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NASA NTRS1998

An Integrated Tool for the Coupled Thermal and Mechanical Analysis of Pyrolyzing Heatshield Materials

Materials that pyrolyze at elevated temperature have been commonly used as thermal protection materials in hypersonic flight, and advanced pyrolyzing materials for this purpose continue to be developed. Because of the large temperature gradients that can arise in thermal protection materials, significant thermal stresses can develop. Advanced applications of pyrolytic materials are calling for more complex heatshield configurations, making accurate thermal stress analysis more important, and more challenging. For non-pyrolyzing materials, many finite element codes are available and capable of performing coupled thermal-mechanical analyses. These codes do not, however, have a built-in capability to perform analyses that include pyrolysis effects. When a pyrolyzing material is heated, one or more components of the original virgin material pyrolyze and create a gas. This gas flows away from the pyrolysis zone to the surface, resulting in a reduction in surface heating. A porous residue, referred to as char, remains in place of the virgin material. While the processes involved can be complex, it has been found that a simple physical model in which virgin material reacts to form char and pyrolysis gas, will yield satisfactory analytical results. Specifically, the effects that must be modeled include: (1) Variation of thermal properties (density, specific heat, thermal conductivity) as the material composition changes; (2) Energy released or absorbed by the pyrolysis reactions; (3) Energy convected by the flow of pyrolysis gas from the interior to the surface; (4) The reduction in surface heating due to surface blowing; and (5) Chemical and mass diffusion effects at the surface between the pyrolysis gas and edge gas Computational tools for the one-dimensional thermal analysis these materials exist and have proven to be reliable design tools. The objective of the present work is to extend the analysis capabilities of pyrolyzing materials to axisymmetric configurations, and to couple thermal and mechanical analyses so that thermal stresses may be efficiently and accurately calculated.

Pronchick, Stephen W.↗

NASA NTRS1999

Parallelization of the Flow Field Dependent Variation Scheme for Solving the Triple Shock/Boundary Layer Interaction Problem

A parallelized version of the Flowfield Dependent Variation (FDV) Method is developed to analyze a problem of current research interest, the flowfield resulting from a triple shock/boundary layer interaction. Such flowfields are often encountered in the inlets of high speed air-breathing vehicles including NASA's Hyper-X. In order to resolve the complex shock structure and to provide adequate resolution for boundary layer computations of the convective heat transfer from surfaces inside the inlet, models containing over 500,000 nodes are needed. Efficient parallelization of the computation is essential to obtaining the results in a timely manner. Results from different parallelization schemes, based upon multi-threading and message passing, as implemented on multiple processor supercomputers and on distributed workstations are compared.

Schunk, Greg↗

NASA NTRS2001

Parallelization of the Flow Field Dependent Variation Scheme for Solving the Triple Shock/Boundary Layer Interaction Problem

A parallelized version of the Flowfield Dependent Variation (FDV) Method is developed to analyze a problem of current research interest, the flowfield resulting from a triple shock/boundary layer interaction. Such flowfields are often encountered in the inlets of high speed air-breathing vehicles including the NASA Hyper-X research vehicle. In order to resolve the complex shock structure and to provide adequate resolution for boundary layer computations of the convective heat transfer from surfaces inside the inlet, models containing over 500,000 nodes are needed. Efficient parallelization of the computation is essential to achieving results in a timely manner. Results from a parallelization scheme, based upon multi-threading, as implemented on multiple processor supercomputers and workstations is presented.

Schunk, Richard Gregory↗

NASA NTRS2009

Emittance Measurements Relevant to a 250 W(sub t) Class RTPV Generator for Space Exploration

A proposed 250 Wt Radioisotope Thermophotovoltaic (RTPV) power system for utilization in lunar exploration and the subsequent exploration of Mars is described. Details of emitter selection are outlined for use in a maintenance free power supply that is productive over a 14-year mission life. Thorough knowledge of a material s spectral emittance is essential for accurate modeling of the RTPV system. While sometimes treated as a surface effect, emittance involves radiation from within a material. This creates a complex thermal gradient which is a combination of conductive and radiative heat transfer mechanisms. Emittance data available in the literature is a valuable resource but it is particular to the test sample s physical characteristics and the test environment. Considerations for making spectral emittance measurements relevant to RTPV development are discussed. Measured spectral emittance data of refractory emitter materials is given. Planned measurement system modifications to improve relevance to the current project are presented.

Wolford, Dave↗

DOE OSTI2023

Subsetted model output for surface-related variables from a LASSO-CACTI WRF simulation

Surface-related model output from a Weather Research and Forecasting (WRF) simulation from the Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI simulations span grid spacings from 7.5 km to 100 m through the use of four nested domains, labeled d1 through d4. The simulations are of convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. More information can be found at https://www.arm.gov/capabilities/modeling/lasso. This version of the output is a collection of variables subsetted from the raw WRF output to reduce the file overhead for users not needing the full raw dataset. The subset files are in netCDF format with the variables in these files at the surface and sub-surface levels.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Three-Dimensional Surface Downwelling Longwave Radiation Clear-Sky Effects in the Upper Colorado River Basin

In complex terrain, non-parallel surfaces receive emitted radiation from adjacent surfaces. Qualitatively, where surface skin temperatures and lower tropospheric temperature and humidity are not uniform, the downwelling longwave radiation (DLR) will be determined not just by radiation from the atmosphere above a given location, but also by adjacent surface temperatures. We quantify this three-dimensional longwave radiative effect over the Upper Colorado River Basin in clear-sky conditions by calculating surface DLR with observed land-surface temperatures from ECOSTRESS. We find that this effect is due to terrain-subtended sky-view and represents ~22% of the surface longwave flux, rising to ~28% and ~24% in the East and Southeast of the Basin, respectively, and can be >50% in extreme cases. The common omission of this effect in atmospheric radiation models leads to an underestimation of DLR in complex terrain, especially at higher elevations, which has significant implications for mountainous ecohydrology simulations.

3-dimensional effects↗

NASA NTRS1998

Real Time Land-Surface Hydrologic Modeling Over Continental US

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

Houser, Paul R.↗

DOE OSTI2022

Tritium Transport Modeling at the Pore Scale in Ceramic Breeder Materials Using TMAP8

Fusion reactors depend on the blanket material to breed and release tritium at the same rate or faster than it is consumed by the fusion reaction. Cellular ceramic breeders (CCBs) are dense materials that can maintain a high tritium breeding ratio while promoting tritium release because of highly connected pores. Assessing the tritium breeding capabilities of these materials requires a combination of extensive experimental and modeling efforts. In this work, we develop and calibrate a multiphysics model of tritium transport. This novel model accounts for ceramic and pore diffusion, trapping and detrapping, and several surface reactions at the pore surface. We perform a sensitivity analysis and calibrate the model by comparing its predictions against experimental measurements of deuterium absorption. The calibrated model is then used to model tritium absorption in samples with different pore microstructures to investigate the effect of pore interconnectivity on tritium absorption. The model is part of the development of the multiscale, multiphysics framework for tritium transport [i.e., the Tritium Migration Analysis Program (TMAP8)], which is itself built on top of the finite-element multiphysics framework multiphysics object-oriented simulation environment (MOOSE). This study demonstrates some of TMAP8’s capabilities and is the first step toward assessing the tritium breeding capabilities of ceramic breeder material designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

A coarse-grained model of clay colloidal aggregation and consolidation with explicit representation of the electrical double layer

The aggregation of clay minerals in liquid water exemplifies colloidal self-assembly in nature. These negatively charged aluminosilicate platelets interact through multiple mechanisms with different sensitivities to particle shape, surface charge, aqueous chemistry, and interparticle distance and exhibit complex aggregation structures. Experiments have difficulty resolving the associated colloidal assemblages at the scale of individual particles. Conversely, all-atom molecular dynamics (MD) simulations provide detailed insight on clay colloidal interaction mechanisms, but they are limited to systems containing a few particles. We develop a new coarse-grained (CG) model capable of representing assemblages of hundreds of clay particles with accuracy approaching that of MD simulations, at a fraction of the computational cost. Our CG model is parameterized based on MD simulations of a pair of smectite clay particles in liquid water. A distinctive feature of our model is that it explicitly represents the electrical double layer (EDL), i.e., the cloud of charge-compensating cations that surrounds the clay particles. Our model captures the simultaneous importance of long-range colloidal interactions (i.e., interactions consistent with simplified analytical models, already included in extant clay CG models) and short-range interactions such as ion correlation and surface and ion hydration effects. The resulting simulations correctly predict, at low solid-water ratios, the existence of ordered arrangements of parallel particles separated by water films with a thickness up to ~10 nm and, at high solid-water ratios, the coexistence of crystalline and osmotic swelling states, in agreement with experimental observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Surface Quantitative Precipitation Estimates (SQUIRE) of Snow Water Equivalent from the Surface Atmospheric Integrated Field Laboratory

The upper Colorado River basin is the primary source of water for 40 million people. With declining snowpack in the basin, forecasting hydrological budgets in the Southwest United States is more important than ever. However, due in part, to a lack of reliable observations of precipitation in complex terrain, hydrological models struggle to assess and forecast snowpack snow water equivalent (SWE) in the upper Colorado River basin (UCRB). Therefore, the need for more reliable SWE forecasts in the UCRB motivated the U.S. Department of Energy Atmospheric Radiation Measurement Facility’s Surface Atmospheric Integrated Field Laboratory (SAIL) that occurred from June 2021 to June 2023. During SAIL, the X-band precipitation radar from Colorado State University conducted volume scans sampling the precipitation properties over the UCRB. The ARM facility developed a gridded Surface Quantitative Precipitation Estimates (SQUIRE) product from the radar observations. To do this, various daily SWE estimates from radar using the radar reflectivity factor Z e and specific differential phase K dp were compared against ground-based precipitation gauges. SWE in precipitation calculated from Wolfe and Snider’s S–Z e estimator was in best agreement with the rain gauges for the days when SWE < 12 mm. For days with SWE > 12 mm, the WSR-88D Intermountain West relationship had the best agreement with the precipitation gauges. Airborne snow depth observations show that SQUIRE captures regions of orographic enhancement in the mountains to the west and northwest of the SAIL study area, indicating that the scientific community should focus on understanding and ultimately simulating orographic atmospheric precipitation processes to improve UCRB snowpack SWE assessment and forecasting.

Hydrology↗

NASA NTRSDate not supplied

Airport Runway Configuration Management with Offline Model-free Reinforcement Learning

Runway configuration management (RCM) deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction and other environmental variables. RCM is one of the most challenging tasks in air traffic management, as it relies on operational and environmental variables (e.g., weather forecast) that are highly uncertain and complex to model. In this paper, an innovative and automated approach is deployed using offline model-free reinforcement learning to provide decision-support for RCM. The proposed technology processes historical data about variables of interest, decisions made regarding RCM, and their subsequent outcome, to identify a policy that would encourage good decisions and avoid the poor ones. The policy search is guided by an appropriately chosen weighted utility function (e.g., based on minimizing delays and go-arounds). Finally, the performance of the proposed tool is validated using Charlotte Douglas International Airport as the case study, which shows that the proposed method is superior to other conventional rule-based approaches.

Milad Memarzadeh↗

NASA NTRSDate not supplied

Airport Runway Configuration Management with Offline Model-free Reinforcement Learning

Milad Memarzadeh↗

NASA NTRS1991

Kaolinite-catalyzed air oxidation of hydrazine: Consideration of several compositional, structural and energetic factors in surface activation

Clay minerals have been shown to have numerous, curious, energetic properties by virtue of ultra-violet light release which can be triggered by gentle environmental changes such as wetting and dewetting by a variety of liquids, unique among them water and hydrazine. Since both water and hydrazine play multiple key roles in the air-oxidation of hydrazine on kaolinite surfaces, this reaction would seem to have prime potential for studying interrelationships of energy storage, release and chemical reactivity of clay surfaces, capacities basic to either the Bernal or Cairns-Smith roles of minerals in the origin of life. Establishment of the capacity for stored electronic energy to significantly alter surface chemistry is important, regardless of the reaction chosen to demonstrate it. Hydrazine air oxidation is overawingly complex, given the possibilities for step-wise control and monitoring of parameters. In the light of recently extended characterization of the kaolinite and model sheet catalysts we used to study hydrazine oxidation and gamma-irradiated silica, previous studies of hydrazine air-oxidation on aluminosilicate surfaces have been reevaluated. Our former conclusion remains intact that, whereas trace structural and surface contaminants do play some role in the catalysis of oxidation, they are not the only, nor even the dominant, catalytic centers. Initial intermediates in the oxidation can now be proposed which are consistent with production via O(-)-centers as well as ferric iron centers. The greater than square dependence of the initial reaction rate on the weight of the clay is discussed in the light of these various mechanistic possibilities.

Coyne, L. M.↗

DOE OSTI2025

Complex surface topographic changes from explosive experiments at the Dry Alluvium Geology site, southern Nevada, United States

Understanding the surface topographic change that results from underground explosions is important for global security. Current techniques to relate the surface change to underground explosion characteristics usually involve assuming the earth has homogenous properties, leading to highly variable interpretations. Here we use an unoccupied aerial platform and a digital single lens reflex camera along with 200+ ground control points surveyed with a real-time kinematic global navigation satellite system to measure the surface topographic change resulting from two underground explosions at the Dry Alluvium Geology site in Yucca Flat, Nevada National Security Site, southern Nevada, United States. We find areas of 5–7 cm of subsidence that are not directly above the explosion source but rather 200–300 m away. For experiment DAG2, this zone is located south and west of the explosion, while for DAG4, there is a zone of subsidence located northeast of the explosion. In addition, late-time measurements show as much as 5 cm of horizontal change without measurable associated vertical change in the weeks following DAG4 but not DAG2. These indicate that the deformation resulting from underground chemical explosions can be very complex and bear little to no resemblance to predictions using half-space models. It is likely the tectonic environment plays a significant role in controlling the surface change, but the details are not fully understood.

58 GEOSCIENCES↗

NASA NTRS2023

Using Orbiting Carbon Observatory-2 (OCO-2) column CO2 retrievals to rapidly detect and estimate biospheric surface carbon flux anomalies

The global carbon cycle is experiencing continued perturbations via increases in atmospheric carbon concentrations, which are partly reduced by terrestrial biosphere and ocean carbon uptake. Greenhouse gas satellites have been shown to be useful in retrieving atmospheric carbon concentrations and observing surface and atmospheric CO2 seasonal-to-interannual variations. However, limited attention has been placed on using satellite column CO2 retrievals to evaluate surface CO2 fluxes from the terrestrial biosphere without advanced inversion models at low latency. Such applications could be useful to monitor, in near real time, biosphere carbon fluxes during climatic anomalies like drought, heatwaves, and floods, before more complex terrestrial biosphere model outputs and/or advanced inversion modelling estimates become available. Here, we explore the ability of Orbiting Carbon Observatory-2 (OCO-2) column-averaged dry air CO2 (XCO2) retrievals to directly detect and estimate terrestrial biosphere CO2 flux anomalies using a simple mass-balance approach. An initial global analysis of surface–atmospheric CO2 coupling and transport conditions reveals that the western US, among a handful of other regions, is a feasible candidate for using XCO2 for detecting terrestrial biosphere CO2 flux anomalies. Using the CarbonTracker model reanalysis as a test bed, we first demonstrate that a well-established mass-balance approach can estimate monthly surface CO2 flux anomalies from XCO2 enhancements in the western United States. The method is optimal when the study domain is spatially extensive enough to account for atmospheric mixing and has favorable advection conditions with contributions primarily from one background region. We find that errors in individual soundings reduce the ability of OCO-2 XCO2 to estimate more frequent, smaller surface CO2 flux anomalies. However, we find that OCO-2 XCO2 can often detect and estimate large surface flux anomalies that leave an imprint on the atmospheric CO2 concentration anomalies beyond the retrieval error/uncertainty associated with the observations. OCO-2 can thus be useful for low-latency monitoring of the monthly timing and magnitude of extreme regional terrestrial biosphere carbon anomalies.

Andrew F. Feldman↗

DOE OSTI2025

JAX-CanVeg: A Differentiable Land Surface Model

Land surface models consider the exchange of water, energy, and carbon along the soil-canopy-atmosphere continuum, which is challenging to model due to their complex interdependency and associated challenges in representing and parameterizing them. Differentiable modeling provides a new opportunity to capture these complex interactions by seamlessly hybridizing process-based models with deep neural networks (DNNs), benefiting both worlds, that is, the physical interpretation of process-based models and the learning power of DNNs. Here, we developed a differentiable land model, JAX-CanVeg. The new model builds on the legacy CanVeg by incorporating advanced functionalities through JAX in the graphic processing unit support, automatic differentiation, and integration with DNNs. We demonstrated JAX-CanVeg's hybrid modeling capability by applying the model at four flux tower sites with varying aridity. To this end, we developed a hybrid version of the Ball-Berry equation that emulates the water stress impact on stomatal closure to explore the capability of the hybrid model in (a) improving the simulations of latent heat fluxes (LE) and net ecosystem exchange (NEE), (b) improving the optimization trade-off when learning observations of both LE and NEE, and (c) benefiting a multi-layer canopy model setup. Our results show that the proposed hybrid model improved the simulations of LE and NEE at all sites, with an improved optimization trade-off over the process-based model. Additionally, the multi-layer canopy set benefited hybrid modeling at some sites. Anchored in differentiable modeling, our study provides a new avenue for modeling land-atmosphere interactions by leveraging the benefits of both data-driven learning and process-based modeling.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1981

A Reattaching Free Shear Layer in Compressible Turbulent Flow: A Comparison of Numerical and Experimental Results

An investigation of the two-dimensional, free turbulent shear layer reattaching on an inclined surface at Mach 2.92 and at a high Reynolds number is described. The test geometry is specifically designed to isolate the reattachment process of a high-speed separated flow. A numerical solution of the time-dependent, Reynolds-averaged, Navier-Stokes equations for the entire flow field, employing a two-equation eddy viscosity turbulence model, is presented. Detailed comparisons of prediction and experiment are made in the free shear layer, at reattachment, and in the developing boundary layer downstream. These comparisons include mean surface quantities as well as mean and fluctuating flow-field quantities. Although the overall features of this complex flow field are predicted, there are several deficiencies in the numerical solution, particularly in the region downstream of reattachment. Modifications of the turbulence model to correct these deficiencies are discussed.

Horstman, C. C.↗

DOE OSTI2020

Dynamic clay microstructures emerge via ion complexation waves

Clays control carbon, water and nutrient transport in the lithosphere, promote cloud formation5 and lubricate fault slip through interactions among hydrated mineral interfaces. Clay mineral properties are difficult to model because their structures are disordered, curved and dynamic. Consequently, interactions at the clay mineral-aqueous interface have been approximated using electric double layer models based on single crystals of mica and atomistic simulations. We discover that waves of complexation dipoles at dynamically curving interfaces create an emergent long-range force that drives exfoliation and restacking over time- and length-scales that are not captured in existing models. Curvature delocalizes electrostatic interactions in ways that fundamentally differ from planar surfaces, altering the ratio of ions bound to the convex and concave sides of a layer. Multiple-scattering reconstruction of low-dose energy-filtered cryo electron tomography enabled direct imaging of ion complexes and electrolyte distributions at hydrated and curved mineral interfaces with {\aa}ngstrom resolution over micron length scales. Layers exfoliate and restack abruptly and repeatedly over timescales that depend strongly on the counterion identity, demonstrating that the strong coupling between elastic, electrostatic and hydration forces in clays promote collective reorganization previously thought to be a feature only of active matter.

Whittaker, Michael L↗