A1model for chemically reacting nitrogen- oxygen mixtures with application to nonequilibrium air flow
Model for chemically reacting nitrogen-oxygen mixtures - application to computation of chemical nonequilibrium in air flow field
FLOW FIELD↗
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Results for “Mixture modeling”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A simplified chemical model for estimating the nonequilibrium radiant emission of CN /violet/ in shock-heated mixtures of CO sub 2 and N sub 2.
Chemical model for CN nonequilibrium radiant emission intensity profiles in shock heated mixture of N and carbon dioxide
Mckenzie, R. L.↗
Altering the Supply of Shielding Gases to Fabricate Distinct Geometry in GMA Additive Manufacturing
Wire arc additive manufacturing (WAAM) is the process by which large, metallic structures are built, layer-by-layer, using a welding arc to melt wire feedstock. In this process, the proper selection of the shielding gas plays a vital role in the achievement of structurally acceptable part geometries and quality surface finishes. In this study, the authors used either a ternary mix (He, Ar and CO 2 ) or a binary mix (Ar and CO 2 ) of shielding gases to deposit wall geometries using an open loop-controlled WAAM system developed at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility. The binary blend produced a wider and shorter geometry, while the ternary blend resulted in a narrower build that was more equivalent to the CAD geometry. The data indicated that the binary blend provided a higher oxygen concentration in the weld as compared to that of the ternary blend. The results imply that the arc characteristics and heat input had a significantly higher impact on the weld penetration than the surface tension effect of surface active elements. This was further verified by developing and applying a high-fidelity computational fluid dynamics (CFD) model of the thermophysical properties of gas mixtures. The results from the model showed that, while the influence of increased oxygen concentration on the surface tension for the binary blend led to a deeper penetration, the ternary blend gave rise to heat flux to the workpiece.
36 MATERIALS SCIENCE↗
Data-Driven Many-Body Models for Molecular Fluids: CO 2 /H 2 O Mixtures as a Case Study
In this study, we extend the scope of the many-body TTM-nrg and MB-nrg potential energy functions (PEFs), originally introduced for halide ion–water and alkali-metal ion–water interactions, to the modeling of carbon dioxide (CO2) and water (H2O) mixtures as prototypical examples of molecular fluids. Both TTM-nrg and MB-nrg PEFs are derived entirely from electronic structure data obtained at the coupled cluster level of theory and are, by construction, compatible with MB-pol, a many-body PEF that has been shown to accurately reproduce the properties of water. Although both TTM-nrg and MB-nrg PEFs adopt the same functional forms for describing permanent electrostatics, polarization, and dispersion, they differ in the representation of short-range contributions, with the TTM-nrg PEFs relying on conventional Born–Mayer expressions and the MB-nrg PEFs employing multidimensional permutationally invariant polynomials. By providing a physically correct description of many-body effects at both short and long ranges, the MB-nrg PEFs are shown to quantitatively represent the global potential energy surfaces of the CO 2 –CO 2 and CO 2 –H 2 O dimers and the energetics of small clusters, as well as to correctly reproduce various properties in both gas and liquid phases. Furthermore, building upon previous studies of aqueous systems, our analysis provides further evidence for the accuracy and efficiency of the MB-nrg framework in representing molecular interactions in fluid mixtures at different temperature and pressure conditions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Parameterization of Cloud Optical Properties for a Mixture of Ice Particles for use in Atmospheric Models
Based on the single-scattering optical properties that are pre-computed using an improve geometric optics method, the bulk mass absorption coefficient, single-scattering albedo, and asymmetry factor of ice particles have been parameterized as a function of the mean effective particle size of a mixture of ice habits. The parameterization has been applied to compute fluxes for sample clouds with various particle size distributions and assumed mixtures of particle habits. Compared to the parameterization for a single habit of hexagonal column, the solar heating of clouds computed with the parameterization for a mixture of habits is smaller due to a smaller cosingle-scattering albedo. Whereas the net downward fluxes at the TOA and surface are larger due to a larger asymmetry factor. The maximum difference in the cloud heating rate is approx. 0.2 C per day, which occurs in clouds with an optical thickness greater than 3 and the solar zenith angle less than 45 degrees. Flux difference is less than 10 W per square meters for the optical thickness ranging from 0.6 to 10 and the entire range of the solar zenith angle. The maximum flux difference is approximately 3%, which occurs around an optical thickness of 1 and at high solar zenith angles.
Chou, Ming-Dah↗
Liquid nanostructure of choline lysinate with water and a model lignin residue
The structure of the ionic liquid choline lysinate ([Ch][Lys]) and its water mixtures, including a dissolved model lignin residue, guaiacol, is revealed at atomic and nanoscale resolution using neutron diffraction.
Jiang, Haihui Joy↗
Formation of Large Regular Satellites of Giant Planets in an Extended Gaseous Nebula: Subnebula Model and Accretion of Satellites
We model the subnebulae of Jupiter and Saturn wherein satellite accretion took place. We expect a giant planet subnebula to be composed of an optically thick (given gaseous opacity) inner region inside of the planet's centrifugal radius (located at r(sub c, sup J) = l5R(sub J) for Jupiter and r(sub c, sup S) = 22R(sub S) for Saturn), and an optically thin, extended outer disk out to a fraction of the planet's Roche lobe, which we choose to be R(sub roche)/5 (located at approximately 150R(sub J) near the inner irregular satellites for Jupiter, and approximately 200R(sub S) near Phoebe for Saturn). This places Titan and Ganymede in the inner disk, Callisto and Iapetus in the outer disk, and Hyperion in the transition region. The inner disk is the leftover of the gas accreted by the protoplanet. The outer disk results from the solar torque on nebula gas flowing into the protoplanet during the time of giant planet gap opening. For the sake of specificity, we use a cosmic mixture 'minimum mass' model to constrain the gas densities of the inner disks of Jupiter and Saturn (and also Uranus). For the total mass of the outer disk we use the simple scaling M(sub disk) = M(sub P)tau(sub gap)/tau(sub acc), where M(sub P) is the mass of the giant planet, tau(sub gap) is the gap opening timescale, and tau(sub acc) is the giant planet accretion time. This gives a total outer disk mass of approximately 100M(sub Callisto) for Jupiter and possibly approximately 200M(sub Iapetus) for Saturn (which contain enough condensables to form Callisto and Iapetus respectively). Our model has Ganymede at a subnebula temperature of approximately 250 K and Titan at approximately 100 K. The outer disks of Jupiter and Saturn have constant temperatures of 130 K and 90 K respectively.
Mosqueira, I.↗
Uncertain characterization of reservoir fluids due to brittleness of equation of state regression
Equations of state (EoS) play a central role in modeling the phase equilibrium of fluid mixtures. Their parameterization involves fitting a model to experimental data, i.e., solving a nonlinear, non-convex, multivariate optimization problem. The latter requires one to select design variables, domains of definition for each variable, and weights assigned to individual measurements. We demonstrate that subjective choices of an optimization algorithm and an initial guess also impact the regression process. Consequently, EoS predictions are fundamentally uncertain even after the EoS tuning to a limited set of experimental data points. We demonstrate this observation for two hydrocarbon reservoir fluids, in which five properties of the heaviest carbon fraction are treated as design variables. While all the optimization algorithms and initial guesses match experimental data for the gas and liquid properties, the resulting EoS parameterizations lead to dramatically different predictions of the fluid’s thermophysical behavior in the unsampled pressure and temperature regions. In conclusion, we propose the probabilistic treatment of design variables to quantify the predictive uncertainty of the resulting fluid models.
15 GEOTHERMAL ENERGY↗
Rapid Coal-Ash Characterization using Geophysical Methods & Machine Learning
Coal combustion products (CCP) are challenging to delineate in heterogeneous field settings. Conventional methods (test pits, coring, and laboratory analyses) are labor-intensive, slow, invasive, and provide sparse spatial coverage. This study evaluates whether rapid non-invasive geophysical screening methods—induced polarization (IP), magnetic susceptibility, and nuclear magnetic resonance (NMR) —combined with surface colorimetry (RGB_24), can discriminate CCP-soil mixtures and provide reliable estimates of CCP content. Laboratory measurements were collected on five CCP-soil mixtures (series) and modeled using (i) a linear baseline, (ii) a calibrated non-linear (power-mean) model, and (iii) a machine-learning (ML) Random Forest approach, with validation via leave-one-series-out and site-specific tests. Across the five series, individual signals—particularly IP and magnetic susceptibility—were strongly predictive of ash content but were consistently outperformed by combined models. The pooled calibrated non-linear and ML models captured the observed non-linearity and achieved high accuracy and precision, improving on linear fits. Colorimetry showed the weakest direct relationship with ash content for the tested samples but improved performance when included in multi-signal models. At pre-selected 3.5% decision threshold, calibrated and ML approaches yielded near-perfect classification (Matthews correlation coefficient ˜ 1), suggesting strong practical operability for field screening. Additionally, field-analog tests highlighted the role of endmembers—accuracy declined without access to end-member measurements but was largely recovered by collecting a minimal labeled pair for local recalibration. With end members, accuracy remained high. Globally trained models performed well on three operational unknowns; however, series-specific refits provided the most accurate predictions. Overall, these results highlight the potential of combining rapid geophysics and minimal local calibration for improved coal-ash delineation.
Peshtani, Klaudio↗
Assessment of simulated and observed cavitation-induced erosion damage in Spallation Neutron Source target vessels
Cavitation-induced erosion damage in different Spallation Neutron Source (SNS) target designs are simulated using explicit finite element–based techniques and compared with observations of erosion in targets after operation. The efficacy of the previously developed method, called saturation time, was evaluated using erosion-damaged samples from new target designs. A new metric called maximum bubble size was implemented under the rationale that larger cavitation bubbles will collapse more intensely. The maximum cavitation bubble size over 1 ms of simulated time was calculated based on the Rayleigh–Plesset equation for each element integration point and presented as a contour map at the vessel surface for assessing with erosion observations. SNS targets are now operated with helium gas injection to reduce cavitation damage. A simulation method using a material model for the mixture of mercury and gas bubbles was recently developed and used to account for the effect of small gas bubbles on the structural response of the target vessel. Furthermore, this work compares the new method's results with observed cavitation damage. Maps of the calculated maximum bubble size for targets operated with and without gas injection were compared with photographs of erosion damage observed in SNS targets. The patterns in maximum bubble size maps correlated well with observations of erosion patterns in target vessels after service. Advantages and challenges of the maximum bubble size simulation technique are provided, and differences between results from the previous and the newly proposed metric are discussed.
Jiang, Hao↗
Capturing Deuteration Effects in a Molecular Mechanics Force Field: Deuterated THF and the THF–Water Miscibility Gap
Deuteration is a common chemical modification used in conjunction with experiments such as neutron scattering, NMR, and Fourier-transform infrared for the study of molecular systems. Under the Born–Oppenheimer (BO) approximation, while the underlying potential energy surface remains unchanged by isotopic substitutions, isotopic substitution still alters intramolecular vibrations, which in turn may alter intermolecular interactions. Molecular mechanics (MM) force fields used in classical molecular dynamics simulations are assumed to represent local approximations of the BO potential energy surfaces, and hence, MD simulations using simple isotopic mass substitutions should capture BO-compatible isotope effects. However, standard MM force-field parameterizations do not directly fit to the local harmonic quantum mechanical (QM) Hessian that describes the BO surface, but rather to QM normal-modes and/or mass-dependent internal-coordinate derived distortion energies. In this study, using tetrahydrofuran (THF)–water mixtures as our model system, we show that not only does a simple mass-substitution approach fail to capture an experimentally characterized deuteration effect (the loss of the closed-loop miscibility gap associated with the complete deuteration of THF) but also it is necessary to generate new MM force-field parameters that correctly describe isotopic dependent vibrations to capture the experimental deuteration effect. We show that the origin of this failure is a result of using mass-dependent features to fit the THF MM force field, which unintentionally biases the bonded terms of the force field to represent only the isotopologue used during the original force-field parameterization. In addition, we make use of our isotopologue-corrected force field for D 8 THF to examine the molecular origins of the isotope-dependent loss of the THF–water miscibility gap.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Molecular-scale origins of wettability at petroleum–brine–carbonate interfaces
Wettability control of carbonates is a central concept for enhanced petroleum recovery, but a mechanistic understanding of the associated molecular-scale chemical processes remains unclear. We directly probe the interface of calcium carbonate (calcite) with natural petroleum oil, synthetic petroleum analogues, and aqueous brines to understand the molecular scale behavior at this interface. The calcite–petroleum interface structure is similar whether or not calcite was previously exposed to an aqueous brine, and is characterized by an adsorbed interfacial layer, significant structural changes within the calcite surface, and increased surface roughness. No evidence for an often-assumed thin-brine wetting layer at the calcite–petroleum interface is observed. These features differ from those observed at the calcite–brine interface, and for parallel measurements using model synthetic petroleum mixtures (consisting of representative components, including dodecane, toluene, and asphaltene). Changes to the interface after petroleum displacement by aqueous brines are also discussed.
02 PETROLEUM↗
Emergence of Lanes and Turbulent-like Motion in Active Spinner Fluid
Assemblies of self-rotating particles are gaining interest as a novel realization of active matter with unique collective behaviors such as edge currents and non-trivial dynamic states. Here, we develop a continuum model for a system of fluid-embedded spinners by coarse-graining the equations of motion of the discrete particles. We apply the model to explore mixtures of clockwise and counterclockwise rotating spinners. We find that the dynamics is sensitive to fluid inertia: in the inertialess system, after transient turbulent-like motion the spinners segregate and form steady traffic lanes. At small but finite Reynolds number instead, the turbulent-like motion persists and the system exhibits a chirality breaking transition leading to a single rotation sense state. Our results shed light on the dynamic behavior of non-equilibrium materials exemplified by active spinners.
36 MATERIALS SCIENCE↗
Compression behavior of dense H 2 -He mixtures up to 160 GPa
We have studied the compression behavior of H 2 -He mixtures in comparison with pure H 2 and He using powder synchrotron x-ray diffraction and present the pressure-volume (PV) compression data of H 2 -He mixtures to 160 GPa. The results indicate that both H 2 and He in H 2 -He mixtures remain in hcp to the maximum pressure studied, yet develop a substantial level of lattice distortion in the (100) plane, most profound in He-rich solids and below 66 GPa. The measured PV data also indicate softening of He (or H 2 )-rich lattice upon increasing the level of the guest H 2 (or He) concentration. We suggest that the observed softening and lattice distortion are due to a substitutional incorporation of H2 (guest) molecules into the basal plane of hcp-He (host) lattice and, thereby, reflect the miscibility between H 2 and He in H 2 -He mixtures. Interestingly, solid He exhibits a lesser degree of preferred orientation in H2-He mixtures than in pure He, likely due to the presence of solid H 2 disturbing the crystalline ordering of He-rich solids. Finally, the present PV compression data of H 2 -rich and He-rich solids to 160 GPa deviate from those of pure H 2 and pure He above ~70 and 45 GPa respectively, providing new constraints for development of the EOS for H 2 -He mixtures for planetary models.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Generalized master equation for particle transport in binary random media with renewal statistics
Particle transport in binary stochastic mixtures is classically modeled assuming Markovian or exponential mixing statistics but in many applications material memory invalidates the Markov assumption. For non-Markovian mixing characterized by alternating renewal processes, a transport-theoretic framework is presented that provides an exact description of transport in nonscattering random binary media with general non-exponential statistics. Our approach is to Markovianize the problem by augmenting the {material type, particle flux} state space with the age or distance from the last interface. A Chapman-Kolmogorov equation is formulated for the joint probability density of the material type, particle flux, and age, and subsequently reduced to a generalized Master equation (GME) in differential form. This constitutes the primary result of this work. A state-updating Monte Carlo algorithm consistent with the GME is developed and benchmarked against analytical solutions for multiple chord-length laws. For purely absorbing renewal statistical media, the GME reproduces analytical benchmarks for the equilibrium age distribution, interior mean/variance of material-conditioned fluxes, and boundary transmittance. Simulations further demonstrate that a Markov (exponential) approximation of non-exponential statistics can introduce large errors in transmittance and interior flux profiles. Lastly, the reintroduction of memory due to scattering is briefly addressed through heuristic considerations.
Fluctuations & noise↗
PhILMs: Collaboratory on Mathematics and Physics-Informed Learning Machines for Multiscale and Multiphysics Problems
The landscape of computational science and engineering is continually evolving, with the challenge of high-dimensional regression problems standing as a significant hurdle in numerous scientific endeavors. Addressing this challenge, our research, funded by this award, has led to the development of an innovative computational framework known as Probabilistic Partition of Unity Networks (PPOU-Nets). This initiative represents a collaborative effort to harness the potential of mathematics and physics-informed machine learning in tackling multiscale and multiphysics problems prevalent in high-dimensional spaces. Through this work, we have proposed a novel methodology that seamlessly integrates adaptive dimensionality reduction and a mixture of experts model, thereby facilitating a more efficient and accurate approximation of complex functions. This research effort has not only advanced the state of computational science but also opened new avenues for exploration in quantum computing and beyond. This report outlines the motivation, methodology, key findings, and implications of our work, underscoring our contributions to the broader scientific community and the potential pathways for future research.
97 MATHEMATICS AND COMPUTING↗
Dynamics of an explosive reaction center
Gas dynamic effects of reaction center in explosive gas mixture analyzed by model and numerical computation
Oppenheim, A. K.↗
Microwave emission and scattering from vegetated terrain
Models are developed for the apparent temperature and backscattering coefficient of vegetated terrain to illustrate the effects of vegetation on the sensitivity of these parameters to variations of soil moisture. Three types of terrain are simulated for both the passive and the active case: a uniform canopy over a smooth surface, plant rows on a smooth surface, and plant rows on a rough surface. In each case the canopy is defined by its overall dimensions and by its electric permittivity, which is determined from Weiner model for dielectric mixture. Emission and scattering from both the soil and the canopy are considered, but atmospheric effects are neglected. Calculated data indicate that the sensitivity of the apparent temperature and backscattering coefficient to variations of soil moisture, decreases as the amount of vegetation increases. It is shown that the same effect results from increasing signal frequency or angle of incidence.
Sibley, T. G.↗