A novel forcing technique to simulate turbulent mixing in a decaying scalar field

2016

Physics of Fluids

The isotropy of the smallest turbulent scales is investigated in premixed turbulent combustion by analyzing the vorticity vector in a series of high Karlovitz number premixed flame direct numerical simulations. It is found that increasing the Karlovitz number and the ratio of the integral length scale to the flame thickness both reduce the level of anisotropy. By analyzing the vorticity transport equation, it is determined that the vortex stretching term is primarily responsible for the development of any anisotropy. The local dynamics of the vortex stretching term and vorticity resemble that of homogeneous isotropic turbulence to a greater extent at higher Karlovitz numbers. This results in small scale isotropy at sufficiently high Karlovitz numbers and supports a fundamental similarity of the behavior of the smallest turbulent scales throughout the flame and in homogeneous isotropic turbulence. At lower Karlovitz numbers, the vortex stretching term and the vorticity alignment in the strain-rate tensor eigenframe are altered by the flame. The integral length scale has minimal impact on these local dynamics but promotes the effects of the flame to be equal in all directions. The resulting isotropy in vorticity does not reflect a fundamental similarity between the smallest turbulent scales in the flame and in homogeneous isotropic turbulence. Published by AIP Publishing. [http://dx

Section: High Karlovitz Number Casementioning

confidence: 89%

Vorticity isotropy in high Karlovitz number premixed flames

Bobbitt

2016

Physics of Fluids

“…In this work, the source of anisotropy in the scalar field is eliminated by adopting a scalar field forcing method that has no preferred direction or directional dependence. This forcing method, termed the linear scalar forcing method [26], does not assume any particular scalar field distribution, nor does it enforce one. It simply preserves the (isotropic or non-isotropic) character of the scalar field.…”

Section: Scalar Field Forcingmentioning

confidence: 99%

A new framework for simulating forced homogeneous buoyant turbulent flows

Carroll

Theor. Comput. Fluid Dyn.

2015

Self Cite

This work proposes a new simulation methodology to study variable density turbulent buoyant flows. The mathematical framework, referred to as homogeneous buoyant turbulence, relies on a triply periodic domain and incorporates numerical forcing methods commonly used in simulation studies of homogeneous, isotropic flows. In order to separate the effects due to buoyancy from those due to large-scale gradients, the linear scalar forcing technique is used to maintain the scalar variance at a constant value. Two sources of kinetic energy production are considered in the momentum equation, namely shear via an isotropic forcing term and buoyancy via the gravity term. The simulation framework is designed such that the four dimensionless parameters of importance in buoyant mixing, namely the Reynolds, Richardson, Atwood, and Schmidt numbers, can be independently varied and controlled. The framework is used to interrogate fully non-buoyant, fully buoyant, and partially buoyant turbulent flows. The results show that the statistics of the scalar fields (mixture fraction and density) are not influenced by the energy production mechanism (shear vs. buoyancy). On the other hand, the velocity field exhibits anisotropy, namely a larger variance in the direction of gravity which is associated with a statistical dependence of the velocity component on the local fluid density.

“…III C and V were computed for a scalar field forced by imposing a mean scalar gradient (MSG) [15]. Identical computations were carried out for a scalar field mimicking the dynamics of decaying scalar fluctuations (linear scalar forcing [16]). The alignment trends observed were identical in both cases (Table III), even though the means of sustaining small scale fluctuations, and consequently, the scalar variance spectra, have been seen to differ at high Schmidt numbers [16].…”

Section: B Effect Of Scalar Forcingmentioning

confidence: 99%

“…The velocity field was forced by injecting energy in a low-wave-number shell [14]. Two distinct scalar-forcing techniques were used, one characterized by the presence of a mean scalar gradient (MSG) [15] and the other simulating the decay of scalar fluctuations (linear scalar forcing, LS) [16]. The use of the two scalar-forcing methods allows us to investigate differences in τ φ alignment that might be related to distinct scalar variance cascade mechanisms (forced vs decaying) at the small length scales.…”

Section: Simulation Detailsmentioning

confidence: 99%

“…Identical computations were carried out for a scalar field mimicking the dynamics of decaying scalar fluctuations (linear scalar forcing [16]). The alignment trends observed were identical in both cases (Table III), even though the means of sustaining small scale fluctuations, and consequently, the scalar variance spectra, have been seen to differ at high Schmidt numbers [16]. The indifference of τ φ orientation to the forcing method is reminiscent of the Schmidt number and filter-width independence observed in Sec.…”

Section: B Effect Of Scalar Forcingmentioning

confidence: 99%

See 1 more Smart Citation

Subfilter scalar-flux vector orientation in homogeneous isotropic turbulence

Verma

2014

Phys. Rev. E

Self Cite

The geometric orientation of the subfilter-scale scalar-flux vector is examined in homogeneous isotropic turbulence. Vector orientation is determined using the eigenframe of the resolved strain-rate tensor. The Schmidt number is kept sufficiently large so as to leave the velocity field, and hence the strain-rate tensor, unaltered by filtering in the viscous-convective subrange. Strong preferential alignment is observed for the case of Gaussian and box filters, whereas the sharp-spectral filter leads to close to a random orientation. The orientation angle obtained with the Gaussian and box filters is largely independent of the filter width and the Schmidt number. It is shown that the alignment direction observed numerically using these two filters is predicted very well by the tensor-diffusivity model. Moreover, preferred alignment of the scalar gradient vector in the eigenframe is shown to mitigate any probable issues of negative diffusivity in the tensor-diffusivity model. Consequentially, the model might not suffer from solution instability when used for large eddy simulations of scalar transport in homogeneous isotropic turbulence. Further a priori tests indicate poor alignment of the Smagorinsky and stretched vortex model predictions with the exact subfilter flux. Finally, strong filter dependence of subfilter scalar-flux orientation suggests that explicit filtering may be preferable to implicit filtering in large eddy simulations.