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At least 685 records · Page 38

Pairing Directional Solar Inputs From Ray Tracing to Solar Receiver/Reactor Heat Transfer Models on Unstructured Meshes: Development and Case Studies

A novel method for pairing surface irradiation and volumetric absorption from Monte Carlo ray tracing to computational heat transfer models is presented. The method is well-suited to directionally and spatially complex concentrated radiative inputs (e.g., solar receivers and reactors). The method employs a generalized algorithm for directly mapping absorbed rays from a Monte Carlo ray tracing model to boundary or volumetric source terms in the computational mesh. The algorithm is compatible with unstructured, two and three-dimensional meshes with varying element shapes. Four case studies were performed on a directly irradiated, windowed solar thermochemical reactor model to validate the method. The method was shown to conserve energy and preserve spatial variation when mapping rays from a Monte Carlo ray tracing model to a computational heat transfer model in ansys fluent.

14 SOLAR ENERGY↗

Global Precipitation Experiment—A New World Climate Research Programme Lighthouse Activity

The future state of the global water cycle and the prediction of freshwater availability for humans around the world remain among the challenges of climate research and are relevant to several United Nations Sustainable Development Goals. The Global Precipitation Experiment (GPEX) takes on the challenge of improving the prediction of precipitation quantity, phase, timing, and intensity, characteristics that are products of a complex integrated system. It will achieve this by leveraging existing World Climate Research Programme (WCRP) activities and community capabilities in satellite, surface-based, and airborne observations, modeling, and experimental research and by conducting new and focused activities. It was launched in October 2023 as a WCRP Lighthouse Activity. Here, we present an overview of the GPEX Science Plan that articulates the primary science questions related to precipitation measurements, process understanding, model performance and improvements, and plans for capacity development. The central phase of GPEX is the WCRP Years of Precipitation for 2–3 years with coordinated global field campaigns focusing on different storm types (atmospheric rivers, mesoscale convective systems, monsoons, and tropical cyclones, among others) over different regions and seasons. Activities are planned over the three phases (before, during, and after the Years of Precipitation) spanning a decade. These include gridded data evaluation and development, advanced modeling, enhanced understanding of processes critical to precipitation, multiscale prediction of precipitation events across scales, and capacity development. These activities will be further developed as part of the GPEX Implementation Plan.

Climate change↗

A constitutive law for finite element contact problems with unclassical friction

Techniques for modeling complex, unclassical contact-friction problems arising in solid and structural mechanics are discussed. A constitutive modeling concept is employed whereby analytic relations between increments of contact surface stress (i.e., traction) and contact surface deformation (i.e., relative displacement) are developed. Because of the incremental form of these relations, they are valid for arbitrary load-deformation histories. The motivation for the development of such a constitutive law is that more realistic friction idealizations can be implemented in finite element analysis software in a consistent, straightforward manner. Of particular interest is modeling of two-body (i.e., unlubricated) metal-metal, ceramic-ceramic, and metal-ceramic contact. Interfaces involving ceramics are of engineering importance and are being considered for advanced turbine engines in which higher temperature materials offer potential for higher engine fuel efficiency.

Plesha, M. E.↗

LDEF microenvironments, observed and predicted

Complex protrusions and surface indentations on spacecraft equipment alter exposure environments by casting shadows, producing reflections and scattering incident atomic oxygen flux and UV radiation. A computer model is being developed to predict these effects. The model accounts for any arbitrary shape, size, orientation, or curvature of exposed objects. LDEF offers a unique opportunity to compare model prediction with observations. For this purpose, a study is underway on twelve of LDEF's copper grounding straps. These straps were exposed at various angles from the ram vector during the LDEF flight. Microenvironment variables include shadowing and reflections from clamps and fasteners, and varying exposure caused by bending of the straps. Strap measurements include optical properties, surface film composition by ESCA, and film thickness measurements by optical interference techniques. The features of the microenvironment model and the analytical methods used to examine the straps are discussed. Data are presented showing predicted microenvironmental variations. These variations are compared with observed point to point differences in surface properties of the straps.

Bourassa, R. J.↗

Microgravity and Charge Transfer in the Neuronal Membrane: Implications for Computational Neurobiology

Evidence from natural and artificial membranes indicates that the neural membrane is a liquid crystal. A liquid-to-gel phase transition caused by the application of superposed electromagnetic fields to the outer membrane surface releases spin-correlated electron pairs which propagate through a charge transfer complex. The propagation generates Rydberg atoms in the lipid bilayer lattice. In the present model, charge density configurations in promoted orbitals interact as cellular automata and perform computations in Hilbert space. Due to the small binding energies of promoted orbitals, their automata are highly sensitive to microgravitational perturbations. It is proposed that spacetime is classical on the Rydberg scale, but formed of contiguous moving segments, each of which displays topological equivalence. This stochasticity is reflected in randomized Riemannian tensor values. Spacetime segments interact with charge automata as components of a computational process. At the termination of the algorithm, an orbital of high probability density is embedded in a more stabilized microscopic spacetime. This state permits the opening of an ion channel and the conversion of a quantum algorithm into a macroscopic frequency code.

Wallace, Ron↗

High Temperature Superconductor/Semiconductor Hybrid Microwave Devices and Circuits

Contents include following: film deposition technique; laser ablation; magnetron sputtering; sequential evaporation; microwave substrates; film characterization at microwave frequencies; complex conductivity; magnetic penetration depth; surface impedance; planar single-mode filters; small antennas; antenna arrays phase noise; tunable oscillations; hybrid superconductor/semiconductor receiver front ends; and noise modeling.

Romanofsky, Robert R.↗

The Effect of Viscosity on the Spherical Stability of Oscillating Gas Bubbles

Gas bubbles driven in radial oscillations are subject to an instability of the spherical shape that is opposed by surface tension and viscosity. An exact linear formulation for the study of the phenomenon has been available for many years, but its complexity has discouraged a detailed investigation. With the recent theory of sonoluminescence of Lohse and co-workers, there has been a renewed interest in the problem and new data have become available. This paper presents a numerical method for the solution of the pertinent equations and compares the theory with these new data. The coupling of the strong nonlinearity of the bubble radial oscillations with the parametric mechanism of the surface instability results in a very complex structure for the stability boundary. Nevertheless, a good agreement between theory and data is found. A comparison with earlier approximate models is also made.

Hao, Y.↗

Kestrel Results at Liftoff Conditions for a Space Launch System Configuration in Proximity to the Launch Tower

Aerodynamic data books for Space Launch System vehicles require databases for the integrated forces and moments and section loads during liftoff and transition to the ascent phase of flight. While the force and moment database can be generated from wind tunnel results, computational analyses are necessary to provide the extensive surface information required to generate proper lineloads. Of the two flight regimes, the liftoff problem is the more costly and complex situation to simulate, as it requires modeling of the vehicle in proximity to the launch tower. The effects of massive separation on the leeward pressure fields of both the tower and vehicle are not well captured with RANS methods, necessitating the use of more advanced methods, such as Delayed Detached Eddy Simulation, in conjunction with computational grids sufficiently refined to resolve the wakes. Details on the computational setup for employing the Kestrel flow solver to address the liftoff problem are presented. The methodology involves the use of independent unstructured near-body grids for the vehicle and the tower, overset by a solution adaptive Cartesian off-body grid. Results from the simulations are compared to experimental results from a test in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel.

Computational fluid dynamics↗

An Observation-Driven Framework for Modeling Post-Fire Hydrologic Response: Evaluation for Two Central California Case Studies

In a warming climate, wildfires are becoming increasingly common, especially in semi-arid environments. Wildfires can disrupt forest ecosystems and induce changes to the land surface. Collectively, these impacts can alter the hydrologic response of a catchment following a fire, resulting in increased potential for surface runoff, reduced evapotranspiration, and, ultimately, a higher risk for flash flooding and mass wasting. The timescale for post-fire recovery of hydrological processes to return to pre-fire conditions is not well established due to the lack of ground measurements. Accurate characterization of fire impacts on hydrologic response is also challenging to simulate, given the complex interplay of various processes. Here, we present a generalized framework to quantify wildfire impacts on runoff generation. We consider the vegetation and soil disturbances as the primary contributors to post-fire floods. Using an ensemble modeling structure to account for parameter uncertainty and consider model sensitivity, remotely sensed leaf area index (LAI) is assimilated into a land surface model (LSM) to simulate vegetation disturbance, and the maximum land surface saturation LSM parameter is decreased to parameterize the soil disturbance following observed fires. We evaluated the impacts of fire-induced changes to LAI and soil saturation on hydrologic states like runoff and evapotranspiration. Analysis of two events in central California shows that 1) the LAI assimilation has a greater impact on water balance; and 2) the soil scheme captures a range of outcomes, with substantial impacts on surface runoff for some ensemble members, which could affect flood potential.

Timothy M Lahmers↗

Gas-Granular Simulation Framework for Spacecraft Landing Plume-Surface Interaction and Debris Transport Analysis

The Gas-Granular Flow Solver (GGFS) multi-phase flow computational framework has been developed to enable simulations of particle flows complex extra-terrestrial regolith materials. Particle flows of interest include the damage of unprepared landing sites from rocket plume impingement on Moon, Mars, and asteroids. The flow solver implements an Eulerian-Eulerian two-fluid model with fluid representation of the gas phase and granular phase to avoid the need to model billions of particle interactions. The granular phase is modeled as an Eulerian fluid with constituent physics closure models derived from first-principle Discrete Element Model (DEM) particle interaction simulations that capture the complex, non-linear granular particle interaction effects. Granular phase constituent models have been developed and integrated that address the complex, non-linear granular material mechanics complexities resulting from both: the irregular, jagged particle shapes and poly-disperse mixture effects encountered in extra-terrestrial regolith, with lunar regolith as the extreme. The GGFS capabilities are being integrated into a proven NASA plume-surface interaction and debris transport simulation framework featuring the Loci/CHEM CFD program and Debris Transport Analysis (DTA) post-processing tools for applications in robotic and human Moon and Mars lander development. Integration of the three simulation tool components. Loci/CHEM, GGFS, and DTA, into a coordinated simulation framework will enable time-accurate spacecraft landing simulations that account for the alteration of the landing surface through plume-induced cratering and the resulting redirection of plume impingement flow and debris transport. Initial implementation of this simulation framework and application examples will be presented.

Liever, Peter A.↗

Structural insights into redox signal transduction mechanisms in the control of nitrogen fixation by the NifLA system

NifL is a conformationally dynamic flavoprotein responsible for regulating the activity of the σ 54 -dependent activator NifA to control the transcription of nitrogen fixation (nif) genes in response to intracellular oxygen, cellular energy, or nitrogen availability. The NifL-NifA two-component system is the master regulatory system for nitrogen fixation. NifL serves as a sensory protein, undergoing signal-dependent conformational changes that modulate its interaction with NifA, forming the NifL–NifA complex, which inhibits NifA activity in conditions unsuitable for nitrogen fixation. While NifL-NifA regulation is well understood, these conformationally flexible proteins have eluded previous attempts at structure determination. In work described here, we advance a structural model of the NifL dimer supported by a combination of scattering techniques and mass spectrometry (MS)-coupled structural analyses that report on the average structure in solution. Using a combination of small angle X-ray scattering-derived electron density maps and MS-coupled surface labeling, we investigate the conformational dynamics responsible for NifL oxygen and energy responses. Our results reveal conformational differences in the structure of NifL under reduced and oxidized conditions that provide the basis for a model for modulating NifLA complex formation in the regulation of nitrogen fixation in response to oxygen in the model diazotroph,Azotobacter vinelandii.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding Uncertainty of Snow Radiative Transfer Modeling Within a Mixed Deciduous and Evergreen Forest

Satellite-based passive microwave observations provide the best available continuous observational estimates of global snow water storage due to their broad geographic footprint and low sensitivity to clouds and precipitation. However, these observations are subject to substantial uncertainty due to the complex radiative properties of snow and from interference in forested areas. Physical radiative transfer models can be leveraged to improve the fidelity of these observations and as a data-assimilation tool. In this article, the Dense Media Radiative Transfer model with Multiple Layers (DMRT-ML) is used to simulate snow brightness temperatures from data collected from snow pits excavated during a two-day-long field study performed a temperate forest in the Northeast United States. The simulations are evaluated against surface-based radiometer observations collected at the snow pits. The DMRT-ML is configured with varying complexity to determine the snowpack characteristics most essential toward simulating brightness temperature within a temperate forest with complicated snow stratigraphy. In general, the single-layer configurations were not sufficiently complex to accurately simulate snow brightness temperature without significant tuning. The most accurate simulation was a two-layer configuration with a prescribed ice layer separating the snow layers. This simulation had a root-mean-square error <;15 K for the 37-GHz frequency. More complicated snowpack stratigraphy configurations did not substantively improve the results over the two-layer model configuration. The DMRT-ML was also used to examine differences between redundant datasets of density and grain size. It was determined that similar snow data collection and radiative transfer model configuration techniques are critical to ensure cross-study comparability.

Theodore Letcher↗

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A Liever↗

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A. Liever↗

Clifford Neural Operators on Atmospheric Data Influenced Partial Differential Equations

Mathematical representations of the atmosphere are key to forecasting and research tasks across Earth science. Numerically solving the underlying partial differential equations(PDEs) of the atmosphere, however, can be difficult and computationally expensive with numerous trade-offs between computing efficiency and accuracy. Utilizing neural net-works to learn approximations of the PDE solutions from the data can help us model complex phenomena more efficiently than traditional numerical schemes. Here, we have applied Clifford algebra-based neural operators for predicting atmospheric variables. Clifford Fourier neural operators are used with two different backbone architectures, ResNet and UNet, on custom data of U10, V10 and surface pressure as well as U500, V500 and Z500. Clifford Fourier neural operators, coupled with ResNet and UNet architectures, are applied to a key reanalysis dataset. Model performance is initially strong, but we observe increasing errors, resulting in the model becoming highly unstable.

Sujit Roy↗

Numerical Solutions for the CAWAPI Configuration on Unstructured Grids at NASA LaRC, United States

In support of the Cranked Arrow Wing Aerodynamic Project International (CAWAPI) with its goal of improving the Technology Readiness Level of flow solvers by comparing results with measured F-16XL-1 flight data, NASA Langley employed the TetrUSS unstructured grid solver, USM3D, to obtain solutions for all seven flight conditions of interest. A newly available solver version that incorporates a number of turbulence models, including the two-equation linear and non-linear k- , was used in this study. As a first test, a choice was made to utilize only a single grid resolution with the solver for the simulation of the different flight conditions. Comparisons are presented with three turbulence models in USM3D, flight data for surface pressure, boundary-layer profiles, and skin-friction distribution, as well as limited predictions from other solvers. A result of these comparisons is that the USM3D solver can be used in an engineering environment to predict vortex-flow physics on a complex configuration at flight Reynolds numbers with a two-equation linear k- turbulence model.

Lamar, John E.↗

Facet-Dependent Adsorption of Pb(II) on Hematite (001), (116), and (104) Surfaces

Hematite’s common (001) and (012) facets are frequently used in model studies of lead (Pb) adsorption behavior, but there is a lack of research on the high-energy facets, e.g. (104), present in nature. Also, few studies have attempted to connect the molecular details of facet-specific Pb adsorption to macroscopic uptake behavior. Here, to address these knowledge gaps, we investigated Pb(II) adsorption behaviors on facet-engineered hematite nanoparticles dominated by (001), (104), and (116). Adsorption experiments revealed significant variations in Pb(II) uptake among the three samples, with (001) demonstrating the highest capacity and (116) showing the best adsorption efficiency when normalized to specific surface area. Adsorption kinetics followed the pseudo-second-order model, indicating the adsorption process is governed mostly by chemisorption. Adsorption isotherms were well fitted by the Langmuir model, indicating uptake proceeds until roughly monolayer adsorption. Detailed characterization revealed Pb(II) was adsorbed as single atoms with complex inner-sphere binding modes that varied across different facets, indicating adsorption is both structurally and energetically facet-dependent. Co-adsorption experiments further demonstrated Cu 2+ , Zn 2+ , and humic acid significantly promoted Pb(II) adsorption. This study advances the understanding of hematite surface reactivity in controlling macroscopic wet adsorption behaviors, providing valuable insights into the environmental fate of Pb(II).

Contaminant removal↗

INTERDUNE DEPOSITS AND STRATIGRAPHIC FRAMEWORK OF THE NAVAJO SANDSTONE IN THE LAKE POWELL AREA, UTAH, USA

The Western Interior of the USA was dominated by desert environments for much of the Jurassic. Of these desert environments, the most extensive by far was the Navajo Sandstone erg, which, in conjunction with its correlative Nugget and Aztec Sandstones, is thought to have covered well over 500,000 km2, and is one of the largest ergs preserved in the rock record. The Navajo Sandstone is also one of a few geologic units which show promise as a potential CO2 sequestration reservoir in Utah. It outcrops along the eastern and southern margin of the state, and subcrops throughout most of the central area. The Navajo Sandstone consists of stacked eolian deposits, composed of well sorted, clean sandstone, deposited in commonly tabular, high angle cross bedded paleodunes, which are on average 15 m thick. Interspersed between these paleodunes are interdune deposits. Interdune deposits consist of sandy to calcareous, predominantly planar bedded, lensoid units, ranging from <1 m up to 7 m thick. In some cases, these interdune deposits occur along more extensive stratigraphic bounding surfaces. Dating within the Navajo Sandstone has historically been very difficult, as a result of its predominantly clean, aeolian sandstone composition. In addition, complexity of internal stratigraphic surfaces coupled with a low structural dip and generally flat topography has resulted in a poor understanding of the internal stratigraphy of the Navajo Sandstone. Exceptional three-dimensional exposures of the Navajo Sandstone in the upper portions of Lake Powell permit us to relate interdune carbonates to a hierarchical bounding surfaces model. Here we use this combined approach to interpret the internal stratigraphy of the Navajo Sandstone in this region. This work forms part of a larger study of the Navajo Sandstone across Utah and its potential as a CO2 reservoir, by developing a more comprehensive stratigraphic framework, and increasing understanding of stratigraphic complexity within one of the most significant eolian systems in the world.

Mahon, Elizabeth↗