Language：English   Publishing type：Research paper (scientific journal)   Publisher：Journal of Ocean Engineering and Marine Energy  

This paper focuses on the issue of accuracy degradation when directly constructing a reduced-order model (ROM) using dynamic mode decomposition for a volume of fluid (VOF) field of two-phase flow simulations, and proposes a improved method that utilizes the signed distance function (SDF), also known as the level set function, with respect to the gas–liquid interface. The effectiveness of the proposed method was demonstrated by applying it to sloshing tank problems under two different conditions. The oscillation modes were observed to appear only near the interface when using the VOF field directly; however, the influence of the interface is alleviated over a larger distance, resulting in smoother oscillation and improved performance of the ROM when employing the level set function. The results show that ROM for a level set function in cases with small oscillation was shown to be effectively equivalent to that for one-dimensionalized interface. Moreover, the ROM of the level set function could reproduce the physics of this phenomenon with higher accuracy than that of the VOF fields in the cases where one dimensionalization is not possible, such as when the liquid inside the tank surges and climbs up to the ceiling.

DOI： 10.1007/s40722-025-00385-x

Web of Science

Scopus

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Experiments in Fluids  

Visual feedback control of a flow field by a controller that operates plasma actuators with sparse processing particle image velocimetry as an observer was implemented in a wind tunnel test. The control objective was the suppression of a Kàrmàn vortex around a circular cylinder. Sum-of-absolute-values control based on an L1 optimization problem was implemented to enable real-time processing. Real-time visual feedback control at 2000 Hz was achieved with the proposed system owing to the use of sparse processing particle image velocimetry, which evaluates only a limited number of interrogation windows, and a sophisticated solver for the L1 optimization problem. The techniques adopted in the present study can accelerate the feedback control rate by a factor of 10 to 100. It was confirmed that the proposed system suppresses the Kàrmàn vortex to a certain extent. The results show that the control law using forecasts further ahead performs better.

DOI： 10.1007/s00348-025-04039-4

Web of Science

Scopus

Authorship：Lead author,　Corresponding author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Institute of Electrical and Electronics Engineers (IEEE)  

DOI： 10.1109/JSEN.2025.3537702

Web of Science

Scopus

researchmap

Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.ymssp.2024.111864

Open Access

researchmap

Publisher：Actuators  

This study investigated the effectiveness of a dielectric barrier discharge (DBD) plasma actuator operating in burst-in-burst (BIB) mode for flow separation control on a NACA 0015 airfoil. Time-resolved particle image velocimetry measurements were conducted at a Reynolds number of 66,000 and 13° angle of attack. Various BIB signal configurations were tested, with actuation periods of 70 ms and 150 ms, non-actuation periods ranging from 5 ms to 50 ms, and burst frequencies of 300 Hz and 600 Hz. Proper orthogonal decomposition was applied to analyze the flow field dynamics. The results showed that BIB actuation maintained flow attachment with reduced power consumption compared with continuous burst actuation. However, the effectiveness was highly sensitive to the BIB parameters, with some configurations failing to achieve consistent reattachment and becoming unstable. This study reveals complex interactions between actuation vortices and separation processes, highlighting both the potential and challenges of intermittent plasma actuation for efficient flow control.

DOI： 10.3390/act13110435

Web of Science

Scopus

Publishing type：Research paper (scientific journal)  

DOI： 10.1109/JSEN.2024.3388849

Web of Science

Scopus

researchmap

Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.ifacsc.2024.100261

Web of Science

Scopus

researchmap

Language：English   Publisher：Sensors  

Optimization approaches that determine sensitive sensor nodes in a large-scale, linear time-invariant, and discrete-time dynamical system are examined under the assumption of independent and identically distributed measurement noise. This study offers two novel selection algorithms, namely an approximate convex relaxation method with the Newton method and a gradient greedy method, and confirms the performance of the selection methods, including a convex relaxation method with semidefinite programming (SDP) and a pure greedy optimization method proposed in the previous studies. The matrix determinant of the observability Gramian was employed for the evaluations of the sensor subsets, while its gradient and Hessian were derived for the proposed methods. In the demonstration using numerical and real-world examples, the proposed approximate greedy method showed superiority in the run time when the sensor numbers were roughly the same as the dimensions of the latent system. The relaxation method with SDP is confirmed to be the most reasonable approach for a system with randomly generated matrices of higher dimensions. However, the degradation of the optimization results was also confirmed in the case of real-world datasets, while the pure greedy selection obtained the most stable optimization results.

DOI： 10.3390/s23135961

Open Access

Web of Science

Scopus

PubMed

Publishing type：Research paper (scientific journal)   Publisher：AIP Publishing  

The present study proposes a reservoir computing reduced-order model (RCROM) of the post-stall flow around the National Advisory Committee for Aeronautics 0015 airfoil based on the time series velocity field, and the estimation accuracy of the RCROM is evaluated compared to that of a linear reduced-order model (LROM). The data were experimentally obtained by particle image velocimetry at a chord Reynolds number of 6.4 × 104 and an angle of attack of 18°. The low-dimensional description of the velocity field can be obtained by decomposing the velocity field with a proper orthogonal decomposition (POD) technique and by employing the leading POD mode coefficients as temporal variables of the data instead of the velocity field. Reservoir computing (RC) is adopted as a nonlinear function that predicts several steps ahead of the leading POD mode coefficients. The hyperparameters of RC are tuned by Bayesian optimization, and the optimized RCROM outperforms the LROM in terms of estimation accuracy. The estimation accuracy of the RCROM can be investigated under different numbers of the predicted dominant POD modes and prediction step conditions. As a result, the RCROM shows higher estimation accuracy than the LROM.

DOI： 10.1063/5.0150947

Open Access

researchmap

Publisher：IEEE Access  

In this paper, the sparse sensor placement problem for least-squares estimation is considered, and the previous novel approach of the sparse sensor selection algorithm is extended. The maximization of the determinant of the matrix which appears in pseudo-inverse matrix operations is employed as an objective function of the problem in the present extended approach. The procedure for the maximization of the determinant of the corresponding matrix is proved to be mathematically the same as that of the previously proposed QR method when the number of sensors is less than that of state variables (undersampling). On the other hand, the authors have developed a new algorithm for when the number of sensors is greater than that of state variables (oversampling). Then, a unified formulation of the two algorithms is derived, and the lower bound of the objective function given by this algorithm is shown using the monotone submodularity of the objective function. The effectiveness of the proposed algorithm on the problem using real datasets is demonstrated by comparing with the results of other algorithms. The numerical results show that the proposed algorithm improves the estimation error by approximately 10% compared with the conventional methods in the oversampling case, where the estimation error is defined as the ratio of the difference between the reconstructed data and the full observation data to the full observation. For the NOAA-SST sensor problem, which has more than ten thousand sensor candidate points, the proposed algorithm selects the sensor positions in few seconds, which required several hours with the other algorithms in the oversampling case on a 3.40 GHz computer.

DOI： 10.1109/ACCESS.2021.3076186

Open Access

Web of Science

Scopus

Publisher：IEEE Sensors Letters  

A vector-measurement-sensor problem for the least squares estimation is considered, by extending a previous novel approach in this letter. An extension of the vector-measurement-sensor selection of the greedy algorithm is proposed and is applied to particle-image-velocimetry data to reconstruct the full state based on the information given by sparse vector-measurement sensors.

DOI： 10.1109/LSENS.2020.2999186

Web of Science

Scopus

Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.3390/en13061325

Open Access

Web of Science

Scopus

researchmap

Event date： 2023.10

Language：Japanese   Presentation type：Oral presentation (general)  

researchmap

Event date： 2023.8

Language：English   Presentation type：Oral presentation (general)  

researchmap

Event date： 2023.7

Language：English   Presentation type：Oral presentation (general)  

researchmap

Event date： 2022.11

Language：English   Presentation type：Oral presentation (general)  

researchmap

Event date： 2022.11

Language：Japanese   Presentation type：Oral presentation (general)  

researchmap

Event date： 2022.9

Language：Japanese   Presentation type：Oral presentation (general)  

researchmap

Event date： 2022.1

Language：English   Presentation type：Oral presentation (general)  

researchmap

Event date： 2021.11

Language：Japanese   Presentation type：Oral presentation (general)  

researchmap

Event date： 2020.11

Presentation type：Oral presentation (general)  

researchmap

Event date： 2020.9

Language：English   Presentation type：Oral presentation (general)  

researchmap

Event date： 2020.3

Language：Japanese   Presentation type：Oral presentation (general)  

researchmap