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12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019

作者： Lee, Han-Joo Melchor, Noe Loh, Kenneth J. Materials Science and Engineering Program University of California-San Diego San DiegoCA92093 United States Department of Mechanical and Aerospace Engineering University of California-San Diego San DiegoCA92093 United States Department of Structural Engineering University of California-San Diego San DiegoCA92093 United States

ISBN: (纸本)9781605956015

Remotely operated vehicles (ROV) conduct tasks that are generally dangerous or ineffective for humans, such as exploring and surveying the ocean for extended periods of time. Current underwater ROVs are complex assemblies of mostly rigid components designed for interacting with the environment, locomotion, and buoyancy control. Several recent studies introduced methods to replace these components with soft actuators to improve their performance. This study shows that actuation through ultrasonic atomization is capable of inflating a soft structure that can potentially replace traditional variable buoyancy systems. Ultrasonic waves were applied to a soft hollow structure that was partially filled with ethanol. The ultrasonic waves propagated through the wall of the structure and atomized ethanol into small vapor droplets. The liquid-togas phase transformation of the small droplets inflated the structure and controlled the buoyancy of the system. In this study, the volumetric change of the soft structure was analyzed underwater, and a simple system to control buoyancy was demonstrated. © International Workshop on Structural Health Monitoring. All rights reserved.

关键词： Ethanol

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State Observation of Affine-in-the-States Time-Varying Systems with Unknown Parameters and Delayed Measurements

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IFAC-PapersOnLine 2021年第14期54卷 108-113页

作者： Alexey Bobtsov Nikolay Nikolaev Romeo Ortega Denis Efimov Department of Control Systems and Robotics ITMO University Kronverkskiy av. 49 Saint-Petersburg 197101 Russia Departamento Académico de Sistemas Digitales ITAM Ciudad de México México INRIA Univ. Lille CNRS UMR 9189 - CRIStAL F-59000 Lille France Laboratory “Control of Complex Systems” Institute of Problems of Mechanical Engineering V.O. Bolshoj pr. 61 St. Petersburg 199178 Russia

In this paper we address the problem of adaptive state observation of affine-in-the-states time-varying systems with delayed measurements and unknown parameters. The case with known parameters has been studied by many researchers—see [Sanz et al. 2019, Bobtsov et al. 2021] and references therein—where, similarly to the approach adopted here, the system is treated as a linear time-varying system. We show that the parameter estimation-based observer (PEBO) design proposed in [Ortega et al. 2015, 2020] provides a very simple solution for the unknown parameter case. Moreover, when PEBO is combined with the dynamic regressor extension and mixing (DREM) estimation technique [Aranovskiy et al. 2016, Ortega et al. 2019], the estimated state converges in fixed-time with extremely weak excitation assumptions.

关键词： Nonlinear time-varying systems state observer delay systems parameter estimation

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Socially-Acceptable Walking Parameters for Wheelchair Automation

Socially-Acceptable Walking Parameters for Wheelchair Automa...

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IEEE Conference on Cybernetics and Intelligent Systems

作者： Sean Wong Jun Zhong Lee Wai Leong Marcelo H. Ang Department of Mechanical Engineering National University of Singapore Singapore Faculty of Engineering Advanced Robotics Center National University of Singapore Singapore

ISBN: (数字)9781728134581

ISBN: (纸本)9781728134598

Socially-acceptable navigation patterns are key to smoothly integrating robots into human daily life. This paper addresses such issues without attempting to use complex algorithms that are difficult to support with low-level controllers. Through observational data collection, this paper finds average walking patterns that can be adhered to by rough guidelines that provide significant tolerances for low-level robots in varying situations. These guidelines can be applied to many different robotic systems but are intended for use with the WHILL Model C wheelchair, where parameter data has been collected to ensure compatibility. Finally, the concept of rider comfort has been briefly accounted briefly accounted for when adjusting the robot's parameters.

关键词： Turning Legged locomotion Acceleration Wheelchairs Standards

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Bending wave based characterization of viscoelastic materials 23

Bending wave based characterization of viscoelastic material...

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23rd International Congress on Acoustics: Integrating 4th EAA Euroregio, ICA 2019

作者： Miller, Max Malakooti, Sadeq Taghvaee, Tahereh Xiang, Ning Lu, Hongbing Leventis, Nicholas Graduate Program in Architectural Acoustics Rensselaer Polytechnic Institute United States Department of Mechanical Engineering University of Texas Dallas United States Department of Chemistry Missouri University of Science and Technology United States

ISBN: (纸本)9783939296157

Obtaining broadband dynamic mechanical properties of viscoelastic materials is challenging. Commercially available characterization equipment is typically limited to about 500 Hz. Ultrasonic testing is a common strategy but requires time-temperature superposition extrapolation to audible frequencies. These techniques are indirect and sensitive to inhomogeneities. Modal methods do not yield broadband data and can fail for materials with high loss factors. A new relatively simple characterization method, relying on bending wave excitation and laser Doppler vibrometer measurement, is proposed. Complex elastic moduli and phase speeds are now attainable over the entire range of building acoustics frequencies. The materials under test are an array of polyurea aerogels with fixed chemical composition but tailorable nanomorphologies. Low cost and ease of synthesis add appeal to materials already noted for their sound transmission loss performance [4]. © 2019 Proceedings of the International Congress on Acoustics. All rights reserved.

关键词： Bending Characterization Damping Flexural Transmission

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EPN: Edge-Aware PointNet for Object Recognition from Multi-View 2.5D Point Clouds

EPN: Edge-Aware PointNet for Object Recognition from Multi-V...

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

作者： Syeda Mariam Ahmed Pan Liang Chee Meng Chew Department of Mechanical Engineering National University of Singapore Advanced Robotics Center National University of Singapore

Performance of current 3D point based detectors is limited by the number of points they can process, consequently limiting their accuracy. In this paper we propose a novel architecture coined as Edge-Aware PointNet, that incorporates geometric shape priors as binary maps, integrated in parallel with the PointNet++ framework, through convolutional neural networks (CNNs). The proposed architecture takes individual object instances as input and learns the task of object recognition for 3D shapes. To train the network, we present a dataset of 31k 2.5D synthetic point clouds rendered from ModelNet40. Through 2.5D representation, the network learns object recognition despite occlusion that enables improved performance on objects from real world, while 2D binary maps enable feature learning that is independent of number of points in the point cloud. Comprehensive experimentation shows that the proposed network is able to improve performance by 2.5% on ModelNet40 and 2.6% on ModelNet10 datasets, as compared to the baseline PointNet++. We also show improved performance as compared to state-of-the-art methods, on a real world RGBD dataset where our network improves results by 8%. Our code and dataset is publicly available at ***/Merium88/Edge-Aware-PointNet.

关键词：

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Comparative Analysis of Hybrid Sliding Mode and Classical Controllers for Ni-Ti SMA Smart Actuator Position Control 6

Comparative Analysis of Hybrid Sliding Mode and Classical Co...

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6th International Conference on Advanced Control Circuits and Systems and 5th International Conference on New Paradigms in Electronics and Information Technology, ACCS/PEIT 2019

作者： Alsayed, Y.M. Salem, Mahmoud M. Abouelsoud, A.A. Fath Elbab, A.M.R. School of Innovative Design Engineering Egypt-Japan University of Science and Technology Mechatronics and Robotics Engineering Department PO Box: 21934 New Borg E1 Arab City Alexandria Egypt Power Electronics and Energy Conversion Dept. Cairo Egypt Cairo University Dept. of Electrical Engineering Cairo Egypt Assiut University Dept. of Mechanical Engineering Assiut Egypt

ISBN: (纸本)9781728163543

In this paper, a comparative analysis of Hybrid Sliding Mode PI and classical PI with intelligent properties controllers for Ni-Ti SMA smart actuator position control is presented. The SMA actuator mechanical dynamics are obtained using one-way actuator model. The actuator returns to its initial position using bias spring force. The SMA material model using the shear-strain driven approach is discussed. Two different controllers are presented and compared as a SMA actuator position controllers. The Hybrid Sliding Mode PI and the classical PI with intelligent properties controllers are compared. The comparison results depict that the controller with intelligent properties advantages surpass the advantages of the Hybrid Sliding Mode PI controller and it improves the rising and settling times of output displacement response. Both controllers provide output displacement without overshoot and zero steady state error which are essential in smart actuators applications. © 2019 IEEE.

关键词： Controllers

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Corrigendum: Moving Next-Generation Phase-Field Models to BMS Applications -A Case Study that Confirms Professor Uzi Landau's Foresight [J. Electrochem. Soc., 171, 063507 (2024)]

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Journal of The Electrochemical Society 2024年第8期171卷 089002-089002页

作者： Tushar K. Telmasre Anthony César Concepción Suryanarayana Kolluri Lubhani Mishra Raghav S. Thiagarajan Aditya Naveen Matam Akshay Subramaniam Taylor R. Garrick Venkat R. Subramanian Materials Science and Engineering Program Texas Materials Institute The University of Texas at Austin Austin TX 78712 United States of America Walker Department of Mechanical Engineering The University of Texas at Austin Austin TX 78712 United States of America Battery Materials and Systems Research General Motors Global Research and Development Center Warren MI 48090 United States of America Chandra Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX 78712 United States of America Energy Storage and Propulsion R&D and Manufacturing Engineering General Motors Technical Center Warren MI 48092 United States of America Affiliate Faculty Oden Institute for Computational Science and Engineering The University of Texas at Austin Austin TX 78712 United States of America

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Prediction of the time constant of small-scale concentrated solar CHP plants

Prediction of the time constant of small-scale concentrated ...

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2020 Applied Energy Symposium (ICAE), 100RES 2020

作者： Tascioni, Roberto Pirro, Matteo Arteconi, Alessia Del Zotto, Luca Bartolini, Carlo M. Mahkamov, Khamid Mahkamova, Irina Cabeza, Luisa F. De Gracia, Alvaro Pili, Piero Mintsa, André C. Gimbernat, Toni Botargues, Teresa Mullen, David Cioccolanti, Luca 20060 Italy Diaee Sapienza Università di Roma via Eudossiana 18 Rome00184 Italy Società per Il TRAsferimento TEcnologico e Guida All'Innovation Engineering S.TRA.TE.G.I.E. Srl via Sandro Totti 1 Ancona60131 Italy Diism Università Politecnica Delle Marche Via Brecce Bianche 1 Ancona60131 Italy Department of Mechanical Engineering Ku Leuven Celestijnenlaan 300 Leuven3001 Belgium Department Mechanical Engineering and Construction Northumbria University Newcastle upon TyneNE1 8ST United Kingdom GREiA Research Group Universitat de Lleida Pere de Cabrera s/n Lleida25001 Spain 09010 Italy Enogia S.A.S 19 Avenue Paul héroult Marseille13015 France E3G Ingegneria y Energia Av. Estudi General 7 Altell 5 Lleida25001 Spain User Feedback Program Sl Sant Jaume Apòstol 8 Almenar25126 Spain Aavid Thermacore Europe 12 Wansbeck Business Park Ashington NorthumberlandNE63 8QW United Kingdom

The operation of a power plant based on solar energy can vary significantly with time because of the intrinsic intermittency of the energy resource. Hence, a smart management is required to deal with the complex dynamic variations of the different subsystems. In order to do that, different control logics can be implemented but their effectiveness strictly depends on the temporal evolution of the parameters considered. For a given plant configuration, their exact estimation can be obtained through experimental tests during the commissioning of the plant. However, any change in the design parameters of the plant reflects in a different time constant, whose preliminary knowledge may be of support in tuning the control logic of the plant during the design stage. Therefore, based on the configuration of a small-scale concentrated solar combined heat and power plant as designed and built under the EU funded project Innova MicroSolar by several universities and companies, in this study a prediction of the time constant of several plant configurations with varying solar multiple and size of the storage tank is performed. By making use of the dynamic simulator previously developed by some of the authors, an estimation of such characteristic is assessed in case of potential redesign of the plant, providing also useful suggestions into the design of the control logic. © The Authors, published by EDP Sciences, 2021.

关键词： Cogeneration plants

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A Hybrid Optimization Approach Towards Energy Recovery from Torrefied Waste Blends

SSRN

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SSRN 2022年

作者： Silveira, Edgar Amaral Chaves, Bruno Santanna Macedo, Lucélia A. Ghesti, Grace F. Evaristo, Rafael B.W. Lamas, Giulia Cruz Luz, Sandra M. de Paula Protásio, Thiago Rousset, Patrick Mechanical Sciences Graduate Program University of Brasília DF Brasília Brazil Forest Engineering Department University of Brasília DF Brasília70910-900 Brazil Laboratory of Brewing Bioprocesses and Catalysis to Renewable Energy Chemistry Institute University of Brasilia DF Brasilia70910-900 Brazil Pará Parauapebas68515-000 Brazil CIRAD UPR BioWooEB MontpellierF-34398 France BioWooEB Univ. Montpellier CIRAD Montpellier France

Waste-to-energy has gained momentum as a valorization pathway for resource-efficient strategies. Previous studies assessed the improvement of single biomass sources by torrefaction, evoking its potential in optimizing solid renewable fuel. However, as commercial torrefaction expands, the common feedstock will likely be a biomasses blend. Therefore, property improvement of the biomasses and their blends is required to elevate commercial product value. This article proposes a hybrid approach based on multicriteria decision methods (MCDM) and response surface methodology (RSM) to optimize the definition of Urban Forest Waste (UFW) blends and their torrefaction. First, the physicochemical characteristics (proximate, ultimate, and calorific) of six urban wood waste ( Mangifera indica, Ficus benjamina, Pelthophorum dubium, Persea americana, Anadenanthera colubrina, Tapirira guianensis ) were assessed. Then, based on the understanding that wastes rely on distinct species that do not always show promising properties for conversion, an optimum blend (OB) was determined by MCDM. Next, the OB was subjected to inert (nitrogen) torrefaction in macro-thermogravimetric equipment (residence time (20–60 min) and temperature (225–275 °C). Finally, the process parameters were optimized using a central composite design (RSM-CCD) model, providing the optimum torrefaction condition and a torrefied optimum blend (TOB). As the main application of biomass for urban integration is direct combustion, the main properties and combustion behavior of optimized blends were assessed. The MCDM and RSM-CCD provided a superior solid biofuel (TOB) with lower ash (2.67%), a higher heating value of 20.87 *** -1 , and more stable combustion with a less costly torrefaction (273 °C for 40 min). In addition, the blend optimization reduced by 28.4% the nitrogen content in TOB compared to non-optimized biomass, providing a solid biofuel with a lower potential of NO emissions in further applications. The resu

关键词： Biomass

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Deep reinforcement learning with feedback-based exploration

arXiv

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arXiv 2019年

作者： Scholten, Jan Wout, Daan Celemin, Carlos Kober, Jens Cognitive Robotics Department Faculty of Mechanical Maritime and Materials Engineering Delft University of Technology Netherlands

Deep Reinforcement Learning has enabled the control of increasingly complex and high-dimensional problems. However, the need of vast amounts of data before reasonable performance is attained prevents its widespread application. We employ binary corrective feedback as a general and intuitive manner to incorporate human intuition and domain knowledge in model-free machine learning. The uncertainty in the policy and the corrective feedback is combined directly in the action space as probabilistic conditional exploration. As a result, the greatest part of the otherwise ignorant learning process can be avoided. We demonstrate the proposed method, Predictive Probabilistic Merging of Policies (PPMP), in combination with DDPG. In experiments on continuous control problems of the OpenAI Gym, we achieve drastic improvements in sample efficiency, final performance, and robustness to erroneous feedback, both for human and synthetic feedback. Additionally, we show solutions beyond the demonstrated knowledge. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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