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At least 109 records · Page 6

SiC and Si3N4 Recession Due to SiO2 Scale Volatility Under Combustor Conditions

SiC and Si3N4 materials were tested under various turbine engine combustion environments, chosen to represent either conventional fuel-lean or fuel-rich mixtures proposed for high speed aircraft. Representative CVD, sintered, and composite materials were evaluated in both furnace and high pressure burner rig exposure. While protective SiO2 scales form in all cases, evidence is presented to support paralinear growth kinetics, i.e. parabolic growth moderated simultaneously by linear volatilization. The volatility rate is dependent on temperature, moisture content, system pressure, and gas velocity. The burner tests were used to map SiO2 volatility (and SiC recession) over a range of temperature, pressure, and velocity. The functional dependency of material recession (volatility) that emerged followed the form: exp(-QIRT) * P(exp x) * v(exp y). These empirical relations were compared to rates predicted from the thermodynamics of volatile SiO and SiO(sub x)H(sub Y) reaction products and a kinetic model of diffusion through a moving, boundary layer. For typical combustion conditions, recession of 0.2 to 2 micron/h is predicted at 1200- 1400C, far in excess of acceptable long term limits.

Smialek, James L.

SiC and Si3N4 Recession Due to SiO2 Scale Volatility Under Combustor Conditions

Silicon carbide (SiC) and Si3N4 materials were tested in various turbine engine combustion environments chosen to represent either conventional fuel-lean or fuel-rich mixtures proposed for high-speed aircraft. Representative chemical vapor-deposited (CVD), sintered, and composite materials were evaluated by furnace and high-pressure burner rig exposures. Although protective SiO2 scales formed in all cases, the evidence presented supports a model based on paralinear growth kinetics (i.e., parabolic growth moderated simultaneously by linear volatilization). The volatility rate is dependent on temperature, moisture content, system pressure, and gas velocity. The burner tests were thus used to map SiO2 volatility (and SiC recession) over a range of temperatures, pressures, and velocities. The functional dependency of material recession (volatility) that emerged followed the form A[exp(-Q / RT)](P(sup x)v(sup y). These empirical relations were compared with rates predicted from the thermodynamics of volatile SiO and SiOxHy reaction products and a kinetic model of diffusion through a moving boundary layer. For typical combustion conditions, recession of 0.2 to 2 micrometers/hr is predicted at 1200 to 1400 C, far in excess of acceptable long-term limits.

Smialek, James L.

Long-term dynamical stability and transition in a spectral model

The relationship between blocking and multiple equilibria was investigated in a two layer model of the Northern Hemisphere January heating and boundary conditions are imposed. The truncation varies over global wavenumbers 4-8 and the coefficients of horizontal diffusion of heat and potential vorticity are varied about realistic values. It is shown that while severely truncated models can exhibit multiple quasi equilibria under realistic domain, forcing, and boundary conditions, higher resolution is required to allow realistic transitions to be mediated by strong baroclinic wave activity. It is indicated that for extended range forecasting blocking transitions are not likely to be forecast well unless the associated synoptic events can be forecasted statistically.

Wobus, R. L.

A preliminary assessment of olivine phenocrysts from the monogenetic basalt of the McCartys Flow, Zuni-Bandera Volcanic Field, New Mexico

Monogenetic small-volume basaltic volcanoes are the most abundant subaerial volcanic landforms on Earth but are some of the most poorly understood systems. Their short durations, small volumes, and lack of recurrence make monitoring and hazard assessment difficult. The Zuni-Bandera volcanic field in western New Mexico contains small-volume basaltic centers erupting tholeiitic to alkalic basalts. Evidence shows no correlation of magma composition with eruption age, location, or volumetric output, prompting questions about the influence of magma ascent rates, magma storage conditions, and mantle source characteristics on lava compositions. Here, we present olivine major and minor element mineral chemistry from the 3200-year-old McCartys Flow, the youngest tholeiite basalt in the volcanic field. Olivine displays four phenocryst types with unique textures and major and minor element compositions. Multiple olivine types co-exist at the thin section scale. Major and minor element diffusion at frozen melt–phenocryst interfaces was modeled, revealing magma residence times ranging from 3–9 months. Type 3 olivine phenocrysts require step function initial conditions and record diffusion re-equilibration followed by magma mixing. These profiles indicate the magma resided in the reservoir for 10–15 years and accumulated from multiple batches of mixed magmas less than 10 days before the eruption. Our results show that primitive magmas in small-volume monogenetic volcanoes have complex lithospheric magmatic histories and stored in magma bodies influenced by an open system to develop different local chemical environments.

Gary S. Michelfelder

HTO and selenate diffusion through compacted Na-, Na–Ca-, and Ca-montmorillonite

Radionuclide transport in smectite clay barrier systems used for nuclear waste disposal is controlled by diffusion, with adsorption significantly retarding transport rates. While a relatively minor component of spent nuclear fuel, 79 Se is a major driver of the safety case for spent fuel disposal due to its long half-life (3.3×10 5 yr) and its low adsorption to clay (K D < 10 L/kg), thus a thorough understanding of Se diffusion through clay is critical for understanding the long-term safety of spent fuel disposal systems. Through-diffusion experiments with tritiated water (HTO, conservative tracer) and Se(VI) were conducted with a well-characterized, purified montmorillonite source clay (SWy-2) under a constant ionic strength (0.1 M) and three different electrolyte compositions: Na + , Ca 2+ , and a Na + -Ca 2+ mixture at pH 6.5 in order to probe the effects of electrolyte composition and interlayer cation composition on clay microstructure, Se(VI) aqueous speciation, and ultimately diffusion. Further, the results were modeled using a reactive transport modeling approach to determine values of porosity (ε), D e (effective diffusion coefficient), and K D (distribution coefficient for adsorption). HTO diffusive flux was higher in Ca-montmorillonite (D e =1.68×10 -10 m 2 s -1 ) compared to Na-montmorillonite (De=7.83×10 -11 m 2 s -1 ). This increase in flux is likely due to a greater degree of clay layer stacking in the presence of Ca 2+ compared to Na + , which leads to larger inter-particle pores. Overall, the Se(VI) flux was much lower than the HTO flux due to anion exclusion, with Se(VI) flux following the order Ca (D e = 1.03×10 -11 m 2 s -1 ) > Na–Ca (D e = 2.12×10 -12 m 2 s -1 ) > Na (D e = 1.28×10 -12 m 2 s -1 ). These differences in Se(VI) flux are due to a combination of factors, including (1) larger accessible porosity in Ca-montmorillonite due to clay layer stacking and smaller electrostatic effects compared to Na-montmorillonite, (2) larger accessible porosity for neutral-charge CaSeO4 species which makes up 32% of aqueous Se(VI) in the pure Ca system, and (3) possibly higher Se(VI) adsorption for Ca-montmorillonite. Through a combination of experimental and modeling work, this study highlights the compounding effects that electrolyte and counterion compositions can have on radionuclide transport through clay. Diffusion models that neglect these effects are not transferable from laboratory experimental conditions to in situ repository conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W

Oxidation of Carbon Fibers in a Cracked Ceramic Matrix Composite Modeled as a Function of Temperature

The oxidation model simulates the oxidation of the reinforcing carbon fibers within a ceramic matrix composite material containing as-fabricated microcracks. The physics-based oxidation model uses theoretically and experimentally determined variables as input for the model. The model simulates the ingress of oxygen through microcracks into a two-dimensional plane within the composite material. Model input includes temperature, oxygen concentration, the reaction rate constant, the diffusion coefficient, and the crack opening width as a function of the mechanical and thermal loads. The model is run in an iterative process for a two-dimensional grid system in which oxygen diffuses through the porous and cracked regions of the material and reacts with carbon in short time steps. The model allows the local oxygen concentrations and carbon volumes from the edge to the interior of the composite to be determined over time. Oxidation damage predicted by the model was compared with that observed from microstructural analysis of experimentally tested composite material to validate the model for two temperatures of interest. When the model is run for low-temperature conditions, the kinetics are reaction controlled. Carbon and oxygen reactions occur relatively slowly. Therefore, oxygen can bypass the carbon near the outer edge and diffuse into the interior so that it saturates the entire composite at relatively high concentrations. The kinetics are limited by the reaction rate between carbon and oxygen. This results in an interior that has high local concentrations of oxygen and a similar amount of consumed carbon throughout the cross section. When the model is run for high-temperature conditions, the kinetics are diffusion controlled. Carbon and oxygen reactions occur very quickly. The carbon consumes oxygen as soon as it is supplied. The kinetics are limited by the relatively slow rate at which oxygen is supplied in comparison to the relatively fast rate at which carbon and oxygen reactions occur. This results in a sharp gradient in oxygen concentration from the edge where it is supplied to the nearest source of carbon, which is where the oxygen is quickly consumed. A moving reaction front is seen in which the outlaying carbon is consumed before the next inner layer of carbon begins to react.

Halbig, Michael C.

Mean Line Pump Flow Model in Rocket Engine System Simulation

A mean line pump flow modeling method has been developed to provide a fast capability for modeling turbopumps of rocket engines. Based on this method, a mean line pump flow code PUMPA has been written that can predict the performance of pumps at off-design operating conditions, given the loss of the diffusion system at the design point. The pump code can model axial flow inducers, mixed-flow and centrifugal pumps. The code can model multistage pumps in series. The code features rapid input setup and computer run time, and is an effective analysis and conceptual design tool. The map generation capability of the code provides the map information needed for interfacing with a rocket engine system modeling code. The off-design and multistage modeling capabilities of the code permit parametric design space exploration of candidate pump configurations and provide pump performance data for engine system evaluation. The PUMPA code has been integrated with the Numerical Propulsion System Simulation (NPSS) code and an expander rocket engine system has been simulated. The mean line pump flow code runs as an integral part of the NPSS rocket engine system simulation and provides key pump performance information directly to the system model at all operating conditions.

Veres, Joseph P.

Generative unfolding with distribution mapping

Machine learning enables unbinned, highly-differential cross section measurements. A recent idea uses generative models to morph a starting simulation into the unfolded data. We show how to extend two morphing techniques, Schrödinger Bridges and Direct Diffusion, in order to ensure that the models learn the correct conditional probabilities. This brings distribution mapping (DM) to a similar level of accuracy as the state-of-the-art conditional generative unfolding methods. Numerical results are presented with a standard benchmark dataset of single jet substructure as well as for a new dataset describing a 22-dimensional phase space of Z+2 -jets.

Butter, Anja

Molecular oxygen measurements at 200 km from AE-D near winter solstice, 1975

Utilizing the fly-through mode, the open source neutral mass spectrometer on Atmosphere Explorer-D (AE-D) has measured O2 densities, as well as N2 densities and in situ neutral temperatures, at midmorning during winter solstice over the latitude range 90 degrees S to 90 degrees N. The expected seasonal variation in N2 was found at 200 km together with a more complex behavior in molecular oxygen than might be expected from a diffusive equilibrium model with constant lower boundary values. Under geomagnetically quiet conditions the equatorial 200 km value of O2 was about 1.7 x 10 to the 8th/cu cm. A local maximum in the 200 km O2 densities was found near 70 degrees N, where an average quiet time value was 2.5 x 10 to the 8th/cu cm, implying a 120 km density of 8.3 x 10 to the 10th/cu cm. The in situ temperature measurements confirm the presence of higher temperatures near 70 degrees N latitude, even during geomagnetically quiet conditions.

Kayser, D. C.

A numerical analysis of high-temperature heat pipe startup from the frozen state

Continuum and rarefied vapor flows co-exist along the heat pipe length for most of the startup period. A two-region model is proposed in which the vapor flow in the continuum region is modeled by the compressible Navier-Stokes equations, and the vapor flow in the rarefied region is simulated by a self-diffusion model. The two vapor regions are linked with appropriate boundary conditions, and heat pipe wail, wick, and vapor flow are solved as a conjugate problem. The numerical solutions for the entire heat pipe startup process from the frozen state are compared with the corresponding experimental data with good agreement.

Cao, Y.

Theoretical Study of the Effect of an AlGaAs Double Heterostructure on Metal-Semiconductor-Metal Photodetector Performance

The impulse and square-wave input response of different GaAs metal-semiconductor-metal photodetector (MSM) designs are theoretically examined using a two dimensional drift- diffusion numerical calculation with a thermionic-field emission boundary condition model for the heterojunctions. The rise time and the fall time of the output signal current are calculated for a simple GaAs, epitaxially grown, MSM device as well as for various double-heterostructure barrier devices. The double heterostructure devices consist of an AlGaAs layer sandwiched between the top GaAs active, absorption layer and the bottom GaAs substrate. The effect of the depth of the AlGaAs layer on the speed and responsivity of the MSM devices is examined. It is found that there is an optimal depth, at fixed applied bias, of the AlGaAs layer within the structure that provides maximum responsivity at minimal compromise in speed.

Salem, Ali F.

Effects of thermal-solutal convection on temperature and solutal fields under various gravitational orientations

Semiconductor crystals such as Hg(1-x)CD(x)Te grown by unidirectional solidification Bridgmann method have shown compositional segregations in both the axial and radial directions. Due to the wide separation between the liquidus and the solidus of its pseudobinary phase diagram, there is a diffusion layer of higher HgTe content built up in the melt near the melt-solid interface which gives a solute concentration gradient in the axial direction. The value of effective diffusion coefficient calculated from fitting of the data to 1D model varies with Hg(1-x)Cd(x)Te growth conditions. This indicates that the growth condition of the Hg(1-x)Cd(x)Te is not purely diffusion controlled. Because of the higher thermal conductivity in the melt than that in the crystal in the growth system, there is a thermal leakage through the fused silica crucible wall near the melt-solid interface. This gives a thermal gradient in the radial direction. Hart, and Thorpe, Hutt and Soulsby have shown that under such conditon a fluid will become convectively unstable as a result of different diffusitivities of temperature and solute. It is quite important to understand the effects of this thermosolute convection on the compositonal segregation in both axial and radial directions in the unidirectionally solidified crystals under various gravitational directions. To reach this goal, we start with a simplified problem to study the effects of thermal-solutal convection on the temperature and solutal fields under various gravitional orientations. We begin by reviewing model governing equations.

Wang, Jai-Ching

Unified Material-Environment Interaction Model for Binary UHTC Composites

A new model for the surface chemistry of zirconium and hafnium diborides containing silicon-carbide when exposed to high temperature conditions in air is formulated. Oxidation dynamics are simplified by considering the diffusion-limited equilibrium regime within the material at elevated temperatures. This model is first assessed against experimental mass-gain data taken from UHTC samples heated to high temperature in an oxygen environment. Then, further evaluations of the new model are conducted using hypersonic CFD simulations to analyze conditions experienced by HfB2-SiC in arc jet experiments conducted at NASA Ames Research Center. Measurements of stagnation point heat transfer and pressure are then used to calibrate the simulations. Results of coupled CFD-material response simulations are then compared to the surface temperatures measured during the Ames arc jet test. Results support the use of the proposed model while highlighting the need for improved gas-phase data on the additional constituents considered.

ultra high temperature ceramic

The rigorous upscaling of advection-dominated transport in heterogeneous porous media via the Method of Finite Averages

Systems involving advection-dominated transport through heterogeneous porous and fractured media are ubiquitous in subsurface engineering applications. However, upscaling such systems continues to challenge rigorous modeling efforts, particularly when advection is stronger than diffusion at fine spatial scales (i.e., when the Péclet number is greater than one at length scales that characterize a system’s unit-cells, representative elementary volumes, or averaging regions). Here, in this work, we propose and validate a strategy for extending the Method of Finite Averages (MoFA), a rigorous upscaling methodology for heterogeneous porous media, to upscale transport systems experiencing stronger advection than diffusion at fine scales (i.e., fine-scale Péclet numbers greater than one). We detail the strategy, the physical conditions under which it can be applied while retaining a priori modeling error guarantees, and implement the strategy to obtain a MoFA model for advective-diffusive transport that accommodates advective physics at fine spatial scales. We then perform two numerical experiments considering systems with system-scale Péclet numbers of 300 and 1000 — which correspond to fine-scale Péclet numbers of 30 and 100, respectively — to verify that the error guarantees are met under the strategy. After, we conduct a numerical study to demonstrate the strategy’s advantages over the original MoFA methodology. The results suggest that rigorously-upscaled transport models for heterogeneous porous media experiencing advective physics at finer spatial scales can be derived through MoFA and resolved orders of magnitude faster than their pore-scale counterparts. The results also suggest that the presented strategy is limited to modeling shallow concentration gradients when there are large differences between the time scales related to advection and a system’s temporally-varying boundary conditions. This limitation hinders the strategy’s practicality in modeling more advective systems, and as such, opportunity exists for developing additional strategies that accommodate rapidly-varying boundary conditions — and consequentially, steeper concentration gradients — while modeling advective systems with MoFA.

36 MATERIALS SCIENCE

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION

FDNS CFD Code Benchmark for RBCC Ejector Mode Operation

Computational Fluid Dynamics (CFD) analysis results are compared with benchmark quality test data from the Propulsion Engineering Research Center's (PERC) Rocket Based Combined Cycle (RBCC) experiments to verify fluid dynamic code and application procedures. RBCC engine flowpath development will rely on CFD applications to capture the multi-dimensional fluid dynamic interactions and to quantify their effect on the RBCC system performance. Therefore, the accuracy of these CFD codes must be determined through detailed comparisons with test data. The PERC experiments build upon the well-known 1968 rocket-ejector experiments of Odegaard and Stroup by employing advanced optical and laser based diagnostics to evaluate mixing and secondary combustion. The Finite Difference Navier Stokes (FDNS) code was used to model the fluid dynamics of the PERC RBCC ejector mode configuration. Analyses were performed for both Diffusion and Afterburning (DAB) and Simultaneous Mixing and Combustion (SMC) test conditions. Results from both the 2D and the 3D models are presented.

Holt, James B.

Structural constraint integration in a generative model for the discovery of quantum materials

Billions of organic molecules have been computationally generated, yet functional inorganic materials remain scarce due to limited data and structural complexity. Here, in this work, we introduce Structural Constraint Integration in a GENerative model (SCIGEN), a framework that enforces geometric constraints, such as honeycomb and kagome lattices, within diffusion-based generative models to discover stable quantum materials candidates. SCIGEN enables conditional sampling from the original distribution, preserving output validity while guiding structural motifs. This approach generates ten million inorganic compounds with Archimedean and Lieb lattices, over 10% of which pass multistage stability screening. High-throughput density functional theory calculations on 26,000 candidates shows over 95% convergence and 53% structural stability. A graph neural network classifier detects magnetic ordering in 41% of relaxed structures. Furthermore, we synthesize and characterize two predicted materials, TiPd 0.22 Bi 0.88 and Ti 0.5 Pd 1.5 Sb, which display paramagnetic and diamagnetic behaviour, respectively. Our results indicate that SCIGEN provides a scalable path for generating quantum materials guided by lattice geometry.

36 MATERIALS SCIENCE

Decomposition of methane diluted with inert gas in an RF discharge cell

Decomposition of methane using non-thermal plasmas is an attractive route for producing hydrogen-rich gases and valuable carbon nanomaterials. Understanding how plasma discharge modes influence methane decomposition in optimizing plasma-assisted chemical conversion remains unexplored. This study explores the coupling between the discharge structure and product selectivity in RF capacitively coupled discharges operating in methane/inert gas mixtures in the pressure range of 2–3 torr. Under our experimental conditions the discharge exhibits mode transitions from uniform to striated in Ar and Kr and from diffuse to contracted in Ar and Kr with <5% CH 4 . The discharges in He and Ne remained uniform under our operating conditions, and their mixtures with CH 4 remained diffuse. A 0-d model for Ar/CH 4 discharge established a threshold for contraction while also asserting the importance of Ar$^{*}_{\textrm{m}}$ in the dissociation and ionization processes. The highest degree of methane decomposition, >99.7% with the main products of acetylene and graphitized solid carbon was achieved in the contracted discharge mode for both Kr or Ar with ⩽5% CH 4 . We demonstrate that contraction can play a crucial role in the effective decomposition of methane with value-added products and that both the electronic and thermal properties of plasma gas are responsible for this effect.

RF plasma