PhD Position: Data assimilation for simulation–experiment coupling applied to wakes near the free surface (M/F)

Job Description

Thesis Subject

At the CNRS, at the Futuroscope site, the PPRIME Institute is recruiting a PhD student to study he flow around lifiting surfaces will be studied through the developpement of a data assimilation methodology coupling experimental results and numerical simulations, applied to bodies moving near a free surface.


1- CONTEXT:
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Understanding and predicting fluid flows around fixed or moving structures are major challenges in many defense-related applications. In both aerodynamics and hydrodynamics, fixed and rotating wings, control surfaces, and propellers are subjected to fluid forces generated by complex unsteady physical phenomena that remain difficult to predict and measure accurately. In most practical situations, these phenomena govern fluid–structure interactions, and their understanding requires detailed knowledge of the unsteady flow dynamics, wake development, and the associated fluid forces. In particular, turbulent flows generate structures over a wide range of spatial and temporal scales that strongly influence pressure and skin-friction forces (and therefore hydrodynamic performance), wake dynamics, aeration, and cavitation, which in turn also affect wake development.

In this context, theoretical and numerical tools developed to predict fluid flows are generally validated against available experimental data using statistical, modal, or spectral quantities. However, direct comparison between numerical simulations and experiments remains challenging because both approaches are independently conditioned and rely on different temporal bases. Furthermore, numerical simulations provide detailed information close to solid boundaries and within regions inaccessible to experimental measurements, making direct comparisons difficult. Consequently, beyond simple validation, numerical simulations and experiments should be combined in a complementary manner to provide improved flow predictions in otherwise inaccessible regions while sharing a common physical conditioning.

The objective of this PhD project is therefore to develop a methodology coupling numerical simulations and experimental measurements in order to predict the flow around an Eppler hydrofoil operating near the free surface. The representativeness of the coupled solution will be quantified through uncertainty estimation applied consistently to both numerical and experimental datasets.


2- PROGRAMM:
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The proposed PhD aims at developing, validating, and applying an operational data assimilation methodology for unsteady turbulent flows. A first approach will investigate the extent to which hybridization - namely the direct coupling of numerical and experimental data using arbitrary weighting coefficients - can provide satisfactory flow reconstructions. This first stage will be complemented by a stochastic estimation approach, in which the uncertainty levels associated with each dataset will be explicitly taken into account during the coupling process. Finally, a Kalman filter-based stochastic data assimilation framework will be developed. In this approach, a dynamical model based on the Navier–Stokes equations will be combined with an observation model representing the experimental measurements. The uncertainties associated with both numerical simulations and experiments will be incorporated to provide the best possible estimate of the flow state. The performance of these methodologies will be assessed by comparing assimilated flow fields with independent experimental datasets used for validation. Additional work will focus on identifying the minimum experimental datasets required to achieve efficient data assimilation, with the objective of reducing experimental acquisition costs and data volumes.

Applications will focus on both laminar and turbulent flows around airfoil sections (Eppler profiles). Particular attention will be devoted to reconstructing three-dimensional flow structures from bi- or three-component velocity measurements acquired over two- or three-dimensional measurement domains. The reconstructed pressure fields and hydrodynamic forces will be compared with direct sensor measurements as well as with estimates obtained using conventional postprocessing techniques


3- SKILLS:
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-Holder of a Master's degree or an engineering school qualification
-Fluid Mechanics
-Computational Fluid Dynamics (OpenFOAM),
-Experimental techniques,
-Scientific programming

Your Work Environment

The PhD student will be based at the ISAE-ENSMA site (pprime.fr) and must enrol at the MIMME Doctoral School.

Constraints and risks

Short-term travel, both within France and abroad, is to be expected.

Compensation and benefits

Compensation

2300 € gross monthly

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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