arXiv subjects

William Wolf

Publications and source records attributed to William Wolf.

8 recordsLinked to original sources

arXiv2025

Interplay between streaks and vortices in shock-boundary layer interactions with conditional bubble events over a turbine airfoil

The shock-boundary layer interaction over the convex wall of a supersonic turbine vane is studied with a focus on extreme separation bubble events and the interplay between the bubble, streaks, and streamwise vortices. The present analysis is performed on a dataset computed by a LES of a supersonic turbine at Ma = 2.0 and Re = 395000. Building on findings related to near-wall streaks and vortices that drive the bubble breathing motion, here, we employ conditional analysis to study extreme bubble events. In events where the recirculation region is small, near-wall high-speed streaks penetrate the bubble and lead to higher tangential Reynolds stresses upstream of the incident shock compared to those with large recirculation. The streaks are accompanied by streamwise vortices that meander and induce intense fluid mixing, leading to higher wall-normal and spanwise Reynolds stresses, and consequently, higher turbulent kinetic energy. This turbulent activity also causes intense fluctuations in wall pressure and skin-friction coefficient along the separation region. In contrast, during events with bubble expansion, high-speed streaks are advected over the separation region, with streamwise vortices appearing only downstream of the shock, resulting in minimal fluid mixing inside the bubble. The analysis of mass flux along the bubble surface reveals that during its contraction phase, mass flux out of the bubble occurs predominantly upstream of the incident shock because of high-speed streaks dragged towards the wall by the streamwise vortices. In the expansion phase, pronounced mass flux into the bubble is observed downstream of the shock, near reattachment. This increased fluid injection is associated with the presence of streamwise vortices and low-momentum flow structures near reattachment, suggesting that fluid entrainment by vortices plays a key role in the mass flux into the bubble.

physics.flu-dyn↗

arXiv2024

Intermittency of a transitional airfoil flow with laminar separation bubble solved by the lattice-Boltzmann method

The flow over a NACA0012 airfoil at a moderate Reynolds number Re = 50,000 and angle of attack of alpha = 3 degrees is investigated using the lattice-Boltzmann method (LBM). The LBM solutions are computed in direct numerical simulation (DNS) mode, i.e., without a wall model. A validation is performed against a Navier-Stokes wall-resolved large eddy simulation, and good agreement is achieved between the different approaches, showing that the LBM can provide accurate solutions of boundary layers under transitional regime, but with a significant computational cost reduction. A laminar separation bubble (LSB) forms over the suction side of the airfoil, leading to intermittent vortex shedding that impacts transition to turbulence and the generation of strong spanwise-coherent vortices. Different shedding patterns are observed including the advection of single vortical structures and pairing of two vortices, which may or may not break into finer turbulent scales. Such flow features are characterized by 2D and 3D events that directly impact the sound generation by the trailing edge. Frequency and amplitude modulations from the LSB lead to a noise spectrum with a main tone plus equidistant secondary tones, and a time-frequency analysis shows that the main tones may switch frequencies due to intermittency. This research advances in the comprehension of the LSB behavior in transitional airfoil flows, impacting the performance and noise generation of blades and propellers.

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arXiv2023

Neural networks in feedback for flow analysis, sensor placement and control

This work presents a novel methodology for analysis and control of nonlinear fluid systems using neural networks. The approach is demonstrated on four different study cases being the Lorenz system, a modified version of the Kuramoto-Sivashinsky equation, a streamwise-periodic 2D channel flow, and a confined cylinder flow. Neural networks are trained as models to capture the complex system dynamics and estimate equilibrium points through a Newton method, enabled by backpropagation. These neural network surrogate models (NNSMs) are leveraged to train a second neural network, which is designed to act as a stabilizing closed-loop controller. The training process employs a recurrent approach, whereby the NNSM and the neural network controller (NNC) are chained in closed loop along a finite time horizon. By cycling through phases of combined random open-loop actuation and closed-loop control, an iterative training process is introduced to overcome the lack of data near equilibrium points. This approach improves the accuracy of the models in the most critical region for achieving stabilization. Through the use of L1 regularization within loss functions, the NNSMs can also guide optimal sensor placement, reducing the number of sensors from an initial candidate set. The datasets produced during the iterative training process are also leveraged for conducting a linear stability analysis through a modified dynamic mode decomposition approach. The results demonstrate the effectiveness of computationally inexpensive neural networks in modeling, controlling, and enabling stability analysis of nonlinear systems, providing insights into the system behaviour and offering potential for stabilization of complex fluid systems.

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arXiv2023

Influence of Different Subgrid Scale Models in LES of Supersonic Jet Flows

Current design constraints have encouraged the studies of aeroacoustics fields around compressible jet flows. The present work addresses the numerical study of subgrid scale modeling for unsteady turbulent jet flows as a preliminary step for future aeroacoustic analyses of main engine rocket plumes. An in-house large eddy simulation (LES) tool is developed in order to reproduce high fidelity results of compressible jet flows. In the present study, perfectly expanded jets are considered because the authors want to emphasize the effects of the jet mixing phenomena. The large eddy simulation formulation is written using the finite difference approach, with an explicit time integration and using a second order spatial discretization. The energy equation is carefully discretized in order to model the energy equation of the filtered Navier-Stokes formulation. The classical Smagorinsky model, the dynamic Smagorinsky model and the Vreman models are the chosen subgrid scale closures for the present work. Numerical simulations of perfectly expanded jets are performed and compared with the literature in order to validate and compare the performance of each subgrid closure in the solver.

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arXiv2023

Computational Performance of a LES Solver for Supersonic Jet Flow Applications

An in-house large eddy simulation tool is developed in order to reproduce high fidelity results of compressible jet flows. The large eddy simulation formulation is written using the finite difference approach, with an explicit time integration and using a second order spatial discretization. The energy equation is carefully discretized in order to model the energy equation of the filtered Navier-Stokes formulation. Such nu\-me\-ri\-cal studies are very expensive and demand high performance computing. Message passage interface protocols are implemented into the code in order to perform parallel computations. The present work addresses the computational performance of the solver running on up to 400 processors in parallel. Different mesh configurations, whose size varies from approximately 5.9 million points to approximately 1.0 billion points, are evaluate in the current paper. Speedup and efficiency curves are evaluated in order to assess the strong scalability of the solver.

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arXiv2022

Large Eddy Simulations of Supersonic Jet Flows for Aeroacoustic Applications

Current design constraints have encouraged the studies of aeroacoustics fields around compressible jet flows. The present work addresses the numerical study of unsteady turbulent jet flows for aeroacoustic analyses of main engine rocket plumes. A novel large eddy simulation (LES) tool is developed in order to reproduce high fidelity results of compressible jet flows which could be used for aeroacoustic studies with the Ffowcs Williams and Hawkings approach. The numerical solver is an upgrade of an existing Reynolds-averaged Navier-Stokes solver previously developed in the group. The original framework is rewritten in a modern fashion and intensive parallel computation capabilities have been added to the code. The LES formulation is written using the finite difference approach. The energy equation is carefully discretized in order to model the energy equation of the filtered Navier-Stokes formulation. The classical Smagorinsky model is the chosen subgrid scale closure for the present work. Numerical simulations of perfectly expanded jets are performed and compared with the literature in order to validate the new solver. Moreover, speedup and the computational performance of the code are evaluated and discussed. Flow results are used for an initial evaluation of the noise radiated from the rocket plume.

physics.flu-dyn↗

arXiv2021

On the application of incomplete FWH surfaces for aeroacoustic predictions

This work is motivated by CFD simulations from a realistic landing gear performed modeling only the half bottom of the aircraft fuselage [15]. Hence, in this previous analysis, the aeroacoustic predictions had to employ incomplete FWH surfaces. In the present study, a discussion on the closed surface requirement is provided for the frequency domain FWH formulation, although we believe that the approach presented here can also be applied for the time-domain methodology. We show that all sources computed on the closed permeable surface may play an important role if the acoustic prediction is sought at observer positions distributed along the entire circular arc. However, results obtained for 2D and 3D model problems show that, if wisely designed, a permeable FWH surface composed only by a finite patch, i.e., an incomplete surface, can be employed to accurately predict the noise at specific observer positions. In this case, the surface must be placed between the line of sight from the sources to the observers, for example, in flyover or sideline locations. In the current applications, results from finite surfaces agree with the expected values as long as the source magnitudes decay on elements distant from the true incident source, i.e., the airframe. Hence, in order for this approach to be valid, the sources cannot be truncated. The planar setup is beneficial in airframe noise applications since it avoids contamination by quadrupole sources crossing the boundaries and also may simplify the surface design.

physics.flu-dyn↗

arXiv2021

Data-Driven Closure of Projection-Based Reduced Order Models for Unsteady Compressible Flows

A data-driven closure modeling based on proper orthogonal decomposition (POD) temporal modes is used to obtain stable and accurate reduced order models (ROMs) of unsteady compressible flows. Model reduction is obtained via Galerkin and Petrov-Galerkin projection of the non-conservative compressible Navier-Stokes equations. The latter approach is implemented using the least-squares Petrov-Galerkin (LSPG) technique and the present methodology allows pre-computation of both Galerkin and LSPG coefficients. Closure is performed by adding linear and non-linear coefficients to the original ROMs and minimizing the error with respect to the POD temporal modes. In order to further reduce the computational cost of the ROMs, an accelerated greedy missing point estimation (MPE) hyper-reduction method is employed. A canonical compressible cylinder flow is first analyzed and serves as a benchmark. The second problem studied consists of the turbulent flow over a plunging airfoil undergoing deep dynamic stall. For the first case, linear and non-linear closure coefficients are both low in intrusiveness, capable of providing results in excellent agreement with the full order model. Regularization of calibrated models is also straightforward for this case. On the other hand, the dynamic stall flow is significantly more challenging, specially when only linear coefficients are used. Results show that non-linear calibration coefficients outperform their linear counterparts when a POD basis with fewer modes is used in the reconstruction. However, determining a correct level of regularization is more complicated with non-linear coefficients. Hyper-reduced models show good results when combined with non-linear calibration and an appropriate sized POD basis.

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