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Solution-processable electrode-material embedding in dynamically inscribed nanopatterns(SPEEDIN)for continuous fabrication of durable flexible devices

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Microsystems & Nanoengineering 2021年第5期7卷 173-181页

作者： Wonseok Lee Hyoungseok Chae Dong Kyo Oh Minyoung Lee Hyunsoo Chun Gyubeom Yeon Jaewon Park Joohoon Kim Hongseok Youn Junsuk Rho Jong G.Ok Department of Mechanical and Automotive Engineering Seoul National University of Science and TechnologySeoul 01811Republic of Korea Department of Mechanical Engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea Graduate Program of Energy Technology School of Integrated TechnologyInstitute of Integrated TechnologyGwangju Institute of Science and TechnologyGwangju 61005Republic of Korea Department of Mechanical Engineering Hanbat National UniversityDaejeon 34158Republic of Korea Department of Chemical Engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea POSCO-POSTECH-RIST Convergence Research Center for Flat Optics and Metaphotonics Pohang 37673Republic of Korea

A facile and scalable lithography-free fabrication technique,named solution-processable electrode-material embedding in dynamically inscribed nanopatterns(SPEEDIN),is developed to produce highly durable *** uniquely utilizes a single continuous flow-line manufacturing process comprised of dynamic nanoinscribing and metal nanoparticle solution coating with selective ***-and/or micro-trenches are inscribed into arbitrary polymers,and then an Ag nanoparticle solution is dispersed,soft-baked,doctor-bladed,and hard-baked to embed Ag micro-and nanowire structures into the *** to lithographically embossed metal structures,the embedded SPEEDIN architectures can achieve higher durability with comparable optical and electrical properties and are robust and power-efficient even under extreme stresses such as scratching and *** one tangible application of SPEEDIN,we demonstrate a flexible metal electrode that can operate at 5 V at temperatures up to 300℃even under the influence of harsh external *** can be applied to the scalable fabrication of diverse flexible devices that are reliable for heavy-duty operation in harsh environments involving high temperatures,mechanical deformations,and chemical hazards.

关键词： electrode process embedding

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Molecular Dynamics Study of Nanoparticle Collision with a Surface — Implication to Nanoparticle Filtration

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Aerosol and Air Quality Research 2024年第3期7卷 278-303页

作者： Sato, Shintaro Chen, Da-Ren Pui, David Y. H. Particle Technology Laboratory Mechanical Engineering Department University of Minnesota Minneapolis USA Fujitsu Laboratories Ltd. Atsugi Kanagawa Japan Department of Mechanical Engineering Join Program in Environmental Engineering Science Washington University in St. Louis St. Louis USA

Collision dynamics of nanoparticles with a surface was studied by classical molecular dynamics simulations. Silver, nickel and silica were selected as the particle materials, and silver as the surface material. Particle sizes ranged approximately from 0.5 to 2 nm. The results indicate that particles with thermal energy at room temperature do not bounce off a surface, even when a very weak interaction potential between the particles and the surface is assumed. The loss mechanisms of the center-of-mass energy of nanoparticles colliding with a surface were also investigated. The findings indicate that energy losses to the surface and the rotational degree of freedom are important. The loss to the surface is significant when a harder particle hits a softer surface. This is because the center-of-mass energy is mainly transferred to the surface as elastic energy, and the energy is not effectively transferred back to the particle. Non-spherical silica particles were found to lose more energy than the other types of particles. This phenomenon is due to a large energy transfer to the rotational degree of the freedom upon collision.

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Research on Track Fasteners and Rails Surface Detection using Image Recognition and Data Management System technology

Research on Track Fasteners and Rails Surface Detection usin...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Ming-An Chung Chun-Chia Lin Department of Electronic Engineering Master Program in Smart Railway National Taipei University of Technology Taipei Taiwan College of Mechanical and Electrical Engineering Master Program in Smart Railway National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

This research uses image recognition to conduct track fastener and rail surface defect detection. To counteract the dataset imbalance, design an image manager system to change the image's size, brightness, flip, and rotation. Comparing original and enhanced datasets by the precision of three different image recognition, results indicate the improvement of YOLO V8 Nano and optimized YOLO V4. However, the YOLO V7 model has a lower precision rate but a more promising recall rate.

关键词： YOLO Rails Training Image recognition Accuracy Force Fasteners

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Experimental investigation of low-NOx H2 combustion using simultaneous Raman and LIF spectroscopy

Experimental investigation of low-NOx H2 combustion using si...

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AIAA Science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Al Hadi, Z. Basnet, S. Marragou, S. Sharma, P. Schuller, T. Guiberti, T.F. Magnotti, G. Thuwal23955-6900 Saudi Arabia Mechanical Engineering Program Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Institut de Mécanique des Fluides de T95T Université de Toulouse CNRS Toulouse France France

ISBN: (纸本)9781624107238

The global push toward decarbonization has positioned hydrogen as a key contender for clean energy applications. This study explores low-NOx hydrogen/air combustion in a lifted flame configuration using simultaneous 1D Raman and OH-LIF spectroscopy. High resolution measurements of temperature and species concentrations (H2, O2, and OH) provide crucial information on the structure of the flame and the stabilization mechanisms within a dual-swirl burner. The results reveal distinct inner and outer reaction fronts, each exhibiting unique combustion behaviors due to differences in gas composition, temperature, turbulence levels, and strain rates. The study focuses on the dynamics of the edge flame at the base of the outer reaction front, where air and hydrogen progressively mix along the flow axis. Detailed analysis of flow structure, flame dynamics, and properties at key locations highlights the interplay between flow and combustion processes. These findings provide a unique experimental data set for understanding the fundamental characteristics of swirled H2 flames, validating numerical models, and guiding the development of optimized low-NOx H2 combustion systems. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Flow structure

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Improving Track Fastener And Rail Crack Detection Based On Data Enhancement Of Defect Images

Improving Track Fastener And Rail Crack Detection Based On D...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Ming-An Chung Pu-Chun Chen Department of Electronic Engineering Master Program in Smart Railway National Taipei University of Technology Taipei Taiwan College of Mechanical & Electrical Engineering Master Program in Smart Railway National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

In order to solve the defect images of fastener damage and rail fracture are seriously less than the normal images, this study proposes to use the lightweight and fast-identifying YoLov5 to train the model for fastener and rail defects based on the data enhancement of the track defect *** show that the detection data of the model after data enhancement is better than that without data enhancement.

关键词： Rails YOLO Accuracy Fasteners Data models Consumer electronics

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Data Enhancement Based on Adding Noise to Improve The Detection of Rail Surface Defects and Sleeper Fractures

Data Enhancement Based on Adding Noise to Improve The Detect...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Ming-An Chung Jia-Wei Lin Department of Electronic Engineering Master Program in Smart Railway National Taipei University of Technology Taipei Taiwan College of Mechanical & Electrical Engineering Master Program in Smart Railway National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

Railway track inspection and maintenance is a significant topic. This research introduces a track inspection method based on image recognition to attain a rapid and effective track inspection methodology. The approach employs image enhancement technology to augment the dataset’s content, thereby improving the detection accuracy of the track detection model. The experiment indicates an improvement of substantial accuracy when employing image enhancement technology to augment the dataset, irrespective of the YOLOv5n or YOLOv5s model. The model’s average accuracy (mAP50) in detecting sleeper breaks reached the highest score of 99.5%. The datasets are publicly available at https://***/softteacherrail-xxepi/l10_ul_50_2.

关键词： Rails YOLO Training Accuracy Noise Inspection Predictive models

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A Railway Inspection System Based On A Semantic Segmentation Network And Image Processing

A Railway Inspection System Based On A Semantic Segmentation...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Ming-An Chung Chen-You Gao Department of Electronic Engineering Master Program in Smart Railway National Taipei University of Technology Taipei Taiwan Department of Mechanical and Electrical Engineering Master Program in Smart Railway National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

Rail surface defects and missing fasteners are significant topics in railway detection. However, the detection of images may be subject to noise due to the diversity of environmental conditions, leading to a reduction in accuracy. Therefore, the paper proposes a method based on a semantic segmentation network and image processing. First, to address the problem of data preprocessing, this article introduces a bilateral filter into the U-Net algorithm to reduce noise and improve the efficiency of extracting edge features. Second, locations of rail surface defects and missing fasteners were detected from the U-Net. Finally, the article compares with other literature. The proposed method's effectiveness is demonstrated through experimental results, with accuracy rates of 99.9% for rail surface defects and 98.1% for missing fasteners, respectively.

关键词： Rails Accuracy Image synthesis Semantic segmentation Noise Fasteners Inspection

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The planning strategy of robotics technology for nuclear decommissioning in Taiwan

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Nuclear engineering and technology 2024年第1期56卷 64-69页

作者： Tu, Chung Yi Chen, Kuen Tsann Ting, Kuen Yang Sheng, Chin Doctoral Program in Data Science and Industrial Analytics National Chung Hsing University Taichung County 402 Taiwan Department of Applied Mathematics National Chung Hsing University Taichung County 402 Taiwan Department of Mechanical Engineering Lunghwa Univesity of Science and Technology Taoyuan County 33306 Taiwan

According to the market research report, the nuclear decommissioning services market is currently experiencing considerable growth, with a projected Compound Annual Growth Rate (CAGR) of nearly 13% during the 2020–2024 forecast period. This expansion is primarily fueled by the advancement of Industry 4.0, in conjunction with the emergence of cutting-edge technologies such as the Internet of Things, big data, artificial intelligence, and 5G. Even though the fact that robots have already been utilized in the nuclear industry, their adoption has been hindered by conservative regulations. However, the nuclear decommissioning market presents an opportunity for the advancement of robotics technology. The British have already invested heavily in encouraging the use of intelligent robots for nuclear decommissioning, and other countries, such as Taiwan, should follow suit. Taiwan's flourishing robotics development industry in manufacturing, logistics, and other domains can be leveraged to introduce advanced robotics in the decommissioning of its nuclear power plants. By doing so, Taiwan can establish itself as a competitive player in the nuclear decommissioning services market for the next two decades. © 2023 Korean Nuclear Society

关键词： Intelligent robotics Nuclear decommissioning Planning strategy

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A stochastic MPEC approach for grid tariff design with demand-side flexibility

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ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS 2023年第3期14卷 707-729页

作者： Askeland, Magnus Burandt, Thorsten Gabriel, Steven A. Energy Systems SINTEF Energy Research Trondheim Norway Department of Electric Power Engineering Norwegian University of Science and Technology Trondheim Norway Workgroup for Infrastructure Policy Technical University of Berlin Berlin Germany The Energy Transportation Environment Department German Institute for Economic Research (DIW Berlin) Berlin Germany Department of Industrial Economics and Technology Management Norwegian University of Science and Technology Trondheim Norway Department of Mechanical Engineering Applied Math and Statistics Scientific Computation Program University of Maryland College Park MD USA

As the end-users increasingly can provide flexibility to the power system, it is important to consider how this flexibility can be activated as a resource for the grid. Electricity network tariffs is one option that can be used to activate this flexibility. Therefore, by designing efficient grid tariffs, it might be possible to reduce the total costs in the power system by incentivizing a change in consumption patterns. This paper provides a methodology for optimal grid tariff design under decentralized decision-making and uncertainty in demand, power prices, and renewable generation. A bilevel model is formulated to adequately describe the interaction between the end-users and a distribution system operator. In addition, a centralized decision-making model is provided for benchmarking purposes. The bilevel model is reformulated as a mixed-integer linear problem solvable by branch-and-cut techniques. Results based on both deterministic and stochastic settings are presented and discussed. The findings suggest how electricity grid tariffs should be designed to provide an efficient price signal for reducing aggregate network peaks.

关键词： Bilevel problem Grid tariffs Mathematical program with equilibrium constraints (MPEC) Uncertainty

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Modification of Deeplab V3+ for Detecting Cracks on Steel Rail Surfaces

Modification of Deeplab V3+ for Detecting Cracks on Steel Ra...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Ming-An Chung Yi-Xuan Ma Department of Electronic Engineering Master Program in Smart Railway National Taipei University of Technology Taipei Taiwan College of Mechanical and Electrical Engineering Master Program in Smart Railway National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

This study proposes an improved deep learning model for detecting surface cracks on railway steel tracks, addressing the urgent safety needs in the growth of railway construction. The improved Deeplab V3+ model architecture can improve feature extraction efficiency and reduce computational costs. Based on experimental results, the model outperforms others in pixel accuracy and processing speed. This study provides an effective approach for improving railway crack detection, and future work will focus on further optimizing the model for practical applications in railway inspections.

关键词： Accuracy Computational modeling Semantic segmentation Refining Computer architecture Rail transportation Safety

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