Engineering topics

Santoni, Christian

Publications and source records attributed to Santoni, Christian.

4 records

DOE OSTI2023

Virtual Flow Solver - Geophysics: A 3D Incompressible Navier-Stokes Solver

Virtual Flow Solver - Geophysics (VFS-Geophysics) is a three-dimensional (3D) incompressible Navier-Stokes solver based on the Curvilinear Immersed Boundary (CURVIB) method. The CURVIB is a sharp interface type of immersed boundary (IB) method that enables the simulation of fluid flows in the presence of geometrically complex moving bodies. The CURVIB method can be applied to wind/MHK turbine simulations and energy applications. VFS-Geophysics is the result of many years of research work by several graduate students, post-docs, and research associates that have been involved in the Computational Hydrodynamics and Biofluids Laboratory directed by Professor Fotis Sotiropoulos. The preparation of the present manual has been supported by the U.S. Department of Energy (DE-EE 0005482).

16 TIDAL AND WAVE POWER↗

DOE OSTI2023

Toward prediction of turbulent atmospheric flows over propagating oceanic waves via machine-learning augmented large-eddy simulation

Wind-wave interactions have important effects on the energy harvesting of offshore wind farms. High-fidelity large-eddy simulation (LES) is a powerful approach for investigating wind-wave interactions in turbulent oceanic environments. Due to the large scale of the flow domain and the high grid resolution required to resolve multi-scale flow motions, however, brute-force LES of wind-wave interactions is computationally very expensive. We propose augmenting brute-force LES via machine-learning data-driven modeling (ML-LES) to dramatically reduce the computational time required to obtain converged turbulence statistics when the brute-force approach is employed. Namely, we employ a convolutional neural network (CNN) autoencoder trained and validated with LES data sets to develop a highly efficient ML-LES approach for computing turbulence statistics from just a few snapshots of instantaneous LES flow fields. Further, our results demonstrate the accuracy and efficiency of ML-LES in predicting the mean velocity, velocity fluctuations, and turbulence kinetic energy in highly stretched computational grid systems required to carry out simulations in real-life oceanic environments.

42 ENGINEERING↗

DOE OSTI2023

Coupling turbulent flow with blade aeroelastics and control modules in large-eddy simulation of utility-scale wind turbines

We present a large-eddy simulation framework capable of control co-design of large wind turbines, coupling the turbulent flow environment with blade aeroelastics and turbine controllers. The geometry and aerodynamics of the rotor blades and the turbine nacelle are parameterized using an actuator surface model. The baseline collective pitch control and individual pitch control (IPC) algorithms, consisting of a single-input, single-output proportional–integral controller and two integral controllers, respectively, are incorporated into the simulation framework. Furthermore, a second-order model based on the Euler–Bernoulli beam theory is implemented to describe the blade deformation. Simulations are carried out to investigate the impact of collective and individual pitch control strategies on the deflection of turbine blades. Our results show that the IPC reduces the blade tip deflection fluctuations in the out-of-plane direction, while the fluctuations of the blade tip deflection along the in-plane direction are barely affected by the IPC. Furthermore, the blade out-of-plane deformation fluctuation is underestimated by the one-way coupling approach compared to the two-way coupling approach. Furthermore, the findings of this study reveal the importance of advanced control systems in reducing the dynamic loads on wind turbine blades and underscore the potential of control co-design to reduce the levelized cost of wind energy.

42 ENGINEERING↗

DOE OSTI2022

Toward control co-design of utility-scale wind turbines: Collective vs. individual blade pitch control

A large-eddy simulation framework has been coupled with controller modules to systematically investigate the impacts of collective (CPC) and individual (IPC) pitch control strategies on utility-scale wind turbine energy production and fatigue loads. Wind turbine components were parameterized using an actuator surface model to simulate the rotor blades and the turbine nacelle. The baseline CPC and IPC algorithms, consisting of single-input single-output proportional–integral controllers and two integral controllers, respectively, were incorporated into the numerical framework. A series of simulations were carried out to investigate the relative performance of the two controllers under various turbulent inflow conditions, spanning hub-height velocities of 7 to 14 m/s. The numerical simulation results of this study showed that, in comparison to the CPC, the IPC controller could successfully reduce the damage equivalent loads of utility-scale turbines at regions 2 and 3 of turbine operation by about 3% and 40%, respectively, without any penalty on the power production of the turbine. It was also shown that, despite its minor impact on the turbulence kinetic energy of the wake, the IPC controller did not influence the recovery of the turbine wake.

17 WIND ENERGY↗