Okano Yasunori - Program search result - SCEJ 53rd Autumn Meeting (Nagano, 2022)

`SCEJ 53rd Autumn Meeting (Nagano, 2022)`

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Program search result : Okano Yasunori : 5 programs

The preprints can be viewed by clicking the Paper IDs.
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Authors and Chairs (J) field exact matches “Okano Yasunori”; 5 programs are found. (“Poster with Flash” presentations are double-counted.)
The search results are sorted by the start time.

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
Day 1 17:20– 17:40	GA126	Numerical Study of Transport Phenomena in an iPS Cell Mass Culture System Using Non-Newtonian Fluids (Osaka U.) *(Stu)Shima Keisuke, (Reg)Okano Yasunori, (Osaka U./Fujimori Kogyo) Tokura Tomohiro, (Osaka U.) (Reg)Kino-oka Masahiro	iPS cells Bingham fluids OpenFOAM	SY-68	106
Day 2 9:20– 9:40	DA202	A Numerical Investigation of Stresses, Printing Efficiency, Printability, and Cell Viability in Nozzle Printheads for 3D Extrusion Bioprinting (Osaka U.) *(Stu)Zhang Colin, (Stu)Hidaka Mitsuyuki, (Reg)Kojima Masaru, (Reg)Sakai Shinji, (Reg)Okano Yasunori	3D extrusion bioprinting controlling stresses numerical simulation	SY-70	57
Day 2 10:20– 10:40	DA205	Development of single nozzle in multi-material 3D bioprinting for the construction of advanced cell (Osaka U.) *(Stu)Hidaka Mitsuyuki, (Stu)Zhang Colin, (Reg)Kojima Masaru, (Reg)Nakahata Masaki, (Reg)Horiguchi Ikki, (Reg)Okano Yasunori, (Reg)Sakai Shinji	3D extrusion printing multi-material printing numerical simulation	SY-70	514
Day 3 15:00– 15:20	DC319	[Featured presentation] Development of digital twin of the bulk single crystal growth of Si by using PINNs (Physics Informed Neural Networks) (Osaka U.) *(Stu)Takehara Yuto, (Reg)Okano Yasunori	Digital twin Machine learning Physics Informed Neural Networks	ST-21	396
Day 3 15:20– 15:40	DC320	Growth interface shape optimization and adaptive process control for InGaSb crystal growth under microgravity using machine learning (Osaka U.) *(Stu)Ghritli Rachid, (JAXA-SOKENDAI) Inatomi Yuko, (Osaka U.) (Reg)Okano Yasunori	Machine Learning Reinforcement Learning Crystal Growth	ST-21	428

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SCEJ 53rd Autumn Meeting (Nagano, 2022)

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