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VISION-iT:A Framework for Digitizing Bubbles and Droplets

Energy and AI 2024年第1期15卷 26-35页

作者： Youngjoon Suh sanghyeon chang Peter Simadiris Tiffany B.Inouye Muhammad Jahidul Hoque Siavash Khodakarami Chirag Kharangate Nenad Miljkovic Yoonjin Won Department of Mechanical and Aerospace Engineering University of CaliforniaIrvine4200 Engineering GatewayCA 92617-2700USA Department of Electrical Engineering and Computer Science University of CaliforniaIrvine5200 Engineering HallCA 92617-2700USA Department of Mechanical Science and Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA Mechanical and Aerospace Engineering Department Case Western Reserve UniversityClevelandOH44106USA Department of Electrical and Computer Engineering University of Illinois at Urbana-ChampaignUrbanaIL61801USA Materials Research Laboratory University of Illinois at Urbana-ChampaignUrbanaIL61801USA International Institute for Carbon Neutral Energy Research(WPI-12CNER) Kyushu University744 Moto-okaNishi-kuFukuoka 819-0395Japan

Quantifying the nucleation processes involved in liquid-vapor phase-change phenomena,while dauntingly challenging,is central in designing energy conversion and thermal management *** technological advances in the deep learning and computer vision field offer the potential for quantifying such complex two-phase nucleation processes at unprecedented *** leveraging these new technologies,a multiple object tracking framework called“vision inspired online nuclei tracker(VISION-iT)”has been proposed to extract large-scale,physical features residing within boiling and condensation ***,extracting high-quality features that can be integrated with domain knowledge requires detailed discussions that may be field-or case-specific *** this regard,we present a demonstration and discussion of the detailed construction,algorithms,and optimization of individual modules to enable adaptation of the framework to custom *** concepts and procedures outlined in this study are transferable and can benefit broader audiences dealing with similar problems.

关键词： Deep learning Computer vision Nucleation Heat transfer Phase-change phenomena

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Splitting of the virtual class for genus one stable quasimaps

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Science China Mathematics 2024年

作者： sanghyeon Lee Mu-Lin Li Shanghai Center for Mathematical Sciences Fudan University School of Mathematics Hunan University

We analyze the local structure of the moduli space of genus one stable quasimaps. Combining it with the p-fields theory developed by chang and Li（2020）, we prove the splitting formula for the virtual cycle of stable...

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