Deep reinforcement learning-based digital twin for droplet microfluidics control
author
Gyimah, Nafisat
Scheler, Ott
Rang, Toomas
Pardy, Tamas
statement of authorship
Nafisat Gyimah, Ott Scheler, Toomas Rang, Tamás Pardy
source
Physics of Fluids
publisher
AIP
journal volume number month
vol. 35, 8
year of publication
2023
pages
art. 082020
url
https://doi.org/10.1063/5.0159981
subject term
mikrovedelikundus
algoritmid
tehisõpe
vedelikud
TalTech subject term
digikaksikud
keyword
computational fluid dynamics
deep learning
e-learning
microfluidics
ISSN
1070-6631
notes
Bibliogr.: 66 ref
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
https://www.scopus.com/sourceid/29210
https://www.scopus.com/record/display.uri?eid=2-s2.0-85169800005&origin=resultslist&sort=plf-f&src=s&sid=443787aa9b1ca10ee6304e8733795725&sot=b&sdt=b&s=TITLE-ABS-KEY%28%22Deep+reinforcement+learning-based+digital+twin+for+droplet+microfluidics+control%22%29&sl=266&sessionSearchId=443787aa9b1ca10ee6304e8733795725&relpos=0
WOS
https://jcr.clarivate.com/jcr-jp/journal-profile?journal=PHYS%20FLUIDS&year=2023
https://www.webofscience.com/wos/woscc/full-record/WOS:001053895200005
category (general)
Engineering
Tehnika
Physics and astronomy
Füüsika ja astronoomia
Chemical engineering
Keemiatehnoloogia
category (sub)
Engineering. Computational mechanics
Tehnika. Arvutusmehaanika
Engineering. Mechanical engineering
Tehnika. Masinaehitus
Physics and astronomy. Condensed matter physics
Füüsika ja astronoomia. Kondenseeritud aine füüsika
Engineering. Mechanics of materials
Tehnika. Materjalide mehaanika
Chemical engineering. Fluid flow and transfer processes
Keemiatehnoloogia. Vedeliku voolu- ja ülekandeprotsessid
quartile
Q1
TalTech department
Thomas Johann Seebecki elektroonikainstituut
keemia ja biotehnoloogia instituut
language
inglise