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At least 487 records · Page 27

Reynolds stress closure in jet flows using wave models

A collection of papers is presented. The outline of this report is as follows. Chapter three contains a description of a weakly nonlinear turbulence model that was developed. An essential part of the application of such a closure scheme to general geometry jets is the solution of the local hydrodynamic stability equation for a given jet cross-section. Chapter four describes the conformal mapping schemes used to map such geometries onto a simple computational domain. Chapter five describes a solution of a stability problem for circular, elliptic, and rectangular geometries. In chapter six linear models for the shock shell structure in non-circular jets is given. The appendices contain reprints of papers also published during this study including the following topics: (1) instability of elliptic jets; (2) a technique for predicting the shock cell structure in non-circular jets using a vortex sheet model; and (3) the resonant interaction between twin supersonic jets.

Morris, Philip J.↗

Reynolds stress closure in jet flows using wave models

A wave model was developed for the two dimensional shear layer. This configuration is being used as a test case for the closure schemes. Numerical methods are under development to solve the nonseparable Rayleigh equation. A model problem is being used to assist in the algorithm development. 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 are being examined.

Morris, P. J.↗

Machine-learned closure of URANS for stably stratified turbulence: connecting physical timescales & data hyperparameters of deep time-series models

Stably stratified turbulence (SST), a model that is representative of the turbulence found in the oceans and atmosphere, is strongly affected by fine balances between forces and becomes more anisotropic in time for decaying scenarios. Moreover, there is a limited understanding of the physical phenomena described by some of the terms in the Unsteady Reynolds-Averaged Navier–Stokes (URANS) equations—used to numerically simulate approximate solutions for such turbulent flows. Rather than attempting to model each term in URANS separately, it is attractive to explore the capability of machine learning (ML) to model groups of terms, i.e. to directly model the force balances. We develop deep time-series ML for closure modeling of the URANS equations applied to SST. We consider decaying SST which are homogeneous and stably stratified by a uniform density gradient, enabling dimensionality reduction. We consider two time-series ML models: long short-term memory and neural ordinary differential equation. Both models perform accurately and are numerically stable in a posteriori (online) tests. Furthermore, we explore the data requirements of the time-series ML models by extracting physically relevant timescales of the complex system. We find that the ratio of the timescales of the minimum information required by the ML models to accurately capture the dynamics of the SST corresponds to the Reynolds number of the flow. The current framework provides the backbone to explore the capability of such models to capture the dynamics of high-dimensional complex dynamical system like SST flows.

97 MATHEMATICS AND COMPUTING↗

The Asymmetric Inner Disk of the Herbig Ae Star HD 163296 in the Eyes of VLTI/MATISSE: Evidence for a Vortex?

Context.A complex environment exists in the inner few astronomical units of planet-forming disks. High-angular-resolution observa-tions play a key role in our understanding of the disk structure and the dynamical processes at work.Aims.In this study we aim to characterize the mid-infrared brightness distribution of the inner disk of the young intermediate-massstar HD 163296 from early VLTI/MATISSE observations taken in theL- andN-bands. We put special emphasis on the detection ofpotential disk asymmetries.Methods.We use simple geometric models to fit the interferometric visibilities and closure phases. Our models include a smoothedring, a flat disk with an inner cavity, and a 2D Gaussian. The models can account for disk inclination and for azimuthal asymmetriesas well. We also perform numerical hydrodynamical simulations of the inner edge of the disk.Results.Our modeling reveals a significant brightness asymmetry in theL-band disk emission. The brightness maximum of the asym-metry is located at the NW part of the disk image, nearly at the position angle of the semimajor axis. The surface brightness ratio inthe azimuthal variation is3.5±0.2. Comparing our result on the location of the asymmetry with other interferometric measurements,we confirm that the morphology of ther<0.3au disk region is time-variable. We propose that this asymmetric structure, located in ornear the inner rim of the dusty disk, orbits the star. To find the physical origin of the asymmetry, we tested a hypothesis where a vortexis created by Rossby wave instability, and we find that a unique large-scale vortex may be compatible with our data. The half-lightradius of theL-band-emitting region is0.33±0.01au, the inclination is52◦+5◦−7◦, and the position angle is143◦±3◦. Our models predictthat a non-negligible fraction of theL-band disk emission originates inside the dust sublimation radius forμm-sized grains. Refractorygrains or large (&10μm-sized) grains could be the origin of this emission.N-band observations may also support a lack of smallsilicate grains in the innermost disk (r.0.6au), in agreement with our findings fromL-band data.

J Varga↗

Verification of Data-Driven Models of Physical Phenomena using Interpretable Approximation

Machine-learned models, specifically neural networks, are increasingly used as “closures” or “constitutive models” in engineering simulators to represent fine-scale physical phenomena that are too computationally expensive to resolve explicitly. However, these neural net models of unresolved physical phenomena tend to fail unpredictably and are therefore not used in mission-critical simulations. In this report, we describe new methods to authenticate them, i.e., to determine the (physical) information content of their training datasets, qualify the scenarios where they may be used and to verify that the neural net, as trained, adhere to physics theory. We demonstrate these methods with neural net closure of turbulent phenomena used in Reynolds Averaged Navier-Stokes equations. We show the types of turbulent physics extant in our training datasets, and, using a test flow of an impinging jet, identify the exact locations where the neural network would be extrapolating i.e., where it would be used outside the feature-space where it was trained. Using Generalized Linear Mixed Models, we also generate explanations of the neural net (à la Local Interpretable Model agnostic Explanations) at prototypes placed in the training data and compare them with approximate analytical models from turbulence theory. Finally, we verify our findings by reproducing them using two different methods.

42 ENGINEERING↗

Near-wall response in turbulent shear flows subjected to imposed unsteadiness

Rapid-distortion theory is adapted to introduce a truly unsteady closure into a simple phenomenological turbulence model in order to describe the unsteady response of a turbulent wall layer exposed to a temporarily oscillating pressure gradient. The closure model is built by taking the ratio of turbulent shear stress to turbulent kinetic energy to be a function of the effective strain. The latter accounts for the history of the flow. The computed unsteady velocity fluctuations and modulated turbulent stresses compare favorably in the 'non-quasi-steady' frequency range, where quasi-steady assumptions would fail. This suggests that the concept of rapid distortion is especially appropriate for unsteady flows. This paper forms the basis for acoustical studies of the problem to be reported elsewhere.

Mankbadi, Reda R.↗

On the coalescence-dispersion modeling of turbulent molecular mixing

The general coalescence-dispersion (C/D) closure provides phenomenological modeling of turbulent molecular mixing. The models of Curl and Dopazo and O'Brien appear as two limiting C/D models that bracket the range of results one can obtain by various models. This finding is used to investigate the sensitivtiy of the results to the choice of the model. Inert scalar mixing is found to be less model-sensitive than mixing accompanied by chemical reaction. Infinitely fast chemistry approximation is used to relate the C/D approach to Toor's earlier results. Pure mixing and infinite rate chemistry calculations are compared to study further a recent result of Hsieh and O'Brien who found that higher concentration moments are not sensitive to chemistry.

Givi, Peyman↗

Improving Time Step Convergence in an Atmosphere Model With Simplified Physics: The Impacts of Closure Assumption and Process Coupling

Convergence testing is a common practice in the development of dynamical cores of atmospheric models but is not as often exercised for the parameterization of sub-grid physics. An earlier study revealed that the stratiform cloud parameterizations in several predecessors of the Energy Exascale Earth System Model (E3SM) showed strong time-step sensitivity and slower-than-expected convergence when the model's time step was systematically refined. In this work, a simplified atmosphere model is configured that consists of the spectral-element dynamical core of the E3SM atmosphere model coupled with a large-scale condensation parameterization based on commonly used assumptions. This simplified model also resembles E3SM and its predecessors in the numerical implementation of process coupling and shows poor time-step convergence in short ensemble tests. We present a formal error analysis to reveal the expected time-step convergence rate and the conditions for obtaining such convergence. Numerical experiments are conducted to investigate the root causes of convergence problems. We show that revisions in the process coupling and closure assumption help to improve convergence in short simulations using the simplified model; the same revisions applied to a full atmosphere model lead to significant changes in the simulated long-term climate. This work demonstrates that causes of convergence issues in atmospheric simulations can be understood by combining analyses from physical and mathematical perspectives. Addressing convergence issues can help to obtain a discrete model that is more consistent with the intended representation of the physical phenomena.

54 ENVIRONMENTAL SCIENCES↗

Supersonic Aftbody Closure Wind-Tunnel Testing, Data Analysis, and Computational Results

This paper reports on the model, test, and results from the Langley Supersonic Aftbody Closure wind tunnel test. This project is an experimental evaluation of the 1.5% Technology Concept Aircraft (TCA) aftbody closure model (Model 23) in the Langley Unitary Plan Wind Tunnel. The baseline TCA design is the result of a multidisciplinary, multipoint optimization process and was developed using linear design and analysis methods, supplemented with Euler and Navier-Stokes numerical methods. After a thorough design review, it was decided to use an upswept blade attached to the forebody as the mounting system. Structural concerns dictated that a wingtip support system would not be feasible. Only the aftbody part of the model is metric. The metric break was chosen to be at the fuselage station where prior aft-sting supported models had been truncated. Model 23 is thus a modified version of Model 20. The wing strongback, flap parts, and nacelles from Model 20 were used, whereas new aftbodies, a common forebody, and some new tails were fabricated. In summary, significant differences in longitudinal and direction stability and control characteristics between the ABF and ABB aftbody geometries were measured. Correcting the experimental data obtained for the TCA configuration with the flared aftbody to the representative of the baseline TCA closed aftbody will result in a significant reduction in longitudinal stability, a moderate reduction in stabilizer effectiveness and directional stability, and a moderate to significant reduction in rudder effectiveness. These reductions in the stability and control effectiveness levels of the baseline TCA closed aftbody are attributed to the reduction in carry-over area.

Allen, Jerry↗

Validation of EDQNM for subgrid and supergrid models

From preliminary calculations it was concluded that the two-point Eddy Damping Quasi-Normal Markovian (EDQNM) closure accurately describes the behavior of second order moments. This closure can be applied as subgrid and supergrid models for Large Eddy Simulations at higher Reynolds numbers. In the case of homogeneous anisotropic turbulence, when the nonlinear terms are introduced the calculation becomes quite onerous but is still considerably less expensive than the calculation of a DS. The major merit of two-point closure models is that they can be easily applied to flows at Reynolds numbers that are unreachable by a DS. Work is in progress to derive expressions for the nonlinear terms that give good global conservation properties.

Orlandi, P.↗

SAM-ML: Integrating data-driven closure with nuclear system code SAM for improved modeling capability

Advanced reactors often involve complicated thermal-fluid (T-F) phenomena. Modeling such phenomena with the traditional one-dimensional (1-D) system code is a challenging task. The System Analysis Module (SAM), a modern nuclear system code, has developed a coarse mesh multi-dimensional (multi-D) flow model to capture the spatial effect of T-F phenomena in advanced reactors. As a coarse mesh solver, constitutive relations are required for SAM's multi-D model for unresolved fine-scale physics, such as turbulence. Here this work presents a novel approach that integrates neural networks as data-driven closure for SAM's multi-D flow model. The data-driven closure is trained with fine-resolution data to ensure its accuracy while maintaining a coarse mesh setup to ensure its efficiency and consistency with SAM. We demonstrate the applicability of this SAM-ML capability in an open volume thermal stratification problem, where a neural network model serves as the eddy viscosity closure. A customized interface between the neural network and SAM is developed to ensure flexible and efficient data exchange. The SAM-ML results demonstrate superior performance compared to SAM's built-in zero-equation eddy viscosity closure. The case study shows that although the generalization capability of the data-driven closure still needs to be improved for different transient case or different geometric setup, SAM -ML demonstrates good potential for challenging simulation problems with improved accuracy and computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The growth of short cracks in 4340 steel and aluminum-lithium 2090

The objectives were to investigate crack initiation characteristics and short crack growth behavior for Al-Li 2090 and for 4340 steel and to evaluate the ability of a closure-based crack-growth model to predict fatigue crack growth rates and total fatigue lives for the steel. Single-edge-notched tension specimens of each alloy were used to obtain the short crack growth rate information via an acetate replica technique. In addition to constant amplitude loading, tests on the steel were conducted using the Felix/28 variable amplitude spectrum (a shortened form of a standard loading sequence for fixed or semi-rigid helicopter rotors). The short crack growth rates were compared to those for long cracks grown under similar loading conditions. Metallurgical features associated with crack initiation are discussed. For Al-Li 2090 under R = -1 loading, the short cracks grew well below the long crack threshold and grew at acute angles to the loading axis. For 4340 steel under constant amplitude loading at R = 0.5 and 0 and for the Felix/28 spectrum loading, short-crack growth rates agreed well with long-crack growth rates, even near the long-crack threshold. A slight short-crack effect, growth below the long-crack threshold, was observed at R = -1. Fatigue lives were found to depend on the size and type of initiation site, especially for the Felix/28 loading sequence. A semi-empirical crack-growth model incorporating crack-closure effects was used to predict crack growth rates and total fatigue lives of notched 4340 steel specimens. An initial defect size and shape typical of those identified in this steel was assumed for the life predictions. For all loading conditions, reasonable agreement was found between measured and predicted values for both crack growth rates and fatigue lives.

Swain, M. H.↗

Mesh Convergence Requirements for Composite Damage Models

The ability of the finite element method to accurately represent the response of objects with intricate geometry and loading renders the finite element method as an extremely versatile analysis technique for structural analysis. Finite element analysis is routinely used in industry to calculate deflections, stress concentrations, natural frequencies, buckling loads, and much more. The method works by discretizing complex problems into smaller, simpler approximations that are valid over small uniform domains. For common analyses, the maximum size of the elements that can be used is often be determined by experience. However, to verify the quality of a solution, analyses with several levels of mesh refinement should be performed to ensure that the solution has converged. In recent years, the finite element method has been used to calculate the resistance of structures, and in particular that of composite structures. A number of techniques such as cohesive zone modeling, the virtual crack closure technique, and continuum damage modeling have emerged that can be used to predict cracking, delaminations, fiber failure, and other composite damage modes that lead to structural collapse. However, damage models present mesh refinement requirements that are not well understood. In this presentation, we examine different mesh refinement issues related to the representation of damage in composite materials. Damage process zone sizes and their corresponding mesh requirements will be discussed. The difficulties of modeling discontinuities and the associated need for regularization techniques will be illustrated, and some unexpected element size constraints will be presented. Finally, some of the difficulties in constructing models of composite structures capable of predicting transverse matrix cracking will be discussed. It will be shown that to predict the initiation and propagation of transverse matrix cracks, their density, and their saturation may require models that are significantly more refined than those that have been contemplated in the past.

Davila, Carlos G.↗

Summary of Analytical Results from Samples Supporting Tank Closure Cesium Removal (TCCR) Batch 3 and Modeling Results for Cs Loading on CST

Savannah River Remediation (SRR) is currently operating the Tank Closure Cesium Removal (TCCR) process to remove 137 Cs from tank waste supernate using an ion exchange process. As part of that process, Savannah River National Laboratory (SRNL) receives and analyzes samples in support of the qualification of each batch to be processed. SRNL recently received supernate samples retrieved from Tank 10H as well as in-tank batch contact samples for characterization in support of qualifying Batch 3 for processing through the TCCR unit. Some results from analysis of those samples have been previously reported. This report documents the remaining analyses of the in-tank batch contact samples as well as the results of ZAM (Zheng, Anthony, Miller) isotherm modeling performed for comparison to the measured results. Results of the additional analyses include analysis of the loading of other radionuclides besides 137 Cs on the crystalline silicotitanate (CST) contained within the in-tank batch contact test samples. Results from those analyses revealed the next highest contributor to the activity on the CST was 90 Sr with an average loading of 2.76E+08 dpm/g CST compared to 3.56E+10 dpm/g CST for the 137Cs. Isotopes of plutonium were also detected on the samples. ZAM modeling was performed using the measured composition of the Tank 10H Batch 3 qualification samples. The modeling predicted a maximum Cs loading approximately 2.2x higher than the measured result. This is a slightly lower ratio (expected/measured) compared to what was observed for the prior TCCR in-tank batch contact testing performed for Batches 1A and 2 where the ZAM results were 2.7-2.8x higher than the measured values.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Simulated Precipitation Diurnal Variation With a Deep Convective Closure Subject to Shallow Convection in Community Atmosphere Model Version 5 Coupled With CLUBB

In order to improve the physical consistency between shallow and deep convection, we modify the deep convective closure in the Community Atmosphere Model version 5 (CAM5) coupled with a third-order turbulence closure parameterization (i.e., Cloud Layers Unified by Binormals; CLUBB). The revised closure reserves a portion of the total convective available potential energy for shallow convection via utilizing the heating and moistening profiles from CLUBB to distribute moisture and energy between shallow and deep convection. Simulations at two resolutions (i.e. 2° and 0.5°, respectively) are conducted to investigate the impacts of convective closure on the simulated precipitation diurnal variations. Results from low-resolution simulations show that the revised closure suppresses deep convection until the lower troposphere is sufficiently moistened by shallow convection, which improves the precipitation diurnal variation simulations compared to the default closure, with the precipitation diurnal peak over tropical lands delayed from 12LST to 19LST. The revised closure better simulates the diurnal variations for precipitation over the Asian monsoon region, such as the delayed precipitation onset, but still fails to well capture the nighttime peak for precipitation there. This deficiency is alleviated to some extent when applying the revised closure in highresolution simulations, but nighttime precipitation is still underestimated probably because key processes responsible for nighttime convection are missing. Altogether, our results indicate that establishing the consistency between shallow and deep convection is critical for the precipitation diurnal cycle simulations.

54 ENVIRONMENTAL SCIENCES↗

Mineral Dust Optical Properties for Remote Sensing and Global Modeling: A Review

Dust plays a key role in many Earth system processes and is ubiquitous in the Martian atmosphere. Various intensive field campaigns, laboratory analyses, space-based remote sensing missions, and global modeling efforts aim to characterize dust optical properties. This is a bountiful time for dust scientists, and yet the interpretation of retrievals and comparison to models remains complicated by various conflicting assumptions that are part of each algorithm. For example, the conversion of satellite radiance measurements into products like aerosol optical depth for model evaluation depends upon aerosol properties like particle size and shape that are often prescribed and not part of the retrieval. Conversely, the model calculation of aerosol optical depth often uses different assumptions. The goal of this review is to first document algorithmic assumptions by various satellite retrieval products and models, and identify where there is consistency and where there are differences. In general, the differences documented in this paper reflect uncertainties resulting from incomplete observational characterization of dust aerosols and limitations in our understanding. Second, we note what observations might reduce uncertainties in our knowledge and bring greater consistency to retrievals and models, allowing for a more rigorous and harmonious comparison. The lack of comprehensive and realistic shape models for dust is an outstanding issue, such that closure between forward modeling from particle refractive index, shape, and size and observed optical properties cannot be achieved. Limitations in the computational methods that must be applied to model scattering from complex shapes also makes accurate optical modeling for dust challenging. Field observations indicate the persistence of coarse and giant dust particles at higher altitudes and farther downwind from their source than previously expected. Remote sensing retrieval algorithms based on observations at visible wavelengths have limited sensitivity to these particles and generally do not consider them, although a recent product based on longwave radiances is encouraging. Current measurements of the refractive index of bulk dust and fundamental dust minerology components such as hematite vary widely, inhibiting attempts to represent the variability in dust optical properties and forcing, as expected from different major dust source regions on Earth that have varying mineralogical composition. Some remote sensing retrieval algorithms allow for limited refractive index variability in their inversion solutions through mixing with other fine mode aerosol models, or optimizing the single scattering albedo, but Earth system models surveyed for this paper assume a globally uniform, size-invariant refractive index. Although no Martian dust samples have yet been returned to Earth, remote sensing observations indicate that Martian dust is globally homogenous in composition, and a single spectral refractive index assumption has been widely adopted to represent Martian dust. The lack of comprehensive, statistically representative measurements of dust particle microphysical properties (size distribution, morphology, complex index of refraction spectra, internal structure heterogeneity), and the resulting optical properties, limits our ability to verify the fidelity of these assumptions. A chain of measurements is needed, ranging from characterizing individual dust mineralogy components (e.g., pure hematite and goethite) to in situ sampling of complex atmospheric aerosol mixtures. Such results could be applied to both remote sensing retrievals that characterize the optical properties of the total aerosol burden in the atmosphere from total radiance measurements, and to global models that represent the total aerosol burden in the atmosphere by building it up from the balance of individual aerosol sources and sinks.

Aeolian dust↗

Predicting equilibrium states with Reynolds stress closures in channel flow and homogeneous shear flow

Turbulent channel flow and homogeneous shear flow have served as basic building block flows for the testing and calibration of Reynolds stress models. A direct theoretical connection is made between homogeneous shear flow in equilibrium and the log-layer of fully-developed turbulent channel flow. It is shown that if a second-order closure model is calibrated to yield good equilibrium values for homogeneous shear flow it will also yield good results for the log-layer of channel flow provided that the Rotta coefficient is not too far removed from one. Most of the commonly used second-order closure models introduce an ad hoc wall reflection term in order to mask deficient predictions for the log-layer of channel flow that arise either from an inaccurate calibration of homogeneous shear flow or from the use of a Rotta coefficient that is too large. Illustrative model calculations are presented to demonstrate this point which has important implications for turbulence modeling.

Abid, R.↗

Predicting equilibrium states with Reynolds stress closures in channel flow and homogeneous shear flow

Turbulent channel flow and homogeneous shear flow have served as basic building block flows for the testing and calibration of Reynolds stress models. A direct theoretical connection is made between homogeneous shear flow in equilibrium and the log-layer of fully-developed turbulent channel flow. It is shown that if a second-order closure model is calibrated to yield good equilibrium values for homogeneous shear flow it will also yield good results for the log-layer of channel flow provided that the Rotta coefficient is not too far removed from one. Most of the commonly used second-order closure models introduce an ad hoc wall reflection term in order to mask deficient predictions for the log-layer of channel flow that arise either from an inaccurate calibration of homogeneous shear flow or from the use of a Rotta coefficient that is too large. Illustrative model calculations are presented to demonstrate this point which has important implications for turbulence modeling.

Abid, R.↗