates with such a graph-based based interpretation of underlying structures effectively.
Adaptive Linear Programming Algorithm With Parameter Learning for Managing Engineering-Design Problems
Authors: Guo Lin , Balu Nellippallil Anand , Smith Warren F. , Allen Janet K. , Mistree Farrokh 
Published: November 2020

Abstract
The adaptive linear programming (ALP) algorithm is an extension of the sequential linear programming algorithm where nonlinear formulations are iteratively approximated as linear formulations linearized about an iteration starting point. In the ALP algorithm, heuristics are used to determine the value of a critical parameter, namely, the reduced move coefficient (RMC). The RMC defines how far to move towards the solution of iteration “n” from the starting point for iteration “n” in specifying the starting point for iteration “n+1”. The RMC choice affects the efficacy of the approximation; however, there is no mechanism of evaluating the algorithm performance with respect to the RMC value so as to improve the design efficiency and effectiveness. This limitation is addressed in this paper.
In this paper, we enhance the ALP algorithm with parameter learning (ALPPL) and generalize to make the knowledge gained reusable. We propose a three-step procedure of rule-based parameter learning leading to robust solutions. An industry-inspired problem, the integrated design of a hot rolling process chain for the production of a steel rod, is used to demonstrate the implementation. The three-step procedure could be used to improve other critical parameter determinations, especially when there is a lack of mechanisms for algorithm-performance evaluation, evaluation criteria vary with problems, or heuristics are over-used.
Multi-Context Generation in Virtual Reality Environments Using Deep Reinforcement Learning
Authors: Cunningham James , Lopez Christian , Ashour Omar , Tucker Conrad S. 
Published: November 2020

Abstract
In this work, a Deep Reinforcement Learning (RL) approach is proposed for Procedural Content Generation (PCG) that seeks to automate the generation of multiple related virtual reality (VR) environments for enhanced personalized learning. This allows for the user to be exposed to multiple virtual scenarios that demonstrate a consistent theme, which is especially valuable in an educational context. RL approaches to PCG offer the advantage of not requiring training data, as opposed to other PCG approaches that employ supervised learning approaches. This work advances the state of the art in RL-based PCG by demonstrating the ability to generate a diversity of contexts in order to teach the same underlying concept. A case study is presented that demonstrates the feasibility of the proposed RL-based PCG method using examples of probability distributions in both manufacturing facility and grocery store virtual environments. The method demonstrated in this paper has the potential to enable the automatic generation of a variety of virtual environments that are connected by a common concept or theme.
Recursive Newton-Euler Dynamics and Sensitivity Analysis for Robot Manipulator With Revolute Joints
Authors: Barman Shuvrodeb , Xiang Yujiang 
Published: November 2020

Abstract
In this study, recursive Newton-Euler sensitivity equations are derived for robot manipulator motion planning problems. The dynamics and sensitivity equations depend on the 3 × 3 rotation matrices based on the moving coordinates. Compared to recursive Lagrangian formulation, which depends on 4 × 4 Denavit-Hartenberg (DH) transformation matrices, the moving coordinate formulation increases computational efficiency significantly as the number of matrix multiplications required for each optimization iteration is greatly reduced. A two-link manipulator time-optimal trajectory planning problem is solved using the proposed recursive Newton-Euler dynamics formulation. Only revolute joint is considered in the formulation. The predicted joint torque and trajectory are verified with the data in the literature. In addition, the optimal joint forces are retrieved from the optimization using recursive Newton-Euler dynamics.
Predictive Human-in-the-Loop Simulations for Assistive Exoskeletons
Authors: Zhou Xianlian 
Published: November 2020

Abstract
Design and evaluation of exoskeletons is often a time consuming and costly process that involves prototyping, human testing, and multiple design iterations. For active exoskeletons, the primary challenge is to detect the wearer’s movement intent and provide potent assistance, which often requires sophisticated control algorithms. The goal of this study is to integrate human musculoskeletal models with robot modeling and control for virtual human-in-the-loop evaluation of exoskeleton design and control. We present potential strategies for assisting various human motions such as squatting, lifting, walking, and running. Several exoskeleton designs (for back, upper extremity, and lower extremity) and their control methods are evaluated with an integrated human-in-the-loop simulation approach to study their functionalities and biomechanical effects on the wearer’ musculoskeletal system. We hope this simulation paradigm can be utilized for virtual design and evaluation of exoskeletons and pave the way to build or optimize exoskeletons.
An Image-Based Approach to Variational Path Synthesis of Linkages
Authors: Deshpande Shrinath , Purwar Anurag 
Published: November 2020

Abstract
This paper brings together computer vision, mechanism synthesis, and machine learning to create an image-based variational path synthesis approach for linkage mechanisms. An image-based approach is particularly amenable to mechanism synthesis when the input from mechanism designers is deliberately imprecise or inherently uncertain due to the nature of the problem. In addition, it also lends itself naturally to the creation of a unified approach to mechanism synthesis since pixels do not care if they were generated from a four-bar or six-bar. Path synthesis problem has generally been solved for a set of precision points on the intended path such that the designed mechanism passes through those points. This approach usually leads to a small set of over-fitting solutions to the particular precision points. However, most kinematic synthesis problems are concept generation problem where a designer cares more about generating a large number of plausible solutions. This paper models the input curve as a probability distribution of image pixels and employs a probabilistic generative model to capture the inherent uncertainty in the input. In addition, it gives feedback on the input quality and provides corrections for a more conducive input. The image representation allows for capturing local spatial correlations, which plays an important role in finding a variety of solutions with similar semantics as the input curve.
Design Framework for Multi-Section Shape Memory Alloy Axial Actuators Considering Material and Geometric Uncertainties
Authors: Guan Weilin , Peraza Hernandez Edwin A. 
Published: November 2020

Abstract
Shape memory alloys are metallic materials with the capability of performing as high energy density actuators driven by temperature control. This paper presents a design framework for shape memory alloy (SMA) axial actuators composed of multiple wire sections connected in series. The various wire sections forming the actuators can have distinct cross-sectional areas and lengths, which can be modulated to adjust the overall thermomechanical response of the actuator. The design framework aims to find the optimal cross-sectional areas and lengths of the wire sections forming the axial actuator such that its displacement vs. temperature actuation path approximates a target path. Constraints on the length-to-diameter aspect ratio and stress of the wire sections are incorporated. A reduced-order numerical model for the multi-section SMA actuators that allows for efficient design evaluations is derived and implemented. An approach to incorporate uncertainty in the geometry and material parameters of the actuators within the design framework is implemented to allow for the determination of robust actuator designs. A representative application example of the design framework is provided illustrating the benefits of using multiple wire sections in axial actuators to modulate their overall response and approximate a target displacement vs. temperature actuation path.
Design of Tensegrity-Based Lattices With Engineered Load-Bearing and Thermal Expansion Properties
Authors: Baldwin Drake D. , Peraza Hernandez Edwin A. 
Published: November 2020

Abstract
Tensegrity lattices are networks of axially loaded members designed to efficiently use material and exhibit properties such as minimum mass load-carrying or energy absorption capabilities. This work entails the modeling and design of tensegrity “D-bar” lattices with specified orthotropic compressive strength. The objectives for the design of the lattices include minimum mass density and minimum error between the orthotropic coefficients of thermal expansion (CTEs) of the lattice and given target values. The studied D-bar structures are formed by joining two equal pyramids base-to-base where tensile strings form the edges of the pyramid bases and compressive bars form the remaining edges. Orthorhombic lattices having D-bars as their edges are designed to support compressive forces and exhibit positive, zero, or negative CTE values along their three principal directions. It is investigated how the geometry of the individual D-bar components may be adjusted, for the given compressive strength, to prevent local yielding and buckling failure with the minimum required material. Analytical formulas for the minimum density and the CTE of the D-bar lattices are provided, and a numerical framework for the integration of these formulas along with size and topological constraints is developed. Design trade-offs between minimum lattice density and minimum error from the target CTE, which are found to be competing structural performance metrics, are visualized and investigated.
Design and Simulations of a Novel Stiction-Free Laterally Actuated NEM Relay With Flexible Source-Drain Contact
Authors: Zandigohar Mehrdad , Shavezipur Mohammad 
Published: November 2020

Abstract
A novel design for laterally actuated nanoelectromechanical (NEM) relays with flexible source-drain contact is presented. The design uses a thin curved source that can provide expandable contact area between the source and the drain in ON-STATE position. The presence of the thin film curved source creates a local nonlinear stiffness in addition to the main stiffness of the source beam. This additional stiffness not only controls the contact area with over-drive voltage after the pull-in, but can also generate repulsive force when the actuation voltage is removed to separate the two contacting surfaces. The additional repulsive force creates a “peel-off” separation mechanism and can overcome relatively large adhesion forces. Finite element simulations are used to verify the applicability of this design and ANSYS® APDL structural solver and contact technology is used to determine the nonlinear stiffness of the curved source and also to simulate the stiction and repulsive forces generated in the curved source. Curved source structures with different curvatures are simulated to examine the applicability of the design idea in overcoming the adhesion between source and drain. FEM results demonstrate that secondary structural stiffness created at the source-drain contact can overcome large adhesion stress and allow the separation in a peel-off mechanism after the actuation voltage is removed.
Robust Relative Hand Placement for Bi-Manual Tasks
Authors: Sinha Anirban , Chakraborty Nilanjan 
Published: November 2020

Abstract
In many bi-manual robotic tasks, like peg-in-a-hole assembly, the success of the task execution depends on the error in achieving the desired relative pose between the peg and the hole in a pre-insertion configuration. Random actuation errors in the joint space usually prevents the two arms from reaching their desired task space poses, which in turn results in random error in relative pose between the two hands. This random error varies from trial to trial, and thus depending on the tolerance between the peg and the hole, the outcome of the assembly task may be random (sometimes the task execution succeeds and sometimes it fails). In general, since the relative pose has 6 degrees-of-freedom, there are an infinite number of joint space solutions for the two arms that correspond to the same task space relative pose. However, in the presence of actuation errors, the joint space solutions are not all identical since they map the joint space error sets differently to the task space. Thus, the goal of this paper is to develop a methodical approach to compute a joint space solution such that the maximum task space error is below a (specified) threshold with high probability. Such a solution is called a robust inverse kinematics solution for the bi-manual robot. Our proposed method also allows the robot to self-evaluate whether it can perform a given bi-manual task reliably. We use a square peg-in-a-hole assembly scenario on the dual-arm Baxter robot for numerical simulations that shows the utility of our approach.
Design Elements Inflatable Origami-Based Forceps
Authors: Abulon Dina Joy K. , McCarthy J. Michael 
Published: November 2020

Abstract
Forceps are a multifunctional tool that can solve various grasping needs. An action origami-based forcep design allows a structure to deploy from a flat state to 3D state plus create motion while in a final 3D state. The origami-based design allows the structure to compact. A fabric inflatable structure allows for shape transformation and stiffness adjustment. This paper explores the design of three prototypes and guides the selection of optimal features of inflatable action origami-based forceps.
Metamodel Based Forward and Inverse Design for Passive Vibration Suppression
Authors: Behjat Amir , Oddiraju Manaswin , Attarzadeh Mohammad Ali , Nouh Mostafa , Chowdhury Souma 
Published: November 2020

Abstract
Aperiodic metamaterials represent a class of structural systems that are composed of different building blocks (cells), instead of a self-repeating chain of the same unit cells. Optimizing aperiodic cellular structural systems thus presents high-dimensional design problems, that become intractable to solve using purely high-fidelity structural analysis coupled with optimization. Specialized analytical modeling along with metamodel based optimization can provide a more tractable alternative to designing such aperiodic metamaterials. To explore this concept, this paper presents an initial design automation framework applied to a case study representative of a simple 1D metamaterial system. The case under consideration is a drill string, where vibration suppression is of utmost importance. The drill string comprises a set of nonuniform rings attached to the outer surface of a longitudinal rod. As such, the resultant system can now be perceived as an aperiodic 1D metamaterial with each ring/gap representing a cell. Despite being a 1D system, the simultaneous consideration of multiple degrees of freedom (associated with torsional, axial, and lateral motions) poses significant computational challenges. To deal with these challenges, a transfer matrix method (TMM) is employed to analytically determine the frequency response of the drill string. However, due to the minute scale cost of the TMM method, the optimization remains computationally burdensome. This latter challenge is addressed by training a suite of neural networks on a set of TMM samples, with each network providing the response w.r.t. a specific frequency. Optimization is then performed to minimize mass subject to constraints on the gap between consecutive resonance peaks in one case, and minimizing this gap in the second case. Crucial improvements are accomplished over the initial baselines in both cases. Further novel contributions occur through the development of an inverse modeling approach that can learn optimal inverse designs with minimum mass and a desirable non-resonant frequency range, which partially mimics band gap behavior in perfectly periodic dispersive structures. To this end, we introduce the use of an emerging modeling formalism called in-vertible neural nets. Our study indicates that the inverse model is able to generate constraint satisfying designs with slightly higher mass.
Increasing the Life Span of Foldable Manipulators With Fabric
Authors: Sharifzadeh Mohammad , Jiang Yuhao , Khodambashi Roozbeh , Aukes Daniel 
Published: November 2020

Abstract
This paper evaluates how laminated techniques may be used to replicate the performance of more traditionally manufactured robotic manipulators. This evaluation is conducted by addressing the advantages and challenges of laminated manufacturing techniques, specifcally mechanism durability. In this study, we propose a novel fabric-polyester hinge design with an improved life-span. We additionally provide an overview of the design and construction workfow for a laminated 2-DOF spherical parallel manipulator for use as a camera stabilizer. Using the proposed manipulator as a case study, we demonstrate that mechanisms fabricated with lamination techniques can achieve similar performance to devices made using conventional methods.
Characterization of On-Field Head Impact Exposure in Youth Soccer
Authors: Tomblin Brian T. , Pritchard N. Stewart , Filben Tanner M. , Miller Logan E. , Miles Christopher M. , Urban Jillian E. , Stitzel Joel D. 
Published: November 2020

The objective of this research was to characterize head impacts with a validated mouthpiece sensor in competitive youth female soccer players during a single season with a validated mouthpiece sensor. Participants included 14 youth female soccer athletes across 2 club-level teams at different age levels (team 1, ages 12–13 y; team 2, ages 14–15 y). Head impact and time-synchronized video data were collected for 66 practices and games. Video data were reviewed to characterize the type and frequency of contact experienced by each athlete. A total of 2216 contact scenarios were observed; heading the ball (n = 681, 30.7%) was most common. Other observed contact scenarios included collisions, dives, falls, and unintentional ball contact. Team 1 experienced a higher rate of headers per player per hour of play than team 2, while team 2 experienced a higher rate of collisions and dives. A total of 935 video-verified contact scenarios were concurrent with recorded head kinematics. While headers resulted in a maximum linear acceleration of 56.1g, the less frequent head-to-head collisions (n = 6) resulted in a maximum of 113.5g. The results of this study improve the understanding of head impact exposure in youth female soccer players and inform head impact exposure reduction in youth soccer.
Injury characteristics in male youth athletics: a five-season prospective study in a full-time sports academy
Authors: Martínez-Silván Daniel , Wik Eirik Halvorsen , Alonso Juan Manuel , Jeanguyot Evan , Salcinovic Benjamin , Johnson Amanda , Cardinale Marco 
Published: November 2020

ObjectivesTo describe the injury characteristics of male youth athletes exposed to year-round athletics programmes.MethodsInjury surveillance data were prospectively collected by medical staff in a cohort of youth athletics athletes participating in a full-time sports academy from 2014–2015 to 2018–2019. Time-loss injuries (>1 day) were recorded following consensus procedures for athletics. Athletes were clustered into five event groups (sprints, jumps, endurance, throws and non-specialised) and the number of completed training and competition sessions (athletics exposures (AE)) were calculated for each athlete per completed season (one athlete season). Injury characteristics were reported overall and by event groups as injury incidence (injuries per 1000 AE) and injury burden (days lost per 1000 AE).ResultsOne-hundred and seventy-eight boys (14.9±1.8 years old) completed 391 athlete seasons, sustaining 290 injuries. The overall incidence was 4.0 injuries per 1000 AE and the overall burden was 79.1 days lost per 1000 AE. The thigh was the most common injury location (19%). Muscle strains (0.7 injuries per 1000 AE) and bone stress injuries (0.5 injuries per 1000 AE) presented the highest incidence and stress fractures the highest burden (17.6 days lost per 1000 AE). The most burdensome injury types by event group were: bone stress injuries for endurance, hamstring strains for sprints, stress fractures for jumps, lesion of meniscus/cartilage for throws and growth plate injuries for non-specialised athletes.ConclusionAcute muscle strains, stress fractures and bone stress injuries were identified as the main injury concerns in this cohort of young male athletics athletes. The injury characteristics differed between event groups.