Owing to the ever-growing resources available at supercomputing centers, High Performance Computing (HPC) analyses of flow configurations including several complex concurring aspects are becoming an established reality. Thus, the development of reliable numerical strategies capable to provide an accurate representation of multi-physics problems is a timely central challenge in Computational Fluid Dynamics (CFD). The accurate prediction of numerous flow features of unstationary flows such as aerodynamic forces is driven by the precise representation of localized near-wall dynamics. This aspect is particularly challenging for the flow prediction around complex geometries. In this case classical body-fitted approaches may have to deal with high deformation of the mesh elements, possibly providing poor numerical prediction. Additionally, the simulation of moving bodies may require prohibitively expensive mesh updates. The Immersed Boundary Method (IBM) has emerged as one of the most popular strategies to handle these two problematic aspects. Among the different proposal in the literature, the tool recently proposed by the PI and his colleagues has shown favorable features of accuracy and scaling properties for parallel computing. The main difficulty of IBM is the high computational demands for the representation of wall turbulence, which is a governing aspect in most engineering cases.
Project IWP-IBM-DA aims for a breakthrough in the advancement of these numerical techniques for the analysis of complex flows. To do so, an interdisciplinary strategy relying on tools from the Estimation Theory (ET) is proposed. ET is a branch of statistics dealing with the estimation of optimized parametric description, using data which is affected by a level of uncertainty. The very first applications of ET tools in CFD deal with Uncertainty Quantification (UQ). More recently, seminal works in Data Assimilation (DA) have been proposed for flow investigation. Among these proposals, the estimator developed by the PI for the analysis of turbulent incompressible flows integrates high-fidelity data (observation) in classical CFD solvers in order to obtain an augmented prediction of the flow.
The present project aims to obtain advancement of the IBM method via DA, exploiting the synergistic integration and further development of the two tools developed by the team. The accuracy of the IBM will be improved integrating high-fidelity observation (including experimental data), targeting a precise representation of near-wall dynamics for turbulent flows. The development will follow two different strategies, investigating both wall representation and wall-function calculation. The latter is associated with reduced-order CFD modelling such as RANS and LES. The bullet points of the present proposal representing innovation with respect to the state-of-the-art are i) the research development will be conceived for intrusive DA applications, ii) multigrid methods will be employed to improve DA results iii) the application to complex, realistic cases is envisioned.
The development of the IBM-DA strategies will be investigated in two scientific Tasks, which aim for advancement of the two strategies previously introduced. Test cases of increasing complexity will be investigated, including the simulation of the flow around a car model with moving actuators integrating experimental PIV measurements. The analysis will be developed in the framework of the open-source code OpenFOAM, which is among the reference tools for academic and industrial CFD analysis and is optimized for parallel calculations in national supercomputing centers. The diffusion of the results obtained will be magnified by the reach of the PI, who is a board member of the French user association of OpenFOAM.
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Pprime Institut P' : Recherche et Ingénierie en Matériaux, Mécanique et Energétique
Help of the ANR 291,424 euros
Beginning and duration of the scientific project: September 2021 - 48 Months