Evaluating convective parameterization closures using cloud‐resolving model simulation of tropical deep convection
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In this research, a near-wall second-order closure based on the Speziable et al.(1991) or SSG model for the pressure-strain term is proposed. Unlike the LRR model, the SSG model is quasi-nonlinear and yields better results when applied to calculate rotating homogeneous turbulent flows. An asymptotic analysis near the wall is applied to both the exact and modeled, equations so that appropriate near-wall corrections to the SSG model and the modeled dissipation-rate equation can be derived to satisfy the physical wall boundary conditions as well as the asymptotic near-wall behavior of the exact equations. Two additional model constants are introduced and they are determined by calibrating against one set of near-wall channel flow data. Once determined, their values are found to remain constant irrespective of the type of flow examined. The resultant model is used to calculate simple turbulent flows, near separating turbulent flows, complex turbulent flows and compressible turbulent flows with a freestream Mach number as high as 10. In all the flow cases investigated, the calculated results are in good agreement with data. This new near-wall model is less ad hoc, physically and mathematically more sound and eliminates the empiricism introduced by Zhang. Therefore, it is quite general, as demonstrated by the good agreement achieved with measurements covering a wide range of Reynolds numbers and Mach numbers.
Numerical methods were developed that will form the computational part of the turbulence closure scheme. A wave model was developed for the two-dimensional shear layer. This configuration is being used as a test case for the closure schemes. Various numerical schemes were examined to give efficient solutions of the Rayleigh equation for this geometry. These include both spectral and finite difference methods. Secondly, numerical methods are under development to solve the non-separable Rayleigh equation. This solution is required for the closure scheme in more complex geometries. A model problem was used to assist in the algorithm development. Two-dimensional spectral methods and a hybrid spectral/finite difference technique were developed. An analytic solution of the Rayleigh equation for a basic elliptic flow was obtained. This will be used to verify the stability codes developed for arbitrary geometries. Other numerical methods for solving the Rayleigh equation based on the boundary element technique were also examined. These solutions are forming the basis of a model for the shock structure in jets of arbitrary geometry.
The derivation of Reynolds-stress models for viscous incompressible turbulent flow on the basis of the Navier-Stokes and continuity equations is explored in an analytical review. The formulation of the basic equations is outlined, and particular attention is given to zero-equation and one-equation models based on eddy viscosity, two-equation (k-l, k-epsilon, and k-omega) models, and second-order closure models. The superior performance of the second-order models is demonstrated by numerical results for (1) the return to isotropy from anisotropic homogeneous turbulence, (2) homogeneous turbulent shear flow in a rotating frame, (3) and fully developed inhomogeneous turbulent channel flow in a rotating frame. The inherent limitations of the Reynolds-stress approach and areas for further improvement are discussed.
The elliptic relaxation model of Durbin (1993) for modeling near-wall turbulence using second moment closures (SMC) is compared to DNS data for a channel flow at Re(sub t) = 395. The agreement for second order statistics and even the terms in their balance equation is quite satisfactory, confirming that very little viscous effects (via Kolmogoroff scales) need to be added to the high Reynolds versions of SMC for near-wall-turbulence. The essential near-wall feature is thus the kinematic blocking effect that a solid wall exerts on the turbulence through the fluctuating pressure, which is best modeled by an elliptic operator. Above the transition layer, the effect of the original elliptic operator decays rapidly, and it is suggested that the log-layer is better reproduced by adding a non-homogeneous reduction of the return to isotropy, the gradient of the turbulent length scale being used as a measure of the inhomogeneity of the log-layer. The elliptic operator was quite easily applied to the non-linear Craft & Launder pressure-strain model yielding an improved distinction between the spanwise and wall normal stresses, although at higher Reynolds number (Re) and away from the wall, the streamwise component is severely underpredicted, as well as the transition in the mean velocity from the log to the wake profiles. In this area a significant change of behavior was observed in the DNS pressure-strain term, entirely ignored in the models.
A second order closure turbulence model for compressible flows is developed and implemented in a 2D Reynolds-averaged Navier-Stokes solver. From the beginning where a kappa-epsilon turbulence model was implemented in the bidiagonal implicit method of MACCORMACK (referred to as the MAC3 code) to the final stage of implementing a full second order closure in the efficient line Gauss-Seidel algorithm, numerous work was done, individually and collectively. Besides the collaboration itself, the final product of this work is a second order closure derived from the Launder, Reece, and Rodi model to account for near wall effects, which has been called FRAME model, which stands for FRench-AMerican-Effort. During the reporting period, two different problems were worked out. The first was to provide Ames researchers with a reliable compressible boundary layer code including a wide collection of turbulence models for quick testing of new terms, both in two equations and in second order closure (LRR and FRAME). The second topic was to complete the implementation of the FRAME model in the MAC5 code. The work related to these two different contributions is reported. dilatation in presence of stron shocks. This work, which has been conducted during a work at the Center for Turbulence Research with Zeman aimed also to cros-check earlier assumptions by Rubesin and Vandromme.
The first objective is to evaluate current two-equation and second order closure turbulence models using available direct numerical simulations and experiments, and to identify the models which represent the state of the art in turbulence modeling. The second objective is to study the near-wall behavior of turbulence, and to develop reliable models for an engineering calculation of turbulence and transition. The third objective is to develop a two-scale model for compressible turbulence.
The abilities of cloud-resolving models (CRMs) with the double-Gaussian based and the single-Gaussian based third-order closures (TOCs) to simulate the shallow cumuli and their transition to deep convective clouds are compared in this study. The single-Gaussian based TOC is fully prognostic (FP), while the double-Gaussian based TOC is partially prognostic (PP). The latter only predicts three important third-order moments while the former predicts all the thirdorder moments. A shallow cumulus case is simulated by single-column versions of the FP and PP TOC models. The PP TOC improves the simulation of shallow cumulus greatly over the FP TOC by producing more realistic cloud structures. Large differences between the FP and PP TOC simulations appear in the cloud layer of the second- and third-order moments, which are related mainly to the underestimate of the cloud height in the FP TOC simulation. Sensitivity experiments and analysis of probability density functions (PDFs) used in the TOCs show that both the turbulence-scale condensation and higher-order moments are important to realistic simulations of the boundary-layer shallow cumuli. A shallow to deep convective cloud transition case is also simulated by the 2-D versions of the FP and PP TOC models. Both CRMs can capture the transition from the shallow cumuli to deep convective clouds. The PP simulations produce more and deeper shallow cumuli than the FP simulations, but the FP simulations produce larger and wider convective clouds than the PP simulations. The temporal evolutions of cloud and precipitation are closely related to the turbulent transport, the cold pool and the cloud-scale circulation. The large amount of turbulent mixing associated with the shallow cumuli slows down the increase of the convective available potential energy and inhibits the early transition to deep convective clouds in the PP simulation. When the deep convective clouds fully develop and the precipitation is produced, the cold pools produced by the evaporation of the precipitation are not favorable to the formation of shallow cumuli.
This dataset contains simple condensation mdoel output and CAM4 model output that were used to produce figures in the following paper: Wan, H., Woodward, C. S., Zhang, S., Vogl, C. J., Stinis, P., Gardner, D. J., Rasch, P. J., Zeng, X., Larson, V. E., and Singh, B. (2020): Improving time-step convergence in an atmosphere model with simplified physics: the impacts of closure assumption and process coupling, Journal of Advances in Modeling Earth Systems, https://doi.org/10.1029/2019MS001982
It is generally accepted that pressure dilatation, which is an additional compressibility term in turbulence transport equations, may be important for high speed flows. Recent direct simulations of homogeneous shear turbulence have given concrete evidence that the pressure dilatation is important insofar that it contributes to the reduced growth of turbulent kinetic energy due to compressibility effects. The problem of modeling pressure dilatation is addressed. A component of the pressure dilatation is isolated which exhibits temporal oscillations and, using direct numerical simulations of homogeneous shear turbulence and isotropic turbulence, show that it has a negligible contribution to the evolution of turbulent kinetic energy. Then, an analysis for the case of homogeneous turbulence is performed to obtain a model for the nonoscillatory pressure dilatation. This model algebraically relates the pressure dilatation to quantities traditionally obtained in incompressible turbulence closures. The model is validated by direct comparison with the pressure dilatation data obtained from the simulations.
A computer code has been developed for the calculation of three-dimensional turbulent flow in circular to rectangular transition ducts. The governing equations are written in a general curvilinear coordinate system so that all singly-connected geometrical configurations can be accommodated. Turbulence closure is through the standard k-epsilon model or a Reynolds stress closure model. Computed results show qualitative agreement with experimental data. Pressure-induced secondary flow is the dominant mode through the transition, but turbulence-induced secondary flow becomes prominent some distance downstream of the transition.
A simple model, parameterized by the Reynolds stress anisotropy, is proposed for the spectrum of weakly anisotropic turbulence. It contains a model constant that affects its region of realizability. This spectrum model is used to derive a one-point closure to the rapid pressure-strain term. The derived pressure-strain model is linear in the Reynolds stress anisotropy and is of the same form as the closure model of Launder et al. (1975). The spectrum model becomes unrealizable in some regions of wave space for sufficiently large anisotropy of the Reynolds stress, and this is used to infer the region of validity of the linear closure model. It is found that the extent of the valid region is very small when the model constant is set to match rapid distortion theory, and largest for a model-constant set close to the value suggested by LRR. However, even the largest valid domain does not extend very far from isotropy, suggesting inherent weakness in the linear pressure-strain models.
Simulations of simple compressible flows have been performed to enable the direct estimation of the pressure-dilatation correlation. The generally accepted belief that this correlation may be important in high-speed flows has been verified by the simulations. The pressure-dilatation correlation is theoretically investigated by considering the equation for fluctuating pressure in an arbitrary compressible flow. This leads to the isolation of a component of the pressure-dilatation that exhibits temporal oscillations on a fast time scale. Direct numerical simulations of homogeneous shear turbulence and isotropic turbulence show that this fast component has a negligible contribution to the evolution of turbulent kinetic energy. Then, an analysis for the case of homogeneous turbulence is performed to obtain a formal solution for the nonoscillatory pressure-dilatation. Simplifications lead to a model that algebraically relates the pressure-dilatation to quantities traditionally obtained in incompressible turbulence closures. The model is validated by direct comparison with the simulations.
Variable resolution methods have become frontline CFD tools, but in order to take full advantage of this promising new technology, more formal theoretical development is desirable. Two general classes of variable resolution methods can be identified: hybrid or zonal methods in which RANS and LES models are solved in different flow regions, and bridging or seamless models which interpolate smoothly between RANS and LES. This paper considers the formulation of bridging methods using methods of two-point closure theory. The fundamental problem is to derive a subgrid two-equation model. We compare and reconcile two different approaches to this goal: the Partially Integrated Transport Model, and the Partially Averaged Navier-Stokes method.
The integration of kinetic effects in fluid models is important for global simulations of Earth's magnetosphere. The use of the two-fluid ten-moment model, which includes the pressure tensor for both species, has had some success in simulating Ganymede and Mercury with a simple closure model. Here, we discuss a heat flux closure which accounts for some limitations of the earlier work while remaining computationally tractable. Comparisons with kinetic simulations for magnetic reconnection and lower-hybrid drift instabilities show good agreement with kinetic results and improvements on previous closure models.
A critical assessment is made of the closure coefficients used for turbulence length scale in existing models of the transport equation, with reference to the extension of these models to compressible flow. It is shown that to satisfy the compressible 'law of the wall', the model coefficients must actually be functions of density gradients. The magnitude of the errors that result from neglecting this dependence on density varies with the variable used to specify the length scale. Among the models investigated, the k-omega model yields the best performance, although it is not completely free from errors associated with density terms. Models designed to reduce the density-gradient effect to an insignificant level are proposed.
We report in regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three-dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi-fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi-fidelity model to employ low-fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization.
Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy ( LE ) and sensible heat ( H ) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R 2 = 0.81–0.94) and H (R 2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.