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318 results on '"Nonomura, T."'

1. Construction of KAGRA: an Underground Gravitational Wave Observatory

Author

Akutsu, T., Ando, M., Araki, S., Araya, A., Arima, T., Aritomi, N., Asada, H., Aso, Y., Atsuta, S., Awai, K., Baiotti, L., Barton, M. A., Chen, D., Cho, K., Craig, K., DeSalvo, R., Doi, K., Eda, K., Enomoto, Y., Flaminio, R., Fujibayashi, S., Fujii, Y., Fujimoto, M. -K., Fukushima, M., Furuhata, T., Hagiwara, A., Haino, S., Harita, S., Hasegawa, K., Hasegawa, M., Hashino, K., Hayama, K., Hirata, N., Hirose, E., Ikenoue, B., Inoue, Y., Ioka, K., Ishizaki, H., Itoh, Y., Jia, D., Kagawa, T., Kaji, T., Kajita, T., Kakizaki, M., Kakuhata, H., Kamiizumi, M., Kanbara, S., Kanda, N., Kanemura, S., Kaneyama, M., Kasuya, J., Kataoka, Y., Kawaguchi, K., Kawai, N., Kawamura, S., Kawazoe, F., Kim, C., Kim, J., Kim, J. C., Kim, W., Kimura, N., Kitaoka, Y., Kobayashi, K., Kojima, Y., Kokeyama, K., Komori, K., Kotake, K., Kubo, K., Kumar, R., Kume, T., Kuroda, K., Kuwahara, Y., Lee, H. -K., Lee, H. -W., Lin, C. -Y., Liu, Y., Majorana, E., Mano, S., Marchio, M., Matsui, T., Matsumoto, N., Matsushima, F., Michimura, Y., Mio, N., Miyakawa, O., Miyake, K., Miyamoto, A., Miyamoto, T., Miyo, K., Miyoki, S., Morii, W., Morisaki, S., Moriwaki, Y., Muraki, Y., Murakoshi, M., Musha, M., Nagano, K., Nagano, S., Nakamura, K., Nakamura, T., Nakano, H., Nakano, M., Nakao, H., Nakao, K., Narikawa, T., Ni, W. -T., Nonomura, T., Obuchi, Y., Oh, J. J., Oh, S. -H., Ohashi, M., Ohishi, N., Ohkawa, M., Ohmae, N., Okino, K., Okutomi, K., Ono, K., Ono, Y., Oohara, K., Ota, S., Park, J., Arellano, F. E. Peña, Pinto, I. M., Principe, M., Sago, N., Saijo, M., Saito, T., Saito, Y., Saitou, S., Sakai, K., Sakakibara, Y., Sasaki, Y., Sato, S., Sato, T., Sato, Y., Sekiguchi, T., Sekiguchi, Y., Shibata, M., Shiga, K., Shikano, Y., Shimoda, T., Shinkai, H., Shoda, A., Someya, N., Somiya, K., Son, E. J., Starecki, T., Suemasa, A., Sugimoto, Y., Susa, Y., Suwabe, H., Suzuki, T., Tachibana, Y., Tagoshi, H., Takada, S., Takahashi, H., Takahashi, R., Takamori, A., Takeda, H., Tanaka, H., Tanaka, K., Tanaka, T., Tatsumi, D., Telada, S., Tomaru, T., Tsubono, K., Tsuchida, S., Tsukada, L., Tsuzuki, T., Uchikata, N., Uchiyama, T., Uehara, T., Ueki, S., Ueno, K., Uraguchi, F., Ushiba, T., van Putten, M. H. P. M., Wada, S., Wakamatsu, T., Yaginuma, T., Yamamoto, K., Yamamoto, S., Yamamoto, T., Yano, K., Yokoyama, J., Yokozawa, T., Yoon, T. H., Yuzurihara, H., Zeidler, S., Zhao, Y., Zheng, L., Agatsuma, K., Akiyama, Y., Arai, N., Asano, M., Bertolini, A., Fujisawa, M., Goetz, R., Guscott, J., Hashimoto, Y., Hayashida, Y., Hennes, E., Hirai, K., Hirayama, T., Ishitsuka, H., Kato, J., Khalaidovski, A., Koike, S., Kumeta, A., Miener, T., Morioka, M., Mueller, C. L., Narita, T., Oda, Y., Ogawa, T., Tamura, H., Tanner, D. B., Tokoku, C., Toritani, M., Utsuki, T., Uyeshima, M., Brand, J. van den, van Heijningen, J., Yamaguchi, S., and Yanagida, A.

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Instrumentation and Detectors
Abstract

Major construction and initial-phase operation of a second-generation gravitational-wave detector KAGRA has been completed. The entire 3-km detector is installed underground in a mine in order to be isolated from background seismic vibrations on the surface. This allows us to achieve a good sensitivity at low frequencies and high stability of the detector. Bare-bones equipment for the interferometer operation has been installed and the first test run was accomplished in March and April of 2016 with a rather simple configuration. The initial configuration of KAGRA is named {\it iKAGRA}. In this paper, we summarize the construction of KAGRA, including the study of the advantages and challenges of building an underground detector and the operation of the iKAGRA interferometer together with the geophysics interferometer that has been constructed in the same tunnel., Comment: Resolution of some figures has been decreased from its original version submitted to a journal

Published
2017
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5. High-efficiency sound source localization using data-driven sparse sampling with validation using monopole laser sound source.

Author

Kaneko, S., Ozawa, Y., Nakai, K., Saito, Y., Asai, K., Nonomura, T., and Ura, H.

Subjects
ACOUSTIC localization, WIND tunnel testing, WIND tunnels, LASERS, MICROPHONE arrays, ACOUSTIC imaging, MICROPHONES, STEERING gear
Abstract

This study proposes a framework that reduces the calculation cost of sound source localization with the Amiet model, using a data-driven sparse sampling method. This method accelerates the calculation of the steering vector used in conventional beamforming. An aeroacoustic wind tunnel test was conducted in a 2 × 2 m2 low-speed wind tunnel, and the proposed method was verified. During the test, a monopole laser sound source, which does not interfere with the flow, was used, and its acoustic signals were measured using a microphone array. Next, steering vectors were reconstructed by discovering dominant modes and optimized sampling points from the training data based on the Amiet model and the modified data-driven sparse sampling method. Finally, the sound-source positions when the steering vector of the proposed model was used were compared with the positions observed when the steering vector of which all the grid points were calculated was used. The error was less than 2 mm when 16 modes were used, and the calculation time was reduced to ∼1/33 of that of the previous Amiet model. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Development of Ni-Base Disk Alloy for Large-Size Gas Turbines by Improving Macrosegregation Property of Alloy 718

Author

Shibayama, T., Sato, J., Sato, N., Nonomura, T., Shimohira, E., Uehara, T., Imano, S., Ott, Eric, editor, Liu, Xingbo, editor, Andersson, Joel, editor, Bi, Zhongnan, editor, Bockenstedt, Kevin, editor, Dempster, Ian, editor, Groh, Jon, editor, Heck, Karl, editor, Jablonski, Paul, editor, Kaplan, Max, editor, Nagahama, Daisuke, editor, and Sudbrack, Chantal, editor

Published
2018
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24. Direct numerical simulation of flow over a triangular airfoil under martian atmospheric conditions

Author

Caros Roca, L, Buxton, O, Shigeta, T, Nagata, T, Nonomura, T, Asai, K, Vincent, P, and Engineering & Physical Science Research Council (EPSRC)

Subjects
Technology, Science & Technology, Engineering, Aerospace & Aeronautics, Engineering, Aerospace, 0901 Aerospace Engineering, 0905 Civil Engineering, 0913 Mechanical Engineering
Abstract

Martian conditions present various challenges when designing rotorcraft. Specifically, the thin atmosphere and low sound speed require Martian rotor blades to operate in a low Reynolds number (1,000 to 10,000) compressible regime, for which conventional airfoils are not designed. Here we utilize PyFR to undertake high-order Direct Numerical Simulations (DNS) of flow over a triangular airfoil at a Mach number of 0.15 and Reynolds number of 3,000. Initially, span-wise periodic DNS are undertaken. Extending the domain-span-to-chord ratio from 0.3 to 0.6 leads to better agreement with wind tunnel data at higher angles of attack, when the flow is separated. This is because smaller domain spans artificially suppress three-dimensional breakdown of coherent structures above the suction surface of the airfoil. Subsequently, full-span DNS in a virtual wind tunnel are undertaken, including all wind tunnel walls. These capture blockage and wall boundary layer effects, leading to better agreement with wind tunnel data for all angles of attack compared to span-wise periodic DNS. The results are important in terms of understanding discrepancies between previous span-wise periodic DNS and wind tunnel data. They also demonstrate the utility of high-order DNS as a tool for accurately resolving flow over triangular airfoils under Martian conditions.

Published
2022

25. Seismic wavefield reconstruction based on compressed sensing using data-driven reduced-order model.

Author

Nagata, T, Nakai, K, Yamada, K, Saito, Y, Nonomura, T, Kano, M, Ito, S, and Nagao, H

Subjects
COMPRESSED sensing, REDUCED-order models, KRIGING, GROUND motion, GREEDY algorithms, SINGULAR value decomposition, APPLIED mechanics, EMERGENCY management
Abstract

Reconstruction of the distribution of ground motion due to an earthquake is one of the key technologies for the prediction of seismic damage to infrastructure. Particularly, the immediate reconstruction of the spatially continuous wavefield is valuable for decision-making of disaster response decisions in the initial phase. For a fast and accurate reconstruction, utilization of prior information is essential. In fluid mechanics, full-state recovery, which recovers the full state from sparse observation using a data-driven model reduced-order model, is actively used. In this study, the framework developed in the field of fluid mechanics is applied to seismic wavefield reconstruction. A seismic wavefield reconstruction framework based on compressed sensing using the data-driven reduced-order model (ROM) is proposed and its characteristics are investigated through numerical experiments. The data-driven ROM is generated from the data set of the wavefield using the singular value decomposition. The spatially continuous seismic wavefield is reconstructed from the sparse and discrete observation and the data-driven ROM. The observation sites used for reconstruction are effectively selected by the sensor optimization method for linear inverse problems based on a greedy algorithm. The proposed framework was applied to simulation data of theoretical waveform with the subsurface structure of the horizontally stratified three layers. The validity of the proposed method was confirmed by the reconstruction based on the noise-free observation. Since the ROM of the wavefield is used as prior information, the reconstruction error is reduced to an approximately lower error bound of the present framework, even though the number of sensors used for reconstruction is limited and randomly selected. In addition, the reconstruction error obtained by the proposed framework is much smaller than that obtained by the Gaussian process regression. For the numerical experiment with noise-contaminated observation, the reconstructed wavefield is degraded due to the observation noise, but the reconstruction error obtained by the present framework with all available observation sites is close to a lower error bound, even though the reconstructed wavefield using the Gaussian process regression is fully collapsed. Although the reconstruction error is larger than that obtained using all observation sites, the number of observation sites used for reconstruction can be reduced while minimizing the deterioration and scatter of the reconstructed data by combining it with the sensor optimization method. Hence, a better and more stable reconstruction of the wavefield than randomly selected observation sites can be realized, even if the reconstruction is carried out with a smaller number of observations with observation noise, by combining it with the sensor optimization method. [ABSTRACT FROM AUTHOR]

Published
2023
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47. Construction of KAGRA: an underground gravitational-wave observatory

Author

Akutsu, T., Ando, M., Araki, S., Araya, A., Arima, T., Aritomi, N., Asada, H., Aso, Y., Atsuta, S., Awai, K., Baiotti, L., Barton, M. A., Chen, D., Cho, K., Craig, K., DeSalvo, R., Doi, K., Eda, K., Enomoto, Y., Flaminio, R., Fujibayashi, S., Fujii, Y., Fujimoto, M. -K., Fukushima, M., Furuhata, T., Hagiwara, A., Haino, S., Harita, S., Hasegawa, K., Hasegawa, M., Hashino, K., Hayama, K., Hirata, N., Hirose, E., Ikenoue, B., Inoue, Y., Ioka, K., Ishizaki, H., Itoh, Y., Jia, D., Kagawa, T., Kaji, T., Kajita, T., Kakizaki, M., Kakuhata, H., Kamiizumi, M., Kanbara, S., Kanda, N., Kanemura, S., Kaneyama, M., Kasuya, J., Kataoka, Y., Kawaguchi, K., Kawai, N., Kawamura, S., Kawazoe, F., Kim, C., Kim, J., Kim, J. C., Kim, W., Kimura, N., Kitaoka, Y., Kobayashi, K., Kojima, Y., Kokeyama, K., Komori, K., Kotake, K., Kubo, K., Kumar, R., Kume, T., Kuroda, K., Kuwahara, Y., Lee, H. -K., Lee, H. -W., Lin, C. -Y., Liu, Y., Majorana, E., Mano, S., Marchio, M., Matsui, T., Matsumoto, N., Matsushima, F., Michimura, Y., Mio, N., Miyakawa, O., Miyake, K., Miyamoto, A., Miyamoto, T., Miyo, K., Miyoki, S., Morii, W., Morisaki, S., Moriwaki, Y., Muraki, Y., Murakoshi, M., Musha, M., Nagano, K., Nagano, S., Nakamura, K., Nakamura, T., Nakano, H., Nakano, M., Nakao, H., Nakao, K., Narikawa, T., Ni, W. -T., Nonomura, T., Obuchi, Y., Oh, J. J., Oh, S. -H., Ohashi, M., Ohishi, N., Ohkawa, M., Ohmae, N., Okino, K., Okutomi, K., Ono, K., Ono, Y., Oohara, K., Ota, S., Park, J., Peña Arellano, F. E., Pinto, I. M., Principe, M., Sago, N., Saijo, M., Saito, T., Saito, Y., Saitou, S., Sakai, K., Sakakibara, Y., Sasaki, Y., Sato, S., Sato, T., Sato, Y., Sekiguchi, T., Sekiguchi, Y., Shibata, M., Shiga, K., Shikano, Y., Shimoda, T., Shinkai, H., Shoda, A., Someya, N., Somiya, K., Son, E. J., Starecki, T., Suemasa, A., Sugimoto, Y., Susa, Y., Suwabe, H., Suzuki, T., Tachibana, Y., Tagoshi, H., Takada, S., Takahashi, H., Takahashi, R., Takamori, A., Takeda, H., Tanaka, H., Tanaka, K., Tanaka, T., Tatsumi, D., Telada, S., Tomaru, T., Tsubono, K., Tsuchida, S., Tsukada, L., Tsuzuki, T., Uchikata, N., Uchiyama, T., Uehara, T., Ueki, S., Ueno, K., Uraguchi, F., Ushiba, T., van Putten, M. H. P. M., Wada, S., Wakamatsu, T., Yaginuma, T., Yamamoto, K., Yamamoto, S., Yamamoto, T., Yano, K., Yokoyama, J., Yokozawa, T., Yoon, T. H., Yuzurihara, H., Zeidler, S., Zhao, Y., Zheng, L., Agatsuma, K., Akiyama, Y., Arai, N., Asano, M., Bertolini, A., Fujisawa, M., Goetz, R., Guscott, J., Hashimoto, Y., Hayashida, Y., Hennes, E., Hirai, K., Hirayama, T., Ishitsuka, H., Kato, J., Khalaidovski, A., Koike, S., Kumeta, A., Miener, T., Morioka, M., Mueller, C. L., Narita, T., Oda, Y., Ogawa, T., Tamura, H., Tanner, D. B., Tokoku, Chihiro, Toritani, M., Utsuki, T., Uyeshima, M., van den Brand, J. F. J., van Heijningen, J. V., Yamaguchi, S., Yanagida, A., Akutsu, T., Ando, M., Araki, S., Araya, A., Arima, T., Aritomi, N., Asada, H., Aso, Y., Atsuta, S., Awai, K., Baiotti, L., Barton, M. A., Chen, D., Cho, K., Craig, K., DeSalvo, R., Doi, K., Eda, K., Enomoto, Y., Flaminio, R., Fujibayashi, S., Fujii, Y., Fujimoto, M. -K., Fukushima, M., Furuhata, T., Hagiwara, A., Haino, S., Harita, S., Hasegawa, K., Hasegawa, M., Hashino, K., Hayama, K., Hirata, N., Hirose, E., Ikenoue, B., Inoue, Y., Ioka, K., Ishizaki, H., Itoh, Y., Jia, D., Kagawa, T., Kaji, T., Kajita, T., Kakizaki, M., Kakuhata, H., Kamiizumi, M., Kanbara, S., Kanda, N., Kanemura, S., Kaneyama, M., Kasuya, J., Kataoka, Y., Kawaguchi, K., Kawai, N., Kawamura, S., Kawazoe, F., Kim, C., Kim, J., Kim, J. C., Kim, W., Kimura, N., Kitaoka, Y., Kobayashi, K., Kojima, Y., Kokeyama, K., Komori, K., Kotake, K., Kubo, K., Kumar, R., Kume, T., Kuroda, K., Kuwahara, Y., Lee, H. -K., Lee, H. -W., Lin, C. -Y., Liu, Y., Majorana, E., Mano, S., Marchio, M., Matsui, T., Matsumoto, N., Matsushima, F., Michimura, Y., Mio, N., Miyakawa, O., Miyake, K., Miyamoto, A., Miyamoto, T., Miyo, K., Miyoki, S., Morii, W., Morisaki, S., Moriwaki, Y., Muraki, Y., Murakoshi, M., Musha, M., Nagano, K., Nagano, S., Nakamura, K., Nakamura, T., Nakano, H., Nakano, M., Nakao, H., Nakao, K., Narikawa, T., Ni, W. -T., Nonomura, T., Obuchi, Y., Oh, J. J., Oh, S. -H., Ohashi, M., Ohishi, N., Ohkawa, M., Ohmae, N., Okino, K., Okutomi, K., Ono, K., Ono, Y., Oohara, K., Ota, S., Park, J., Peña Arellano, F. E., Pinto, I. M., Principe, M., Sago, N., Saijo, M., Saito, T., Saito, Y., Saitou, S., Sakai, K., Sakakibara, Y., Sasaki, Y., Sato, S., Sato, T., Sato, Y., Sekiguchi, T., Sekiguchi, Y., Shibata, M., Shiga, K., Shikano, Y., Shimoda, T., Shinkai, H., Shoda, A., Someya, N., Somiya, K., Son, E. J., Starecki, T., Suemasa, A., Sugimoto, Y., Susa, Y., Suwabe, H., Suzuki, T., Tachibana, Y., Tagoshi, H., Takada, S., Takahashi, H., Takahashi, R., Takamori, A., Takeda, H., Tanaka, H., Tanaka, K., Tanaka, T., Tatsumi, D., Telada, S., Tomaru, T., Tsubono, K., Tsuchida, S., Tsukada, L., Tsuzuki, T., Uchikata, N., Uchiyama, T., Uehara, T., Ueki, S., Ueno, K., Uraguchi, F., Ushiba, T., van Putten, M. H. P. M., Wada, S., Wakamatsu, T., Yaginuma, T., Yamamoto, K., Yamamoto, S., Yamamoto, T., Yano, K., Yokoyama, J., Yokozawa, T., Yoon, T. H., Yuzurihara, H., Zeidler, S., Zhao, Y., Zheng, L., Agatsuma, K., Akiyama, Y., Arai, N., Asano, M., Bertolini, A., Fujisawa, M., Goetz, R., Guscott, J., Hashimoto, Y., Hayashida, Y., Hennes, E., Hirai, K., Hirayama, T., Ishitsuka, H., Kato, J., Khalaidovski, A., Koike, S., Kumeta, A., Miener, T., Morioka, M., Mueller, C. L., Narita, T., Oda, Y., Ogawa, T., Tamura, H., Tanner, D. B., Tokoku, Chihiro, Toritani, M., Utsuki, T., Uyeshima, M., van den Brand, J. F. J., van Heijningen, J. V., Yamaguchi, S., and Yanagida, A.

Abstract

著者人数: 227名 (所属. 宇宙航空研究開発機構宇宙科学研究所(JAXA)(ISAS): 東谷, 千比呂), Number of authors: 227 (Affiliation. Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency(JAXA)(ISAS): Tokoku, Chihiro), Accepted: 2017-11-21

Published
2018

48. Coupled Simulation of Shock Waves in Gas-Particle Mixtures Introducing Motion Equations

Author

Mizuno, Y., Takahashi, S., Nonomura, T., Nagata, T., and Kota Fukuda

Subjects
Physics::Fluid Dynamics, Finite element method, Three-dimensional compressible Navier-Stokes equation, direct numerical simulation, moving particles, shock wave, Elements finits, Mètode dels, Coupled problems (Complex systems) -- Numerical solutions, Matemàtiques i estadística::Anàlisi numèrica::Mètodes en elements finits [Àrees temàtiques de la UPC]
Abstract

In this work, direct numerical analyses for flow around particles passing a shock wave was carried out to predict effects of small particles in rocket plumes. A flow solver based on three-dimensional compressible Navier-Stokes equations is developed for the purpose of high accurate prediction of the acoustic field around rocket plumes. This flow solver is capable of analysing a flow around moving multiple particles and motion equations was introduced. The flow field and the drag coefficient after the shock wave passage were validated by comparing with the drag models at shock Mach number 1.2-2.8. The result was in good agreement with the drag models. In the flow around multiple particles, the interference between particles was confirmed.

Published
2015

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