检索结果-内蒙古大学图书馆

SSRN 2022年

作者： Wells, David Vadala-Roth, Ben Lee, Jae Ho Griffith, Boyce E. Department of Mathematics University of North Carolina Chapel HillNC United States U.S. Army Corps of Engineers Engineer Research and Development Center Coastal and Hydraulic Laboratory VicksburgMS United States Department of Mechanical Engineering Institute for Computational Medicine Johns Hopkins University BaltimoreMD United States Departments of Mathematics Applied Physical Sciences and Biomedical Engineering University of North Carolina Chapel HillNC United States Carolina Center for Interdisciplinary Applied Mathematics University of North Carolina Chapel HillNC United States Computational Medicine Program University of North Carolina Chapel HillNC United States McAllister Heart Institute University of North Carolina Chapel HillNC United States

The immersed finite element-finite difference (IFED) method is a computational approach to modeling interactions between a fluid and an immersed structure. The IFED method uses a finite element (FE) method to approximate the stresses and forces on a structural mesh and a finite difference (FD) method to approximate the momentum of the entire fluid-structure system on a Cartesian grid. The fundamental approach used by this method follows the immersed boundary framework for modeling fluid-structure interaction (FSI), in which a force spreading operator prolongs structural forces to a Cartesian grid, and a velocity interpolation operator restricts a velocity field defined on that grid back onto the structural mesh. With an FE structural mechanics framework, force spreading first requires that the force itself be projected onto the finite element space. Similarly, velocity interpolation requires projecting velocity data onto the FE basis functions. Consequently, evaluating either coupling operator requires solving a matrix equation at every time step. Mass lumping, in which the projection matrices are replaced by diagonal approximations, has the potential to accelerate this method considerably. This paper provides both numerical and computational analyses of the effects of this replacement for evaluating the force projection and for the IFED coupling operators. Constructing the coupling operators also requires determining the locations on the structure mesh where the forces and velocities are sampled. Here we show that sampling the forces and velocities at the nodes of the structural mesh is equivalent to using lumped mass matrices in the IFED coupling operators. A key theoretical result of our analysis is that if both of these approaches are used together, the IFED method permits the use of lumped mass matrices derived from nodal quadrature rules for any standard interpolatory element. This is different from standard FE methods, which require specialized treatments to

关键词： Fluid structure interaction

来源：评论

学校读者我要写书评

暂无评论

Bayesian Learning-Based Adaptive Control for Safety Critical Systems

Bayesian Learning-Based Adaptive Control for Safety Critical...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： David D. Fan Jennifer Nguyen Rohan Thakker Nikhilesh Alatur Ali-akbar Agha-mohammadi Evangelos A. Theodorou Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta GA USA Department of Mechanical and Aerospace Engineering West Virginia University Morgantown WV USA NASA Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Deep learning has enjoyed much recent success, and applying state-of-the-art model learning methods to controls is an exciting prospect. However, there is a strong reluctance to use these methods on safety-critical systems, which have constraints on safety, stability, and real-time performance. We propose a framework which satisfies these constraints while allowing the use of deep neural networks for learning model uncertainties. Central to our method is the use of Bayesian model learning, which provides an avenue for maintaining appropriate degrees of caution in the face of the unknown. In the proposed approach, we develop an adaptive control framework leveraging the theory of stochastic CLFs (Control Lyapunov Functions) and stochastic CBFs (Control Barrier Functions) along with tractable Bayesian model learning via Gaussian Processes or Bayesian neural networks. Under reasonable assumptions, we guarantee stability and safety while adapting to unknown dynamics with probability 1. We demonstrate this architecture for high-speed terrestrial mobility targeting potential applications in safety-critical high-speed Mars rover missions.

关键词： Safety Adaptation models Bayes methods Stochastic processes Uncertainty Computational modeling Switches

来源：评论

学校读者我要写书评

暂无评论

Magic-angle bilayer phononic graphene

引用

Physical Review B 2020年第18期102卷 180304(R)-180304(R)页

作者： Yuanchen Deng Mourad Oudich Nikhil JRK Gerard Jun Ji Minghui Lu Yun Jing Graduate Program in Acoustics Penn State University University Park Pennsylvania 16802 USA Université de Lorraine CNRS Institut Jean Lamour F-54000 Nancy France Department of Mechanical and Aerospace Engineering North Carolina State University Raleigh North Carolina 27695 USA National Laboratory of Solid State Microstructures and Department of Materials Science and Engineering Nanjing University Nanjing Jiangsu 210093 China

Thanks to the recent discovery of the magic-angle bilayer graphene, twistronics is quickly becoming a burgeoning field in condensed matter physics. This Rapid Communication expands the realm of twistronics to acoustics by introducing twisted bilayer phononic graphene, which remarkably also harbors the magic angle, evidenced by the associated ultraflat bands. Beyond mimicking quantum-mechanical behaviors of twisted bilayer graphene, we show that their acoustic counterpart offers a considerably more straightforward and robust way to alter the interlayer hopping strength, enabling us to unlock magic angles (>3∘) inaccessible in classical twisted bilayer graphene. This study not only establishes the acoustical analog of twisted (magic-angle) bilayer graphene, providing a test bed more easily accessible to probe the interaction and misalignment between stacked two-dimensional materials, but also points out the direction to a new phononic crystal design paradigm that could benefit applications such as enhanced acoustic emission and sensing.

关键词： Acoustic wave phenomena mechanical & acoustical properties Phonons Acoustic metamaterials Metamaterials

来源：评论

学校读者我要写书评

暂无评论

A modified step characteristic method for solving the SN transport equation

A modified step characteristic method for solving the SN tra...

引用

2019 Transactions of the American Nuclear Society, ANS 2019

作者： Wang, Dean Wu, Zeyun Nuclear Engineering Program Ohio State University 201 W 19th Avenue ColumbusOH43210 United States Department of Mechanical and Nuclear Engineering Virginia Commonwealth University 401 West Main Street RichmondVA23284 United States

来源：评论

学校读者我要写书评

暂无评论

Development of a Learning-Based Intention Detection Framework for Power-Assisted Manual Wheelchair Users

Development of a Learning-Based Intention Detection Framewor...

引用

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Mahsa Khalili Yang Zhang Alexandra Gil Leo Zhao Calvin Kuo H. F. Machiel Van der Loos Jaimie F. Borisoff School of Biomedical Engineering the University of British Columbia Vancouver BC Canada Department of Mechanical Engineering the University of British Columbia Vancouver BC Canada Mathematics Department the University of British Columbia Vancouver BC Canada Engineering Physics Program the University of British Columbia Vancouver BC Canada International Collaboration on Repair Discoveries (ICORD) British Columbia Institute of Technology (BCIT)

ISBN: (数字)9781728160757

ISBN: (纸本)9781728160764

Pushrim-activated power-assisted wheels (PAPAWs) are assistive technologies that provide on-demand assistance to wheelchair users. PAPAWs operate based on a collaborative control scheme. Therefore, they rely on accurate interpretation of the user's intent to provide effective propulsion assistance. This paper presents a learning-based approach to predict wheelchair users' intention when performing a variety of wheelchair activities. We obtained kinematic and kinetic data from manual wheelchair users when performing standard wheelchair activities such as turns and ascents. Our measurements revealed variability in physical capabilities and propulsion habits of different users, therefore, highlighting the need for the development of personalized intention inference models. We used Gaussian Mixture models to label different phases of user-pushrim interactions based on individual user's wheeling behaviour. Supervised classifiers were trained with each user's data and these models were used to predict the user's intentions during different propulsion activities. We found random forest classifiers had high accuracy (>92%) in predicting different states of individual-specific wheelchair propulsion and user intent for 2 participants. This proposed framework is computationally efficient and can be used for real-time prediction of wheelchair users' intention. The outcome of this clustering-classification pipeline provides relevant information for designing user-specific and adaptive PAPAW controllers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Homography-Based Deep Visual Servoing Methods for Planar Grasps

Homography-Based Deep Visual Servoing Methods for Planar Gra...

引用

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Austin S. Wang Wuming Zhang Daniel Troniak Jacky Liang Oliver Kroemer Department of Mechanical Engineering Carnegie Mellon University Pittsburgh PA USA Robotics Institute Carnegie Mellon University Pittsburgh PA USA National Robotics Engineering Center Pittsburgh PA USA

We propose a visual servoing framework for learning to improve grasps of objects. RGB and depth images from grasp attempts are collected using an automated data collection process. The data is then used to train a Grasp Quality Network (GQN) that predicts the outcome of grasps from visual information. A grasp optimization pipeline uses homography models with the trained network to optimize the grasp success rate. We evaluate and compare several algorithms for adjusting the current gripper pose based on the current observation from a gripper-mounted camera to perform visual servoing. Evaluations in both simulated and hardware environments show considerable improvement in grasp robustness with models trained using less than 30K grasp trials. Success rates for grasping novel objects unseen during training increased from 18.5% to 81.0% in simulation, and from 17.8% to 78.0% in the real world.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards efficient human-robot collaboration with robust plan recognition and trajectory prediction

arXiv

引用

arXiv 2019年

作者： Cheng, Yujiao Sun, Liting Liu, Changliu Tomizuka, Masayoshi School of Engineering Mechanical Engineering Department University of California Berkeley United States Robotics Institute Carnegie Mellon University Pittsburgh United States

Human-robot collaboration (HRC) is becoming increasingly important as the paradigm of manufacturing is shifting from mass production to mass customization. The introduction of HRC can significantly improve the flexibility and intelligence of automation. To efficiently finish tasks in HRC systems, the robots need to not only predict the future movements of human, but also more high-level plans, i.e., the sequence of actions to finish the tasks. However, due to the stochastic and time-varying nature of human collaborators, it is quite challenging for the robot to efficiently and accurately identify such task plans and respond in a safe manner. To address this challenge, we propose an integrated human-robot collaboration framework. Both plan recognition and trajectory prediction modules are included for the generation of safe and efficient robotic motions. Such a framework enables the robots to perceive, predict and adapt their actions to the human's work plan and intelligently avoid collisions with the human. Moreover, by explicitly leveraging the hierarchical relationship between plans and trajectories, more robust plan recognition performance can be achieved. Physical experiments were conducted on an industrial robot to verify the proposed framework. The results show that the proposed framework could accurately recognize the human workers' plans and thus significantly improve the time efficiency of the HRC team even in the presence of motion classification noises. Copyright © 2019, The Authors. All rights reserved.

关键词： Industrial robots

来源：评论

学校读者我要写书评

暂无评论

The influence of industrial work practices and workshop infrastructure facilities on work readiness of students

引用

Journal of Physics: Conference Series 2021年第1期1833卷

作者： M R A Setyadi M B Triyono R W Daryono Graduate Program of Technological and Vocational Education Universitas Negeri Yogyakarta Yogyakarta Indonesia Department of Mechanical Engineering Education Faculty of Engineering Universitas Negeri Yogyakarta Yogyakarta Indonesia

This study aims to determine the influence of industrial work practice and workshop facilities on work readiness in class XI mechanical engineering. The research subjects were 101 students of class XI mechanical engineering, using the ex post facto research method using statistical analysis using the SPSS program. The results of the study are as follows: (1) Industrial work practices have a positive effect on job readiness with a significance of 0.000, a determination coefficient of 30% has an effect; (2) Workshop infrastructure has a positive influence on work readiness with a significance value of 0.000, 28.6% determination efficiency has an effect; (3) Industrial work practices and infrastructure together have an influence on job readiness indicated by a significance value of 0.000 having a coefficient of determination 58,6% in influencing job readiness.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Wind dispersal of natural and biomimetic maple samaras

arXiv

引用

arXiv 2020年

作者： Nave, Gary K. Hall, Nathaniel Somers, Katrina Davis, Brock Gruszewski, Hope Powers, Craig Collver, Michael David, G. Schmale Ross, Shane D. Engineering Mechanics program Virginia Tech BlacksburgVA United States School of Plant and Environmental Sciences Virginia Tech BlacksburgVA United States Department of Mechanical Engineering Virginia Tech BlacksburgVA United States Department of Civil and Environmental Engineering Virginia Tech BlacksburgVA United States Blacksburg High School BlacksburgVA United States Department of Aerospace and Ocean Engineering Virginia Tech BlacksburgVA United States

Maple trees (genus Acer) accomplish the task of distributing objects to a wide area by producing seeds which are carried by the wind as they slowly descend to the ground, known as samaras. With the goal of supporting engineering applications, such as gathering environmental data over a broad area, we developed 3D-printed artificial samaras. Here, we compare the behavior of both natural and artificial samaras in both still-air laboratory experiments and wind dispersal experiments in the field. We show that the artificial samaras are able to replicate (within 1 standard deviation) the behavior of natural samaras in a lab setting. We further introduce the notion of windage to compare dispersal behavior, and show that the natural samara has the highest mean windage, corresponding to the longest flights during both high wind and low wind experimental trials. This research provides a bioinspired design for the dispersed deployment of sensors and provides a better understanding of wind-dispersal of both natural and artificial samaras. Copyright © 2020, The Authors. All rights reserved.

关键词： 3D printers

来源：评论

学校读者我要写书评

暂无评论

Carpie: A soft, mechanically-reconfigurable worm robot

Carpie: A soft, mechanically-reconfigurable worm robot

引用

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Pouya Ahmadian Rainier F. Natividad Chen-Hua Yeow Department of Mechanical and Industrial Engineering University of Toronto (UofT) Canada Department of Biomedical Engineering National University of Singapore (NUS) Singapore Advanced Robotics Center NUS

Soft robots are a burgeoning archetype in robotics due to their ability to perform intricate movements easily and seamlessly. They serve as an ideal concept for realistically emulating animal movements. However, the majority of soft robots today are unable to vary their motions due to the coupled interaction of the nature of their kinematics and structural composition. We therefore created Carpie, a robotic caterpillar adapted from a modular, pneumatic actuator. Carpie is designed to perform a variety of caterpillar movements by tuning its mechanical structure through physical reconfiguration. The robot has a completely soft body that enables a variety of movements and contortions into different shapes, making Carpie is perhaps the perfect example to showcase a soft robot's aptness for animal mimicry. We analyzed the robot's control aspect. Its capabilities were measured by performing gait velocity studies on three different configurations. Each configuration was executed by applying various modules on Carpie's structure without fully refabricating the entire assembly. We also analyzed the accompanying change in the robot's maximum height during gait. Finally, we demonstrate how physical reconfiguration was able to radically alter Carpie's movement, allowing it to perform a turning motion.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：