We investigate the forces and unsteady flow structures associated with harmonic oscillations of an airfoil in the streamwise (surging) and transverse (plunging) directions in two-dimensional simulations at low Reynolds number. For the surging case, we show that there are specific frequencies where the wake instability synchronizes with the unsteady motion of the airfoil, leading to significant changes in the mean forces. Resonant behaviour of the time-averaged forces is observed near the vortex shedding frequency and its subharmonic; the behaviour is reminiscent of the dynamics of the generic nonlinear oscillator known as the Arnol'd tongue or the resonance horn. Below the wake instability frequency, there are two regimes where the fluctuating forces are amplified and attenuated, respectively. A detailed study of the flow structures associated with leading-edge vortex (LEV) growth and detachment are used to relate this behaviour with the LEV acting either in phase with the quasi-steady component of the forces for the amplification case, or out of phase for the attenuation case. Comparisons with wind tunnel measurements show that phenomenologically similar dynamics occur at higher Reynolds number. Finally, we show that qualitatively similar phenomena occur during both surging and plunging.

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We investigate the unsteady aerodynamic forces and energy transfer associated with harmonic surging (streamwise) and plunging (transverse) motion of a thin airfoil at low Reynolds number. Two-dimensional unsteady flows are simulated over a large range of amplitude and reduced-frequency of the oscillatory motion using the immersed boundary projection method, and the computational results are compared to inviscid flow models and experiments. At low angle of attack there is reasonable agreement with inviscid theory for the amplitude and phase of lift fluctuations, despite the low Reynolds number. At high angle of attack, the separated flow leads to larger lift and drag fluctuations not captured by inviscid models. At frequencies below the vortex shedding frequency, lift fluctuations are first enhanced and then attenuated depending on the phase between the freestream velocity and the forming leading-edge vortex. Resonance with the vortex shedding frequency also occurs. The time-averaged forces and power supplied by the oscillating airfoil are also evaluated to find frequency ranges that are favorable for the airfoil.

It is a common intuition from battery experts that many shape features in the voltage profile image contain abundant information related to battery performance. However, such features are often too subtle for a human to extract by eye inspection and further correlate with battery performance. Using long cycling data from hundreds of large-format pouch cells and a total of 2 million cycles tested over 1000 days, we demonstrate here for the first time that it is advantageous to accurately predict the capacity and remaining useful life in real time by learning battery voltage profile images rather than voltage values. A strategy of end-to-end performance prediction of large-format battery cells is thus demonstrated to be feasible using only a few of the previous cycles at any given time point during the cycling test. Our work paves the way toward the application of machine learning for real-time battery performance prediction and regulation for electric vehicle applications.