Coarse mesh turbulence prediction for reactor transient simulations using densely connected convolutional networks

Yang Liu; Rui Hu; Prasanna Balaprakash; Acacia Brunett; Aleksandr Obabko

doi:10.13182/T123-32854

Coarse mesh turbulence prediction for reactor transient simulations using densely connected convolutional networks

Yang Liu, Rui Hu, Prasanna Balaprakash, Acacia Brunett, Aleksandr Obabko

Research output: Contribution to journal › Conference article › peer-review

6 Scopus citations

Original language	English
Pages (from-to)	1601-1604
Number of pages	4
Journal	Transactions of the American Nuclear Society
Volume	123
Issue number	1
DOIs	https://doi.org/10.13182/T123-32854
State	Published - 2020
Externally published	Yes
Event	2020 Transactions of the American Nuclear Society Winter Meeting, ANS 2020 - Virtual, Online, United States Duration: Nov 16 2020 → Nov 20 2020

Funding

This material is based upon work supported by Laboratory Directed Research and Development (LDRD) funding from Argonnc National Laboratory, provided by the Director, Office of Science, of the U.S. Department ofEncrgy under Contract No. DEAC02-06CH11357. The authors thank Adam Kraus for his help on the STAR-CCM+ simulation.

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10.13182/T123-32854

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title = "Coarse mesh turbulence prediction for reactor transient simulations using densely connected convolutional networks",

author = "Yang Liu and Rui Hu and Prasanna Balaprakash and Acacia Brunett and Aleksandr Obabko",

year = "2020",

doi = "10.13182/T123-32854",

language = "English",

volume = "123",

pages = "1601--1604",

journal = "Transactions of the American Nuclear Society",

issn = "0003-018X",

number = "1",

note = "2020 Transactions of the American Nuclear Society Winter Meeting, ANS 2020 ; Conference date: 16-11-2020 Through 20-11-2020",

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TY - JOUR

T1 - Coarse mesh turbulence prediction for reactor transient simulations using densely connected convolutional networks

AU - Liu, Yang

AU - Hu, Rui

AU - Balaprakash, Prasanna

AU - Brunett, Acacia

AU - Obabko, Aleksandr

PY - 2020

Y1 - 2020

UR - https://www.scopus.com/pages/publications/85104968532

U2 - 10.13182/T123-32854

DO - 10.13182/T123-32854

M3 - Conference article

AN - SCOPUS:85104968532

SN - 0003-018X

VL - 123

SP - 1601

EP - 1604

JO - Transactions of the American Nuclear Society

JF - Transactions of the American Nuclear Society

IS - 1

T2 - 2020 Transactions of the American Nuclear Society Winter Meeting, ANS 2020

Y2 - 16 November 2020 through 20 November 2020

ER -

Coarse mesh turbulence prediction for reactor transient simulations using densely connected convolutional networks

Funding

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