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At least 631 records · Page 35

Application of Linear Additive Conditions for Near-Infrared Diffuse Reflectance Absorption Spectroscopy

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.

Feng, Zhiyue↗

Enhancing photoionization rate calculations in low-temperature plasmas using spectral methods

Photoionization plays a central role in the development of streamer discharges and other non-equilibrium plasma phenomena. It creates seed electrons, which are essential for positive streamer propagation, allowing the ionization front to move forward. Because of this, accurate modeling of photoionization is very important for predicting streamer behavior and plasma evolution. The photoionization process in air (N 2 – O 2 mixture) is often described by the Zheleznyak model (1982). This model is usually solved through Helmholtz-type equations that approximate the Zheleznyak photoionization model (Zheleznyak et al. 1982) as Partial Differential Equations (PDEs). Conventional numerical methods, such as the Finite Difference Method (FDM) or Finite Volume Method (FVM), are widely used to solve these equations. Although they are prevalent, the computational cost of these methods due to their need for matrix operations and iterative solver is demanding. To address this challenge, this work develops a spectral solver based on the Fast Fourier Transform (FFT) combined with Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) to calculate the photoionization rate efficiently in an axisymmetric cylindrical domain. This method naturally satisfies the boundary conditions used in the model and converts the PDE into algebraic ones in spectral space. Thus, avoids the need for iterative matrix solvers. When compared with FDM results, it is demonstrated that the new solver not only maintains accuracy, but also reduces the computational cost, showing a performance increase of approximately 100 compared to FDM over a wide range of problem sizes. The method is parallelized using Message Passing Interface (MPI) and has been integrated into a fluid plasma model for streamer simulation. Here, this FFT-based approach provides a fast and reliable alternative for calculating photoionization in fluid models, helping large-scale plasma simulations run faster and efficiently, and allows higher-resolution simulation without extra computational cost.

Axisymmetric system↗

Geoid Anomalies and Dynamic Topography from Time Dependent, Spherical Axisymmetric Mantle Convection

Geoid anomalies and dynamic topography are two important diagnostics of mantle convection. We present geoid and topography results for several time-dependent convection models in spherical axisymmetric geometry for Rayleigh numbers between 10(exp 6) and 10(exp 7) with depth-dependent viscosity and mixtures of bottom and internal heating. The models are strongly chaotic, with boundary layer instabilities erupting out of both thermal boundary layers. In some instances, instabilities from one boundary layer influence the development of instabilities in the other boundary layer. Such coupling between events at the top and bottom of the mantle has been suggested to play a role in a mid-Cretaceous episode of enhanced volcanism in the Pacific. These boundary layer instabilities produce large temporal variations in the geoid anomalies and dynamic nd to the topography associated with the convection. The amplitudes of these fluctuations depend on the detailed model parameter,.% it of this but fluctuations of 30-50% relative to the time-averaged geoid and topography are common. The convective planform is strongly sensitive to the specific initial conditions. Convection cells with larger aspect ratio tend to have larger fractional fluctuations in their geoid and topography amplitudes, because boundary layer instabilities have more time to develop in long cells. In some instances, we observe low-amplitude topographic highs adjacent to the topographic lows produced by cold downwellings. We discuss applications of these results to several situations, including the temporal variability of m basis. hotspots such as Hawaii, the topography of subduction zone outer rises, and the topography of coronae on Venus.

Kiefer, Walter S.↗

A fluctuating hydrodynamics model for nanoscale surfactant-laden interfaces

A multispecies diffuse interface model is formulated in a fluctuating hydrodynamics framework for the purpose of simulating surfactant interfaces at the nanoscale. The model generalizes previous work to ternary mixtures, employing a Cahn-Hilliard free energy density combined with incompressible, isothermal fluctuating hydrodynamics where dissipative fluxes include both deterministic and stochastic terms. The intermolecular parameters in the free energy are chosen such that one species acts as a partially miscible surfactant. From Laplace pressure measurements, we show that in this model the surface tension decreases linearly with surfactant concentration, leading to Marangoni convection for interfaces with concentration gradients. In the capillary wave spectrum for interfaces with and without surfactant, we find that for the former, the spectrum deviates significantly from classical capillary wave theory, presumably due to Gibbs elasticity. In non-equilibrium simulations of the Rayleigh-Plateau instability, deterministic simulations showed that the surfactant delays pinching of a fluid cylinder into droplets. However, stochastic simulations indicate that thermal fluctuations disrupt the surfactant's stabilizing effect. Similarly, the spreading of a patch of surfactant, driven by Marangoni convection, was found to be partially suppressed by thermal fluctuations.

Capillary waves↗

Combined Experimental/Numerical Study of the Soot Formation Process in a Gasoline Direct-Injection Spray in the Presence of Laser-Induced Plasma Ignition

Here, combustion issued from an eight-hole, direct-injection spray was experimentally studied in a constant-volume pre-burn combustion vessel using simultaneous high-speed diffused back-illumination extinction imaging (DBIEI) and OH* chemiluminescence. DBIEI has been employed to observe the liquid-phase of the spray and to quantitatively investigate the soot formation and oxidation taking place during combustion. The fuel-air mixture was ignited with a plasma induced by a single-shot Nd:YAG laser, permitting precise control of the ignition location in space and time. OH* chemiluminescence was used to track the high-temperature ignition and flame. The study showed that increasing the delay between the end of injection and ignition drastically reduces soot formation without necessarily compromising combustion efficiency. For long delays between the end of injection and ignition (1.9 ms) soot formation was eliminated in the main downstream charge of the fuel spray. However, poorly atomized and large droplets formed at the end of injection (dribble) eventually do form soot near the injector even when none is formed in the main charge. The quantitative soot measurements for these spray and ignition scenarios, resolved in time and space, represents a significant new achievement. Reynolds-averaged Navier-Stokes (RANS) simulations were performed to assess spray mixing and combustion. An analysis of the predicted fuel-air mixture in key regions, defined based upon experimental observations, was used to explain different flame propagation speeds and soot production tendencies when varying ignition timing. The mixture analysis indicates that soot production can be avoided if the flame propagates into regions where the equivalence ratio (Φ) is already below 2. Reactive RANS simulations have also been performed, but with a poor match against the experiment, as the flame speed and heat-release rate are largely over estimated. This modeling weakness appears related to a very high level of turbulent viscosity predicted for the high-momentum spray in the RANS simulations, which is an important consideration for modeling ignition and flame propagation in mixtures immediately created by the spray.

42 ENGINEERING↗

Study of Unsteady, Sphere-Driven, Shock-Induced Combustion for Application to Hypervelocity Airbreathing Propulsion

A premixed, shock-induced combustion engine has been proposed in the past as a viable option for operating in the Mach 10 to 15 range in a single stage to orbit vehicle. In this approach, a shock is used to initiate combustion in a premixed fuel/air mixture. Apparent advantages over a conventional scramjet engine include a shorter combustor that, in turn, results in reduced weight and heating loads. There are a number of technical challenges that must be understood and resolved for a practical system: premixing of fuel and air upstream of the combustor without premature combustion, understanding and control of instabilities of the shock-induced combustion front, ability to produce sufficient thrust, and the ability to operate over a range of Mach numbers. This study evaluated the stability of the shock-induced combustion front in a model problem of a sphere traveling in a fuel/air mixture at high Mach numbers. A new, rapid analysis method was developed and applied to study such flows. In this method the axisymmetric, body-centric Navier-Stokes equations were expanded about the stagnation streamline of a sphere using the local similarity hypothesis in order to reduce the axisymmetric equations to a quasi-1D set of equations. These reduced sets of equations were solved in the stagnation region for a number of flow conditions in a premixed, hydrogen/air mixture. Predictions from the quasi-1D analysis showed very similar stable or unstable behavior of the shock-induced combustion front as compared to experimental studies and higher-fidelity computational results. This rapid analysis tool could be used in parametric studies to investigate effects of fuel rich/lean mixtures, non-uniformity in mixing, contaminants in the mixture, and different chemistry models.

Axdahl, Erik↗

Orbital transfer rocket engine technology: Advanced engine study

An advanced LOX/LH2 engine study for the use of NASA and vehicle prime contractors in developing concepts for manned missions to the Moon, Mars, and Phobos is documented. Parametric design data was obtained at five engine thrusts from 7.5K lbf to 50K lbf. Also, a separate task evaluated engine throttling over a 20:1 range and operation at a mixture ratio of 12 plus or minus 1 versus the 6 plus or minus 1 nominal. Cost data was also generated for DDT&E, first unit production, and factors in other life cycle costs. The major limitation of the study was lack of contact with vehicle prime contractors to resolve the issues in vehicle/engine interfaces. The baseline Aerojet dual propellant expander cycle was shown capable of meeting all performance requirements with an expected long operational life due to the high thermal margins. The basic engine design readily accommodated the 20:1 throttling requirement and operation up to a mixture ratio of 10 without change. By using platinum for baffled injector construction the increased thermal margin allowed operation up to mixture ratio 13. An initial engine modeling with an Aerojet transient simulation code (named MLETS) indicates stable engine operation with the baseline control system. A throttle ratio of 4 to 5 seconds from 10 percent to 100 percent thrust is also predicted. Performance predictions are 483.1 sec at 7.5K lbf, 487.3 sec at 20K lbf, and 485.2 sec at 50K lbf with a mixture ratio of 6 and an area ratio of 1200. Engine envelopes varied from 120 in. length/53 in. exit diameter at 7.5K lbf to 305 in. length/136 in. exit diameter at 50 K lbf. Packaging will be an important consideration. Continued work is recommended to include more vehicle prime contractor/engine contractor joint assessment of the interface issues.

Hayden, Warren R.↗

Fractional vortices, Z 2 gauge theory, and the confinement-deconfinement transition

Here, in this Letter we discuss the classical three-dimensional XY model whose nearest-neighbor interaction is a mixture of cos (θ i -θ j ) (ferromagnetic) and cos 2 (θ i -θ j ) (nematic). This model is dual to a theory with integer and half-integer vortices. While both types of vortices interact with a noncompact U(1) gauge field, the half-integer vortices interact with an extra interaction mediated by a Z 2 gauge field. We shall discuss the confinement-deconfinement transition of the half-integer vortices, the Wilson and the 't Hooft loops, and their mutual statistics in path integral language. In addition, we shall present a quantum version of the classical model which exhibits these physics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Inverse-Velocity Transformation Wall Model for Reacting Turbulent Hypersonic Boundary Layers

The present study builds on prior work by taking advantage of the novel framework proposed by Griffin et al. (hereafter referred to as the GFM) as a baseline. The model is progressively extended to multicomponent reacting mixtures, accounting for differential diffusion and finite-rate chemistry in a similar fashion to Di Renzo & Urzay and Di Renzo et al. The accuracy of the present approach, as well the prior model of Di Renzo & Urzay, is assessed in an a priori sense for the first time in a turbulent reacting boundary layer, using the boundary-layer data of Williams et al. Five species are included in the present analysis, i.e., N s = 5, namely N 2 , O 2 , NO, N and O, a neutral mixture most representative of dissociation/recombination phenomena for temperatures below 6000 K. A schematic of a flow over a wedge representative of the described configuration is presented in Figure 1. The brief is organized as follows: In Section 2, the wall-model equations and the computational framework are presented. In Section 3, the a priori results of the proposed model are described and compared to the extended EWM. Finally, in Section 4, some conclusions are offered.

97 MATHEMATICS AND COMPUTING↗

Understanding the variation in the millimeter-wave emission of Venus

Recent observations of the millimeter-wave emission from Venus at 112 GHz (2.6 mm) have shown significant variations in the continuum flux emission that may be attributed to the variability in the abundances of absorbing constituents in the Venus atmosphere. Such constituents include gaseous H2SO4, SO2, and liquid sulfuric acid (cloud condensates). Recently, Fahd and Steffes have shown that the effects of liquid H, SO4, and gaseous SO2 cannot completely account for this measured variability in the millimeter-wave emission of Venus. Thus, it is necessary to study the effect of gaseous H2SO4 on the millimeter-wave emission of Venus. This requires knowledge of the millimeter-wavelength (MMW) opacity of gaseous H2SO4, which unfortunately has never been determined for Venus-like conditions. We have measured the opacity of gaseous H2SO4 in a CO2 atmosphere at 550, 570, and 590 K, at 1 and 2 atm total pressure, and at a frequency of 94.1 GHz. Our results, in addition to previous centimeter-wavelength results are used to verify a modeling formalism for calculating the expected opacity of this gaseous mixture at other frequencies. This formalism is incorporated into a radiative transfer model to study the effect of gaseous H2SO4 on the MMW emission of Venus.

Fahd, Antoine K.↗

Chondrule-matrix relationships in chondritic meteorites

The relationship between chondrules and matrix (fine grained material with a grain size less than 5 micrometers) in chondritic meteorites has been the subject of considerable controversy and no consensus currently exists. The coexistence of these two components in meteorites with bulk compositions that deviate only slightly from CI abundances suggests that cosmochemically their origins are closely linked. Any consideration of the relationship between chondrules and matrix hinges to a large degree on the origin of matrix. The entire spectrum of models exists from matrix as a nebular product to derivation entirely from chondrules. Early models of solar nebular evolution viewed chondrites as a two-component mixture of high- and low-temperature condensates. However, this model has been challenged by the recognition that the nebula was probably not uniformly vaporized.

Brearley, A. J.↗

Air Density Measurements in a Mach 10 Wake Using Iodine Cordes Bands

An exploratory study designed to examine the viability of making air density measurements in a Mach 10 flow using laser-induced fluorescence of the iodine Cordes bands is presented. Experiments are performed in the NASA Langley Research Center 31 in. Mach 10 air wind tunnel in the hypersonic near wake of a multipurpose crew vehicle model. To introduce iodine into the wake, a 0.5% iodine/nitrogen mixture is seeded using a pressure tap at the rear of the model. Air density was measured at 56 points along a 7 mm line and three stagnation pressures of 6.21, 8.62, and 10.0 MPa (900, 1250, and 1450 psi). Average results over time and space show rho(sub wake)/rho(sub freestream) of 0.145 plus or minus 0.010, independent of freestream air density. Average off-body results over time and space agree to better than 7.5% with computed densities from onbody pressure measurements. Densities measured during a single 60 s run at 10.0 MPa are time-dependent and steadily decrease by 15%. This decrease is attributed to model forebody heating by the flow.

Balla, Robert J.↗

Thermosteam: BioSTEAM's Premier Thermodynamic Engine

Thermosteam is a thermodynamic engine capable of solving mass and energy balances, estimating mixture properties, solving thermodynamic phase equilibria, and modeling stoichiometric reactions. All chemical data in Thermosteam is imported from the chemicals library, an open-source compilation of data and functions for the estimation of pure component chemical and mixture properties. Thermosteam’s fast and flexible platform has enabled the evaluation of conceptual and emerging biochemical production processes. The Biorefinery Simulation and Techno-Economic Analysis Modules (BioSTEAM) — capable of modeling reactors, distillation columns, heat exchangers, and other unit operations — has adopted Thermosteam as its premier thermodynamic engine. Published biorefinery designs modeled in BioSTEAM implement thermodynamic property packages created with Thermosteam, including a cornstover biorefinery for the production of cellulosic ethanol, a lipid-cane biorefinery for the co-production of ethanol and biodiesel, and a wheatstraw biorefinery for the production of cellulosic ethanol.

97 MATHEMATICS AND COMPUTING↗

Design of Multi-Stage Solvent Extraction Process for Separation of Rare Earth Elements

Flowsheet design and stage determination for the separation of rare earth elements (REEs) using solvent extraction (SX) is a challenging task because of the chemical similarity of the REEs. Low separation factors between the elements and complex equilibrium chemistry provide unique challenges to designing an efficient flowsheet for the separation of elements. The multi-stage nature of the SX process adds further complexity, making the assessment of products for a proposed design and stage combination difficult. Therefore, to develop a SX flowsheet, it is essential to quantify the performance for various design and separation conditions. This paper attempts to address the challenge by utilizing an equilibrium and process modeling approach. Results from a bench-scale study performed on a 10 g/L rare earth salt mixture were used in studying the extraction/stripping behavior and developing equilibrium models. DEHPA with TBP as a phase modifier was used as an extractant, while hydrochloric acid was utilized as a stripping agent. The results obtained were used in developing extraction/stripping models, which were integrated into a process framework of a SX train in a Matlab/Simulink environment. The models were programmed as a function block routine and used for developing a flowsheet, which was simulated for differing separation and design conditions. To identify optimum stage combinations, a particle swarm optimization (PSO) routine was developed and implemented for each SX train. Recovery and purity of elements of interest were used as objective function criteria. The stage combination leading to the minimization of the objective function was used to identify the optimum stage combination for a series of SX trains to attempt a balance of purity and recovery. The models and optimization method were implemented to separate a feed mixture containing REEs, which indicated that 99.52 and 85.41 percent purity is achievable for Yttrium and Lanthanum separation using 8-12-3 and 10-3-5 stage combination for loading, scrubbing, and striping. The model also indicated difficult separability between neodymium, praseodymium, and cerium.

Srivastava, Vaibhav (ORCID:0000000212645987)↗

Generative Electrolyte Solvent and Formulation Discovery

Molecular mixtures and/or formulations are of great importance in fields ranging from materials science to pharmaceuticals to chemistry. In batteries, electrolytes are complex molecular mixtures consisting of multiple salts and solvents and additives at different concentrations that dictate battery capacity, safety, and cycle life, among others. Unfortunately, due to the complex composition and infinite design space as well as the conflicting property requirements, electrolyte design is the rate-determining step in the design of next generation battery chemistries. In this work, we develop a transformer-based generative AI model − ElectrolyteGPT − capable of generating solvents and electrolyte formulations to satisfy a wide range of desired property requirements. First, we curate an electrolyte-relevant database and develop a new line notation for formulations. Then, we show that ElectrolyteGPT can generate solvents and formulations conditioned on a wide range of important electrolyte properties such as ionic conductivity, oxidative stability, Coulombic efficiency, viscosity, and more. Finally, we experimentally synthesize the generated solvents and fabricate the electrolyte formulations and show that they can meet the desired property requirements and enable longterm cycling in energy-dense anode-free lithium metal batteries. Our work showcases the ability of generative models to address challenges in molecular mixture design for next generation batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical mixture exposure patterns and obesity among U.S. adults in NHANES 2005–2012

The effect of chemical exposure on obesity has raised great concerns. Real-world chemical exposure always imposes mixture impacts, however their exposure patterns and the corresponding associations with obesity have not been fully evaluated. To discover obesity-related mixed chemical exposure patterns in the general U.S. population. Sparse Decompositional Regression (SDR), a model adapted from sparse representation learning technique, was developed to identify exposure patterns of chemical mixtures with exclusion (non-targeted model) and inclusion (targeted model) of health outcomes. We assessed the relationships between the identified chemical mixture patterns and obesity-related indexes. We also conducted a comprehensive evaluation of this SDR model by comparing to the existing models, including generalized linear regression model (GLM), principal component analysis (PCA), and Bayesian kernel machine regression (BKMR). Eight core exposure patterns were identified using the non-targeted SDR model. Patterns of high levels of MEP, high levels of naphthalene metabolites (ΣOH-Nap), and a pattern of high exposure levels of MCOP, MCNP, and MCPP were positively associated with obesity. Patterns of high levels of BP3, and a pattern of higher mixed levels of MPB, PPB, and MEP were found to have negative associations. Associations were strengthened using the targeted SDR model. In the single chemical analysis by GLM, BP3, MBP, PPB, MCOP, and MCNP showed significant associations with obesity or body indexes. The SDR model exceeded the performance of PCA in pattern identification. Both SDR and BKMR identified a positive contribution of ΣOH-Nap and MCOP, as well as a negative contribution of BP3 and PPB to obesity. Our study identified five core exposure patterns of chemical mixtures significantly associated with obesity using the newly developed SDR model. The SDR model could open a new avenue for assessing health effects of environmental mixture contaminants.

54 ENVIRONMENTAL SCIENCES↗

Soot formation and precursor chemistry in Counterflow flames of aviation fuel surrogates

To meet market demands, the aviation sector is interested in utilizing drop-in Synthetic Aviation Turbine Fuels (SATF), either as neat fuels or in blends with conventional Jet A. SATF currently approved in standard specifications may have lower aromatic content with significant fractions of normal, branched, and cyclo-alkanes. Fundamental studies on soot formation from aviation fuels (Jet A, SATF) and their surrogate components are essential to understand how fuel composition influences soot and soot precursor formation. Here, this study reports new measurements of polycyclic aromatic hydrocarbons (PAH) and soot in counterflow diffusion flames (CDFs) of aviation fuel surrogates. Both intrusive and non-intrusive diagnostics are employed to determine the profiles of temperature, gas phase species, PAHs (up to C16), and soot volume fraction (SVF) in CDFs of iso-octane and surrogate mixtures. These measurements shed light on the transition of soot precursors to primary soot particles. In addition to serving as a common surrogate component in Jet A surrogate mixtures, iso-octane is a template species for larger, less volatile branched alkanes found in SATF mixtures. The newly developed Lawrence Livermore National Laboratory (LLNL) PAH and soot model successfully captures temperature, precursor species, and SVF profiles for the mixtures and conditions discussed in this work. Finally, a high-fidelity surrogate for Jet A is proposed that matches targeted physical and chemical properties well, while leveraging the wide range of candidate fuel molecules available in the LLNL detailed chemical model. The proposed surrogate formulation is validated against newly acquired measurements of the surrogate and literature measurements of Jet A. These new experiments and simulations provide critical insights into the PAH and soot formation from aviation fuels. Reaction pathways which require further investigation are highlighted, such that future work may bridge the remaining quantitative gaps in predicting soot formation from aviation fuel surrogates and surrogate components.

Aviation fuels↗

Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo

Sequential Monte Carlo (SMC) samplers are powerful tools for Bayesian inference but suffer from high computational costs due to their reliance on large particle ensembles for accurate estimates. We introduce persistent sampling (PS), an extension of SMC that systematically retains and reuses particles from all prior iterations to construct a growing, weighted ensemble. By leveraging multiple importance sampling and resampling from a mixture of historical distributions, PS mitigates the need for excessively large particle counts, directly addressing key limitations of SMC such as particle impoverishment and mode collapse. Crucially, PS achieves this without additional likelihood evaluations-weights for persistent particles are computed using cached likelihood values. This framework not only yields more accurate posterior approximations but also produces marginal likelihood estimates with significantly lower variance, enhancing reliability in model comparison. Furthermore, the persistent ensemble enables efficient adaptation of transition kernels by leveraging a larger, decorrelated particle pool. Experiments on high-dimensional Gaussian mixtures, hierarchical models, and non-convex targets demonstrate that PS consistently outperforms standard SMC and related variants, including recycled and waste-free SMC, achieving substantial reductions in mean squared error for posterior expectations and evidence estimates, all at reduced computational cost. PS thus establishes itself as a robust, scalable, and efficient alternative for complex Bayesian inference tasks.

Karamanis, Minas↗