Hokkaido University · Engineering
Professor Shuichiro Miwa's research lab specializes in advanced thermal-hydraulics and nuclear safety engineering, with a strong focus on two-phase flow phenomena, critical heat flux (CHF) prediction, and the development of high-performance emission control systems. The lab integrates artificial intelligence and machine learning techniques—such as convolutional neural networks, transformers, and transfer learning—into traditional thermal-hydraulic modeling to improve accuracy and robustness in predicting complex flow behaviors and system responses. Additionally, the lab is actively involved in the design and durability testing of advanced materials, including silicon carbide-based diesel particulate filters, for high-temperature and high-stress applications.
Figures are computed from collected data and may differ slightly.
Identification of flow regime and feature extraction of bubble characteristics in gas-liquid two-phase flow systems have been significant issues in various engineering disciplines, including nuclear thermal-hydraulics field. In nuclear safety analysis codes, flow regime transition criteria and bubble size-dependent correlations are often utilized to obtain solutions for the governing equations. However, even today, they still rely on flow regime maps and empirical criteria that are based on visu
<div class="htmlview paragraph">This paper presents the performance and durability test results of a newly developed diesel particulate filter (DPF) made of silicon carbide (SiC). While SiC offers thermal resistance that is superior to cordierite, it requires a complex, multi-segment bonded design structure due to the thermal expansion coefficient that is higher than cordierite, which leads to a higher thermal stress during regeneration. This company has developed a honeycomb slit-type DPF
Research and development in nuclear reactor physics and thermal-hydraulics continue to be vital parts of nuclear science and technology in Japan. The Fukushima accident not only brought tremendous change in public attitudes towards nuclear engineering and technology, but also had huge influence towards the research and development culture of scientific communities in Japan. After the Fukushima accident, thorough accident reviews were completed by independent committees, namely, Tokyo Electric Po
Fluctuating force induced by horizontal gas–liquid two-phase flow on 90 deg pipe bend at atmospheric pressure condition is considered. Analysis was conducted to develop a model which is capable of predicting the peak force fluctuation frequency and magnitudes, particularly at the stratified wavy two-phase flow regime. The proposed model was developed from the local instantaneous two-fluid model, and adopting guided acoustic theory and dynamic properties of one-dimensional (1D) waves to consider
Critical Heat Flux (CHF) plays a pivotal role in ensuring reliability and safety within boiling two-phase flow systems. Despite the development of numerous CHF prediction tools using conventional empirical correlations, machine learning, and deep learning methods, the complex mechanisms underlying CHF continue to challenge the development of a unified, accurate, and robust prediction model. The complexity is further exacerbated by varying experimental dataset developed over the decades of CHF re
Summary form only given, as follows. This paper describes a high efficiency and high output power GaN power amplifier for C-band space applications. The amplifier uses on-chip harmonic tuned FETs to improve efficiency. A 2nd harmonic input tuning circuit is incorporated into each unit on-chip FET cell and realizes highly precise control of 2nd harmonic input impedance. A 100 W power amplifier with 4-chips achieves a 67.0% PAE at 3.7 GHz. To the best of our knowledge, this is the highest efficien
Abstract Flow-induced vibration (FIV) continues to be a critical phenomenon for plant safety. Notably, the understanding of FIV generated by multiphase flow is still immature, and various accidents and troubles have been reported for the plant components including a steam generator, natural gas lines, piping systems, and so on. It is because FIV is complicated to be predicted during the plant’s design stage, and usually is first noticed in the operation stage. Hence, a practical solution for new
Open papers in the app to read, cite, and organize with AI.