Multiphase Flow Simulations of Reactor Flows

PI Igor Bolotnov, North Carolina State University
Co-PI Jun Fang, Argonne National Laboratory
Project Summary

Researchers will utilize interface capturing methods and direct numerical simulation to perform state-of-the-art, large-scale simulations of reactor flows. Their work aims to help resolve existing challenges in predictive capabilities of two-phase flow, heat transfer, and plasma science.

Project Description

This ALCC project will utilize interface capturing methods and direct numerical simulation to perform state-of-the-art, large-scale simulations of reactor flows. The team will use the PHASTA code, a finite-element based flow solver with level-set method for the interface capturing approach.

The project will include three major subprojects: (1) full-scale simulation of table-top bubbly plasma generator; (2) two-phase validation of restricted pipe flow, and (3) heat transfer simulation of turbulent flows for advanced nuclear reactor model development (using different fluids, including molten salts and liquid metals). Each of the projects represent a novel simulation of a single- or two-phase flow which has not been done before at the proposed conditions and computational scale.

The first subproject is focused on a collaboration with experimental work at NCSU aiming to ignite a plasma inside submerged bubbles. Plasma ignition is dependent on the electric field strength, which is strongly dependent on the precise shape of the bubbles. While the researchers have run some initial simulations at low flow rates, they plan to use Theta to look into the bubble behavior as formed from multiple injection sites.

The second project will be focused on reproducing restricted pipe two-phase flow experiments and validating the numerical approach, as well as enhancing the database for complex geometry two-phase flow conditions and evaluating and further improving advanced DNS analysis techniques.

The third project will focus on performing heat transfer simulations to support the forced and natural heat convection model development for advanced nuclear reactor designs. Preliminary work demonstrated the code scalability and validated the predictive capabilities in this physics domain as well.

All the subprojects are tightly aligned with DOE’s mission to ensure America’s security and prosperity by addressing its energy, environmental, and nuclear challenges through transformative science and technology solutions. In particular, they help resolve the existing challenges in predictive capabilities of two-phase flow, heat transfer, and plasma science. All of those are directly related to modern and future energy generation and transformation, and involve HPC capabilities to demonstrate novel approaches of HPC applications to energy-related problems.

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