bluuebunny/crossref_metadata_2025 huggingface dataset:
Percepción de las necesidades en salud mental de población migrante venezolana en 13 departamentos de Colombia. Reflexiones y desafíos
Authors: Ruiz Eslava Luisa Fernanda , Rodríguez Pérez David Alejandro
Published: November 2021

Objetivo: identificar las necesidades en salud mental de población migrante venezolana de los departamentos priorizados por la Organización Internacional para las Migraciones (OIM) en Colombia. Metodología: estudio cualitativo que utilizó una encuesta de preguntas abiertas a 59 profesionales en humanidades, ciencias sociales y de la salud, quienes trabajan con la OIM en los territorios priorizados. Resultados: Se encuentra que las necesidades más significativas de la población migrante se relacionan con la atención en salud mental, el acceso a vivienda digna, servicios y redes de apoyo. Los problemas en salud mental más comunes fueron el consumo de sustancias psicoactivas, así como distintas formas de violencia. Se reportan como principales trastornos mentales la ansiedad y la depresión. Finalmente, se reportan como problemas emergentes del fenómeno migratorio la explotación sexual y laboral, y ausencia/perdida del proyecto de vida, la violencia sexual y de género, así como la xenofobia y distintas formas de discriminación. Conclusión: La migración ha afectado la salud mental de miles de personas, principalmente en términos de bienestar y buen vivir. Esas afectaciones no se reducen exclusivamente a los problemas o los trastornos mentales, sino que tienen incidencia en el sentido de vida, la posibilidad de autonomía, desarrollo y capacidad de agencia de los sujetos.
Salud y privación farmacéutica en España. Una devaluación de la ciudadanía social
Authors: Martínez Gayo Gema , Martínez López José Ángel
Published: November 2021

El acceso a la salud es uno de los pilares básicos del estado de bienestar español. Desde finales de los años setenta, los cambios legislativos introducidos han modificado tanto las condiciones de acceso como el grado de cobertura estatal de los productos farmacéuticos. El sistema de copago farmacéutico establecido en España ha sufrido cambios sustanciales recientes, tanto en la cobertura de medicamentos como en el aporte económico para acceder a estos. El objetivo de esta investigación es conocer las implicaciones de dichas reformas en la población y determinar cuáles son los perfiles más afectados. La aproximación al objeto de estudio se ha realizado siguiendo un pluralismo metodológico. Se analizaron los principales cambios normativos y las fuentes de datos relacionadas con el acceso a productos farmacéuticos. Los resultados confirman la falta de progresividad de las reformas legales en relación al copago sanitario. Igualmente, se muestra un incremento de las dificultades de acceso a los medicamentos prescritos por parte de las personas más vulnerables, en este caso, las mujeres y los hogares con menor renta disponible.
Toma de decisiones estratégicas en organizaciones de salud. Una revisión de la literatura
Authors: León Vanegas Yuly Licet , González Rodríguez Javier Leonardo
Published: November 2021

Introducción. “La toma de decisiones estratégicas es un proceso vital dentro de las organizaciones, debido a las múltiples variables que intervienen, los recursos involucrados y al impacto en el mediano y largo plazo” (1). Objetivo: identificar los factores que influyen en el proceso de toma de decisiones estratégicas en las organizaciones del sector salud. Materiales y método: revisión sistemática de los estudios en el sistema integrado de búsqueda y en las bases de datos electrónicas: Pubmed, EMBASE, ScienceDirect y Google Scholar. La búsqueda se enfocó en artículos empíricos publicados en los últimos 10 años, sin restricción de idioma y con disponibilidad del texto completo. Resultados: se incluyeron 14 artículos que analizaron variables relacionadas con los siguientes factores: tomadores de decisiones, aspectos de la organización y aspectos ambientales externos. Ningún estudio incluyó dentro de su análisis la influencia de los factores específicos de la decisión. Conclusiones: existen diferentes factores contextuales que influyen en el proceso de toma de decisiones estratégicas en organizaciones de salud. No obstante, existen pocos estudios que permitan establecer un marco global que integre las diferentes perspectivas.
Effects of Simulation Length and Flexible Foundation on Long-Term Response Extrapolation of a Bottom-Fixed Offshore Wind Turbine
Authors: Barreto David , Karimirad Madjid , Ortega Arturo
Published: November 2021

This paper deals with statistical and modeling uncertainty on the estimation of long-term extrapolated extreme responses in a monopile offshore wind turbine. The statistical uncertainty is addressed by studying the effect of simulation length. Modeling uncertainty is explored by evaluating the effects of considering a rigid and flexible foundation. The soil's flexibility is taken into account by considering the improved apparent fixity method. To identify the most relevant environmental conditions, the modified environmental contour method is used. The analysis focuses on the fore-aft shear force (FASF) and the fore-aft bending moment (FABM) at the mudline. The results show that using a simulation length of 10 min does not provide sufficient accuracy. It was found that for the FASF, simulation lengths of at least 30 min are required to achieve an accuracy of about +/−5%. For the FABM, it was found that both the extrapolations made with 20 min and 30 min simulations achieved similar levels of accuracy of about 20%. Meanwhile, the results obtained from 10 min simulations reached deviations of about 40%. Finally, from the comparison made between a rigid and flexible foundation, it was found that the extrapolated responses exhibit maximum deviations up to around 5% and 10% for the FASF and the FABM, respectively. Also, for the FABM, it was observed that the consideration of a flexible foundation causes the critical wind speed to shift from 16.5 m/s (rigid) to 18 m/s (flexible).
The Inspiration Design Toolkit: A Human-Centered Design Tool for a System Engineering Course
Authors: Lee Sheng-Hung , Yang Maria C. , Carramolino Beatriz , Rudnik John
Published: November 2021

System Engineering education typically includes content to help students learn to design and engineer large, complex systems in a structured way. In this paper, we describe the outcomes of introducing a human-centered design tool, the Inspiration Design Toolkit (IDT), to encourage students to think non-linearly. The IDT is an educational resource consisting of a deck of illustrated cards that contain provocative questions, reflection messages and icons, applicative examples, and key takeaways on microlearning units. The aim of the IDT is to improve the participants’ learning experience and course engagement, increase opportunities for them to interact with their peers and teaching team, enable them to practice and reinforce the concepts through the creation of their own IDT cards, and share the cards in the discussion to increase learners’ engagement with course material and peers. We designed the IDT for an MIT online course on System Thinking. We collected, analyzed, and synthesized qualitative and quantitative feedback from 171 course participants. Our findings suggest that IDT provides learners with a digital asset that allows them to reinforce and recall the course takeaways, and apply them to other contexts. For future research, we want to understand how learners like and use IDT through demographic differences and preferred self-identified learning styles. We discuss how these findings may help educators consider critical design principles and for creating a digital self-learning toolkit connected to the course content and increasing its content adaptability.
Parameter-Dependent Feedback Compensator Design for a Time-Fractional Reaction-Diffusion Equation
Authors: Wang Jun-Wei , Zhou Hua-Cheng
Published: November 2021

This paper presents a parameter-dependent design of feedback compensator with space-varying gains for Mittag-Leffler stabilization of linear time fractional parabolic MIMO partial differential equations subject to space-varying diffusion and reaction coefficients. In the proposed design method, under a boundedness assumption, the reaction coefficient is written in a parametric form. By using the parametric form for the reaction coefficient and multiple non-collocated observation outputs, an observer-based state feedback compensator with space-varying gains is then constructed such that the resulting closed-loop coupled equations are Mittag-Leffler stable. By applying the Lyapunov technique with Caputo fractional derivative and variants of Poincaré–Wirtinger’s inequality, a sufficient condition for the existence of such feedback compensator is presented in terms of standard linear matrix inequalities. Finally, simulation results are presented to support the proposed design method.
Deep Reinforcement Learning Enhanced Convolutional Neural Networks for Robotic Grasping
Authors: Fang Jianhao , Hu Weifei , Wang Chuxuan , Liu Zhenyu , Tan Jianrong
Published: November 2021

Robotic grasping is an important task for various industrial applications. However, combining detecting and grasping to perform a dynamic and efficient object moving is still a challenge for robotic grasping. Meanwhile, it is time consuming for robotic algorithm training and testing in realistic. Here we present a framework for dynamic robotic grasping based on deep Q-network (DQN) in a virtual grasping space. The proposed dynamic robotic grasping framework mainly consists of the DQN, the convolutional neural network (CNN), and the virtual model of robotic grasping. After observing the result generated by applying the generative grasping convolutional neural network (GG-CNN), a robotic manipulation conducts actions according to Q-network. Different actions generate different rewards, which are implemented to update the neural network through loss function. The goal of this method is to find a reasonable strategy to optimize the total reward and finally accomplish a dynamic grasping process. In the test of virtual space, we achieve an 85.5% grasp success rate on a set of previously unseen objects, which demonstrates the accuracy of DQN enhanced GG-CNN model. The experimental results show that the DQN can efficiently enhance the GG-CNN by considering the grasping procedure (i.e. the grasping time and the gripper’s posture), which makes the grasping procedure stable and increases the success rate of robotic grasping.
Multi-Material and Multi-Joint Topology Optimization for Lightweight and Cost-Effective Design
Authors: Crispo Luke , Roper Stephen William Knox , Bohrer Rubens , Morin Rosalie , Kim Il Yong
Published: November 2021

Lightweighting and cost reduction are overarching research themes in aerospace and automotive industries, leading to the exploration of new materials, advanced manufacturing methods, and design optimization algorithms. Multi-material topology optimization is an important tool that can generate unconventional designs leveraging the differing mechanical properties of multiple material types to increase performance. However, these approaches do not consider joining design during optimization, which can ultimately result in higher cost, worse performance, and unrealistic designs that must be altered in the interpretation stage. This work presents a multi-material and multi-joint topology optimization methodology that models joints at the interfaces between dissimilar materials, controls the joining pattern using joint design variables, and reduces cost through the addition of a joining cost constraint. Design variable interpolation schemes, interface detection for unstructured meshes, and sensitivity analysis are outlined in detail in this paper. The approach is applied to a real-world rocker arm geometry to demonstrate the importance of considering joints during multi-material topology optimization. The results of the numerical example indicate that the methodology can successfully detect interfaces in unstructured meshes and strategically place joints to maximize stiffness of the structure. A parameter study of various joining cost constraint levels illustrates how the optimizer alters part topology and joining design to reduce cost.
Remote Emergency Braking System for Autonomous Racing Electric Vehicles
Authors: Sorrentino Gennaro , Danese Luca , Circosta Salvatore , Feraco Stefano , Khan Irfan , Luciani Sara , Bonfitto Angelo , Amati Nicola
Published: November 2021

Advanced brake assist systems can avoid road accidents since the vehicles impact speed can be significantly reduced. To this end, different autonomous emergency braking systems are designed for recent vehicles on the market. This paper presents a pneumo-hydraulic Emergency Braking System (EBS) for autonomous racing vehicles. The purpose of the system is safely stopping the vehicle in case of any failures during autonomous driving. Failures can be detected both by the autonomous system itself and by human supervisors. The actuation system involves passive energy storage of compressed air to directly activate the hydraulic braking lines through pneumo-hydraulic pressure intensifiers. The coupling component between failures detection and actuation is a normally-open solenoid valve. The system is designed to respect deceleration and actuation time requirements, together with packaging constraints due to integration in an existing racing prototype. Specifically, the system requirements are specified by the racing competition rules: the overall reaction time of the retained EBS must be lower than 0.2 s, and the actuated mean deceleration must be greater than 8 m/s2 on a dry track surface while keeping stable driving conditions. The validation and tuning of the system is performed in a simulated environment. Therefore, an extensive experimental validation of the system is required in the real applications.
Multifidelity Uncertainty Quantification for Online Simulations of Automotive Propulsion Systems
Authors: Yang Hang , Gorodetsky Alex , Fujii Yuji , Wang Kon-Well
Published: November 2021

The increasing complexity and demanding performance requirement of modern automotive propulsion systems necessitate more intelligent and robust predictive controls. Due to the significant uncertainties from both unavoidable modeling errors and probabilistic environmental disturbances, the ability to quantify the effect of these uncertainties to the system behaviors is of crucial importance to enable advanced control designs for automotive propulsion systems. Furthermore, the quantification of uncertainty must be computationally efficient such that it can be conducted on board a vehicle in real-time. However, traditional uncertainty quantification methods for complicated nonlinear systems, such as Monte Carlo, often rely on sampling — a computationally prohibitive process for many applications. Previous research has shown promises of using spectral decomposition methods such as generalized Polynomial Chaos to reduce the online computational cost of uncertainty quantification. However, such method suffers from scalability and bias issues. This paper seeks to alleviate these computational bottlenecks by developing a multifidelity uncertainty quantification method that combines low-order generalized Polynomial Chaos with Monte Carlo estimation via Control Variates. Results on the mean and variance estimates of the axle shaft torque show that the proposed method can correct the bias of low-order Polynomial Chaos expansions while significantly reducing variance compared to the conventional Monte Carlo.
Virtual Reality Exergames: Promoting Physical Health Among Industry Workers
Authors: Stranick Thomas , Lopez Christian
Published: November 2021

This work introduces a Virtual Reality (VR) Exergame application to prevent Work Related Musculoskeletal Disorders (WMSDs). WMSDs are an important issue that can have a direct economic impact since they can injure workers, who are then forced to take time off. Exercise and stretching is one method that can benefit workers’ muscles and help prevent WMSDs. While several applications have been developed to prevent WMSDs, most of the existing applications suffer from a lack of immersivity or just focus on education and not necessarily helping workers warm-up or stretch. Hence, this work presents an Exergame application that leverages VR and Depth-sensor technology to help provide users with an immersive first-person experience. The objective of the VR Exergame is to encourage and motivate users to perform full-body movements in order to pass through a series of obstacles. The application implements a variety of game elements to help motivate users to play the game and stretch. While in the game, users can visualize their motions by controlling the virtual avatar with their body movements. It is expected that this immersivity will motivate and encourage the users. Initial findings show the positive effects that the base exergame has on individuals’ motivation and physical activity level. The results indicate that the application was able to engage individuals in low-intensity exercises that produced significant and consistent increases in their heart rate. Lastly, this work explores the development and benefits that this VR Exergame could bring by motivating workers and preventing WMSDs.
A Study of the Multi-Stability in a Non-Rigid Stacked Miura-Origami Cellular Mechanism
Authors: Tao Jiayue , Li Suyi
Published: November 2021

Multi-stable structures have gathered extensive interest because they can provide a broad spectrum of adaptive functions for many engineering systems. Especially, origami sheets with a translational periodicity can be stacked and assembled to form a multi-stable cellular solid, which has emerged as a promising platform to design functional structures. This paper investigates the multi-stability characteristics of a non-rigid stacked Miura-origami mechanism consisting of Miura-ori sheets and accordion-shaped connecting sheets, focusing on the elemental unit cell. A nonlinear mechanical model based on the barhinge approach is established to quantitatively study the unit cell’s multi-stability with intentionally relaxed rigid-folding conditions. Results show that only two stable states are achievable in the unit cell with enforced rigid-folding kinematics. However, if one relaxes the rigid-folding conditions and allows the facet to deform (i.e. non-rigid folding), four stable states are reachable in the unit cell if the crease torsional stiffness of the connecting sheets becomes sufficiently larger than that of the Miura-ori sheets, or the stress-free folding angle deviates away from 0°. A close examination of the potential energy composition of the non-rigid unit cell provides a detailed principle underpinning the multi-stability. By showing the benefits of exploiting facet compliance, this study can become the building blocks for origami-based structures and material systems with a wider variety of novel functionalities.
A Single-Card GPU Implementation of Peridynamics
Authors: Bartlett John D. , Storti Duane
Published: November 2021

The rapid development of parallelization technology over the recent decades has provided a promising avenue for the acceleration of meshfree simulation methods. One such method, peridynamics, is particularly well-suited for parallelization due to the simplicity of the operations which must occur at each material point. However, while MPI-based parallelization (Message-Passing Interface; a method for CPU-based parallelization) of peridynamic problems is commonplace, GPU parallelization of peridynamics has received far less attention. While GPU technology may have once been an inferior option to MPI parallelization for peridynamics, modern GPU cards are more than capable of handling substantially sized peridynamics problems. This paper presents the parallelization of the peridynamic method for single-card GPU computing, providing a schematic for a compact parallel approach. The resulting method is tested with CUDA on a NVIDIA Tesla P100 card with 16 GB of memory. The per-node memory requirements for each data structure used are evaluated, as well as the per-node execution times for each operation in a million-node benchmark test. This setup is shown to provide speedup factors over 200 for problems sized up to several million nodes, therefore indicating such a GPU is more than adequate for the single-card parallelization of the peridynamic method.
Comparing Nuclear and Chemical Power Sources for MEMS/NEMS Applications
Authors: Barham Oliver M.
Published: November 2021

Nuclear batteries are a class of power sources that harvest energy from decaying radioactive isotopes to generate electricity for powering sensors and electronics. They are well known in the fields of space exploration and implantable medical devices, but are not widely known to micro or nano-technologists in general. Nuclear batteries are compared against chemical sources of energy applicable to small-scale systems, including energy harvesting prototypes and a mm-scale commercial lithium battery, utilizing the metrics of volumetric power and energy density. Nuclear batteries benefit from orders of magnitude more energy density than power sources derived from chemical reactions, however they also have orders smaller power density. For some sensor applications, nuclear batteries enable capabilities not possible with chemical energy sources, and examples are discussed.
Absolute Nodal Coordinate Formulations for Aeroelastic Analysis of Next-Generation Aircraft Wings
Authors: Otsuka Keisuke , Dong Shuonan , Makihara Kanjuro
Published: November 2021

Future aircraft have a high aspect ratio wing (HARW). The low induced drag of the wing can reduce fuel consumption, which enables eco-friendly flight. HARW cannot be designed by using conventional linear aeroelastic analysis methods because it undergoes very flexible motion. Although absolute nodal coordinate formulations (ANCF) have been widely used for analyzing various flexible structures, their application to HAWR is limited because the derivation of the ANCF elastic force for wing cross section is difficult. In this paper, we first describe three ANCF-based beam models that address the difficulty. The three models have different characteristics. Second, an aeroelastic coupling between the beam models and a medium-fidelity aerodynamic model based on unsteady vortex lattice method (UVLM) is briefly explained. Especially, the advantage of ANCF in the aeroelastic coupling is emphasized. Finally, we newly compare the three ANCF-based models in structural and aeroelastic analyses. From the viewpoint of the convergence performance and calculation time, we found the best ANCF-based beam model among the three models in static structural and aeroelastic analyses, while the three models have comparable performances in dynamic structural and aeroelastic analyses. These findings contribute to the development of aeroelastic analysis framework based on ANCF and the design of next-generation aircraft wings.
Design and Analysis of Flexible Continuum Robot Based on Origami and Mortise-Tenon Structure (FCRBOM)
Authors: Yu Yue , Qiu Lifang , Wang Decheng , Zou Jing
Published: November 2021

The continuum robot is a soft robot with infinite degrees of freedom. Origami has a high capacity for spatial deployment. This paper proposes a flexible continuum robot based on origami and mortise-tenon structure (FCRBOM). The robot consists of some flexible hinges based on origami and mortise-tenon structure (FHBOM). The design process of the FCRBOM is given. The compliance of the FCRBOM is analyzed by the compliance matrix method. The Finite element analysis (FEA) is used to simulate and analyze the FCRBOM, and the correctness of the theoretical analysis is verified. Then a spatial FCRBOM (SFCRBOM) is designed. The impact of key dimensional parameters on the flexibility of SFCRBOM is discussed. Finally, an SFCRBOM with higher flexibility is presented.
Effect of Matching Buckling Loads on Post-Buckling Behavior in Compliant Mechanisms
Authors: Numić A. , Blad T. W. A. , van Keulen F.
Published: November 2021

In this paper, a novel method for stiffness compensation in compliant mechanisms is investigated. This method involves tuning the ratio between the first two critical buckling loads. To this end, the relative length and width of flexures in two architectures, a stepped beam and parallel guidance, are adjusted. Using finite element analysis, it is shown that by maximizing this ratio, the actuation force for transversal deflection in post-buckling is reduced. These results were validated experimentally by identifying the optimal designs in a given space and capturing the force-deflection characteristics of these mechanisms.
Geometry Optimization for Resonator Nonlinearities and Modes Controlling
Authors: Hajjaj Amal Z. , Jaber Nizar
Published: November 2021

In this paper, we utilize a passive technique based on geometry optimization to control the nonlinearities and the dynamical response of MEMS resonators. To achieve this, we propose a new hybrid shape combining a straight and initially curved microbeam. The Galerkin method is employed to solve the beam equation and study the effect of the different design parameters on the ratios of the frequencies and the nonlinearities of the structure. We show by adequately selecting the parameters of the structure; we can realize systems with strong quadratic or cubic nonlinearities or even zero nonlinearity. Also, we investigate the resonator shape effect on breaking the symmetry and explore different linear coupling phenomena: crossing, veering, and mode hybridization. We demonstrate the possibility of controlling the frequencies of the different modes of vibrations to achieve commensurate ratios necessary for activating internal resonance. The ability to activate the nonlinearities and tuning the frequencies is essential for wide range of applications in signal filtering, sensing, timing, and mass and gas sensing. The proposed method is simple in principle, easy to fabricate, and offers a wide range of controllability on the sensor nonlinearities and response. In addition, the passive techniques does not need additional circuits, to control the frequencies, which help reducing the device size, cost, and power consumption.
Potential Energy as Design Criterion in Planar Multistable Mechanisms
Authors: Dold Edward J. , Voglewede Philip A.
Published: November 2021

Toggle mechanisms are used throughout engineering to accomplish various tasks, for example residential electrical switching. The design of toggle mechanisms can be broken into three categories: determination of a topology, geometric parameterization, and optimization. While topological determination and optimization have well established processes for use in design, geometric parameterization which includes defining link lengths and spring stiffness has largely been left to engineering judgement. This paper presents a design methodology using potential energy graphs which informs the engineering decisions made in choosing mechanism parameters, giving designers higher confidence in the design. A kinematic analysis coupled with Lagrange’s equation determines the relationship between the mechanism parameters and the potential energy curve. Plotting the potential energy with respect to the generalized coordinate yields a graph with a slope that is the generalized force or moment. The relationships between parameters and their effects on the mechanism are difficult to observe in the equations of motion, but potential energy plots readily provide information pertinent to the design of toggle mechanisms and decouple their effects. The plots also allow design by position rather than time which makes the design process faster. The design process is applied to three examples: a simple toggle mechanism, a compliant mechanism, and a reconfigurable mechanism to show the nuances of the approach.
Understanding Professional Designers’ Knowledge Organization Behavior: A Case Study in Product Teardowns
Authors: Wang Ye , Grandi Daniele , Cui Dixun , Rao Vivek , Goucher-Lambert Kosa
Published: November 2021

Knowledge organization is an essential component of engineering design, and a deeper understanding of how designers organize knowledge could enable more effective insights in support of the design process. To explore this, we examine 23 professional designers’ knowledge organization practices as they virtually engage with data collected during a teardown of a consumer product. Designers organized this data by forming groups of related data, nesting subgroups of data within groups, and creating directional links between groups of data and individual data. Our results indicate three insights about how designers organize and acquire knowledge from product teardowns. First, we observe that while designers find grouping data to be more effective for learning, linking proved more helpful for knowledge transfer. Second, we find that designers employ links between data much more frequently than they do nests, and that links primarily serve to identify trade-offs, requirements, and opportunities for team collaboration. Finally, a graph analysis indicates that design features, product housing, cost, and manufacturing coexist as separate but central groups in designers’ knowledge organization, reflecting the diversity of perspectives on knowledge organization emergent in a constrained teardown activity. These findings provide insight into professional designers’ knowledge organization practices, and represent a preliminary step toward design knowledge bases that more accurately reflect designer behavior, ultimately enabling more effective data-driven support tools for design.
Neural Network Based Transfer Learning for Robot Path Generation
Authors: Tang Houcheng , Notash Leila
Published: November 2021

In this paper, an artificial neural network (ANN) based transfer learning approach of inverse displacement analysis of robot manipulators is studied. ANNs with different structures are applied utilizing data from different end effector paths of a manipulator for training purposes. Four transfer learning methods are proposed by applying pretrained initial parameters. Final training results of ANN with transfer learning are compared with those of ANN with random initialization. To investigate the rate of convergence of data fitting comprehensively, different values of performance targets are defined. The computing epochs and performance measures are compared. It is presented that, depending on the structure of ANN, the proposed transfer learning methods can accelerate the training process and achieve higher accuracy. Depending on the method, the transfer learning improves the performance differently.
Stress and Resistance Relaxation for Carbon Nanoparticle Silicone Rubber Composite Large-Strain Sensors
Authors: Ellingham Richard , Giffney Tim
Published: November 2021

The high stretchability, scalability and bio-compatibility of carbon black nanoparticle (CB)-polydimethylsiloxane (PDMS) elastomer composites are attractive characteristics for diverse applications ranging from the biomedical to aerospace fields. These materials are particularly useful as high strain sensors, but show stress relaxation and resistance relaxation behaviour that must be better understood in order to improve sensing performance and optimize the material design. In this work, we have characterized and modelled the resistance relaxation behaviour of these composites to understand the response of resistance to transient step strain input. CB-PDMS specimens have been fabricated with 7.5 and 10 weight percentage (w.t.%) of CB and subjected to repeated stretching while continually monitoring resistance and stress. A model for the resistive relaxation in time has been developed using 30 relaxations to give maximum coefficients of variance of the constants of 18.54% and 52.72% for 7.5 and 10 w.t.% of CB. The ability to model resistance relaxation is useful for the development of, accurate, highly flexible dynamic strain sensors.
Genetic Algorithm-Based Clustering Method to Formulate Standard Specifications for Merchant Ship Preliminary Design
Authors: Gui Chenwei , Zeng Ranyi , Takahashi Kenji , Herai Naoki , Aoyama Kazuhiro
Published: November 2021

In the preliminary design of merchant ships, shipbuilders generally modify some of the standard specifications to fulfill shipowner needs, which is time-consuming owing to the complex techno-economic constraints of ship design. Therefore, an appropriate standard specifications formulation method is necessary to improve the efficiency of the preliminary design. In this study, we performed genetic algorithm-based clustering to determine the subtypes of a specific type of merchant ship and formulated the standard specification for each subtype. To demonstrate the effectiveness of the proposed method, experiments were performed using 98 specification documents to formulate the standard specifications. The results showed that feature relations among each determined subtype were significantly simpler than those of the main type; thereby, the formulated standard specifications were desirable in the preliminary design of merchant ships.
Geometry and Kinematics of Cylindrical Waterbomb Tessellation
Authors: Imada Rinki , Tachi Tomohiro
Published: November 2021

Folded surfaces of origami tessellations have attracted much attention because they sometimes exhibit non-trivial behaviors. It is known that cylindrical folded surfaces of waterbomb tessellation called waterbomb tube can transform into wave-like surfaces, which is a unique phenomenon not observed on other tessellations. However, the theoretical reason why wave-like surfaces arise has been unclear. In this paper, we provide a kinematic model of waterbomb tube by parameterizing the geometry of a module of waterbomb tessellation and derive a recurrence relation between the modules. Through the visualization of the configurations of waterbomb tubes under the proposed kinematic model, we classify solutions into three classes: cylinder solution, wave-like solution, and finite solution. Furthermore, we give proof of the existence of a wave-like solution around one of the cylinder solutions by applying the knowledge of the discrete dynamical system to the recurrence relation.
A Reusable Unit Process Life Cycle Inventory Model for Infeed Centerless Grinding
Authors: Glišić Marija , Veluri Badrinath , Ramanujan Devarajan
Published: November 2021

Environmental impact minimization is an important aspect for improving the sustainability performance of manufacturing processes. Quantifying the environmental impacts of unit manufacturing processes requires systematic modeling of process life cycle inventories. This paper develops an inventory model for infeed centerless grinding based on the unit process life cycle inventory methodology. The developed model estimates the energy consumption, material losses, and consumable fluids, for a typical high-volume production setup. Process consumption data is estimated from parameters directly used for process setup as well as machine and tool specifications that can be easily obtained from technical documentation and product geometrical specification. The developed model is demonstrated using a case study involving the infeed centerless grinding of an Inconel 718 shaft on a Cincinnati Twin-Grip Centerless Grinding Machine.
An Approach for Identifying and Customizing the Effective Ecodesign Tools for Environmentally Sustainable Product Development
Authors: Singh Prashant Kumar , Sarkar Prabir
Published: November 2021

Producing environmentally benign products has now become one of the key challenges of companies across the globe. It can be achieved by utilizing the ecodesign tools in product development process for reducing the environmental impact of products during the design stage itself. Although, the ecodesign tools are available in abundance but there is a lack of studies that can help companies to identify suitable tools. A novel approach has been developed in this study which assists companies to identify and adopt effective ecodesign tools. In this study, three companies related to different product categories are included for testing the proposed approach. Results show that ‘Ecodesign Checklist,’ ‘Material, Energy, Toxicity (MET) Matrix’ and ‘Life Cycle Design Strategy (LiDS) Wheel’ are the three most effective ecodesign tools among the tested tools. Also, it is realized that if these three ecodesign tools are customized and integrated together in a specific sequence then it can be used by the designers, especially novice designers, as an ecodesign methodology. This methodology has the potential to guide designers in the form of a step by step approach during environmentally conscious product development.
A Larger Range Compliant Nano-Manipulator Supporting Electron Beam Lithography
Authors: Liu Yijie , Zhang Zhen
Published: November 2021

Electron beam lithography (EBL) is an important lithographic process of scanning a focused electron beam to direct write a custom pattern with nanometric accuracy. Due to the very limited e-beam field of the focused election beam, a motion stage is needed to move the sample to the e-beam field for processing large patterns. In order to eliminate the stitching error induced by the existing “step and scan” process, we in this paper propose a large range compliant nano-manipulator so that the manipulator and the election beam can be moved in a simultaneous manner. We also present an optimization design for the geometric parameters of the compliant manipulator under the vacuum environment.
Integrating Hedonic Quality for User Experience Modelling
Authors: Tong Yanzhang , Liang Yan , Liu Ying , Hicks Yulia , Spasic Irena
Published: November 2021

Research on user experience (UX) has attracted much attention from designers. Additionally, hedonic quality can help designers understand user interaction (such as attractive, original and innovative) when they experience a product. Realising the user’s interaction state is a significant step for designers to optimise product design and service. Previous UX modelling lacks exploration in user interaction state. Also, the lack of user interaction state factor will reduce the accuracy of the UX modelling. In this paper, we explore the interaction value of online customer review and introduce a new approach to integrating hedonic quality for UX modelling. Firstly, extracting word list from online customer review; Secondly, hedonic quality words are extracted from the word list and added as a hedonic quality part to UX modelling; Thirdly, we compared the analysis result with our previous study for the conclusion. This research combines hedonic quality with UX modelling to enrich modelling in the field of UX for the first time. The proposed data collection method is superior to the traditional collection methods in hedonic quality studies. Extracting hedonic quality factors from online customer reviews can in-depth provide reflections for designers to improve their product design. Furthermore, it also explored the valuable relationship between UX and online customer reviews to provide proactive thinking in user strategy and design activities.
Programmable Stiffness and Applications of 3D Printed TPU Grid Lattices
Authors: Yuan Yifan , Sung Cynthia
Published: November 2021

Additive manufacturing provides a rapid manufacturing method for a variety of materials with different applications. Thermoplastic Polyurethane (TPU) is a soft polymer material that can be 3D printed. In this work, we explore the mechanical properties of a 3D printed grid pattern structure with TPU. By changing the pattern’s cell size and wall thickness parameters, we control the density of the grid lattice and, as a result, the bulk elastic modulus of the structure. We compare simulation and physical compression tests and conclude that the bulk elastic modulus of a print is related to the infill percentage according to a cubic relationship, with higher infill percentage samples resulting in higher elastic moduli. The precise cell size and wall thickness parameter values are minor influences comparatively. The elastic moduli of the resulting samples span from 0.36 MPa with 23.44% infill to 21.83 MPa with 75% infill, compared to an elastic modulus of 64.31 MPa when printing at 100% density. We also explore other factors such as the sample size, the printer, the build orientation, and the sample geometry. The results have uses in a variety of applications, including a custom linear spring, a bistable gripper, or a soft robot finger.
Strut Diameter Uncertainty Prediction by Deep Neural Network for Additively Manufactured Lattice Structures
Authors: Gorguluarslan Recep M. , Ates Gorkem Can , Gungor O. Utku , Yamaner Yusuf
Published: November 2021

Additive manufacturing introduces geometric uncertainties on the fabricated strut members of lattice structures. These uncertainties lead to deviations between the simulation result and the fabricated mechanical performance. Although these uncertainties can be characterized and quantified in the existing literature, the generation of a high number of samples for the quantified uncertainties to use in the computer-aided design of lattice structures for different strut diameters and angles requires high experimental effort and computational cost. The use of deep neural network models to accurately predict the samples of uncertainties is studied in this research to address this issue. For the training data, the geometric uncertainties on the fabricated struts introduced by the material extrusion process are characterized from microscope measurements using random field theory. These uncertainties are propagated to effective diameters of the strut members using a stochastic upscaling technique. The relationship between the deterministic strut model parameters, namely the model diameter and angle, and the effective diameter with propagated uncertainties is established through a deep neural network model. The validation data results show accurate predictions for the effective diameter when model parameters are given as inputs. Thus, the proposed model has the potential to use the fabricated results in the design optimization processes without requiring computationally expensive repetitive simulations.
Actuation-Coordinated Mobile Parallel Robots With Hybrid Mobile and Manipulation Function
Authors: Gan Dongming , Fu Jiaming , Rastgaar Mo , Min Byung-Cheol , Voyles Richard
Published: November 2021

Mobile robots with manipulation capability are a key technology that enables flexible robotic interactions, large area covering and remote exploration. This paper presents a novel class of actuation-coordinated mobile parallel robots (ACMPRs) that utilize parallel mechanism configurations and perform hybrid moving and manipulation functions through coordinated wheel actuators. The ACMPRs differ with existing mobile manipulators by their unique combination of the mobile wheel actuators and the parallel mechanism topology through prismatic joint connections. The common motion of the wheels will provide the mobile function while their differentiation will actuate the parallel manipulator function. This new concept reduces the actuation requirement and increases the manipulation accuracy and mobile motion stability through the coordinated and connected wheel actuators comparing with existing mobile parallel manipulators. The relative wheel location on the base frame also enables a reconfigurable base size with variable moving stability on the ground. The basic concept and general type synthesis are introduced and followed by the kinematics and inverse dynamics analysis of a selected three limb ACMPR. A numerical simulation also illustrates the dynamics model and the motion property of the new mobile parallel robot. The work provides a basis for introducing this new class of robots for potential applications in surveillance, industrial automation, construction, transportation, human assistance, medical applications and other operations in extreme environment such as nuclear plants, Mars, etc.
Assessment of the Run-Out of an Intervertebral Cervical Cage Fabricated by Additive Manufacturing Using Electron Beam Melting
Authors: Cucinotta Filippo , Mineo Rosalia , Raffaele Marcello , Salmeri Fabio
Published: November 2021

Lattice structures made by means of Additive Manufacturing are more and more used in several fields of application. In particular, reticular Titanium alloy bodies are used in biomechanics as fusion devices, due to their biocompatibility and lightweight characteristics. Although these structures have been extensively investigated, it is currently not possible to predict their behavior easily. Indeed, due to the high number of degrees of freedom of the lattice structures, it is usually required to conduct extensive experimental campaigns in order to anticipate the mechanical behavior of complex components.

The present study proposes a method to predict the run-out in an intervertebral cervical cage based on experimental tests conducted on a similar cage and using Finite Element simulations. The cages were made of Ti-6Al-4V ELI by means of Electron Beam Melting. The experimental tests were carried out in accordance with the appropriate ASTM standards. The numerical simulations were consistent with the experimental results and showed a very good agreement.

This methodology helped to identify the most critical issues and to verify a new cage without a second test campaign, which allows both cost and time savings.
Functional Analysis of the Trunk Flexion-Extension Through Gaussian Functions Fitting of the Movement Profile
Authors: Amici Cinzia , Piovanelli Barbara , Ragni Federica , Formicola Raffaele , Cappellini Valter , Candiani Gabriele , Borboni Alberto , Negrini Stefano
Published: November 2021

A healthy mobility of the trunk plays a fundamental role in the activities of daily living. The flexion-extension movement is one of the main tasks evaluated in clinical practice to assess the functionality of the spine. Nevertheless, no fully shared methods are currently available for the clinician to perform quantitative evaluations on the movement quality. In this paper, the trunk flexion-extension task performed by 36 healthy adult subjects, for a total of 104 acquisitions, was acquired with an optoelectronic system of 8 cameras and 32 skin passive optical markers. The absolute displacement of the subject’s seventh thoracic vertebra (T7) was fitted with an asymmetric Gaussian function, comparing the performance of four alternative cost functions in the optimization process. A set of descriptive parameters for the quantitative evaluation of the profile, suitable for the everyday use in the clinical practice, was designed and applied on the current dataset. Statistical analysis was performed on residuals of the fitting process, coefficients of the optimal fitting functions and proposed descriptive parameters, outlining a preliminary description of the trunk flexion-extension movement in the healthy adult.