Search

Inspired by nature, oscillating foils offer viable options as alternate energy resources to harness energy from wind and water. Here, we propose a proper orthogonal decomposition (POD)-based reduced-order model (ROM) of power generation by flapping airfoils in conjunction with deep neural networks. Numerical simulations are performed for incompressible flow past a flapping NACA-0012 airfoil at a Reynolds number of 1100 using the Arbitrary Lagrangian–Eulerian approach. The snapshots of the pressure field around the flapping foil are then utilized to construct the pressure POD modes of each case, which serve as the reduced basis to span the solution space. The novelty of the current research relates to the identification, development, and employment of long-short-term neural network (LSTM) models to predict temporal coefficients of the pressure modes. These coefficients, in turn, are used to reconstruct hydrodynamic forces and moment, leading to computations of power. The proposed model takes the known temporal coefficients as inputs and predicts the future temporal coefficients followed by previously estimated temporal coefficients, very similar to traditional ROM. Through the new trained model, we can predict the temporal coefficients for a long time duration that can be far beyond the training time intervals more accurately. It may not be attained by traditional ROMs that lead to erroneous results. Consequently, the flow physics including the forces and moment exerted by fluids can be reconstructed accurately using POD modes as the basis set. [ABSTRACT FROM AUTHOR]

Using immersed boundary methods, we perform numerical simulations for flow over an elliptical airfoil oscillating at a reduced frequency of 6.283 over a range of Strouhal number with Reynolds number 500. We quantify the response of this nonlinear system through time-histories of aerodynamic lift and thrust force coefficients, their Fourier spectra, phase maps, Poincáre sections, and higher-order spectral analysis. When the oscillation amplitude increases, this nonlinear system undergoes bifurcations, thus eventually achieving chaotic solutions. The aerodynamic response moves quasi-periodically through to chaos. We also relate these behavioral changes in the response of the system to the wake transitions. We also present cross-bispectrum between the lift and thrust coefficients, and auto-trispectrum for the lift coefficient to study cubic coupling among various frequency components. We find the strongest quadratic and cubic coupling between the excitation frequency components. We also observe the cubic coupling among various frequency components responsible for generating new harmonics in the spectra of the lift force at higher Strouhal numbers. [ABSTRACT FROM AUTHOR]