Low Mach number algorithm for droplet-laden turbulent channel flow including phase transition

Bukhvostova, A; Kuerten, Johannes G.M.; Geurts, Bernardus J.

doi:10.1016/j.jcp.2015.04.021

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…A drawback of the compressible formulation is the severe restriction on the time step if an explicit time-marching method is applied, since realistic Mach numbers are very small. This can be avoided by a low-Mach-number algorithm, which has been shown to yield results in very good agreement with the fully compressible formulation [20]. …”

Section: Dns With Point-particle Approachmentioning

confidence: 99%

Point-Particle DNS and LES of Particle-Laden Turbulent flow - a state-of-the-art review

Kuerten

2016

Flow Turbulence Combust

154

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Particle-laden or droplet-laden turbulent flows occur in many industrial applications and in natural phenomena. Knowledge about the properties of these flows can help to improve the design of unit operations in industry and to predict for instance the occurrence of rain showers. This knowledge can be obtained from experimental research and from numerical simulations. In this paper a review is given of numerical simulation methods for particle-laden flows. There are various simulation methods possible. They range from methods in which all details, including the flow around each particle, are resolved, via point-particle methods, in which for each particle an equation of motion is solved, to Eulerian methods in which equations for particle concentration and velocity are solved. This review puts the emphasis on the intermediate class of methods, the Euler-Lagrange methods in which the continuous phase is described by an Eulerian approach and the dispersed phase in a Lagrangian way with equations of motion for each individual particle.

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Section: Dns With Point-particle Approachmentioning

confidence: 99%

Point-Particle DNS and LES of Particle-Laden Turbulent flow - a state-of-the-art review

Kuerten

2016

Flow Turbulence Combust

154

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“…It employs a perturbation expansion procedure to obtain asymptotic forms of the compressible flow equations using the Mach number to the first [25] or second [47] powers as a small parameter. They are used to this day for complex problems [11] and extensive reviews exist in the literature [49], but these methodologies apply only to low Mach number flows. They are not an arbitrary Mach compressible flow solver such as pressure-based methods.…”

Section: Introductionmentioning

confidence: 99%

Low Mach preconditioned density-based methods with implicit Runge–Kutta schemes in physical-time

Alves

Santos

Falcão³

2021

J Braz. Soc. Mech. Sci. Eng.

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As far as the authors are aware, low Mach preconditioned density-based methods found in the peer-reviewed literature only employ multi-step schemes for physical-time integration. This essentially limits the maximum achievable temporal accuracyorder of these methods to two, since the multi-step schemes of order higher than two are conditionally stable. However, the present paper shows how these methods can employ multi-stage schemes in physical-time using the same low Mach preconditioning techniques developed over the past few decades. In doing so, it opens up the rich field of Runge-Kutta time integration schemes to low Mach preconditioned density-based methods. One and two-dimensional test cases are used to demonstrate the capabilities of this novel approach. The former simulates the propagation of marginally stable entropy perturbations superposed on a uniform flow whereas the latter simulates the temporal growth of vorticity perturbations superposed on an absolutely unstable planar mixing-layer. A novel procedure is employed to generate highly accurate initial conditions for the two-dimensional test case, it minimizes receptivity regions as well as deleterious interactions with artificial boundary conditions due to the numerical error introduced by approximate initial conditions. These test cases show that second, third and fourth order multi-stage schemes with strong linear numerical stability can be successfully utilized for the physical-time integration of low Mach preconditioned density-based methods.

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Evaporation Dynamics in Dilute Turbulent Jet Sprays

Barba

Picano

2019

Direct and Large-Eddy Simulation XI

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Low Mach number algorithm for droplet-laden turbulent channel flow including phase transition

Cited by 4 publications

References 24 publications

Point-Particle DNS and LES of Particle-Laden Turbulent flow - a state-of-the-art review

Point-Particle DNS and LES of Particle-Laden Turbulent flow - a state-of-the-art review

Low Mach preconditioned density-based methods with implicit Runge–Kutta schemes in physical-time

Evaporation Dynamics in Dilute Turbulent Jet Sprays

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