skip to main content
10.1145/3490138.3498573acmotherconferencesArticle/Chapter ViewAbstractPublication PagesscConference Proceedingsconference-collections
poster

In Situ Data-Driven Analysis and Learning of Turbulence Closures at Scale

Published:15 November 2021Publication History

ABSTRACT

No abstract available.

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    ISAV'21: ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization
    November 2021
    36 pages
    ISBN:9781450387156
    DOI:10.1145/3490138

    Copyright © 2021 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 15 November 2021

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • poster
    • Research
    • Refereed limited

    Acceptance Rates

    Overall Acceptance Rate23of63submissions,37%
  • Article Metrics

    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0

    Other Metrics