A two-level machine learning approach for predicting thermal striping in T-junctions with upstream elbow

Author:

Wang Yu-Jou1,Baglietto Emilio1ORCID,Shirvan Koroush1ORCID

Affiliation:

1. Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, USA

Funder

the Generating Electricity Managed by Intelligent Nuclear Access (GEMINA) program of the U.S. Advanced Research Project Agency – Energy

Advanced Research Projects Agency – Energy

Publisher

Informa UK Limited

Subject

Computer Science Applications,Mechanics of Materials,Condensed Matter Physics,Modeling and Simulation,Numerical Analysis

Reference41 articles.

1. C. Betts, A. Judd and M. Lewis, “Avoiding thermal striping damage: experimentally-based design procedures for high-cycle thermal fatigue,” presented at the IWGFR-90, Vienna, Austria: IAEA, 1994.

2. O. Gelineau, M. Sperandio, P. Martin, J. B. Ricard, L. Martin and A. Bougault, “Thermal fluctuation problems encountered in LMFRs,” presented at the IWGFR-90, Vienna, Austria: IAEA, 1994.

3. V. Sobolev and N. Kuzavkov, “Identification of places with fluid temperatures in BN 600 reactor and reactor systems,” presented at the IWGFR-90, Vienna, Austria: IAEA, 1994.

4. V. N. Shah, A. G. Ware, C. L. Atwood, M. B. Sattison, R. S. Hartley and C. Hsu, “Assessment of field experience related to pressurized water reactor primary system leaks,” Idaho Nat. Lab., Idaho Falls, ID, INEEL/CON9900037, 1999.

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