Skip to content

Commit b589117

Browse files
committed
update
1 parent 95754f5 commit b589117

File tree

1 file changed

+1
-1
lines changed

1 file changed

+1
-1
lines changed

paper/paper.md

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -52,7 +52,7 @@ The demand for high-performance computational fluid dynamics and multiphysics so
5252

5353
Fusion energy development draws from a wide range of disciplines to describe design and to develop a functioning system. One challenging engineering task is to develop the fusion core component known as a "blanket." Because this component surrounds the burning plasma and must absorb almost all of the power from nuclear reactions, it must breed fuel, provide nuclear shielding, and provide energy deposition. Molten salt (MS) is a primary choice for cooling the blanket. A “salt blanket” in fusion energy is a layer of molten salt surrounding the fusion plasma. The molten salt acts as both a coolant and a material for neutron absorption, both of which are essential in fusion reactions. The salt blanket absorbs the high-energy neutrons produced by fusion, reducing the wear on reactor components, and converting some of the energy into heat for electricity generation. Molten salts have low electrical and thermal conductivity and experience lesser electromagnetic forces, but they are still turbulent. Heat transfer degradation in an MS flow caused by the reduction of turbulence by a magnetic field is a possible limitation of the MS blanket [@Smolentsev01042005].
5454

55-
Two approaches are commonly adopted to predict MS flows exposed to a magnetic field: high-fidelity simulation (large-eddy simulation (LES) or direct numerical simulation (DNS)), and Reynolds-averaged Navier-Stokes (RANS) turbulence models. LESs can resolve turbulences at temporal and spatial scales at the expense of large HPC resources. Blanket design with LES is not possible because of current HPC limitations. Design optimization often requires multiple simulation runs to investigate performance under various conditions. The main technique that reduces the computational requirements of the analysis is the RANS turbulence model. This approach filters out the instantaneous velocity component, and the influence of the turbulence is modeled solely by the closure models. Turbulence modeling is a complex problem, and many turbulence models are available as described in the literature [@Chen_2022][@Menter1992ImprovedTK], albeit with many limitations [@10.1023/a:1022818327584]. Furthermore, these models are not readily applicable to the MHD flows and would require modifications [@Smolentsev2002] because MHD effects introduce additional terms in the turbulence balance equations.
55+
Two approaches are commonly adopted to predict MS flows exposed to a magnetic field: high-fidelity simulation (large-eddy simulation (LES) or direct numerical simulation (DNS)), and Reynolds-averaged Navier-Stokes (RANS) turbulence models. LESs can resolve turbulences at temporal and spatial scales at the expense of large HPC resources. Blanket design with LES is not possible because of current HPC limitations. Design optimization often requires multiple simulation runs to investigate performance under various conditions. The main technique that reduces the computational requirements of the analysis is the RANS turbulence model. This approach filters out the instantaneous velocity component, and the influence of the turbulence is modeled solely by the closure models. Turbulence modeling is a complex problem, and many turbulence models are available as described in the literature [@Chen_2022; @Menter1992ImprovedTK], albeit with many limitations [@10.1023/a:1022818327584]. Furthermore, these models are not readily applicable to the MHD flows and would require modifications [@Smolentsev2002] because MHD effects introduce additional terms in the turbulence balance equations.
5656

5757
VERTEX-CFD is a new open-source package designed to address the modeling of MHD flows in complex geometries. It provides a robust multi-physics solver that can generate high-fidelity simulations by scaling on HPC platforms. VERTEX-CFD package also integrates artificial intelligence and machine learning (AI&ML) tools. These capabilities will provide the needed resources to extend the applicability of turbulence models to MHD flows, and perform design analysis.
5858

0 commit comments

Comments
 (0)