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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Flow regime and Reynolds number variation effects on the mixing behavior of parallel flows

The hydraulic single-phase mixing of three parallel rectangular channels is experimentally investigated at various Reynolds numbers (Re) and flow regime combinations. Particle Image Velocimetry results for seven mixing cases are presented and discussed with varying Re combinations ranging from 1,824 to 20,844. While all cases result in the same Re ratio of ~0.69 between the inner and outer flows, two cases represent multi-regime mixing with the inner-outer regime pair of laminar-transitional and transitional-turbulent, while the other 5 cases are all characteristic of turbulent mixing with varying levels of turbulence. The outer channels initially share characteristics with a backward facing step. The center channel is found to initially behave like a slot jet, but then sees a significant increase in velocity decay. This inner flow velocity decay increased dramatically in the laminar-transitional mixing case, whose centerline velocity decay was ~6 times larger than the decay in the turbulent mixing cases. Second order statistics revealed a consistent mixing layer thickness of ~0.1 hydraulic diameters for all the cases but showed more intense shearing in the multi-regime mixing cases. The combined point and thereby the mixing layer length is determined using centerline velocity decay profiles, which show a much more aggressive mixing in multi-regime flows. Multi-regime mixing demonstrated superior characteristics relative to turbulent mixing due to a more dramatic velocity decay in the inner flow and a shorter mixing length. The contributions of this work include communicating the benefits of multi-regime mixing and providing detailed characterization efforts that can serve future efforts for validating computational models. Here this research also lays the groundwork for future studies aimed at achieving high levels of mixing without a severe penalty in pressure drop.

42 ENGINEERING↗
DOE OSTI2024

The Dual Nature of Entrainment-Mixing Signatures Revealed through Large-Eddy Simulations of a Convection-Cloud Chamber

Abstract Entrainment of subsaturated air into a cloud can influence its optical and microphysical properties in various ways, depending on the droplet evaporation and turbulent mixing time scales. Previous experiments in the Pi convection-cloud chamber have revealed that, given a fixed entrained air property, the mixing of entrained subsaturated air results in complete evaporation of some cloud droplets, with the rest remaining unchanged. This is a signature of inhomogeneous mixing. While comparing the results of entrainment with varying air properties, the mixing signature appears as if the subsaturated air is well mixed with the cloud to evenly reduce the droplets’ size. In other words, taken together, the experiments appear to have the signature of homogeneous mixing. To explore these results in a greater depth, we conduct large-eddy simulations combined with a bin microphysics scheme. Our results reproduce the similar signatures of inhomogeneous and homogeneous mixing, implying that LES can resolve the inhomogeneous mixing when the grid spacing is smaller than the entrained air parcel. Additionally, we observe that increasing the aerosol injection rate enhances the signature of inhomogeneous mixing, while coarser grid spacing diminishes it. Finally, the change in wall fluxes in response to various entrained air properties confirms that the homogeneous signature seen in the analysis of an ensemble of simulations is the result of various equilibrium states. This further strengthens the suggestion that the homogeneous mixing signature found in aircraft observations near the cloud top may result from combining entrainment events of different intensities, possibly caused by various-sized eddies. Significance Statement Large-eddy simulation and size-resolved microphysics can resolve time scales for turbulent mixing and evaporation and, therefore, are well suited for reproducing, extending, and interpreting the entrainment experiment in the Pi convection-cloud chamber. Our simulation results confirm (i) the inhomogeneous mixing signature for an individual entrainment event and (ii) the appearance of homogeneous mixing in an ensemble of entrainment episodes. Furthermore, we demonstrate that the inhomogeneous mixing signature is more pronounced in a polluted cloud, but coarser grid spacing in simulations may compromise the accuracy of this signature. Last, the homogeneous mixing signature results from various equilibrium states established for different entrainment intensities and adjusted wall fluxes, which are challenging to measure experimentally but can be easily analyzed in the simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Five Year Comparison of Mixing Height Determinations at the Savannah River Site

Air quality dispersion modeling is performed for the Savannah River Site (SRS) to demonstrate compliance with applicable regulations. The AMS/EPA Regulatory Model (AERMOD) modeling system is an EPA recommended model for air quality applications with a data preprocessor (AERMET) to incorporate meteorological data collected on site. AERMET parameterizes or calculates meteorological variables that are not directly measured onsite. One of the parameters estimated by AERMET is the atmospheric mixing height. While the mixing height is not currently a measurement input into AERMET, SRS has the capability to measure the local mixing height. The Savannah River National Laboratory (SRNL) operates a Vaisala CL31 Lidar Ceilometer which estimates mixing height from aerosol backscatter. This study compares the parameterized mixing height from AERMET to the ceilometer estimated mixing height for the current regulatory period at SRS incorporating data from 2015-2019. Results from this study showed the average daily minimum values (morning) from AERMET were an order of magnitude lower than the commonly used Holzworth (1972) method and the ceilometer estimated mixing heights. Additionally, on average, the ceilometer exhibited a daily maximum mixing height value that occurred 1-3 hours later than the AERMET estimated maximum. This difference is likely due to the nighttime atmospheric mixing height assumptions and calculations used by AERMET. The AERMET algorithm cuts off mixing height growth at sunset while the ceilometer data show ongoing evening convection typical of the southeastern United States. These results suggest that the AERMET parametrization scheme assumptions may not be representative of a forested landscape and evening convection which could account for more mixing overnight. The results obtained in this study are significant for air dispersion modeling applications for regulatory purposes and worker safety. Mixing height can impact model estimated pollutant concentrations. A greater mixing height will provide more volume for pollutant dispersion. This report documents efforts to quantify the dependence of mixing height inputs toward a conservative estimated pollutant concentration.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Quantification of Physical and Numerical Mixing in a Coastal Ocean Model Using Salinity Variance Budgets

Numerical mixing, the spurious mixing primarily generated by the discretization of advection, is often significant in estuarine and coastal models due to sharp, energetic fronts. In this study, we compare on- and offline estimates of numerical mixing in a submesoscale-resolving realistic simulation of the ocean state over the Texas-Louisiana continental shelf. While offline estimates of numerical mixing differ from online estimates, offline methods may be the only analysis available. This study offers insight into the differences between the on- and offline methods. We use two methods to estimate numerical mixing offline, based on salinity squared $s^2$ and volume-mean salinity variance $s^{\prime^2}$. Numerical mixing estimated from the $s^{\prime^2}$ budget is generally within 60\% of the magnitude for the online method but captures the temporal variability well. However, the $s^2$ budget compares poorly due to larger truncation errors associated with the tendency and advection terms, which can be reduced by increasing the model output frequency. We also investigate the effects of horizontal resolution on numerical mixing using a two-way nested grid. The volume-integrated numerical mixing constitutes 57\% of the bulk physical mixing -- the mixing prescribed by the turbulence closure scheme -- in the coarse model and may exceed the physical mixing by half an order of magnitude. We find that numerical mixing is reduced by 35\% on average in the nested model, less than expected based on scaling of the numerical mixing for an upwind advection scheme, likely due to new dynamical processes that emerge in the nested simulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model

Abstract. Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. This study aims to verify the global distribution of aerosol mixing state represented by modal models. To quantify the aerosol mixing state, we used the aerosol mixing state indices for submicron aerosol based on the mixing of optically absorbing and non-absorbing species (χo), the mixing of primary carbonaceous and non-primary carbonaceous species (χc), and the mixing of hygroscopic and non-hygroscopic species (χh). To achieve a spatiotemporal comparison, we calculated the mixing state indices using output from the Community Earth System Model with the four-mode version of the Modal Aerosol Module (MAM4) and compared the results with the mixing state indices from a benchmark machine-learned model trained on high-detail particle-resolved simulations from the particle-resolved stochastic aerosol model PartMC-MOSAIC. The two methods yielded very different spatial patterns of the mixing state indices. In some regions, the yearly averaged χ value computed by the MAM4 model differed by up to 70 percentage points from the benchmark values. These errors tended to be zonally structured, with the MAM4 model predicting a more internally mixed aerosol at low latitudes and a more externally mixed aerosol at high latitudes compared to the benchmark. Our study quantifies potential model bias in simulating mixing state in different regions and provides insights into potential improvements to model process representation for a more realistic simulation of aerosols towards better quantification of radiative forcing and aerosol–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluation of a Stochastic Mixing Scheme in the Deep Convective Gray Zone Using a Tropical Oceanic Deep Convection Case Study

Abstract A stochastic horizontal subgrid‐scale mixing scheme is evaluated in ensemble simulations of a tropical oceanic deep convection case using a horizontal grid spacing (Δ h ) of 3 km. The stochastic scheme, which perturbs the horizontal mixing coefficient according to a prescribed spatiotemporal autocorrelation scale, is found to generally increase mesoscale organization and convective intensity relative to a non‐stochastic control simulation. Perturbations applied at relatively short autocorrelation scales induce differences relative to the control that are more systematic than those from perturbations applied at relatively long scales that yield more variable outcomes. A simulation with mixing enhanced by a constant factor of 4 significantly increases mesoscale organization and convective intensity, while turning off horizontal subgrid‐scale mixing decreases both. Total rainfall is modulated by a combination of mesoscale organization, areal coverage of convection, and convective intensity. The stochastic simulations tend to behave more similarly to the constant enhanced mixing simulation owing to greater impacts from enhanced mixing as compared to reduced mixing. The impacts of stochastic mixing are robust, ascertained by comparing the stochastic mixing ensembles with a non‐stochastic mixing ensemble that has grid‐scale noise added to the initial thermodynamic field. Compared to radar observations and a higher resolution Δ h = 1 km simulation, stochastic mixing seemingly degrades the simulation performance. These results imply that stochastic mixing produces non‐negligible impacts on convective system properties and evolution but does not lead to an improved representation of convective cloud characteristics in the case studied here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A buoyancy–shear–drag–scalar-based turbulence model for power-law acceleration-driven Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing

A previously developed phenomenological turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz instability-induced mixing based on a general buoyancy–shear–drag model [O. Schilling, “A buoyancy–shear–drag-based turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing,” Physica D 402, 132238 (2020)] is extended to include active or passive scalar mixing and power-law acceleration-driven Rayleigh–Taylor mixing. The buoyancy–shear–drag equations are coupled to a scalar variance equation that is used to define the molecular mixing parameter θ m , and when the scalar is active, modifies the Rayleigh–Taylor and Kelvin–Helmholtz mixing layer growth parameters to depend on the asymptotic value of this parameter, θ mol . Here, the scalar variance equation is closed by algebraically or differentially modeling the scalar variance dissipation rate. Nonlinear analytical solutions of the model are obtained in the total and separate bubble and spike mixing layer width formulations with the algebraic scalar variance dissipation rate for each instability, which are then used to calibrate the mechanical and scalar equation coefficients to predict specific values of physical observables and molecular mixing parameters. Surrogate mechanical and scalar turbulent fields can be constructed by multiplying a presumed self-similar spatial profile by appropriate functions of the width and its time derivative, and of the scalar obtained by solving the ordinary differential model equations. The explicit modeling and solution of turbulent transport equations are not required. The bubble and spike mixing layer width and scalar variance equations are then solved numerically for constant-acceleration Rayleigh–Taylor, impulsively reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing, confirming that the prescribed level of molecular mixing is correctly predicted and illustrating the spatiotemporal evolution of the scalar fields.

Buoyancy–drag↗
DOE OSTI2025

Observation of kinetic mix enhancement in thin-shell OMEGA implosions

Recent separated reactant experiments for thin-shell (6 µ⁢m) shock-driven implosions on OMEGA have demonstrated significant mix from a buried deuterated layer of the shell into the hot spot. Time resolved D 3 He-p reaction history data demonstrate a (50 ± 20)⁢ ps shift earlier in peak nuclear emission for separated reactant experiments relative to control, in contrast to past experimental data for thicker, 20 µ⁢m shells with no laser burn through that show a 75 ps delay due to the time required for hydrodynamic instabilities to develop. This contrast suggests that the mix mechanism was not hydrodynamic. Ion kinetic simulations utilizing fall line analyses show much closer agreement with mix yield and temperature than diffusion models, predicting a D 3 He-p mix yield of 1.7 × 10 9 as compared to the experimental value of 9.3⁢ (±2.1) × 10 8 . This is three orders of magnitude closer than the fall line analysis from a hydrodynamic simulation with an inline diffusive mix model, which suggests minimal mix and D 3 He-p yields of 5×10 5 . This makes kinetic mechanisms the only feasible explanation for the mix seen, demonstrating impact of a non-standard mix mechanism. An analytical model of this kinetic mix mechanism suggests that it can remain significant in situations when the shell expands significantly to low densities, and diffusive models predict negligible mix. Finally, kinetic mix will impact multiple types of high energy density, laser-driven fusion experiments including high-adiabat direct drive cryoexperiments, nuclear cross section experiments, and thin-shell polar direct drive experiments used to tune heat conduction models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

INVESTIGATION OF TURBULENT JETS, SPRAYS, AND SUPERCRITICAL MIXING BY TIME RESOLVED RAINBOW SCHLIEREN DEFLECTOMETRY

As technological advancements have enabled higher efficiency compression ignition (CI) engines (diesel engines) by operating at higher pressures and temperatures, the mechanisms of fuel-air mixing are postulated to change. Thus, there is a greater need for experimental data to develop and verify new phenomena. However, the fast time scales and harsh environments associated with CI engines present many experimental difficulties and requires high quality non-intrusive diagnostics to obtain useful data. The diagnostics itself must be validated prior to its implementation in an engine environment. The purpose of this research is to advance rainbow schlieren deflectometry (RSD) to study turbulent fuel sprays including the effects of supercritical mixing in CI engine environments. This objective is met by developing and applying quantitative RSD, for the first time, to three separate aspects of fuel sprays: 1) turbulent mixing, 2) phase boundaries, and 3) non-ideal gas mixing. First, quantitative RSD is demonstrated for turbulent mixing in a canonical helium jet. Rayleigh scattering data in the literature is used to validate the concentration measurements obtained by RSD. The results also provide explanations for phenomena occurring in the helium jet and provide data not yet present in the literature. Second, RSD is applied to high pressure multi-phase fuel sprays and new methodologies are developed to distinguish the liquid region from the vapor region and to quantify the in-between region on a probabilistic basis. Isolating liquid and vapor regions generally requires two separate diagnostics, e.g., Mie scattering (liquid region) and Rayleigh scattering (vapor region). However, the results of this study demonstrate that RSD can be used as a single diagnostic to measure both liquid and vapor boundaries. Third, the optical-to-thermodynamic relations associated with refrac-tometry are investigated under non-ideal gas mixing conditions to develop a generalized relationship valid for both ideal or non-ideal gas mixing. The last part of this research develops the theoretical tools to understand and experimentally realize supercritical mixing at diesel conditions. Guided by the theoretical analysis, RSD is applied to compare supercritical versus transcritical mixing at CI conditions using a constant pressure test rig. It is found that while fully supercritical mixing ers benefits in diesel engines, i.e, faster mixing times (50% higher velocities), the absence of droplets which cause high levels of particulate emissions, etc., it would be difficult to achieve in practice because of the requirements of fuels with low critical temperature and/or substantial fuel preheating.

02 PETROLEUM↗
DOE OSTI2023

Mixing across stable density interfaces in forced stratified turbulence

Understanding how turbulence enhances irreversible scalar mixing in density-stratified fluids is a central problem in geophysical fluid dynamics. While isotropic overturning regions are commonly the focus of mixing analyses, we here investigate whether significant mixing may arise in anisotropic statically stable regions of the flow. Focusing on a single forced direct numerical simulation of stratified turbulence, we analyse spatial correlations between the vertical density gradient $\partial \rho /\partial z$ and the dissipation rates of kinetic energy $\epsilon$ and scalar variance $\chi$ , the latter quantifying scalar mixing. The domain is characterized by relatively well-mixed density layers separated by sharp stable interfaces that are correlated with high vertical shear. While static instability is most prevalent within the mixed layers, much of the scalar mixing is localized to the intervening interfaces, a phenomenon not apparent if considering local static instability or $\epsilon$ alone. While the majority of the domain is characterized by the canonical flux coefficient $\varGamma \equiv \chi /\epsilon =0.2$ , often assumed in ocean mixing parametrizations, extreme values of $\chi$ within the statically stable interfaces, associated with elevated $\varGamma$ , strongly skew the bulk statistics. Our findings suggest that current parametrizations of turbulent mixing may be biased by undersampling, such that the most common, but not necessarily the most significant, mixing events are overweighted. Having focused here on a single simulation of stratified turbulence, it is hoped that our results motivate a broader investigation into the role played by stable density interfaces in mixing, across a wider range of parameters and forcing schemes representative of ocean turbulence.

Couchman, Miles M. P. (ORCID:0000000246676829)↗
DOE OSTI2022

Influences of an entrainment–mixing parameterization on numerical simulations of cumulus and stratocumulus clouds

Abstract. Different entrainment–mixing processes can occur in clouds; however, a homogeneous mixing mechanism is often implicitly assumed in most commonly used microphysics schemes. Here, we first present a new entrainment–mixing parameterization that uses the grid mean relative humidity without requiring the relative humidity of the entrained air. Then, the parameterization is implemented in a microphysics scheme in a large eddy simulation model, and sensitivity experiments are conducted to compare the new parameterization with the default homogeneous entrainment–mixing parameterization. The results indicate that the new entrainment–mixing parameterization has a larger impact on the number concentration, volume mean radius, and cloud optical depth in the stratocumulus case than in the cumulus case. This is because inhomogeneous and homogeneous mixing mechanisms dominate in the stratocumulus and cumulus cases, respectively, which is mainly due to the larger turbulence dissipation rate in the cumulus case. Because stratocumulus clouds break up during the dissipation stage to form cumulus clouds, the effects of this new entrainment–mixing parameterization during the stratocumulus dissipation stage are between those during the stratocumulus mature stage and the cumulus case. A large aerosol concentration can enhance the effects of this new entrainment–mixing parameterization by decreasing the cloud droplet size and evaporation timescale. The results of this new entrainment–mixing parameterization with grid mean relative humidity are validated by the use of a different entrainment–mixing parameterization that uses parameterized entrained air properties. This study sheds new light on the improvement of entrainment–mixing parameterizations in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Why is height-dependent mixing observed in stratocumulus clouds?

Recent aircraft measurements in stratocumulus clouds suggest that entrainment mixing is inhomogeneous (IM) near cloud top and homogeneous (HM) within the cloud. However, this proposed height-dependence of mixing transition is uncertain because of artifacts involved in the aircraft measurements. In this study, we use the Explicit Mixing Parcel Model to simulate mixing scenarios in stratocumulus clouds and reconstruct the virtual aircraft measurements to investigate the mixing signature. Results show that, from the aircraft-measurement perspective, the mixing signature always exhibits IM characteristic near cloud top and HM characteristic within cloud, independent of the types of the local entrainment-mixing process. The appearance of the vertical IM-to-HM transition is essentially a collective behavior of multiple parcels sampled at the same height, experiencing distinct entrainment-mixing-evaporation histories. This bulk view of mixing process, which is widely used for aircraft measurements, could lead to misinterpretations of the true mixing mechanism occurring in clouds. Our result underscores the limitations of using aircraft measurements to identify the entrainment-mixing mechanism at the process level.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

An index to characterize gas‐solid and solid‐solid mixing from average volume fraction fields

Abstract A mixing index based on solid volume fraction fields is developed for gas‐solid flows. Conventional mixing indices are based on particle realizations of granular mixing and are applicable to experimental data or discrete element method simulations. However, these indices cannot be used as‐is for multifluid models, and an index for characterizing mixing in gas‐solid flows from continuous fields is needed. The performance of the new mixing index is tested in two applications. The first is a 3D simulation of the mixing of biomass and sand in a fluidized bed reactor, and the second is a 2D simulation of binary particle segregation in a fluidized bed. The simulations are performed using OpenFOAM®. The mixing index is used to quantify gas‐solid mixing using solid volume fractions and solid‐solid mixing using solid fractions. The formulation of conventional mixing indices is extended to be used with solid volume fractions fields, and methods for performance improvement are presented.

09 BIOMASS FUELS↗
DOE OSTI2023

Estimating the Meridional Extent of Adiabatic Mixing in the Stratosphere Using Age-Of-Air

Wave-induced adiabatic mixing in the winter midlatitudes is one of the key processes impacting stratospheric transport. Understanding its strength and structure is vital to understanding the distribution of trace gases and their modulation under a changing climate. Age-of-air is often used to understand stratospheric transport, and this study proposes refinements to the vertical age gradient theory of Linz et al. (2021), https://doi.org/10.1029/2021JD035199. The theory assumes exchange of air between a well-mixed tropics and a well-mixed extratropics, separated by a transport barrier, quantifying the adiabatic mixing flux across the interface using age-based measures. These assumptions are re-evaluated and a refined framework that includes the effects of meridional tracer gradients is established to quantify the mixing flux. This is achieved, in part, by computing a circulation streamfunction in age-potential temperature coordinates to generate a complete distribution of parcel ages being mixed in the midlatitudes. The streamfunction quantifies the “true” age of parcels mixed between the tropics and the extratropics. Applying the revised theory to an idealized and a comprehensive climate model reveals that ignoring the meridional gradients in age leads to an underestimation of the wave-driven mixing flux. Stronger, and qualitatively similar fluxes are obtained in both models, especially in the lower-to-middle stratosphere. While the meridional span of adiabatic mixing in the two models exhibits some differences, they show that the deep tropical pipe, that is, latitudes equatorward of 15° barely mix with older midlatitude air. The novel age-potential temperature circulation can be used to quantify additional aspects of stratospheric transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using Machine Learning to Predict Cloud Turbulent Entrainment–Mixing Processes

Different turbulent entrainment–mixing mechanisms between clouds and environment are essential to cloud–related processes; however, accurate representation of entrainment–mixing in weather/climate models still poses a challenge. This study exploits the use of machine learning (ML) to address this challenge. Four ML (Light Gradient Boosting Machine [LGB], eXtreme Gradient Boosting, Random Forest, and Support Vector Regression) are examined and compared. It is found that LGB performs best, and thus is selected to understand the impact of entrainment–mixing on microphysics using simulation data from Explicit Mixing Parcel Model. Compared with traditional parameterizations, the trained LGB provides more accurate microphysical properties (number concentration and cloud droplet spectral dispersion). The partial dependences of predicted microphysics on features exhibit a strong alignment with physical mechanisms and expectations, as determined by the interpreting method, thus overcoming the limitations of the “black box” scheme. The underlying mechanisms are that the smaller number concentration and larger spectral dispersion correspond to more inhomogeneous entrainment–mixing. Specifically, number concentration after entrainment–mixing is positively correlated with adiabatic number concentration and liquid water content affected by entrainment–mixing, and inversely correlated with adiabatic volume mean radius. Spectral dispersion after entrainment–mixing is negatively correlated with liquid water content affected by entrainment–mixing, turbulent dissipation rate and relative humidity of entrained air. Sensitivity analysis further suggests that number concentration is mainly determined by cloud microphysical properties whereas spectral dispersion is influenced by both cloud microphysical properties and environmental variables. The results indicate that the LGB scheme has the potential to enhance the representation of entrainment–mixing in weather/climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Self-similar Reynolds-averaged mechanical–scalar turbulence models for reshocked Richtmyer–Meshkov instability-induced mixing in the small Atwood number limit

Analytical self-similar solutions to two-, three-, and four-equation Reynolds-averaged mechanical–scalar turbulence models describing incompressible turbulent Richtmyer–Meshkov instability-induced mixing in planar geometry derived in the small Atwood number limit are extended to construct models for reshocked Richtmyer–Meshkov mixing. In this study, the models are based on the turbulent kinetic energy K and its dissipation rate ε, together with the scalar variance S and its dissipation rate χ modeled either differentially or algebraically. The three- and four-equation models allow for a simultaneous description of mechanical and scalar mixing, i.e., mixing layer growth and molecular mixing. Mixing layer growth parameters and other physical observables were obtained explicitly as functions of the model coefficients and were used to calibrate the model coefficients. Here, the solutions for the singly shocked Richtmyer–Meshkov case for the mixing layer width and the turbulent fields are used to construct piecewise-continuous generalizations of these quantities for times after reshock. For generality, the post-reshock mixing layer width is not assumed to grow with the same power-law as the pre-reshock width, and an impulsive approximation applied to Rayleigh–Taylor instability growth is used to establish the expression for the post-reshock width. A four-equation model is then used to illustrate the spatiotemporal behavior of the mean and turbulent fields and late-time turbulent equation budgets across the mixing layer. The reference solutions derived here can provide systematic calibrations and better understanding of mechanical–scalar turbulence models and their predictions for reshocked Richtmyer–Meshkov instability-induced turbulent mixing in the very large Reynolds number limit.

42 ENGINEERING↗
DOE OSTI2024

A study on the scale dependence of mixing indices for Eulerian multiphase models

Abstract Mixing can vary based on the scale at which the system is observed, and a mixing index that can capture the features at different length scales is desirable. In this article, we analyze the scale dependence of the mixing indices developed for Eulerian multiphase models. Relevant length scales are distinguished by filtering solid fraction fields. The scale‐dependence study is first done on manufactured fields of solid fraction to assess the performance of the mixing indices. The study is extended to a two‐dimensional CFD simulation of the segregation of a bidisperse gas–solid mixture. The local mixing index performs well in capturing the spatial variation of mixing at different scales. The scale dependence of two global mixing indices is considered in the study, where the state of mixing is defined based on statistical measures. We demonstrate that the choice of measures influences the sensitivity of mixing indices to mixing at different scales.

Nagawkar, Barlev R.↗
DOE OSTI2024

Engineering advancements in microfluidic systems for enhanced mixing at low Reynolds numbers

Mixing within micro- and millichannels is a pivotal element across various applications, ranging from chemical synthesis to biomedical diagnostics and environmental monitoring. The inherent low Reynolds number flow in these channels often results in a parabolic velocity profile, leading to a broad residence time distribution. Achieving efficient mixing at such small scales presents unique challenges and opportunities. This review encompasses various techniques and strategies to evaluate and enhance mixing efficiency in these confined environments. It explores the significance of mixing in micro- and millichannels, highlighting its relevance for enhanced reaction kinetics, homogeneity in mixed fluids, and analytical accuracy. We discuss various mixing methodologies that have been employed to get a narrower residence time distribution. The role of channel geometry, flow conditions, and mixing mechanisms in influencing the mixing performance are also discussed. Various emerging technologies and advancements in microfluidic devices and tools specifically designed to enhance mixing efficiency are highlighted. We emphasize the potential applications of micro- and millichannels in fields of nanoparticle synthesis, which can be utilized for biological applications. Additionally, the prospects of machine learning and artificial intelligence are offered toward incorporating better mixing to achieve precise control over nanoparticle synthesis, ultimately enhancing the potential for applications in these miniature fluidic systems.

Biochemistry & Molecular Biology↗