Flow Snapshots Research Articles

Thermal performance of two-phase reciprocating anti-gravity closed thermosyphon

Thermal performances of two-phase reciprocating anti-gravity closed thermosyphons of 50% volumetric filling ratio (FR) with/without vacuum are comparatively examined. With different reciprocating frequencies (f) tested; a series of flow snapshots are collected to illustrate the f-dependent temporal variations of flow structures in the reciprocating thermosyphons (RT). At the critical f (fcr), the liquid pool in each thermosyphon sways and then starts surging upward to the top-wall under which the confluent hot stream injects downward into the cool liquid pool to facilitate heat exchanges. Acting together by the additional drags in the shaking liquid due to drifts of immersed air bubbles and the increased air/vapor partial pressures attributing from the heated non-condensable air in evaporator of the RT without vacuum, the fcr is raised from the vacuumed RT counterpart. Further f increases to enrich the momentums of liquid streams, the surges of up-lash streams are advanced to counteract/merge with the down-splashing stream which bounce off the liquid pool repetitively. The responsive time-mean local and averaged Nusselt numbers (Nu) along the evaporator/condenser centerlines are measured at f=1.67, 1.83, 1.92 and 2Hz with sixteen sets of heating/cooling duties at each f tested. Thermal performances in the RT are dominated by reciprocation number (Reci) and subject to the interdependent impacts by the heating/cooling duties. With the vacuumed RT, the phase change activities elevate Nu from the non-vacuumed counterparts; whereas the Nu levels are increased by increasing Reci, boiling number (Bo) and dimensionless thermal resistance of condenser (Rth,con). Thermal resistance properties for present RTs with/without vacuum are examined at various Reci, Bo and Rth,con with the heat transfer correlations devised to evaluate the averaged Nu over the evaporator section of present vacuumed RT.

Dynamic mode decomposition for non-uniformly sampled data

We propose an original approach to estimate dynamic mode decomposition (DMD) modes from non-uniformly sampled data. The proposed strategy processes a time-resolved sequence of flow snapshots in three steps. First, a reduced-order modeling of the non-missing data is made by proper orthogonal decomposition to obtain a low-order description of the state space. Second, the missing data are determined with maximum likelihood by coupling a linear dynamical state-space model with the Expectation-Maximization algorithm. Third, the DMD modes are finally estimated on the reconstructed data with a multiple linear regression method called orthonormalized partial least squares regression. This methodology is assessed for the flow past a NACA0012 airfoil at 20° of angle of attack and a Reynolds number of 103. The flow measurements are obtained with time-resolved particle image velocimetry and artificially subsampled at different ratios of missing data. The results show that the proposed method can reproduce the dominant DMD modes and the main structures of the flow fields for 50 and 75 % of missing data.

Cluster-based reduced-order modelling of a mixing layer

AbstractWe propose a novel cluster-based reduced-order modelling (CROM) strategy for unsteady flows. CROM combines the cluster analysis pioneered in Gunzburger’s group (Burkardt, Gunzburger & Lee,Comput. Meth. Appl. Mech. Engng, vol. 196, 2006a, pp. 337–355) and transition matrix models introduced in fluid dynamics in Eckhardt’s group (Schneider, Eckhardt & Vollmer,Phys. Rev. E, vol. 75, 2007, art. 066313). CROM constitutes a potential alternative to POD models and generalises the Ulam–Galerkin method classically used in dynamical systems to determine a finite-rank approximation of the Perron–Frobenius operator. The proposed strategy processes a time-resolved sequence of flow snapshots in two steps. First, the snapshot data are clustered into a small number of representative states, called centroids, in the state space. These centroids partition the state space in complementary non-overlapping regions (centroidal Voronoi cells). Departing from the standard algorithm, the probabilities of the clusters are determined, and the states are sorted by analysis of the transition matrix. Second, the transitions between the states are dynamically modelled using a Markov process. Physical mechanisms are then distilled by a refined analysis of the Markov process, e.g. using finite-time Lyapunov exponent (FTLE) and entropic methods. This CROM framework is applied to the Lorenz attractor (as illustrative example), to velocity fields of the spatially evolving incompressible mixing layer and the three-dimensional turbulent wake of a bluff body. For these examples, CROM is shown to identify non-trivial quasi-attractors and transition processes in an unsupervised manner. CROM has numerous potential applications for the systematic identification of physical mechanisms of complex dynamics, for comparison of flow evolution models, for the identification of precursors to desirable and undesirable events, and for flow control applications exploiting nonlinear actuation dynamics.

Experimental and CPFD Numerical Study on Hopper Discharge

This study investigated the applicability of computational particle fluid dynamic (CPFD) numerical scheme for simulating flows in a 3-D hopper. A glass bead with a particle size distribution was used as the experimental material, which is characterized on the limit between group A and group B powder. The discharge of glass bead particles was simulated using the CPFD model. The flow snapshots and the solid discharge rates were successfully captured by the CPFD calculations and compared well with the experimental results. It therefore confirmed a good feasibility of CPFD method to simulate the complex flow in the 3-D hopper. Consequently, the snapshots as well as the concrete values of the solid volume fraction, particle and gas velocities, and pressure in the hopper were given by the CPFD model. Based on the simulation results and the hopper structure, three flow regions were divided and flow characteristics in these regions were analyzed. It shows dense-flow in the hopper region, dilute-flue in the transi...

Retraction notice to A hybrid CFD framework for fluidized bed ozonation reactors coupling interface tracking and discrete particle methods

highlights An IT-DP framework was successfully developed for the catalytic ozonation of phenol-like pollutants. The effect of physicochemical properties was investigated in terms of bubble diameter and detachment time profiles. The hybrid CFD model handled agreeably the influence of ozone velocity on multiphase flow patterns. graphical a bstract Interstitial flow snapshots of hydrodynamic flow patterns resulting from IT-DP simulations for bubble abstract In this work, a fluidized bed reactor was investigated theoretically and experimentally for the catalytic ozonation of phenol-like pollutants. First, an interface tracking sub-model dealing with the individual motion of ozone bubbles in the continuous phase, and a discrete particle sub-model accounting for the trajectories of the solid particles were embedded accordingly into a hybrid CFD framework. Second, the effect of physicochemical properties including the surface tension and fluid viscosity was thoroughly evaluated at different hydrodynamic flow regimes. Afterwards, the influence of ozone velocity was quan- tified both on the gas and liquid superficial velocities and on the detoxification efficiency of liquid pollu- tants. Here, the interface tracking-discrete particle hybrid model was found to slightly overestimate radial bubble velocities being almost negligible in the center region of the fluidized bed reactor. As the surface tension increased, the mineralization efficiency was considerably lower and became higher when low-viscosity conditions were used for the ozonation of organic pollutants. Finally, the morphological features of interstitial flow maps at different hydrodynamic and reactive catalytic ozonation conditions highlighted the occurrence of bubble plume-like structures which affected the overall decontamination efficiency of phenol-like pollutants within the gas-liquid-solid ozonation reactor.

Goal seeking in honeybees: matching of optic flow snapshots?

Visual landmarks guide humans and animals including insects to a goal location. Insects, with their miniature brains, have evolved a simple strategy to find their nests or profitable food sources; they approach a goal by finding a close match between the current view and a memorised retinotopic representation of the landmark constellation around the goal. Recent implementations of such a matching scheme use raw panoramic images ('image matching') and show that it is well suited to work on robots and even in natural environments. However, this matching scheme works only if relevant landmarks can be detected by their contrast and texture. Therefore, we tested how honeybees perform in localising a goal if the landmarks can hardly be distinguished from the background by such cues. We recorded the honeybees' flight behaviour with high-speed cameras and compared the search behaviour with computer simulations. We show that honeybees are able to use landmarks that have the same contrast and texture as the background and suggest that the bees use relative motion cues between the landmark and the background. These cues are generated on the eyes when the bee moves in a characteristic way in the vicinity of the landmarks. This extraordinary navigation performance can be explained by a matching scheme that includes snapshots based on optic flow amplitudes ('optic flow matching'). This new matching scheme provides a robust strategy for navigation, as it depends primarily on the depth structure of the environment.

Low-dimensional dynamical systems for a wake-type shear flow with vortex dislocations

Low-dimensional systems are constructed to investigate dynamics of vortex dislocations in a wake-type shear flow. High-resolution direct numerical simulations are employed to obtain flow snapshots from which the most energetic modes are extracted using proper orthogonal decomposition (POD). The first 10 modes are classified into two groups. One represents the general characteristics of two-dimensional wake-type shear flow, and the other is related to the three-dimensional properties or non-uniform characteristics along the span. Vortex dislocations are generated by these two kinds of coherent structures. The results from the first 20 three-dimensional POD modes show that the low-dimensional systems have captured the basic properties of the wake-type shear flow with vortex dislocation, such as two incommensurable frequencies and their beat frequency.

DPIV-driven flow simulation: a new computational paradigm

We present a new approach to simulating unsteady fluid flows, with only very few degrees of freedom, by employing directly eigenmodes extracted from digital particle image velocimetry experimental data. In particular, we formulate standard Galerkin and nonlinear Galerkin approximations of the incompressible Navier–Stokes equations using hierarchical empirical eigenfunctions extracted from an ensemble of flow snapshots. We demonstrate that standard Galerkin approaches produce simulations capable of capturing the short–term dynamics of the flow, but nonlinear Galerkin projections are more effective in capturing both the short– and long–term dynamics, leading to bounded solutions. These findings are documented by applying these approaches to flow past a stationary circular cylinder at Reynolds number 610.

A low-dimensional model for simulating three-dimensional cylinder flow

We investigate the stability and dynamics of three-dimensional limit-cycle states in flow past a circular cylinder using low-dimensional modelling. High-resolution direct numerical simulations are employed to obtain flow snapshots from which the most energetic modes are extracted using proper orthogonal decomposition. We show that the limit cycle is reproduced very accurately with only twenty three-dimensional modes. The addition of two-dimensional modes to the Karhunen–Loeve expansion basis improves the ability of the model to capture the three-dimensional bifurcation, including the discontinuity in the Strouhal number discovered experimentally.