activity
20172022
most citedOn the Strong Scaling of the Spectral Element Solver Nek5000 on Petascale Systems

68 citations · 168 across the 17 of their papers we have counts for

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physics.flu-dyn2022

Direct Numerical Simulation of Low and Unitary Prandtl Number Fluids in Reactor Downcomer Geometry

Cheng-Kai Tai, Tri Nguyen, Arsen S. Iskhakov +3

Buoyancy effect on low-flow condition convective heat transfer of non-conventional coolants, such as liquid metal and molten salts, is a crucial safety factor to advanced reactors…

physics.flu-dyn20223 cited

Direct Numerical Simulation of High Prandtl Number Fluid Flow in the Downcomer of an Advanced Reactor

Tri Nguyen, Elia Merzari, Cheng-Kai Tai +1

The passive safety is a crucial feature of advanced nuclear reactor (Gen IV) design. During loss of power scenarios, the downcomer plays a crucial role. The fluid-flow behavior in…

physics.flu-dyn20221 cited

Direct Numerical Simulation of high Prandtl number fluids and supercritical carbon dioxide canonical flows using the spectral element method

Tri Nguyen, Elia Merzari, Haomin Yuan

The design of advanced nuclear reactors (Gen IV) involves an array of challenging fluid-flow issues that affect safety and performance. Currently, these problems are addressed in a…

physics.flu-dyn20222 cited

Toward Development of an Improved Friction Correlation for the Near-Wall Region of Pebble Bed Systems

David Reger, Elia Merzari, Paolo Balestra +3

The development of nuclear reactors that utilize pebble fuel has drastically increased the demand for improving the capabilities to simulate the packed beds found in these reactors…

physics.flu-dyn2022

Comparison of Pebble Bed Velocity Profiles Between High-Fidelity and Intermediate-Fidelity Codes

David Reger, Elia Merzari, Paolo Balestra +2

Recent interest for the development of high-temperature gas reactors has increased the need for more advanced understanding of flow characteristics in randomly packed pebble beds.…

physics.flu-dyn20222 cited

A Study on Convolution Neural Network for Reconstructing the Temperature Field of Wall-Bounded Flows

Victor Coppo Leite, Elia Merzari, Roberto Ponciroli +1

In the present study, the capabilities of a new Convolutional Neural Network (CNN) model are explored with the paramount objective of reconstructing the temperature field of wall-b…