William H. Cabot

Bio: William H. Cabot is an academic researcher from Lawrence Livermore National Laboratory. The author has contributed to research in topics: Direct numerical simulation & Turbulence. The author has an hindex of 16, co-authored 24 publications receiving 3137 citations. Previous affiliations of William H. Cabot include Stanford University.

A dynamic subgrid‐scale model for compressible turbulence and scalar transport

Abstract: The dynamic subgrid-scale (SGS) model of Germano et al. (1991) is generalized for the large eddy simulation (LES) of compressible flows and transport of a scalar. The model was applied to the LES of decaying isotropic turbulence, and the results are in excellent agreement with experimental data and direct numerical simulations. The expression for the SGS turbulent Prandtl number was evaluated using direct numerical simulation (DNS) data in isotropic turbulence, homogeneous shear flow, and turbulent channel flow. The qualitative behavior of the model for turbulent Prandtl number and its dependence on molecular Prandtl number, direction of scalar gradient, and distance from the wall are in accordance with the total turbulent Prandtl number from the DNS data.

Reynolds number effects on Rayleigh–Taylor instability with possible implications for type Ia supernovae

Abstract: Spontaneous mixing of fluids at unstably stratified interfaces occurs in a wide variety of atmospheric, oceanic, geophysical and astrophysical flows. The Rayleigh–Taylor instability, a process by which fluids seek to reduce their combined potential energy, plays a key role in all types of fusion. Despite decades of investigation, fundamental questions regarding turbulent Rayleigh–Taylor flow persist, namely: does the flow forget its initial conditions, is the flow self-similar, what is the scaling constant, and how does mixing influence the growth rate? Here, we show results from a large direct numerical simulation addressing such questions. The simulated flow reaches a Reynolds number of 32,000, far exceeding that of all previous Rayleigh–Taylor simulations. We find that the scaling constant cannot be found by fitting a curve to the width of the mixing layer (as is common practice) but can be obtained by recourse to the similarity equation for the expansion rate of the turbulent region. Moreover, the ratio of kinetic energy to released potential energy is not constant, but exhibits a weak Reynolds number dependence, which might have profound consequences for flame propagation models in type Ia supernova simulations.

The mixing transition in Rayleigh-Taylor instability

Abstract: A large-eddy simulation technique is described for computing Rayleigh-Taylor instability. The method is based on high-wavenumber-preserving subgrid-scale models, combined with high-resolution numerical methods. The technique is verified to match linear stability theory and validated against direct numerical simulation data. The method is used to simulate Rayleigh-Taylor instability at a grid resolution of 1152 3 . The growth rate is found to depend on the mixing rate. A mixing transition is observed in the flow, during which an inertial range begins to form in the velocity spectrum and the rate of growth of the mixing zone is temporarily reduced. By measuring growth of the layer in units of dominant initial wavelength, criteria are established for reaching the hypothetical self-similar state of the mixing layer. A relation is obtained between the rate of growth of the mixing layer and the net mass flux through the plane associated with the initial location of the interface. A mix-dependent Atwood number is defined, which correlates well with the entrainment rate, suggesting that internal mixing reduces the layer's growth rate

A proposed modification of the Germano subgrid‐scale closure method

Abstract: The subgrid‐scale closure method developed by Germano et al. is modified by use of a least squares technique to minimize the difference between the closure assumption and the resolved stresses. This modification removes a source of singularity and is believed to improve the method’s applicability.

Subgrid-scale stress modelling based on the square of the velocity gradient tensor

Abstract: A new subgrid scale model is proposed for Large Eddy Simulations in complex geometries. This model which is based on the square of the velocity gradient tensor accounts for the effects of both the strain and the rotation rate of the smallest resolved turbulent fluctuations. Moreover it recovers the proper y 3 near-wall scaling for the eddy viscosity without requiring dynamic procedure. It is also shown from a periodic turbulent pipe flow computation that the model can handle transition.

Boundary Layer Theory

Abstract: The boundary layer equations for plane, incompressible, and steady flow are $$\matrix{ {u{{\partial u} \over {\partial x}} + v{{\partial u} \over {\partial y}} = - {1 \over \varrho }{{\partial p} \over {\partial x}} + v{{{\partial ^2}u} \over {\partial {y^2}}},} \cr {0 = {{\partial p} \over {\partial y}},} \cr {{{\partial u} \over {\partial x}} + {{\partial v} \over {\partial y}} = 0.} \cr }$$

Scale-Invariance and Turbulence Models for Large-Eddy Simulation

Abstract: ▪ Abstract Relationships between small and large scales of motion in turbulent flows are of much interest in large-eddy simulation of turbulence, in which small scales are not explicitly resolved and must be modeled. This paper reviews models that are based on scale-invariance properties of high-Reynolds-number turbulence in the inertial range. The review starts with the Smagorinsky model, but the focus is on dynamic and similarity subgrid models and on evaluating how well these models reproduce the true impact of the small scales on large-scale physics and how they perform in numerical simulations. Various criteria to evaluate the model performance are discussed, including the so-called a posteriori and a priori studies based on direct numerical simulation and experimental data. Issues are addressed mainly in the context of canonical, incompressible flows, but extensions to scalar-transport, compressible, and reacting flows are also mentioned. Other recent modeling approaches are briefly introduced.