Stochastic models for capturing dispersion in particle-laden flows

Lattanzi, Aaron M.; Tavanashad, Vahid; Subramaniam, Shankar; Capecelatro, Jesse

doi:10.1017/jfm.2020.625

Cited by 28 publications

(16 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Treating the hydrodynamic force as a stochastic variable offers some potential advantages over the classical BBO treatment of modeling each force contribution separately. Rather than attempting to tease out how each pair-wise neighbor interaction contributes to the hydrodynamic force on a given particle, Lattanzi et al (2020) demonstrated that the statistics obtained from treating the force as a stochastic variable are reconcilable with PR-DNS.…”

Section: Summary Pointsmentioning

confidence: 99%

Modeling high-speed gas-particle flows relevant to spacecraft landings: A review and perspectives

Capecelatro

2021

Preprint

Self Cite

View full text Add to dashboard Cite

The interactions between rocket exhaust plumes and the surface of extraterrestrial bodies during spacecraft landings involve complex multiphase flow dynamics that pose significant risk to space exploration missions. The two-phase flow is characterized by high Reynolds and Mach number conditions with particle concentrations ranging from dilute to close-packing. Low atmospheric pressure and gravity typically encountered in landing environments combined with reduced optical access by the granular material pose significant challenges for experimental investigations. Consequently, numerical modeling is expected to play an increasingly important role for future missions. This article presents a review and perspectives on modeling high-speed disperse two-phase flows relevant to plume-surface interactions (PSI). We present an overview of existing drag laws, with origins from 18th-century cannon fire experiments and new insights from particle-resolved numerical simulations. While the focus here is on multiphase flows relevant to PSI, much of the same physics are shared by other compressible gas-particle flows, such as coal-dust explosions, volcanic eruptions, and detonation of solid material.

show abstract

Section: Summary Pointsmentioning

confidence: 99%

Modeling high-speed gas-particle flows relevant to spacecraft landings: A review and perspectives

Capecelatro

2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The force Langevin (FL) theory examined by Lattanzi et al [19] is employed here to describe the neighbor-induced fluctuating drag force…”

Section: Force Langevin Frameworkmentioning

confidence: 99%

“…where τ F is the integral time scale of the fluctuating drag force, σ F is the standard deviation of the fluctuating drag force, and dW t is a Wiener process increment. We refer the interested reader to Lattanzi et al [19] where a detailed discussion regarding motivation for, and results from, the OU process are provided. Here, we briefly emphasize that the steady solution to the OU process is a normal distribution N [0, σ F ] and a multitude of PR-DNS studies have reported normally distributed drag forces 10,12,13,18].…”

Section: Force Langevin Frameworkmentioning

confidence: 99%

“…Therefore, neglecting higher-order drag statistics, resulting from neighbor-effects, can detrimentally impact EL predictions for higher-order particle statistics (velocity variance and dispersion) [9]. To-date, few drag models have been proposed that account for neighborinduced disturbances; which may be broadly grouped into deterministic [15][16][17] and stochastic approaches [8,18,19]. In the former, the drag force experienced by a given particle is directly mapped to its pairwise neighbor interactions, requiring that the relative position of each particle be known when computing the drag force.…”

Section: Introductionmentioning

confidence: 99%

“…Here, a statistical approach is employed to account for neighbor-induced drag fluctuations. Specifically, we follow the mathematical theory derived by Lattanzi et al [19] for a hierarchy of Langevin equations and employ a stochastic drag force treatment. The interested reader is referred to the cited work for a more inclusive discussion on what the force Langevin (FL) framework yields in terms of particle-phase moments.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A stochastic model for the hydrodynamic force in Euler--Lagrange simulations of particle-laden flows

Lattanzi¹,

Tavanashad²,

Subramaniam³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Standard Eulerian-Lagrangian (EL) methods generally employ drag force models that only represent the mean hydrodynamic force acting upon a particle-laden suspension. Consequently, higherorder drag force statistics, arising from neighbor-induced flow perturbations, are not accounted for; with implications on predictions for particle velocity variance and dispersion. We develop a force Langevin (FL) model that treats neighbor-induced drag fluctuations as a stochastic force within an EL framework. The stochastic drag force follows an Ornstein-Uhlenbeck process and requires closure of the integral time scale for the fluctuating hydrodynamic force and the standard deviation in drag. The former is closed using the mean-free time between successive collisions, derived from the kinetic theory of non-uniform gases. For the latter, particle-resolved direct numerical simulation (PR-DNS) of fixed particle assemblies is utilized to develop a correlation. The stochastic EL framework specifies unresolved drag force statistics, leading to the correct evolution and sustainment of particle velocity variance over a wide range of Reynolds numbers and solids volume fractions when compared to PR-DNS of freely-evolving homogeneous suspensions. By contrast, standard EL infers drag statistics from variations in the resolved flow and thus under-predicts the growth and steady particle velocity variance in homogeneous suspensions. Velocity statistics from standard EL approaches are found to depend on the bandwidth of the projection function used for two-way momentum coupling, while results obtained from the stochastic EL approach are insensitive to the projection bandwidth.

show abstract