Special Issue on Machine learning and data assimilation techniques for fluid flow measurements

Stefano Discetti; Andrea Sciacchitano

doi:10.1088/1361-6501/acce53

Special Issue on Machine learning and data assimilation techniques for fluid flow measurements

Stefano Discetti^*, Andrea Sciacchitano

^*Corresponding author for this work

Aerodynamics

Research output: Contribution to journal › Editorial › Scientific › peer-review

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Original language	English
Article number	090201
Journal	Measurement Science and Technology
Volume	34
Issue number	9
DOIs	https://doi.org/10.1088/1361-6501/acce53
Publication status	Published - 2023

Bibliographical note

Funding Information:
We thank Measurement Science and Technology and its Editorial board for supporting this special issue. The valuable help and support of Dr Ian Forbes, publisher of Measurement Science and Technology, is kindly acknowledged. We also warmly thank the reviewers involved in the peer-review process for the insightful comments and suggestions.

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10.1088/1361-6501/acce53

Discetti_2023_Meas._Sci._Technol._34_090201Final published version, 208 KB

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title = "Special Issue on Machine learning and data assimilation techniques for fluid flow measurements",

author = "Stefano Discetti and Andrea Sciacchitano",

note = "Funding Information: We thank Measurement Science and Technology and its Editorial board for supporting this special issue. The valuable help and support of Dr Ian Forbes, publisher of Measurement Science and Technology, is kindly acknowledged. We also warmly thank the reviewers involved in the peer-review process for the insightful comments and suggestions.",

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AU - Sciacchitano, Andrea

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U2 - 10.1088/1361-6501/acce53

DO - 10.1088/1361-6501/acce53

M3 - Editorial

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VL - 34

JO - Measurement Science and Technology

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IS - 9

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ER -

Special Issue on Machine learning and data assimilation techniques for fluid flow measurements

Bibliographical note

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