Segregated methods for two-fluid models

Journal of Fluids Engineering

et al. 2011

(1) Background. Bubbly flows are used in a wide variety of applications and require accurate modeling. In this paper, three modeling approaches are investigated using the geometrically simple configuration of a gas bubble strongly oscillating in a bubbly medium. (2) Method of approach. A coupled Eulerian-Lagrangian, a multicomponent compressible, and an analytical approach are compared for different void fractions. (3) Results. While the homogeneous mixture models (analytical and multicomponent) compare well with each other, the Eulerian-Lagrangian model captures additional features and inhomogeneities. The discrete bubbles appear to introduce localized perturbations in the void fraction and the pressure distributions not captured by homogeneous mixture models. (4) Conclusions. The bubbly mixture impedes the growth and collapse of the primary bubble while wavy patterns in the velocity, pressure, and void fraction fields propagate in space and time.

Section: Introductionmentioning

confidence: 99%

Study of Pressure Wave Propagation in a Two-Phase Bubbly Mixture

Raju

Singh

Journal of Fluids Engineering

et al. 2011

“…Fully resolved methods such as Direct Numerical Simulation (DNS) or the Boundary Element Method (BEM) can provide, within their limiting assumptions, details at several scales of interests with impressive progress reported [e.g., 11,[13][14][15], but are limited to detail problems and not applications due to high computational cost. In practical engineering applications, cavitating bubbly flows are usually modeled using one of several approaches: equivalent homogeneous continuum models [3,7,16], Eulerian two-fluid models [17][18][19][20], or Eulerian-Lagrangian approaches wherein the bubbles are treated as discrete elements. The former two are based on volume or ensemble averaged approximations thus suitable for cases where the bubbles are much smaller than the characteristic lengths associated with the overall dynamics of the bubbly mixture.…”

Section: Introductionmentioning

confidence: 99%

Shared-Memory Parallelization for Two-Way Coupled Euler-Lagrange Modeling of Bubbly Flows

Volume 1D, Symposia: Transport Phenomena in Mixing; Turbulent Flows; Urban Fluid Mechanics; Fluid Dynamic Behavior of Complex P

Chahine

2014

Cavitating bubbly flows are encountered in many engineering problems involving propellers, pumps, valves, ultrasonic biomedical applications, … etc. In this contribution an OpenMP parallelized Euler-Lagrange model of two-phase flow problems and cavitation is presented. The two-phase medium is treated as a continuum and solved on an Eulerian grid, while the discrete bubbles are tracked in a Lagrangian fashion with their dynamics computed. The intimate coupling between the two description levels is realized through the local void fraction, which is computed from the instantaneous bubble volumes and locations, and provides the continuum properties. Since, in practice, any such flows will involve large numbers of bubbles, schemes for significant speedup are needed to reduce computation times. We present here a shared-memory parallelization scheme combining domain decomposition for the continuum domain and number decomposition for the bubbles; both selected to realize maximum speed up and good load balance. The Eulerian computational domain is subdivided based on geometry into several subdomains, while for the Lagrangian computations, the bubbles are subdivided based on their indices into several subsets. The number of fluid subdomains and bubble subsets are matched with the number of CPU cores available in a share-memory system. Computation of the continuum solution and the bubble dynamics proceeds sequentially. During each computation time step, all selected OpenMP threads are first used to evolve the fluid solution, with each handling one subdomain. Upon completion, the OpenMP threads selected for the Lagrangian solution are then used to execute the bubble computations. All data exchanges are executed through the shared memory. Extra steps are taken to localize the memory access pattern to minimize non-local data fetch latency, since severe performance penalty may occur on a Non-Uniform Memory Architecture multiprocessing system where thread access to non-local memory is much slower than to local memory. This parallelization scheme is illustrated on a typical non-uniform bubbly flow problem, cloud bubble dynamics near a rigid wall driven by an imposed pressure function.

“…Homogeneous models are useful for low void fractions, whereas Eulerian-Lagrangian approaches are more appropriate for higher void fractions [9][10][11][12][13][14][15][16][17][18][19]. In particular, the recent work by Raju et al [20] has examined a continuum homogeneous model [21], an Eulerian multi-component model [22,23], and an Eulerian-Lagrangian model by simulating a cloud of small bubbles interacting with a large bubble oscillating in a viscous liquid.…”

Section: Introductionmentioning

confidence: 99%

Euler-Lagrange Simulations of Bubble Cloud Dynamics Near a Wall

Volume 7A: Fluids Engineering Systems and Technologies

Chahine

2013

We present in this paper a two-way coupled Eulerian-Lagrangian model to study the dynamics of microbubble clouds exposed to incoming pressure waves and the resulting pressure loads on a nearby rigid wall. The model simulates the two-phase medium as a continuum and solves the N-S equations using Eulerian grids with a time and space varying density. The microbubbles are modeled as interacting spherical bubbles, which follow a modified Rayleigh-Plesset-Keller-Herring equation and are tracked in a Lagrangian fashion. A two-way coupling between the Euler and Lagrange components is realized through the local mixture density associated with the bubbles volume change and motion. Using this numerical framework, simulations involving a large number of bubbles were conducted under driving pressures of different frequencies. The results show that the frequency of the driving pressure is critical in determining the overall dynamics: either a collective strongly coupled cluster behavior or non-synchronized weaker multiple bubble oscillations. The former creates extremely high pressures with peak values orders of magnitudes higher than that of the excitation pressures. This occurs when the driving frequency matches the natural frequency of the bubble cloud. The initial distance between the bubble cloud and the wall is also critical on the resulting pressure loads. A bubble cloud collapsing very close to the wall exhibits a cascading collapse with the bubbles farthest from the wall collapsing first and the nearest ones collapsing last, thus the energy accumulates and then results in very violent pressure peaks at the wall. Farther from the wall, the bubble cloud collapses quasi spherically with the cloud center collapsing last.