Michel Rasquin

The present research proposes a new memory-efficient method using diffusion models to inject turbulent inflow conditions into large eddy simulation and direct numerical simulation for various flow problems. A guided diffusion model was trained on decaying homogeneous isotropic turbulence samples, characterized by different turbulent kinetic energy levels and integral length scales. Samples generated by the diffusion model accurately reproduce turbulence statistics, such as the energy spectrum and the two-point autocorrelation functions, while preserving the ability to generate instantaneous three-dimensional velocity fields with detailed fluctuations. Physical representativeness is also evaluated by injecting the synthetic samples into a free domain (i.e., without any wall boundary) through an inlet boundary condition. The method demonstrates promising results regarding energy spectrum, spatial correlation, turbulent kinetic energy level, and integral length scales without increasing the development distance as compared to a library-based method.

This paper presents two recent numerical tools developed respectively to perform traditional post-processing and more advanced in situ processing of high-order polynomial data generated by massively parallel finite element codes. For post-processing and visualisation of high-order solutions, we present a new ParaView plugin that integrates Gmsh used as an external library. This plugin therefore combines respectively ParaView's scalability in parallel and Gmsh's ability to apply h-refinement of the initial mesh followed by solution interpolation on the resulting visualisation grid, thus enabling parallel visualisation of any arbitrary high-order polynomial solutions in client–server mode. In a second stage, this capacity has been extended to an in situ interface based on the Catalyst library which enables in situ analysis and visualisation of high-order solutions. These new capacities are demonstrated with the visualisation of high-order solution of the unsteady flow generated by a discontinuous Galerkin method for an unsteady turbomachinery application.

Absorbing heat from the fuel rod surface, water as coolant can undergo subcooled boiling within a pressurized water reactor (PWR) fuel rod bundle. Because of the buoyancy effect, the vapor bubbles generated will then rise along and interact with the subchannel geometries. Reliable prediction of bubble behavior is of immense importance to ensure safe and stable reactor operation. However, given a complex engineering system like a nuclear reactor, it is very challenging (if not impossible) to conduct high-resolution measurements to study bubbly flows under reactor operation conditions. The lack of a fundamental two-phase-flow database is hindering the development of accurate two-phase-flow models required in more advanced reactor designs. In response to this challenge, first-principles–based numerical simulations are emerging as an attractive alternative to produce a complementary data source along with experiments. Leveraged by the unprecedented computing power offered by state-of-the-art supercomputers, direct numerical simulation (DNS), coupled with interface tracking methods, is becoming a practical tool to investigate some of the most challenging engineering flow problems. In the presented research, turbulent bubbly flow is simulated via DNS in single PWR subchannel geometries with auxiliary structures (e.g., supporting spacer grid and mixing vanes). The geometric effects these structures exert on the bubbly flow are studied with both a conventional time-averaging approach and a novel dynamic bubble tracking method. The new insights obtained will help inform better two-phase models that can contribute to safer and more efficient nuclear reactor systems.

A coordinated experimental/computational study of synthetic jet-based flow control on a vertical tail/rudder assembly has been carried out on a 1/19th-scale model operating at 30 deg rudder deflect...

Some possible future High Fidelity CFD codes for LES simulation of turbomachinery are compared on several test cases increasing in complexity, starting from a very simple inviscid Vortex Convection to a multistage axial experimental compressor. Simulations were performed between 2013 and 2016 by major Safran partners (Cenaero, Cerfacs, CORIA and Onera) and various numerical methods compared: Finite Volume, Discontinuous Galerkin, Spectral Differences. Comparison to analytical results, to experimental data or to RANS simulations are performed to check and measure accuracy. CPU efficiency versus accuracy are also presented. It clearly appears that the level of maturity could be different between codes and numerical approaches. In the end, advantages and disadvantages of every codes obtained during this project are presented.

The scalability of unstructured mesh-based applications depends on partitioning methods that quickly balance the computational work while reducing communication costs. Zhou et al. [SIAM J. Sci. Comput., 32 (2010), pp. 3201--3227; J. Supercomput., 59 (2012), pp. 1218--1228] demonstrated the combination of (hyper)graph methods with vertex and element partition improvement for PHASTA CFD scaling to hundreds of thousands of processes. Our work generalizes partition improvement to support balancing combinations of all the mesh entity dimensions (vertices, edges, faces, regions) in partitions with imbalances exceeding 70%. Improvement results are presented for multiple entity dimensions on up to one million processes on meshes with over 12 billion tetrahedral elements.