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Particle image velocimetry (PIV) is a widely used experimental technique in ocean engineering, for instance, to study the vortex fields near marine risers and the wake fields behind wind turbines or ship propellers. However, the flow fields measured using PIV in water tanks or wind tunnels always have low resolution; hence, it is difficult to accurately reveal the mechanics behind the complex phenomena sometimes observed. In this paper, physics-informed neural networks (PINNs), which introduce the Navier–Stokes equations or the continuity equation into the loss function during training to reconstruct a flow field with high resolution, are investigated. The accuracy is compared with the cubic spline interpolation method and a classic neural network in a case study of reconstructing a two-dimensional flow field around a cylinder, which is obtained through direct numerical simulation. Finally, the validated PINN method is applied to reconstruct a flow field measured using PIV and shows good performance. [ABSTRACT FROM AUTHOR]

An experimental investigation on the vortex/wake-induced force of double unequal-diameter cylinders in tandem was performed. In the experiment, the upstream-to-downstream cylinder diameter ratio was 1.569, and the gap spacing ratio between the cylinder models ranged from 3 to 8. Under uniform flow with Reynolds number up to 11 328, the strains caused by the vortex/wake-induced vibrations were measured for the double flexible cylinders. Based on the measured strains, the displacements were reconstructed with the mode superposition method. Then, the vortex/wake-induced forces were obtained inversely. Subsequently, the time-varying excitation and added mass coefficients were identified by the forgetting factor least squares method. The results show that the wake-induced force coefficient and excitation coefficient of the downstream cylinder are smaller than those of the single cylinder, while the added mass coefficient becomes larger. In addition, the downstream cylinder under frequency capture can absorb a higher proportion of energy from the wake to excite larger vibration amplitudes, especially in the in-line direction. [ABSTRACT FROM AUTHOR]

The objective of this comparison study is to verify and clarify whether the energy competitive force model has significant benefits in eliminating the influence of certain factors on the hydrodynamic coefficient. The typical cases with the smaller Keulegan–Carpenter (KC) number (KC = 31) and larger KC number (KC = 178) under the maximum reduced velocity of 6.5 with the prominent VIV responses are selected for analysis. The characteristics of the ortex-induced vibration (VIV) response, the hydrodynamic force, and the corresponding spatiotemporal coefficients in typical cases are revealed, compared, and discussed. The results suggest that the energy competition force model cannot avoid spatial-temporal distribution characteristics of the hydrodynamic coefficients. Drag and excitation coefficients with energy roles under Sarpkaya's and energy competitive force models are affected by the VIV response and wake effects in an oscillatory flow. The larger coefficients are witnessed under the smaller KC number. When the KC number increases from 31 to 178, the mean drag coefficients decrease from 2.25 to 1.73, and the mean excitation coefficients in in-line (IL) and cross-flow (CF) directions decrease from 1.42 and 1.44 to 0.60 and 0.81, respectively, under the energy competition force model. Changes in wake effects under a larger KC number lead to distinctive differences in drag and excitation coefficients during the acceleration and deceleration phases. Through a quantitative comparative analysis, the current identified drag and excitation coefficients under the energy competition force model can obtain a more accurate prediction result. The present work shows that there exists the blindness in the selection of coefficients within the framework of the energy competition force model. [ABSTRACT FROM AUTHOR]