Mass transfer from small spheroids suspended in a turbulent fluid

By coupling direct numerical simulation of homogeneous isotropic turbulence with a localised solution of the convection–diffusion equation, we model the rate of transfer of a solute (mass transfer) from the surface of small, neutrally buoyant, axisymmetric, ellipsoidal particles (spheroids) in dilute suspension within a turbulent fluid at large Péclet number, $\textit {Pe}$ . We observe that, at $\textit {Pe} = O(10)$ , the average transfer rate for prolate spheroids is larger than that of spheres with equivalent surface area, whereas oblate spheroids experience a lower average transfer rate. However, as the Péclet number is increased, oblate spheroids can experience an enhancement in mass transfer relative to spheres near an optimal aspect ratio $\lambda \approx 1/4$ . Furthermore, we observe that, for spherical particles, the Sherwood number $\textit {Sh}$ scales approximately as $\textit {Pe}^{0.26}$ over $\textit {Pe} = 1.4\times 10^{1}$ to $1.4\times 10^{4}$ , which is below the $\textit {Pe}^{1/3}$ scaling observed for inertial particles but consistent with available experimental data for tracer-like particles. The discrepancy is attributed to the diffusion-limited temporal response of the concentration boundary layer to turbulent strain fluctuations. A simple model, the quasi-steady flux model, captures both of these phenomena and shows good quantitative agreement with our numerical simulations.

Using Physics-Informed Generative Adversarial Networks to Perform Super-Resolution for Multiphase Fluid Simulations

Computational Fluid Dynamics (CFD) simulations are useful to the field of engineering design as they provide deep insights on product or system performance without the need to construct and test physical prototypes. However, they can be very computationally intensive to run. Machine learning methods have been shown to reconstruct high-resolution single-phase turbulent fluid flow simulations from low-resolution inputs. This offers a potential avenue towards alleviating computational cost in iterative engineering design applications. However, little work thus far has explored the application of machine learning image super-resolution methods to multiphase fluid flow (which is important for important for emerging fields such as marine hydrokinetic energy conversion). In this work, we apply a modified version of the Super-Resolution Generative Adversarial Network (SRGAN) model to a multiphase turbulent fluid flow problem, specifically to reconstruct fluid phase fraction at a higher resolution. Two models were created in this work, one with a simple physics-constrained loss function and one without, and the results are discussed and analyzed. We found that both models were able to significantly outperform non-machine learning upsampling methods and can preserve an impressive amount of detail and nuance, showing the versatility of the SRGAN model for upsampling fluid simulations. However, the difference in accuracy between the two models is quite minimal. This indicates that, for these contexts studied here, the additional complexity of a physics-informed approach may not be justified.

Analytical Study of Free Vibrations of Fluid Coupling and Structure in Collision of Turbulent Fluid with FGM Plate

In this paper, the free and forced vibration of a functional rectangular plate in contact with a turbulent fluid is investigated. Functional plates have been considered due to their high thermal resistance to residual stresses. The geometry of the problem is that one side of the reservoir in which the fluid is placed is covered with a plate of Functionally Graded Material (FGM). In order to approximate the displacement of the plate, assuming the third-order theory of shear deformation, trigonometric harmonic test functions are used, which determine the boundary conditions of the simple and fixed plate support. In the equations governing fluid oscillating behavior, the potential velocity of the fluid is obtained by determining the boundary conditions of the fluid in the form of February series functions. To achieve the natural frequency of the plate in contact with turbulent fluid and the shape of the vibrating mode, the Rayleigh-Ritz energy method is used based on the minimum potential energy. In order to check the accuracy of the method used, the results of analytical solution after solving the equations by coding in Wolfram Mathematica software have been compared with numerical solution of Abaqus software and then with accurate results in references, which shows the appropriate accuracy of the solution. Finally, the effect of volumetric coefficient parameters, volume ratio, length ratio, plate thickness ratio, fluid height, reservoir width and boundary conditions on the natural frequency of the plate in contact with turbulent fluid has been investigated and analyzed.