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Design of concentrated solar thermal powered heat exchanger completed with energy storage material

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AIP Conference Proceedings 2023年第1期2719卷

作者： Shafira Riskina Adi Setiawan Gunawati Gunawati Rozanna Dewi Magister Program in Renewable Engineering Faculty of Engineering Universitas Malikussaleh Bukit Indah 24352 Lhokseumawe Indonesia Mechanical Engineering Department Faculty of Engineering Universitas Malikussaleh Bukit Indah 24352 Lhokseumawe Indonesia Department of Physics Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Darussalam 23111 Banda Aceh Indonesia Chemical Engineering Department Faculty of Engineering Universitas Malikussaleh Bukit Indah 24352 Lhokseumawe Indonesia

Indonesia is a tropical area and located under the equator line with more than six hours of sunlight a day or about 2400 hours a year. Solar energy has an intensity between 0.6-0.7 kW/m2 and has a potential of 207.8 GWe (electric). This potential can be utilized to reduce the use of fossil energy by harvesting solar energy and transferring it in a helical coil heat exchanger (HCHE) type. This study aims to develop a special proposed heat exchanger design to collect solar thermal energy. As the energy supply is intermittent, a thermal energy storage system is installed. The design of HCHE has coil diameter of 10 mm with thickness of the tube 0.5 mm. HCHE performance test was performed by feeding water to the heat exchanger at a flow rate of 0.006 kg/s where the inlet water temperatures was 27.2˚C. At the outlet, the average temperature was 32.3˚C. During the test, the maximum temperature can be reached by the system was 269.4˚C. This indicates that the solar thermal collector design is working and potentially can be scale-up for energy generating system.

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Can I lift it? Humanoid robot reasoning about the feasibility of lifting a heavy box with unknown physical properties

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arXiv 2020年

作者： Han, Yuanfeng Li, Ruixin Chirikjian, Gregory S. Department of Mechanical Engineering Johns Hopkins University BaltimoreMD United States Department of Mechanical Engineering National University of Singapore Singapore Laboratory for Computational Sensing and Robotics Johns Hopkins University BaltimoreMD United States

A robot cannot lift up an object if it is not feasible to do so. However, in most research on robot lifting, "feasibility" is usually presumed to exist a priori. This paper proposes a three-step method for a humanoid robot to reason about the feasibility of lifting a heavy box with physical properties that are unknown to the robot. Since feasibility of lifting is directly related to the physical properties of the box, we first discretize a range for the unknown values of parameters describing these properties and tabulate all valid optimal quasi-static lifting trajectories generated by simulations over all combinations of indices. Second, a physical-interaction-based algorithm is introduced to identify the robust gripping position and physical parameters corresponding to the box. During this process, the stability and safety of the robot are ensured. On the basis of the above two steps, a third step of mapping operation is carried out to best match the estimated parameters to the indices in the table. The matched indices are then queried to determine whether a valid trajectory exists. If so, the lifting motion is feasible;otherwise, the robot decides that the task is beyond its capability. Our method efficiently evaluates the feasibility of a lifting task through simple interactions between the robot and the box, while simultaneously obtaining the desired safe and stable trajectory. We successfully demonstrated the proposed method using a NAO humanoid robot. Copyright © 2020, The Authors. All rights reserved.

关键词： Trajectories

Modeling the Neuromuscular Control System of an Octopus Arm

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arXiv 2022年

作者： Wang, Tixian Halder, Udit Gribkova, Ekaterina Gazzola, Mattia Mehta, Prashant G. Department of Mechanical Science and Engineering United States Coordinated Science Laboratory United States Neuroscience Program United States National Center for Supercomputing Applications United States Carl R. Woese Institute for Genomic Biology University of Illinois at Urbana-Champaign ChampaignIL61820 United States

The octopus arm is a neuromechanical system that involves a complex interplay between peripheral nervous system (PNS) and arm musculature. This makes the arm capable of carrying out rich maneuvers. In this paper, we build a model for the PNS and integrate it with a muscular soft octopus arm. The proposed neuromuscular architecture is used to qualitatively reproduce several biophysical observations in real octopuses, including curled rest shapes and target-directed arm reaching motions. Two control laws are proposed for target-oriented arm motions, and their performance is compared against a benchmark. Several analytical results, including rest-state characterization and stability properties of the proposed control laws, are provided. © 2022, CC BY-NC-ND.

关键词： Benchmarking

Impacts of Grid Frequency Variation on Dynamic Performance of DFIG Based Wind Turbine 5

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Impacts of Grid Frequency Variation on Dynamic Performance o...

5th International Symposium on Material, Mechatronics and Energy 2018, ISMME 2018

作者： Shiddiq Yunus, A.M. Energy Conversion Study Program Mechanical Engineering Department Politeknik Negeri Ujung Pandang Indonesia

Wind energy is one of popular sources of renewable energy that massively used to generate electric power nowadays. Among wind generator technologies, Doubly Fed Induction Generator (DFIG) is placed as the first dominant wind generator type that is installed worldwide since 2004. Its popularity is due to the advantages of its capability to extract more energy compare to the fixed speed type. Moreover, it uses only one-third converter size which reduced the total construction cost compared to its closest rival, Full Converter Wind Turbine Generator Type. Although DFIG widely installed worldwide, it is in fact, very sensitive to the grid disturbances such as frequency variation. Based on IEEE standard for 60 Hz system, a power system should not be allowed to work in less than 59.3 Hz or more than 60.5 Hz. In this paper, DFIG-grid connected is extensively simulated in the condition of frequency variation that is carried out using Matlab/Simulink. The results show that some important parameters such as power output of the generator, voltage at point of common coupling, voltage at DC link and generator speed are experiencing significant rise/drop which in turn might damage the wind turbine generator. © Published under licence by IOP Publishing Ltd.

关键词： Wind Turbine Generators

Deep potentials for materials science

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材料展望（英文）

材料展望（英文） 2022年第2期 89-115页

作者： Tongqi Wen Linfeng Zhang Han Wang Weinan E David J Srolovitz Department of Mechanical Engineering The University of Hong KongHong KongHong Kong Special Administrative Region of China DP Technology BeijingPeople's Republic of China AI for Science Institute BeijingPeople's Republic of China Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijingPeople's Republic of China HEDPS CAPTCollege of EngineeringPeking UniversityBeijingPeople's Republic of China AI for Science Institute BeijingPeople's Republic of China School of Mathematical Sciences Peking UniversityBeijingPeople's Republic of China Department of Mathematics and Program in Applied and Computational Mathematics Princeton UniversityPrincetonNJUnited States of America Department of Mechanical Engineering The University of Hong KongHong KongHong Kong Special Administrative Region of China International Digital Economy Academy(IDEA) ShenzhenPeople's Republic of China

To fill the gap between accurate(and expensive)ab initio calculations and efficient atomistic simulations based on empirical interatomic potentials,a new class of descriptions of atomic interactions has emerged and been widely applied;*** learning potentials(MLPs).One recently developed type of MLP is the deep potential(DP)*** this review,we provide an introduction to DP methods in computational materials *** theory underlying the DP method is presented along with a step-by-step introduction to their development and *** also review materials applications of DPs in a wide range of materials *** DP Library provides a platform for the development of DPs and a database of extant *** discuss the accuracy and efficiency of DPs compared with ab initio methods and empirical potentials.

关键词： deep potential atomistic simulation machine learning potential neural network

Functional mimicry of Ruffini receptors with Fiber Bragg Gratings and Deep Neural Networks enables a bio-inspired large-area tactile sensitive skin

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arXiv 2022年

作者： Massari, Luca Fransvea, Giulia D’Abbraccio, Jessica Filosa, Mariangela Terruso, Giuseppe Aliperta, Andrea D’Alesio, Giacomo Zaltieri, Martina Schena, Emiliano Palermo, Eduardo Sinibaldi, Edoardo Oddo, Calogero Maria The BioRobotics Institute Polo Sant’Anna Valdera Scuola Superiore Sant’Anna Viale Rinaldo Piaggio 34 Pontedera 56025 Italy Department of Excellence in Robotics & AI Scuola Superiore Sant’Anna Pisa56127 Italy ARTES4.0 Competence Center on Advanced Robotics and enabling digital TEchnologies and Systems Pontedera 56025 Italy Research Unit of Measurements and Biomedical Instrumentation Department of Engineering Università Campus Bio-Medico di Roma Via Alvaro del Portillo 21 Roma00128 Italy Department of Mechanical and Aerospace Engineering Sapienza University of Rome Via Eudossiana 18 Roma00184 Italy Istituto Italiano di Tecnologia Via Morego 30 Genoa16163 Italy

Collaborative robots are expected to physically interact with humans in daily living and workplace, including industrial and healthcare settings. A related key enabling technology is tactile sensing, which currently requires addressing the outstanding scientific challenge to simultaneously detect contact location and intensity by means of soft conformable artificial skins adapting over large areas to the complex curved geometries of robot embodiments. In this work, the development of a large-area sensitive soft skin with a curved geometry is presented, allowing for robot total-body coverage through modular patches. The biomimetic skin consists of a soft polymeric matrix, resembling a human forearm, embedded with photonic Fiber Bragg Grating (FBG) transducers, which partially mimics Ruffini mechanoreceptor functionality with diffuse, overlapping receptive fields. A Convolutional Neural Network deep learning algorithm and a multigrid Neuron Integration Process were implemented to decode the FBG sensor outputs for inferring contact force magnitude and localization through the skin surface. Results achieved 35 mN (IQR = 56 mN) and 3.2 mm (IQR = 2.3 mm) median errors, for force and localization predictions, respectively. Demonstrations with an anthropomorphic arm pave the way towards AI-based integrated skins enabling safe human-robot cooperation via machine *** Codes 68T40 © 2022, CC BY.

关键词： Fiber Bragg gratings

Development of a Hand Exoskeleton System for Quantitative Analysis of Hand Functions

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Journal of Bionic engineering 2018年第5期15卷 783-794页

作者： Jeongsoo Lee Minhyuk Lee Joonbum Bae Bio-Robotics and Control (BiRC) Laboratory Department of Mechanical Engineering UNIST Ulsan Republic of Korea

This paper proposes a hand exoskeleton system for evaluating hand functions. To evaluate hand functions, the hand exoskeleton system must be able to pull each finger joint, measure the finger joint angle and exerted force on the finger simultaneously. The proposed device uses serially connected 4-bar linkage structures, which have two embedded actuators with encoders and two loadcells per finger, to move each phalanx independently and measure the finger joint angles. A modular design was used for the exoskeleton, to facilitate the removal of unnecessary modules in different experiments and improve convenience. Silicon was used on the surface of the worn part to reduce the skin irritation that results from prolonged usage. This part was also designed to be compatible with various finger thicknesses. Using the proposed hand exoskeleton system, finger independence, multi-finger synergy, and finger joint stiffness were determined in five healthy subjects. The finger movement and force data collected in the experiments were used for analyzing three hand functions based on the physical and physiological phenomena.

关键词： evaluation of hand function hand rehabilitation wearable system exoskeleton

International commitment to safe nuclear reactors-Response

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Science (New York, N.Y.) 2025年第6733期387卷 483页

作者： R Scott Kemp Edwin S Lyman Mark R Deinert Richard L Garwin Frank N von Hippel Department of Nuclear Science and Engineering Massachusetts Institute of Technology Cambridge MA USA. Union of Concerned Scientists Washington DC USA. Nuclear Science and Engineering Program Department of Mechanical Engineering Colorado School of Mines Golden CO USA. IBM Thomas J. Watson Research Center Yorktown Heights NY USA. Program on Science and Global Security Princeton University Princeton NJ USA.

Radar Occupancy Prediction with Lidar Supervision while Preserving Long-Range Sensing and Penetrating Capabilities

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arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh The Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan The Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan The Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

Radar shows great potential for autonomous driving by accomplishing long-range sensing under diverse weather conditions. But radar is also a particularly challenging sensing modality due to the radar noises. Recent works have made enormous progress in classifying free and occupied spaces in radar images by leveraging lidar label supervision. However, there are still several unsolved issues. Firstly, the sensing distance of the results is limited by the sensing range of lidar. Secondly, the performance of the results is degenerated by lidar due to the physical sensing discrepancies between the two sensors. For example, some objects visible to lidar are invisible to radar, and some objects occluded in lidar scans are visible in radar images because of the radar's penetrating capability. These sensing differences cause false positive and penetrating capability degeneration, respectively. In this paper, we propose training data preprocessing and polar sliding window inference to solve the issues. The data preprocessing aims to reduce the effect caused by radar-invisible measurements in lidar scans. The polar sliding window inference aims to solve the limited sensing range issue by applying a near-range trained network to the long-range region. Instead of using common Cartesian representation, we propose to use polar representation to reduce the shape dissimilarity between long-range and near-range data. We find that extending a near-range trained network to long-range region inference in the polar space has 4.2 times better IoU than in Cartesian space. Besides, the polar sliding window inference can preserve the radar penetrating capability by changing the viewpoint of the inference region, which makes some occluded measurements seem non-occluded for a pretrained network. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar