Using large eddy simulations to understand flow mixingMarch 4, 2013
In nuclear power plants, turbulent flow streams of different velocity and density mix rapidly at right angles in pipes. If those mixing flow streams are of different temperatures, thermal fluctuations result on the pipe wall. Such fluctuations can damage a pipe’s structure and, ultimately, cause its failure. To better understand this phenomenon and to predict the effects, scientists have developed modeling methods known as large eddy simulations (LES).
LES models only the energy-carrying large scales of motion, using a filtering mechanism to account for subgrid-scale motion. Thanks to recent advances in high-performance computing, the technique has become increasingly popular for simulating unsteady flows, allowing high fidelity at reduced computational cost.
Three researchers in Argonne’s Mathematics and Computer Science Division— Aleksandr Obabko, Paul Fischer, and Timothy Tautges—and three colleagues from Russia and England have now written an article titled “Large Eddy Simulation of Thermo-Hydraulic Mixing in a T-Junction,” which focuses on thermal fluctuations relevant to the design of nuclear power plant pipe systems.
In the article, Obabko and his coauthors compare three LES codes: Nek5000, developed at Argonne, and two others developed at the Moscow Institute for Nuclear Energy Safety. The codes were tested on a popular benchmark based on recent thermal and velocity experimental measurements. The simulation results of all three methods show encouraging agreement with the experiment, with Nek5000 closely matching experimental data near the T-junction and CABARET capturing the experimental profiles further downstream. Moreover, the results show that large-scale mixing effects are not very sensitive to differences in operating conditions.
The work appears as chapter 2 in the new book Nuclear Reactor Thermal Hydraulics and Other Applications (D. P. Guillen, ed., INTECH, 2013). Divided into two main sections, the book discusses numerical advances and applications to predict fluid flow and heat transfer in nuclear reactors.