Two-Phase Flow Interface Capturing Simulations

PI Igor Bolotnov, North Carolina State University
Co-PI Anna Iskhakova, North Carolina State University
Nam Dinh, North Carolina State University
Bolotnov ALCC Graphic

Example of anisotropic adaptivity, preserving boundary layer mesh structure between two pin electrodes.

Project Summary

This project sets out to resolve the existing challenges in predictive capabilities of two-phase flow and heat transfer by utilizing interface capturing methods and direct numerical simulation to perform state-of-the-art large-scale simulations two-phase flows.

Project Description

The planned ALCC project will capitalize on existing multiphase flow experience to utilize interface capturing methods and direct numerical simulation to perform state-of-the-art large-scale simulations two-phase flows. PHASTA code has a long history of HPC performance, and our group has been awarded 2014, 2016, 2018 and 2020 ALCC awards in the past advancing the mission of DOE. PHASTA is a finite-element based flow solver with level-set method for interface capturing approach.

Three major research projects would be supported by this allocation: (i) project on simulation of the two-phase flow separator design to support advanced boiling water nuclear reactor technology; (ii) two-phase boiling analysis for fundamental understanding of flow boiling in complex geometries to support advanced heat-exchanger designs; (iii) counter-current two-phase flow evaluation in complex geometries to support efficient carbon-capture technologies.

All three subprojects are tightly aligned with DOE’s mission statement: “is to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions”. They help resolve the existing challenges in predictive capabilities of two-phase flow and heat transfer. 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.

Allocations