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

作者： Okamoto, Atsushi Yamada, Takafumi Advanced Mechanical and Control System Engineering Course National Institute of Technology Tsuyama College 624-1 Okayama Numa Tsuyama708-8509 Japan Associate Professor Department of Integrated Science and Technology National Institute of Technology Tsuyama College 624-1 Okayama Numa Tsuyama708-8509 Japan

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

In this study, incompressible flow fields around a NACA0012 airfoil were numerically simulated at low Reynolds number for a Mars environment. For mesh generation, the standard Open FOAM utilities block Mesh and snappy HexMesh were used. Using those meshes and pisoFoam, which is PISO method-based analysis solver, NASA wind tunnel test conditions were numerically simulated in the Earth environment and obtained a similar lift gradient as in the experiment up to the stall. Then, the flow field of 12,000 Reynolds number, which simulates the Martian environment, was calculated. The variation of lift coefficient with increasing angle of attack was almost consistent with the experimental value in the Earth environment, and the stall angle was 16°. From the results of pressure distribution on the wing surface, it is suggested that compared to the Earth environment, the separation point movesfrom the leading edge to aft of the wing upper surface in the Martian environment. The flow field at the stall angle was similar to that of the Earth environment, and vortices were formed, however, their velocity vectors were very small, and dead water regions were observed near the trailing edge of the wing upper surface. More detailed aerodynamic characteristics should be clarified by evaluating the results using drag and moment coefficients until the SciTech Forum 2025. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： NASA

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Fatigue strength simulation of natural porous structure

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International Journal of the Society of Material engineering for Resources 2018年第2期23卷 167-172页

作者： Tanaka, Yohei Masuyama, Tomoya Takahashi, Takeshi Iizuka, Hiroshi Course of Mechanical and Control Engineering Department of Advanced Engineering Course National Institute of Technology Tsuruoka College 104 Ino-oka sawada TsuruokaYamagata997-8511 Japan Course of Mechanical Engineering Department of Creative Engineering National Institute of Technology Tsuruoka College Higashine Yamagata999-3716 Japan Sanwa Yushi Co.Ltd. Higashine Yamagata999-3716 Japan Department of Mechanical System Engineering Faculty of Engineering Yamagata University 4-3-16 Jonan Yonezawa Yamagata992-8510 Japan

Rice hull which is one of the agricultural wastes in Japan has been demanded to reuse as the industrial materials. Rice hull silica carbon (RHSC) material, made from rice hull is produced by mixing rice hull powder with a phenol resin, and then carbonizing and the mixture in the nitrogen gas atmosphere at high temperatures. The RHSC is a porous carbon material utilizing natural porous structure originated from the rice hull. Therefore, reduction in environmental pollution is expected by the RHSC which is inexpensive and unique. In addition, a core competence of low friction coefficient, lubrication free, and high water resistance was reported for the RHSC in previous research. However, the RHSC has low reliability of strength originated potentially from the porous structure. Since the reliability of the RHSC is evaluated by a fatigue test which is required several weeks, calculating the fatigue strength by simulation analysis is useful. In this study, fatigue strength simulation analysis in natural porous structure was figured out and the size effect which influences the strength of the material was investigated. ©2018 Soc. Mater. Eng. Resour. Japan

关键词： Carbon

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Deep Learning-Based Analysis of Neuronal Signal Streams: Estimating the Activity Range of Cultured Neuronal Networks in Consecutive Stimulus Inputs Using CNN 13

Deep Learning-Based Analysis of Neuronal Signal Streams: Est...

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Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Asada, Hiroki Kudoh, Suguru N. Dept. of Human System Interaction Sanda Japan Artificial Intelligence and Mechanical Engineering Course Dept. of Engineering Sanda Japan

ISBN: (纸本)9798350373332

We utilized a Convolutional Neural Network (CNN) -that incorporates a structure designed to integrate local relationship features. The CNN-based deep learning approach enabled us to identify response patterns following stimulus input, using images of neural activity that depict the activity of individual neurons. The feature of CNN-based neural network, integrating local features, considered to contribute to decipher the relationship within time-series data, which are interpreted as streams of signals passing through a single neuron. Utilizing this feature, we attempted to determine the scope of activity that preserves the history of ongoing stimulation within a cultured living neuronal network. We repeatedly subjected the network to the same stimulus, and from the post-stimulus response activity, we extracted spatial combinations of neurons that fired simultaneously within brief 1 ms time windows. We calculated the firing rates for each of these 1 ms intervals in response to 10 different stimuli. By arranging these firing rates into a distinctive configuration that sustains temporal continuity, we generated images that illustrate neuronal activity. We then attempted to discriminate response images obtained at various stimulus intervals, and compared the accuracy of the discrimination to gauge the scope and degree of history retention in sequential activation. © 2024 IEEE.

关键词： Convolutional neural networks

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Identification of the spatiotemporal activity patterns of cultured neuronal networks using deep convolutional neural networks (CNNs) 15

Identification of the spatiotemporal activity patterns of cu...

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15th Biomedical engineering International Conference, BMEiCON 2023

作者： Ogomori, Kaito Kudoh, Suguru N. Dept. of Human System Interaction Sanda Japan Artificial Intelligence and Mechanical Engineering Course Dept. of Engineering Sanda Japan

ISBN: (纸本)9798350345247

To understand the basis of information processing in the brain, it is important to analyze the dynamics of neural activity patterns using an electrophysiological approach. In this study, we attempted to extract units of neural activity that represent certain information and to distinguish between activity patterns induced by electrical stimulation and spontaneous activity patterns. X-means clustering was applied to a triplet of "two-dimensional spatial coordinates and timestamps"of neuronal electrical spike bursts to transform the single extracted spatiotemporal neural activity patterns into a standardized 8×8 2D-spatial pattern map. The pattern maps were then collected in the order of time of occurrence of the neural activity patterns, and a VGG16 deep convolutional neural network (deep CNN) was used to classify stimulus-responsive activity and spontaneous activity. For this purpose, we transformed the 2D spatial pattern map and prepared two types of 224×224 images: Spatial Information-Priority Neural Activity Pattern images (SIP-NAP images) and Temporal Information-Priority Neural Activity Pattern images (TIP-NAP images). As a result, we achieved high discrimination accuracy of over 85% for both types of VGG16 input images, especially with TIP-NAP imagesachieving a discrimination accuracy of 99.5%. This suggests that the 3D clustering extracted spatiotemporal features that contribute to the discrimination between spontaneous and evoked response activities. In addition, the combination of transfer learning and the SIP-NAP/TIP-NAP image transformation method was shown to accurately discriminate spatial patterns of neuroelectric activity even with a small amount of training data. © 2023 IEEE.

关键词： Convolutional neural networks

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Proposal of a novel peeling of nano-particle (PNP) process for localized material removal on a hard material surface by controllable magnetic fields 22

Proposal of a novel peeling of nano-particle (PNP) process f...

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22nd International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2022

作者： Permpatdechakul, Thitipat Khajornrungruang, Panart Suzuki, Keisuke Kutomi, Shotaro Graduate School of Computer Science and System Engineering Mechanical Information Science and Technology Course Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Avanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan School of Computer Science and System Engineering Advanced Mechanical Course Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9781998999118

This article proposes a novel Peeling of Nano-Particle (PNP) process to locally remove material on a hard material surface using controllable magnetic fields. Fe3O4 particles in the size range of 50-100 nm in aqueous solution (pH value 11 adjusted by KOH) were magnetically controlled to adhere and remove from a 4H-SiC surface by two electromagnetic coils, which were sandwiched between the substrate. The particle controlling phenomenon on the surface was experimentally observed and verified by our developed apparatus applying an evanescent field. According to the results, particles could be controlled to approach and remove from the substrate surface with 12mT of magnetic field at the selective area on the substrate surface to realise the proposed PNP process. © European Society for Precision engineering and Nanotechnology, Conference Proceedings - 22nd International Conference and Exhibition, EUSPEN 2022. All rights reserved.

关键词： Magnetic fields

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Development of walking assist system with dry-ice power cell

Development of walking assist system with dry-ice power cell

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50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011

作者： Ishizuka, Hiroki Oyama, Osamu Kitagawa, Ato Post Graduate Course of Mechanical Engineering Meiji University Kanagawa Japan Department of Control and System Engineering Tokyo Institute of Technolgy Tokyo Japan

ISBN: (纸本)9784907764395

A Dry-Ice Power Cell is a portable gas power source. It uses characteristics around the triple point of carbon dioxide. We focus on four characteristics which the Dry-Ice Power Cell has. It is small, light, portable and emits constant pressure gas. Because Dry-Ice is a solid phase of carbon dioxide, it generates a lot of gas for the solid volume. In addition, it is possible to drive without using another electric power supply and can be driven by using environmental heat. If we introduced the Dry-Ice Power Cell into walking assist system, it would be possible to operate the system without motor-driven air compressor. According to the experiment result, the Dry-Ice Power Cell enables the walking duration of system to be longer than another power source such as the air storage vessel. It is confirmed that the Dry-Ice Power Cell has enough capacity to support the walking assist system. © 2011 SICE.

关键词： Carbon dioxide

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Neuronal electrical activity pattern extracted by 3D clustering and discriminated by a deep CNN

Neuronal electrical activity pattern extracted by 3D cluster...

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2022 IEEE International Conference on systems, Man, and Cybernetics, SMC 2022

作者： Ogomori, Kaito Kudoh, Suguru N. Dept. of Human System Interaction Hyougo Sanda Japan Artificial Intelligence and Mechanical Engineering Course Dept. of Engineering Hyougo Sanda Japan

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Analyzing the dynamics of neural activity patterns using an electrophysiological approach is important for understanding the basis of information processing in a brain. In this study, we attempted to extract units of neuronal activity representing certain information and to discriminate activity pattern evoked by electrical stimulus and spontaneous activity without stimulation. We applied X-means clustering to the triplet of '2D-spacial coordinates and timestamps' of neuronal electrical spike bursts and the extracted single spatiotemporal neuronal activity pattern was converted into a standardized 8times 84 2D-spatial pattern map. Most 2D-spatial patterns emerged repeatedly during recording time, corresponding to a representative motif. Then we gathered similar 2D-spatial patterns (primary clusters) into one 'pattern repertoire' and attempted to classify these pattern repertoires depending on the stimulus inducing the pattern repertoire by VGG16 deep convolutional neural networks (deep CNN). For that, we prepared two types of 224times 224 images by converting the 2D-spatial pattern maps, the spatial information priority neural activity pattern image (SIP-NAP image) and the time information priority neural activity pattern image (TIP-NAP image). As a result, over 80% of high discrimination accuracy was obtained for both types of VGG16 input images, especially 99.7% for TIP-NAP image. It suggested that spatiotemporal features contributing to the discrimination between spontaneous and evoked response activities were extracted by 3-D-crustering. In addition, it is shown that the spatial pattern of neuroelectric activity is able to be discriminated with high accuracy by combining transfer learning and SIP-NAP / TIP-NAP image translation method, even with a small amount of training data. © 2022 IEEE.

关键词： Convolutional neural networks

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Absolute longitudinal distance measurement verification of a standard polystyrene nanoparticle near a surface in water by means of multi-wavelength evanescent field 22

Absolute longitudinal distance measurement verification of a...

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22nd International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2022

作者： Blattler, Aran Khajornrungruang, Panart Suzuki, Keisuke Baba, Akiyoshi Goto, Daiki Graduate School of Computer Science and System Engineering Mechanical Information Science and Technology Course Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Advanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan Center of Microelectronic System Kyushu Institute of Technology Fukuoka Japan School of Computer Science and System Engineering Advanced Mechanical Course Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9781998999118

In the wet semiconductor process, abrasive nanoparticles are widely used in the chemical mechanical polishing (CMP) process to polish wafer surfaces for high planarization. During polishing, nanoparticles move with a high-speed three-dimensional (3D) position in the solution. In the 3D particles's moving positions, Z is a perpendicular longitudinal distance between the surface to the nanoparticle that plays a significant role in polishing, which could not be measured by general microscopy without longitudinal scanning. To understand nanoparticle phenomena near-surface, we have proposed and developed the apparatus with real-time fastmotion tracking on optical multi-wavelength evanescent fields microscopy to measure the 3D motion of the nanoparticle in water without scanning. In euspen's 2020, we could verify the relative distance ?Z of nanoparticles in water, but the absolute distance Z is unknown yet. In this manuscript, we have therefore developed an invisible nano-step height in water to verify the absolute height Z of an individual nanoparticle. The invisible nano-step height in water is made from an optical resin with a refractive index of 1.35 that is close to a refractive index of water to avoid unnecessary light during experimental verification. The nano-step height was less than 100 nm on a glass surface, fabricated using nanoimprint lithography. Polystyrene f100 nm standard particles in water were used to verify the height Z. The results of height Z of nanoparticles could be measured less than 100 nm with the measurement uncertainty ±10 nm (2s), which is related to the interferometer result of the nano-step height. © European Society for Precision engineering and Nanotechnology, Conference Proceedings - 22nd International Conference and Exhibition, EUSPEN 2022. All rights reserved.

关键词： Nanoparticles

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Application of quaternion neural network to EMG-based estimation of forearm motion

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2017 International Conference on Artificial Intelligence, ICAI 2017 at 2017 World Congress in Computer Science, Computer engineering and Applied Computing, CSCE 2017

作者： Firdaus, H. Ogawa, T. Mechanical and Electronic Systems Engineering Course Takushoku University Tokyo Japan Department of Electronics and Computer System Takushoku University Tokyo Japan

ISBN: (纸本)9781601324603

This paper presents the Application of Quaternion Neural Network (QNN) to Electromyography (EMG) based Estimation of Forearm Motion. Motion of human body can be modeled as a set of rotations in three-dimensional space by various joints. The aim of this research is to show the efficiency of QNN in estimation from EMG. We are trying to learn, estimate and simulate combined motion using QNN as well as comparing the estimation efficiency with the feedforward neural network (FNN). We are measuring EMG signal of target muscles while performing basic forearm motion. The efficiency of the estimation then determines by simulation with combine motion of forearm. It is expected in better performance of estimation in QNN compare to FNN. CSREA Press ©.

关键词： Efficiency

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Uniaxial stretch-induced axonal injury thresholds for axonal dysfunction and disruption and strain rate effects on thresholds for mouse neuronal stem cells

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Journal of Biomechanical Science and engineering 2017年第1期12卷 16-00598页

作者： Kurtoglu, Evrim Nakadate, Hiromichi Kikuta, Kazuhiro Aomura, Shigeru Kakuta, Akira Graduate School of System Design Tokyo Metropolitan University Tokyo Japan Advanced Course of Mechanical and Computer Systems Engineering Tokyo National College of Technology 1220-2 Kunugida-machi Hachioji-shi Tokyo193-0997 Japan

In this paper, the proposed study aims to achieve a better understanding of neuronal tolerance and contribute to the prediction of the secondary degeneration of diffuse axonal injury (DAI). Therefore, a uniaxial stretching device which subjected cultured neurons to uniaxial stretch was employed to evaluate the effect of strain and strain rate along axon to realize the injury threshold. Neurons differentiated from mouse neuronal stem cells were injured and the morphology was observed before and after stretching with strains of 0.10, 0.12, 0.18, 0.23 at strain rates of 8, 11, 19, 26 s-1 respectively. Results suggest that the threshold for axonal dysfunction is around 0.18 strain whereas the threshold for axonal disruption is around 0.23 and the results of strain rate effect investigations on axonal dysfunction and disruption around these threshold values indicated that higher strain rate values such as 50 s-1 may have diminishing effects on threshold for axonal disruption. © 2017 The Japan Society of mechanical Engineers.

关键词： Stem cells

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