A Deep-Learned Monolithic Nanoparticle Asymmetric Thermal Flow Sensor for Flow Vector Estimation

Flow sensing is essential in various fields, including industrial, environmental, and biomedical applications, where accurate measurement of fluid dynamics is crucial. Traditional flow sensors are often bulky and complex, which can distort the flow and complicate installation when placed directly in...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Huijae Park (18509359) (author)
مؤلفون آخرون:	Sangjin Yoon (18509362) (author), Junhyuk Bang (11581938) (author), Jiyong Ahn (6730046) (author), Gyuho Choi (15172688) (author), Dohyung Kim (634987) (author), JinKi Min (16940204) (author), Jaeho Shin (1454812) (author), Seung Hwan Ko (144180) (author)
منشور في:	2025
الموضوعات:	Biotechnology Sociology Marine Biology Inorganic Chemistry Plasma Physics Plant Biology Space Science Astronomical and Space Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified time data monitoring reinforcement learning algorithms optimized hardware configuration nickel oxide nanoparticles induced selective sintering fabricated via laser improves measurement accuracy traditional flow sensors accurate flow estimation temperature sensor designed temperature sensors accurate measurement flow path versatile solution various fields system features structural design sensor resistance placed directly often bulky including industrial fluid dynamics film device complicate installation biomedical applications asymmetric design
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A Deep-Learned Monolithic Nanoparticle Asymmetric Thermal Flow Sensor for Flow Vector Estimation

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