Data-Driven Methods in Fluid Mechanics: Data Assimilation, Bayesian Inference, Uncertainty Quantification

  in Special Issue   Posted on June 13, 2019

Information for the Special Issue

Submission Deadline: Sun 01 Sep 2019
Journal Impact Factor : 2.313
Journal Name : Computers and Fluids
Journal Publisher:
Website for the Special Issue: https://www.journals.elsevier.com/computers-and-fluids/call-for-papers/data-assimilation-bayesian-inference-uncertainty
Journal & Submission Website: https://www.journals.elsevier.com/computers-and-fluids

Special Issue Call for Papers:

CALL FOR PAPERS

Special issue on Data-Driven Methods in Fluid Mechanics: Data Assimilation, Bayesian Inference, Uncertainty Quantification

This special issue will present recent advances beyond the state of the art in Data-Driven Methods in Fluid Mechanics. The opening date for submission is 1st March 2019 and the deadline is 1st September 2019 Main topics of interest are (but not restricted to):

• Data Assimilation

• Bayesian Inference

• Uncertainty Quantification

• Flow Control

All articles will be refereed according to the standards of Computers & Fluids. The full papers must be submitted through the Elsevier Editorial System from 1st March 2019 to 1st September 2019. When submitting your paper, be sure to specify that the article is a contribution for the Special Issue of VSI:DDM in Fluid Mechanics. Please see the Author Instructions on the site if you have not yet submitted a paper through this web-based system. Accepted papers will be published online individually, before print publication. We are looking forward to receiving your contribution.

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