Calibration of the 2-Phase Bubble Tracking Model for Liquid Mercury Target Simulation with Machine Learning Surrogate Models

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is one of the most powerful accelerator-driven neutron sources in the world. The intense protons strike on SNS’s mercury target to provide bright neutron beams, which also leads to severe fluid-structure interactions inside the tar...

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Veröffentlicht in:	Journal of physics. Conference series 2024-01, Vol.2687 (3), p.32047
Hauptverfasser:	Lin, L, Tran, H, Radaideh, M, Hoover, A, Winder, D, Cousineau, S
Format:	Artikel
Sprache:	eng
Schlagworte:	Fluid-structure interaction Helium Machine learning Mathematical models Neutron beams Neutron sources Neutrons Parameter identification Parameter uncertainty Research facilities Simulation Spallation
Online-Zugang:	Volltext
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