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At least 721 records · Page 40

Scalar flux transport models for self-similar turbulent mixing

A common approach to closing turbulent species flux in multicomponent Reynolds-averaged Navier-Stokes models is to use the standard gradient diffusion approximation. While such an approach has been shown to work well when applied to many canonical turbulent mixing configurations, a gradient diffusion approach is fundamentally limited in its ability to capture complex phenomena such as countergradient transport. For this reason, complicated mixing applications may benefit by treating the turbulent diffusivity with a model transport equation in a manner analogous to second-moment momentum closure in Reynolds-stress transport models. Here, the present work explores the development and application of two different scalar flux transport (SFT) models. Self-similarity constraints are derived for these models, and they are evaluated against gradient-diffusion-based models in several one- and two-dimensional problems of turbulent mixing. It is found that the new SFT models out-perform gradient diffusion models in problems involving rapid acceleration reversal and in problems involving anisotropic transport of materials. In addition, it is found that even a hybrid-SFT approach, in which an SFT equation is utilized along with a gradient diffusion closure, provides some measure of improvement over models that transport the mass flux rather than the scalar flux.

Reynolds-averaged Navier Stokes↗

Numerical Investigation of Fuel Property Effects on Mixed-Mode Combustion in a Spark-Ignition Engine

In this research, lean mixed-mode combustion is numerically investigated using computational fluid dynamics (CFD) in a spark-ignition engine. A new E30 fuel surrogate is developed using a neural network model with matched octane numbers. A skeletal mechanism is also developed by automated mechanism reduction and by incorporating a NO x submechanism. A hybrid approach that couples the G-equation model and the well-stirred reactor model is employed for turbulent combustion modeling. The developed CFD model is shown to well predict pressure and apparent heat release rate (AHRR) traces compared with experiment. Two types of combustion cycles (deflagration-only and mixed-mode cycles) are observed. The mixed-mode cycles feature early flame propagation and subsequent end-gas auto-ignition, leading to two distinctive AHRR peaks. The validated CFD model is then employed to investigate the effects of NO x chemistry. The NO x chemistry is found to promote auto-ignition through the residual gas, while the deflagration phase remains largely unaffected. Sensitivity analysis is finally performed to understand effects of fuel properties, including heat of vaporization (HoV) and laminar flame speed (S L ). An increased HoV tends to suppress auto-ignition through charge cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased S L is found to significantly promote both flame propagation and end-gas auto-ignition. The promoting effect of S L on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end-gas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combining Sparse Approximate Factorizations with Mixed-precision Iterative Refinement

The standard LU factorization-based solution process for linear systems can be enhanced in speed or accuracy by employing mixed-precision iterative refinement. Most recent work has focused on dense systems. We investigate the potential of mixed-precision iterative refinement to enhance methods for sparse systems based on approximate sparse factorizations. In doing so, we first develop a new error analysis for LU- and GMRES-based iterative refinement under a general model of LU factorization that accounts for the approximation methods typically used by modern sparse solvers, such as low-rank approximations or relaxed pivoting strategies. We then provide a detailed performance analysis of both the execution time and memory consumption of different algorithms, based on a selected set of iterative refinement variants and approximate sparse factorizations. Our performance study uses the multifrontal solver MUMPS, which can exploit block low-rank factorization and static pivoting. We evaluate the performance of the algorithms on large, sparse problems coming from a variety of real-life and industrial applications showing that mixed-precision iterative refinement combined with approximate sparse factorization can lead to considerable reductions of both the time and memory consumption.

97 MATHEMATICS AND COMPUTING↗

Electronic, Ionic, and Mixed Conduction in Polymeric Systems

Polymers that simultaneously transport electrons and ions are paramount to drive the technological advances necessary for next-generation electrochemical devices, including energy storage devices and bioelectronics. However, efforts to describe the motion of ions or electrons separately within polymeric systems become inaccurate when both species are present. In this paper, we highlight the basic transport equations necessary to rationalize mixed transport and the multiscale materials properties that influence their transport coefficients. Potential figures of merit that enable a suitable performance benchmark in mixed conducting systems independent of end application are discussed. Practical design and implementation of mixed conducting polymers require an understanding of the evolving nature of structure and transport with ionic and electronic carrier density to capture the dynamic disorder inherent in polymeric materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics

Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Seasonal and Interspecific Variation in Frugivory by a Mixed Resident-Migrant Overwintering Songbird Community

Many temperate passerine bird species switch from diets of mostly invertebrates in the spring and summer to diets that include fruit and seeds in the fall and winter. However, relatively few studies have quantified diet composition or the extent of seasonal shifts during the non-breeding period, particularly among species and across communities with both residents and migrants. We measured carbon and nitrogen stable isotope values in food items (fruits, C3 and C4 seeds, and insects from various trophic levels and plant communities) and in multiple tissues (feathers and plasma/whole blood) from 11 species of songbirds wintering in the southeastern U.S. We combined these diet and tissue values with empirically derived discrimination factors and used concentration-dependent mixing models to quantify seasonal diet shifts. We also validated mixing model results with data from fecal samples. Diets in this bird community, as delineated N and C isotopic space, diverged in the fall and winter relative to the summer as consumption of fruits and seeds increased. Across this songbird community, estimated contributions of fruit to plasma/whole blood increased from 16.2 ± 7.5% in the fall (mean ± SD; range: 4–26%) to 21.7 ± 10.3% (range: 9–37%) in the winter, while contributions of seeds increased from 29.4 ± 2.6% (range: 28–32%) in the fall to 36.6 ± 4.8% (range: 32–42%) in the winter. Fecal data showed qualitatively similar trends to mixing models, but consistently estimated higher contributions of fruit. Our work indicates that fruits and seeds constitute substantial sources of sustenance for non-breeding songbirds, there is considerable separation of resource use among species in the fall and winter, and fecal estimates of contributions to songbird tissues should be interpreted cautiously.

54 ENVIRONMENTAL SCIENCES↗

Impact of dry intrusion events on the composition and mixing state of particles during the winter Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA)

Abstract. Long-range transport of continental emissions has a far-reaching influence over remote regions, resulting in substantial change in the size, morphology, and composition of the local aerosol population and cloud condensation nuclei (CCN) budget. Here, we investigate the physicochemical properties of atmospheric particles collected on board a research aircraft flown over the Azores during the winter 2018 Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) campaign. Particles were collected within the marine boundary layer (MBL) and free troposphere (FT) after long-range atmospheric transport episodes facilitated by dry intrusion (DI) events. Chemical and physical properties of individual particles were investigated using complementary capabilities of computer-controlled scanning electron microscopy and X-ray spectromicroscopy to probe particle external and internal mixing state characteristics. Furthermore, real-time measurements of aerosol size distribution, cloud condensation nuclei (CCN) concentration, and back-trajectory calculations were utilized to help bring into context the findings from offline spectromicroscopy analysis. While carbonaceous particles were found to be the dominant particle type in the region, changes in the percent contribution of organics across the particle population (i.e., external mixing) shifted from 68 % to 43 % in the MBL and from 92 % to 46 % in FT samples during DI events. This change in carbonaceous contribution is counterbalanced by the increase in inorganics from 32 % to 57 % in the MBL and 8 % to 55 % in FT. The quantification of the organic volume fraction (OVF) of individual particles derived from X-ray spectromicroscopy, which relates to the multi-component internal composition of individual particles, showed a factor of 2.06 ± 0.16 and 1.11 ± 0.04 increase in the MBL and FT, respectively, among DI samples. We show that supplying particle OVF into the κ-Köhler equation can be used as a good approximation of field-measured in situ CCN concentrations. We also report changes in the κ values in the MBL from κMBL, non-DI=0.48 to κMBL, DI=0.41, while changes in the FT result in κFT, non-DI=0.36 to κFT, DI=0.33, which is consistent with enhancements in OVF followed by the DI episodes. Our observations suggest that entrainment of particles from long-range continental sources alters the mixing state population and CCN properties of aerosol in the region. The work presented here provides field observation data that can inform atmospheric models that simulate sources and particle composition in the eastern North Atlantic.

54 ENVIRONMENTAL SCIENCES↗

Effects of High-frequency Wind Sampling on Simulated Mixed Layer Depth and Upper Ocean Temperature

Effects of high-frequency wind sampling on a near-global ocean model are studied by forcing the model with a 12 hourly averaged wind product and its 24 hourly subsamples in separate experiments. The differences in mixed layer depth and sea surface temperature resulting from these experiments are examined, and the underlying physical processes are investigated. The 24 hourly subsampling not only reduces the high-frequency variability of the wind but also affects the annual mean wind because of aliasing. While the former effect largely impacts mid- to high-latitude oceans, the latter primarily affects tropical and coastal oceans. At mid- to high-latitude regions the subsampled wind results in a shallower mixed layer and higher sea surface temperature because of reduced vertical mixing associated with weaker high-frequency wind. In tropical and coastal regions, however, the change in upper ocean structure due to the wind subsampling is primarily caused by the difference in advection resulting from aliased annual mean wind, which varies with the subsampling time. The results of the study indicate a need for more frequent sampling of satellite wind measurement and have implications for data assimilation in terms of identifying the nature of model errors.

mixed layered depth↗

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗

Theoretical Study of CH3Cl-N2 Line Shapes in the ν1 Band. Line Mixing Effects in QR Doublets and QQk Sub-Branches

Line coupling and line mixing effects of CH3Cl lines in the ν1 band perturbed by N2 have been investigated. We have taken into account the non-diagonality of the exp(−S2) operator within specified line spaces as well as the k-degeneracy of the transitions (due to the double degeneracy of the j,k levels with k ≠ 0). These transitions should be considered as doublets coupled by the line mixing process. A new problem appears in the calculation when the atom-atom potential model is introduced. In order to overcome this difficulty, a pragmatic approach is proposed. Comparisons of theoretically calculated matrix elements of W with measurements of QR(j,k) doublets as well as some QQk sub-branches, which are strongly affected by line mixing, have been made. The results show that the formalism improved in this way leads to rather accurate predictions.

Methyl chloride↗

Implicit Large-Eddy Simulations of Compressible Mixing Layers

Implicit large-eddy simulations of the self-similar regions of two compressible mixing layers at high Reynolds number and convective Mach numbers of 0.381 and 0.690 were carried out. Experimental data was used as the input into a synthetic eddy method turbulent inflow boundary condition to initiate simulations. Computational grids with nearly isotropic cells were used and the grid counts ranged from 24 to 270 million points. Agreement with experimental velocity and Reynolds stress data was good given the simplifications of the simulation. The decrease in mixing layer growth rate with increasing compressibility compares well with the literature. Budgets for the Reynolds stress transport equation were extracted from the simulations. It was demonstrated that the grids used did not resolve the dissipation term at the experimental Reynolds number. However, low Reynolds number simulations indicate that the numerical dissipation replaces the physical dissipation and the dissipation term in the transport equation can be represented by the summation term that quantifies the imbalance in the budget. The budgets for the high Reynolds number mixing layers agree well with previous low Reynolds number studies; indicating that the primary mechanism for the reduced growth rate and increased anistropy of the Reynolds stress tensor due to compressibility is a reduction in the pressure-strain and production terms. A new scaling based on the magnitude of the Reynolds stress tensor is proposed. This scaling provides better relative comparisons between the data and shows that the decrease in pressure-strain in the shear component is the primary driver in reducing the transverse normal stress.

turbulence↗

Mixed Reality Training and Workspace Integration

Mixed reality technology is being used across Idaho National Laboratory (INL) to enhance training and workforce development. Projects involving mixed reality such as lockout/tagout , the Industrial Control System Laboratory , and a Department of Defense microreactor demonstration have benefited from these innovative approaches. Several key concerns exist with integrating this new technology, including ease of use, ease of setup, and maintenance through the lifecycle. These aspects need to be properly addressed to ensure that this technology remains attractive and useful to operations teams as well as engineers and researchers at INL. Primarily, this requires buy-in from information technology management, designing software/hardware-agnostic tools, and reducing friction with technology integration. To be successful, regular operational use of this new and unfamiliar technology will require straightforward user interfaces, simple setup processes, and feature-rich experiences that reduce the time needed to benefit from the technology. INL is improving its toolset to allow for a streamlined deployment and use of mixed reality technologies that are directly available to researchers and engineers.

99 GENERAL AND MISCELLANEOUS↗

Iodine Electrochemistry Dictates Voltage‐Induced Halide Segregation Thresholds in Mixed‐Halide Perovskite Devices

Abstract Owing to straightforward stoichiometry–bandgap tunability, mixed‐halide perovskites are ideal for many optoelectronic devices. However, unwanted halide segregation under operational conditions, including light illumination and voltage bias, restricts practical use. Additionally, the origin of voltage‐induced halide segregation is still unclear. Herein, a systematic voltage threshold study in mixed bromide/iodide perovskite devices is performed and leads to observation of three distinct voltage thresholds corresponding to the doping of the hole transport material (0.7 ± 0.1 V), halide segregation (0.95 ± 0.05 V), and degradation (1.15 ± 0.05 V) for an optically stable mixed‐halide perovskite composition with a low bromide content (10%). These empirical threshold voltages are minimally affected by composition until very Br‐rich compositions, which reveals the dominant role of iodide/triiodide/iodine electrochemistry in voltage‐induced Br/I phase separation and transport layer doping reactions in halide perovskite devices.

36 MATERIALS SCIENCE↗

The Role of Side Chains and Hydration on Mixed Charge Transport in n ‐Type Polymer Films

Abstract Introducing ethylene glycol (EG) side chains to a conjugated polymer backbone is a well‐established synthetic strategy for designing organic mixed ion‐electron conductors (OMIECs). However, the impact that film swelling has on mixed conduction properties has yet to be scoped, particularly for electron‐transporting (n‐type) OMIECs. Here, the authors investigate the effect of the length of branched EG chains on mixed charge transport ofn‐type OMIECs based on a naphthalene‐1,4,5,8‐tetracarboxylic‐diimide‐bithiophene backbone. Atomic force microscopy (AFM), grazing‐incidence wide‐angle X‐ray scattering (GIWAXS), and scanning tunneling microscopy (STM) are used to establish the similarities between the common‐backbone films in dry conditions. Electrochemical quartz crystal microbalance with dissipation monitoring (EQCM‐D) and in situ GIWAXS measurements reveal stark changes in film swelling properties and microstructure during electrochemical doping, depending on the side chain length. It is found that even in the loss of the crystallite content upon contact with the aqueous electrolyte, the films can effectively transport charges and that it is rather the high water content that harms the electronic interconnectivity within the OMIEC films. These results highlight the importance of controlling water uptake in the films to impede charge transport inn‐type electrochemical devices.

Chemistry↗

Generalization of thermodynamic Langmuir isotherm for mixed‐gas adsorption equilibria

Abstract This work presents a comprehensive thermodynamic model for both pure component isotherms and mixed‐gas adsorption equilibria. A generalization of thermodynamic Langmuir isotherm, the proposed model assumes competitive adsorption of multiple adsorbates on adsorbent surface for mixed‐gas adsorption equilibria, and it applies an area‐based adsorption nonrandom two‐liquid activity coefficient model in the activity coefficient calculations for the adsorbate phase. The resulting generalized Langmuir isotherm properly captures both surface loading dependence and adsorbate phase composition dependence for mixed‐gas adsorption equilibria. The model is validated with accurate representations of gas adsorption equilibrium data for varieties of unary, binary, and ternary gas systems. The model results are further compared with those calculated from extended Langmuir isotherm and Ideal Adsorbed Solution Theory.

Hamid, Usman↗

Mixed‐Valence Cu I /Cu III Metal–Organic Frameworks with Non‐innocent Ligand for Multielectron Transfer

Abstract We report two novel three‐dimensional copper‐benzoquinoid metal–organic frameworks (MOFs), [Cu 4 L 3 ] n and [Cu 4 L 3 ⋅ Cu(iq) 3 ] n (LH 4 =1,4‐dicyano‐2,3,5,6‐tetrahydroxybenzene, iq=isoquinoline). Spectroscopic techniques and computational studies reveal the unprecedented mixed valency in MOFs, formal Cu(I)/Cu(III). This is the first time that formally Cu(III) species are witnessed in metal–organic extended solids. The coordination between the mixed‐valence metal and redox‐non‐innocent ligand L, which promotes through‐bond charge transfer between Cu metal sites, allows better metal‐ligand orbital overlap of the d‐π conjugation, leading to strong long‐range delocalization and semiconducting behavior. Our findings highlight the significance of the unique mixed valency between formal Cu(I) and highly‐covalent Cu(III), non‐innocent ligand, and pore environments of these bench stable Cu(III)‐containing frameworks on multielectron transfer and electrochemical properties.

Fu, Shang‐Yuan↗

Closed‐Loop Recycling of Mixed Plastics of Polyester and CO 2 ‐Based Polycarbonate to a Single Monomer

Abstract Physical blending is an effective strategy for tailoring polymeric materials to specific application requirements. However, physically blended mixed plastics waste adds additional barriers in mechanical or chemical recycling. This difficulty arises from the intricate requirement for meticulous sorting and separation of the various polymers in the inherent incompatibility of mixed polymers during recycling. To overcome this impediment, this work furthers the emerging single‐monomer – multiple‐materials approach through the design of a bifunctional monomer that can not only orthogonally polymerize into two different types of polymers – specifically lactone‐based polyester and CO 2 ‐based polycarbonate – but the resultant polymers and their mixture can also be depolymerized back to the single, original monomer when facilitated by catalysis. Specifically, the lactone/epoxide hybrid bifunctional monomer (BiL O ) undergoes ring‐opening polymerization through the lactone manifold to produce polyester, PE(BiL O ), and is also applied to ring‐opening copolymerization with CO 2 , via the epoxide manifold, to yield polycarbonate, PC(BiL O ). Remarkably, a one‐pot recycling process of a BiL O ‐derived PE/PC blend back to the constituent monomer BiL O in >99 % selectivity was achieved with a superbase catalyst at 150 °C, thereby effectively obviating the requirement for sorting and separation typically required for recycling of mixed polymers.

Shi, Changxia↗

Mixed‐Valence Cu I /Cu III Metal–Organic Frameworks with Non‐innocent Ligand for Multielectron Transfer

Abstract We report two novel three‐dimensional copper‐benzoquinoid metal–organic frameworks (MOFs), [Cu 4 L 3 ] n and [Cu 4 L 3 ⋅ Cu(iq) 3 ] n (LH 4 =1,4‐dicyano‐2,3,5,6‐tetrahydroxybenzene, iq=isoquinoline). Spectroscopic techniques and computational studies reveal the unprecedented mixed valency in MOFs, formal Cu(I)/Cu(III). This is the first time that formally Cu(III) species are witnessed in metal–organic extended solids. The coordination between the mixed‐valence metal and redox‐non‐innocent ligand L, which promotes through‐bond charge transfer between Cu metal sites, allows better metal‐ligand orbital overlap of the d‐π conjugation, leading to strong long‐range delocalization and semiconducting behavior. Our findings highlight the significance of the unique mixed valency between formal Cu(I) and highly‐covalent Cu(III), non‐innocent ligand, and pore environments of these bench stable Cu(III)‐containing frameworks on multielectron transfer and electrochemical properties.

Fu, Shang‐Yuan↗