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An extraordinary-performance gradient nanostructured Hadfield manganese steel containing multi-phase nanocrystalline-amorphous core-shell surface layer by laser surface processing

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Journal of Materials Science & technology 2023年第3期134卷 209-222页

作者： Wanting Sun Jiasi Luo Yim Ying Chan J.H.Luan Xu-Sheng Yang Research Institute for Advanced Manufacturing Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityHung HomHong KongChina Hong Kong Branch of National Rail Transit Electrification and Automation Engineering Technology Research Center The Hong Kong Polytechnic UniversityHung HomHong KongChina Department of Materials Science and Engineering City University of Hong KongHong KongChina

Reducing grain size(*** the fraction of grain boundaries)could effectively strengthen nanograined metals but inevitably sacrifices the ductility and possibly causes a strengthening-softening transition below a critical grain *** this work,a facile laser surface remelting-based technique was employed and optimized to fabricate a∼600μm-thick heterogeneous gradient nanostructured layer on an austenitic Hadfield manganese steel,in which the average grain size is gradually decreased from∼200μm in the matrix to only∼8 nm in the nanocrystalline-amorphous core-shell topmost ***-scale microstructural characterizations dissected the gradient refinement processes along the gradient direction,*** from the dislocations activities and twinning in sub-region to three kinds of martensitic transformations,and finally a multi-phase nanocrystalline-amorphous core-shell structural *** tests(***,bulk-specimen tensile,and micro-pillar compression)were conducted along the gradient *** confirms a tensile strength of∼1055 MPa and ductility of∼10.5%in the laser-processed ***,the core-shell structural surface maintains ultra-strong(tensile strength of∼1.6 GPa,micro-pillar compressive strength of∼4 GPa at a strain of∼8%,and nanoindentation hardness of∼7.7 GPa)to overcome the potential strengthening-softening *** significant strengthening effects are ascribed to the strength-ductility synergetic effects-induced extra work hardening ability in gradient nanostructure and the well-maintained dislocation activities inside extremely refined nanograins in the multi-phase nanocrystalline-amorphous core-shell structural surface,which are evidenced by atomic-scale observations and theoretical *** study provides a unique hetero-nanostructure through a facile laser-related technique for extraordinary mechanical performance.

关键词： Laser surface processing Hadfield manganese steel Gradient nanostructure Nanocrystalline-amorphous Martensitic transformation

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Effects of Control Transition Strategies and Human-Machine Interface Designs on Driver Performance in Automated Driving systems

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International Journal of Automotive engineering 2024年第1期15卷 36-46页

作者： Leung, Chokiu Zhou, Huiping Itoh, Makoto Kitazaki, Satoshi Graduate School of Systems and Information Engineering University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba-city305-8573 Japan Institute of Systems and Information engineering University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba-city305-8573 Japan Institute of Systems and Information engineering Center for Artificial Intelligence Research University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba-city305-8573 Japan National Institute of Advanced Industrial Science and Technology 1-1-1 Higashi Ibaraki Tsukuba305-8566 Japan

This study addresses an issue arising during requests to intervene, usually focused on the direct shift of control from the system to an unprepared driver. We explore an approach based on the concept of adaptive automation. The approach is utilized to establish a strategy that the automated driving system can modulate between different driving states (Level 0 (L0) to Level 3 (L3) driving automation) based on traffic situations. Furthermore, we aim to design Human-Machine Interface (HMI) instructions that align with two design perspectives: system-centered (Implicit) and human-centered (Explicit). These HMI instructions critical to the strategy implemented are intended to sustain awareness on driver roles and decrease inappropriate driver responses during transitions. In the experiment, we utilized two approaches (adaptive control transition strategy and fixed control transition strategy) and two HMI designs. The experiment with a driving simulator was conducted with 60 drivers. The research questions explored include the influence of HMI design on drivers’ awareness during shifts from L3 to L2/L1. Also, we examine how different combinations of a strategy and HMI design affect reaction times from L3 to L0 scenarios. Compared to Implicit-HMI, the use of Explicit-HMI did not lead to inappropriate actions associated with their driving roles. This indicates that Explicit-HMI facilitates accurate response to state changes during the implementation of the adaptive approach. In terms of the comparison of the combinations, it is found that the adaptive approach provides initial guidance for drivers to monitor the environment, thereby providing earlier reaction time for the transition to manual. © 2024 Society of Automotive Engineers of Japan, Inc. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.

关键词： Automation

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Enhancing electronic properties by suppressing nucleation delay for low-temperature processed atomic-layer-deposited amorphous zinc–tin-oxide thin films

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Ceramics International 2024年第9期50卷 15085-15091页

作者： Hung, Hsin-Ning Cheng, Ching-Yun Cheng, I-Chun Shyue, Jing-Jong Wang, Ching-Chiun Tsai, Feng-Yu Department of Materials Science and Engineering National Taiwan University Taipei10617 Taiwan Graduate Institute of Photonics and Optoelectronics National Taiwan University Taipei10617 Taiwan Research Center for Applied Science Academia Sinica Taipei11529 Taiwan Mechanical and Systems Research Laboratories Industrial Technology Research Institute 195 Section 4 Chung Hsing Road Hsinchu Taiwan Advanced Research Center for Green Materials Science and Technology Taipei10617 Taiwan

Atomic-layer-deposited (ALD) zinc-tin-oxide (ZTO) thin films offer promising electronic properties for many applications, but their development has been limited by their tendency to experience significant nucleation delay—which tends to introduce impurity—during deposition. This study utilized in-situ quartz crystal microbalance (QCM) analysis combined with ex-situ compositional analysis to examine the nucleation-delay characteristics of ZTO ALD and their dependence upon the oxidant-precursor settings. The results indicated that nucleation delay occurred solely during the ZnO-on-SnO2 deposition step as a result of persisting ethyl ligands of the organozinc precursor, diethylzinc, which could be mitigated by using H2O2 instead of H2O as the oxidant precursor and introducing a discrete-feeding or exposure procedure for the H2O2 half cycle to increase the effective oxidant dose. The effects of nucleation delay on the electronic properties of ALD ZTO films was examined with thin-film transistor (TFT) devices, where suppression of nucleation delay yielded substantial improvement in the device performance, achieving a high field-effect mobility of 21.5 cm2/V s, low sub-threshold swing of 0.16, high on/off ratio of 2 × 108, and enhance-mode operation without needing elevated-temperature post-processing. The findings present valuable improvements over the state of the art and provide insights useful for the development of other types of ALD multi-component films. © 2024

关键词： Nucleation

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Solving PnP Problem Using Improved Sparrow Search Algorithm

Solving PnP Problem Using Improved Sparrow Search Algorithm

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IEEE International Symposium on Intelligent Signal Processing and Communication systems (ISPACS)

作者： Kurihara Riku Kousuke Matsushima Advanced Engineering Course National Institute of Technology Kurume College Kurume Japan Department of Control and Information Systems Engineering National Institute of Technology Kurume College Kurume Japan

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

The Perspective-n-Point (PnP) problem is a fundamental challenge in engineering that plays a crucial role in fields such as computer vision and augmented reality. This problem aims to estimate the position and orientation (pose) of a camera from known 3D points and their corresponding 2D projections on the image plane. With recent technological advancements, application areas such as autonomous vehicles, drones, and robotics are demanding increasingly faster and more accurate camera pose estimation. To address this challenge, we have introduced an improved Sparrow Search Algorithm (SSA) with the capability to dynamically restrict the search area. While the conventional SSA demonstrated excellent optimization capabilities, it faced efficiency issues when searching in high-dimensional spaces, such as those encountered in PnP problems. Our enhancement enables the algorithm to leverage information obtained during the search process to gradually narrow down the search area, thereby more efficiently locating the optimal solution.

关键词： Point cloud compression Accuracy Three-dimensional displays Heuristic algorithms Robot vision systems Pose estimation Signal processing algorithms Search problems Cameras Optimization

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Mobile Generalized Category Discovery for Road Damage Detection

Mobile Generalized Category Discovery for Road Damage Detect...

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IEEE International Symposium on Intelligent Signal Processing and Communication systems (ISPACS)

作者： Akashi Rintaro Kousuke Matsushima Advanced Engineering Course National Institute of Technology Kurume College Kurume Japan Department of Control and Information Systems Engineering National Institute of Technology Kurume College Kurume Japan

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

In recent years, there has been a considerable amount of research conducted on the topic of road damage detection using deep learning techniques, with the aim of supporting the safe driving of mobility vehicles. To date, convolutional neural networks and supervised learning with large datasets have been employed for road damage detection, demonstrating high classification accuracy. However, all images in the dataset must be manually labeled. Moreover, images cannot be classified into classes that are not included in the training dataset. The real world presents a vast array of damage types, and the unlabeled input images encompass both known and unknown classes. This renders the system unsuitable for use in providing safe driving support for mobility. Considering this background, Generalized Category Discovery (GCD) has been put forth as a potential solution, aiming to achieve accurate classification in a comprehensive setting where both known and unknown classes are present in unlabeled data. The purpose of this study is to propose a novel model for GCD with the aim of providing safe driving assistance for mobility. The model is based on the pre-trained MobileViT. To validate its performance, this paper examines its performance on the general CIFAR-10 and CIFAR-100 datasets and on a road damage-specific dataset, and discusses the challenges encountered.

关键词： Training Deep learning Accuracy Communication systems Roads Clustering methods Supervised learning Signal processing Convolutional neural networks

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High-Current-Density Propellantless Cathode using Graphene/h-BN/Ni-Sapphire Structure

High-Current-Density Propellantless Cathode using Graphene/h...

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

作者： Mutsukawa, Ren Takao, Yoshinori Yamamoto, Masaya Neo, Yoichiro Nagao, Masayoshi Murata, Hiromasa Murakami, Katsuhisa Department of Mechanical Engineering Materials Science and Ocean Engineering Yokohama National University Kanagawa Yokohama240-8501 Japan Division of Systems Research Yokohama National University Kanagawa Yokohama240-8501 Japan Research Institute of Electronics Shizuoka University Shizuoka Hamamatsu432-8011 Japan Device Technology Research Institute National Institute of Advanced Industrial Science and Technology Ibaraki Tsukuba305-8568 Japan

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Electron emission cathodes with graphene/h-BN/Ni-sapphire structures are high-potential devices with high electron current density, low-voltage-driven, and long operational time. Although devices based on graphene/h-BN/Si structures achieved high electron current density and long lifetime, high leakage current and low emission efficiency ( © 2025, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Sapphire

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Multi-Lens Visual SLAM with Integrated Moving Object Removal using Unsupervised Models

Multi-Lens Visual SLAM with Integrated Moving Object Removal...

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Robotics, engineering, Science, and technology (RESTCON), International Conference on

作者： Ryoichirou Hara Kousuke Matsushima Advanced Engineering Course National Institute of Technology Kurume College Fukuoka Japan Department of Control and Information Systems Engineering National Institute of Technology Kurume College Fukuoka Japan

In advanced Driver-Assistance systems (ADAS), SLAM (Simultaneous Localization and Mapping) technology is required to accurately estimate the position and orientation of onboard cameras. Compared to LiDAR SLAM, Visual SLAM has the advantage of collecting rich environmental information at a lower cost. However, the accuracy of the estimated pose and map construction is greatly reduced by moving objects in the camera scene. To solve this problem, a multi-camera SLAM has been proposed, which works robustly in dynamic environments by using multiple cameras to acquire more feature points from omnidirectional environmental information. In this paper, we propose a robust SLAM system based on a multi-camera SLAM system combined with object detection and semantic segmentation networks. We then evaluate the robustness of the proposed method by comparing it to SLAM systems that do not remove moving objects. Experimental results showed that the Absolute Trajectory Error and the Relative Position Error performed better than conventional SLAM by masking moving objects. It also showed that more static objects were detected and constructed in the map.

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Uncertainty-aware Monocular 3D Object Detection for Safe Driving Assistance

Uncertainty-aware Monocular 3D Object Detection for Safe Dri...

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IEEE International Symposium on Intelligent Signal Processing and Communication systems (ISPACS)

作者： Masahiko Ida Kousuke Matsushima Advanced Engineering Course National Institute of Technology Kurume College Fukuoka Japan Department of Control and Information Systems Engineering National Institute of Technology Kurume College Fukuoka Japan

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

Safety is of utmost importance when utilizing mobile vehicles. The introduction of safe driver assistance and automated driving systems will not only solve this problem, but also reduce road accidents and make driving smoother. To achieve these goals, 3D object detection is an essential technology and various methods have been proposed. Among these, monocular 3D object detection is an important technique and it is very difficult to identify the dimensions, direction and position of an object from a monocular image. Previous methods have predicted the dimensions directly from monocular images, resulting in poor accuracy of the dimensions in the depth direction. However, this paper proposes an indirect method for estimating the dimensions in the depth direction by predicting the volume of 3D bounding box. Detection accuracy for distant and partially visible objects is improved by using a loss function that uses uncertainty to account for the variability in predictions that occurs during learning. The proposed method has received an excellent evaluation on KITTI dataset.

关键词： Training Three-dimensional displays Accuracy Uncertainty Road accidents Object detection Signal processing Safety Object recognition Vehicles

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Towards understanding structure–property relations in materials with interpretable deep learning

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npj Computational Materials 2023年第1期9卷 157-168页

作者： Tien-Sinh Vu Minh-Quyet Ha Duong-Nguyen Nguyen Viet-Cuong Nguyen Yukihiro Abe Truyen Tran Huan Tran Hiori Kino Takashi Miyake Koji Tsuda Hieu-Chi Dam Japan Advanced Institute of Science and Technology NomiIshikawaJapan HPC SYSTEMS Inc. MinatoTokyoJapan Applied Artificial Intelligence Institute Deakin UniversityGeelongVICAustralia School of Materials Science and Engineering Georgia Institute of TechnologyAtlantaGAUSA Research and Services Division of Materials Data and Integrated System National Institute for Materials ScienceTsukubaIbarakiJapan Research Center for Computational Design of Advanced Functional Materials National Institute of Advanced Industrial Science and TechnologyTsukubaIbarakiJapan Department of Computational Biology and Medical Sciences Graduate School of Frontier SciencesUniversity of TokyoKashiwa-shiChiba-kenJapan International Center for Synchrotron Radiation Innovation Smart(SRIS) Tohoku UniversityAoba-kuSendaiJapan

Deep learning(DL)models currently employed in materials research exhibit certain limitations in delivering meaningful information for interpreting predictions and comprehending the relationships between structure and material *** address these limitations,we propose an interpretable DL architecture that incorporates the attention mechanism to predict material properties and gain insights into their structure–property *** proposed architecture is evaluated using two well-known datasets(the QM9 and the Materials Project datasets),and three in-house-developed computational materials ***–test–split validations confirm that the models derived using the proposed DL architecture exhibit strong predictive capabilities,which are comparable to those of current state-of-the-art ***,comparative validations,based on first-principles calculations,indicate that the degree of attention of the atoms’local structures to the representation of the material structure is critical when interpreting structure–property relationships with respect to physical *** properties encompass molecular orbital energies and the formation energies of *** proposed architecture shows great potential in accelerating material design by predicting material properties and explicitly identifying crucial features within the corresponding structures.

关键词： properties property structure

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MEASUREMENT OF VOID FRACTION DISTRIBUTION WITH SMALL WIRE MESH SENSOR INWATER-AIR TWO-PHASE BUBBLE AND SLUG FLOWS IN VERTICAL SMALL DIAMETER PIPE

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Multiphase Science and technology 2021年第4期33卷 15-30页

作者： Tsubone, Hiroaki Shiotsuka, Tatsuya Yamashiro, Tomoharu Fujino, Tomohito Department of Creative Engineering National Institute of Technology Ariake College Japan Department of Mechanical and Aerospace Engineering Kyushu University Japan Advanced Production and Information Systems Engineering Course National Institute of Technology Ariake College Japan

Several refrigerants have been developed to solve environmental problems and to create efficient heat exchangers. The optimal design of the heat exchanger depends on the physical properties of the refrigerant. An electrical measurement for the flow characteristics is an effective experimental method. We developed a small wire mesh sensor to measure void fraction distribution parameters in refrigerant-air two-phase flow. Small wire mesh sensors without switching systems can be used for a refrigerant (e.g., HFE-71IPA), which can flow a small electric current under high voltage. For verification of the small wire mesh sensor, instantaneous and time averaged void fraction distribution in water-air two-phase flow in a vertical small diameter pipe was measured and analyzed for both bubble and slug flows. The test channel was a vertical circular 9 mm i.d. glass pipe. Each volumetric flux was 0.2-2.0 m/s for the gas phase and 0.1 m/s for the liquid phase in bubble flow, and 0.5- 1.0 for the gas phase and 0.2-0.3 m/s for the liquid phase in slug flow. The resulting void fraction distribution data were compared with different flow regimes, and past data and literature. The result showed that detail void fraction distribution measurement by using the small wire mesh sensor without switching system is possible for bubble and slug flow. © 2021 Begell House Inc.. All rights reserved.

关键词： Refrigerants

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