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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1991

Geodynamics branch data base for main magnetic field analysis

The data sets used in geomagnetic field modeling at GSFC are described. Data are measured and obtained from a variety of information and sources. For clarity, data sets from different sources are categorized and processed separately. The data base is composed of magnetic observatory data, surface data, high quality aeromagnetic, high quality total intensity marine data, satellite data, and repeat data. These individual data categories are described in detail in a series of notebooks in the Geodynamics Branch, GSFC. This catalog reviews the original data sets, the processing history, and the final data sets available for each individual category of the data base and is to be used as a reference manual for the notebooks. Each data type used in geomagnetic field modeling has varying levels of complexity requiring specialized processing routines for satellite and observatory data and two general routines for processing aeromagnetic, marine, land survey, and repeat data.

Langel, Robert A.↗

NASA NTRS1992

Three-dimensional turbopump flowfield analysis

A program was conducted to develop a flow prediction method applicable to rocket turbopumps. The complex nature of a flowfield in turbopumps is described and examples of flowfields are discussed to illustrate that physics based models and analytical calculation procedures based on computational fluid dynamics (CFD) are needed to develop reliable design procedures for turbopumps. A CFD code developed at NASA ARC was used as the base code. The turbulence model and boundary conditions in the base code were modified, respectively, to: (1) compute transitional flows and account for extra rates of strain, e.g., rotation; and (2) compute surface heat transfer coefficients and allow computation through multistage turbomachines. Benchmark quality data from two and three-dimensional cascades were used to verify the code. The predictive capabilities of the present CFD code were demonstrated by computing the flow through a radial impeller and a multistage axial flow turbine. Results of the program indicate that the present code operated in a two-dimensional mode is a cost effective alternative to full three-dimensional calculations, and that it permits realistic predictions of unsteady loadings and losses for multistage machines.

Sharma, O. P.↗

NASA NTRS1995

P-polarized reflectance spectroscopy: A high sensitive real-time monitoring technique to study surface kinetics under steady state epitaxial deposition conditions

This paper describes the results of real-time optical monitoring of epitaxial growth processes by p-polarized reflectance spectroscopy (PRS) using a single wavelength application under pulsed chemical beam epitaxy (PCBE) condition. The high surface sensitivity of PRS allows the monitoring of submonolayer precursors coverage on the surface as shown for GaP homoepitaxy and GaP on Si heteroepitaxy as examples. In the case of heteroepitaxy, the growth rate and optical properties are revealed by PRS using interference oscillations as they occur during growth. Super-imposed on these interference oscillations, the PRS signal exhibits a fine structure caused by the periodic alteration of the surface chemistry by the pulsed supply of chemical precursors. This fine structure is modeled under conditions where the surface chemistry cycles between phosphorus supersaturated and phosphorus depleted surfaces. The mathematical model describes the fine structure using a surface layer that increases during the tertiarybutyl phosphine (TBP) supply and decreases during and after the triethylgallium (TEG) pulse, which increases the growing GaP film thickness. The imaginary part of the dielectric function of the surface layer is revealed from the turning points in the fine structure, where the optical response to the first precursor pulse in the cycle sequence changes sign. The amplitude of the fine structure is determined by the surface layer thickness and the complex dielectric functions for the surface layer with the underlying bulk film. Surface kinetic data can be obtained by analyzing the rise and decay transients of the fine structure.

Dietz, Nikolaus↗

NASA NTRS2000

A Characterization of the Terrestrial Environment of Kodiak Island, Alaska for the Design, Development and Operation of Launch Vehicles

A quantitative characterization of the terrestrial environment is an important component in the success of a launch vehicle program. Environmental factors such as winds, atmospheric thermodynamics, precipitation, fog, and cloud characteristics are among many parameters that must be accurately defined for flight success. The National Aeronautics and Space Administration (NASA) is currently coordinating weather support and performing analysis for the launch of a NASA payload from a new facility located at Kodiak Island, Alaska in late 2001 (NASA, 1999). Following the first launch from the Kodiak Launch Complex, an Air Force intercontinental ballistic missile on November 5, 1999, the site's developer, the Alaska Aerospace Development Corporation (AADC), is hoping to acquire a sizable share of the many launches that will occur over the next decade. One such customer is NASA, which is planning to launch the Vegetation Canopy Lidar satellite aboard an Athena I rocket, the first planned mission to low earth orbit from the new facility. To support this launch, a statistical model of the atmospheric and surface environment for Kodiak Island, AK has been produced from rawinsonde and surface-based meteorological observations for use as an input to future launch vehicle design and/or operations. In this study, the creation of a "reference atmosphere" from rawinsonde observations is described along with comparisons between the reference atmosphere and existing model representations for Kodiak. Meteorological conditions that might result in a delay on launch day (cloud cover, visibility, precipitation, etc.) are also explored and described through probabilities of launch by month and hour of day. This atmospheric "mission analysis" is also useful during the early stages of a vehicle program, when consideration of the climatic characteristics of a location can be factored into vehicle designs. To be most beneficial, terrestrial environment definitions should a) be available at the inception of the program and based on the desired operational performance of the launch vehicle, b) be issued under the signature of the program manager and be part of the controlled program definition and requirements documentation, and c) specify the terrestrial environment for all phases of activity including prelaunch, launch, ascent, on-orbit, decent, and landing. Since the beginning of the space era, NASA has utilized some of the most detailed assessments of the terrestrial climatic environment in design, development, and operations of both expendable and reusable launch vehicles.

Rawlins, Michael A.↗

NASA NTRS2008

Are Fullerenes Relevant to Cosmochemistry? A New Finding

The abundances of noble gases found in primitive, carbonaceous meteorites are unexpected when compared with our Sun. Known as Q-gases (Q for some unknown carrier dubbed quintessence ), this anomaly has remained a mystery since it was discovered in 1975. Q-gases are characterized by increasing depletions with decreasing atomic number (Z) relative to solar noble gases and normalized to 132Xe (Figure 1). This Q-gas mass fractionation is unexplained, and its investigation is important to understanding the origin of the solar system. However, the subject is fraught with controversy, in part due to the complex nature of Q and in part due to claims of some researchers that cannot be reproduced by other investigators. The topic is discussed in numerous places [e.g., 1-4], with models of Q falling into two basic categories, both involving carbon entrapment of noble gases. First (Group A), there is the conservative two-dimensional view that Q-gases are adsorbed or sorbed onto a "labyrinth" of graphite or carbon grains [5-9], or they undergo active capture onto growing surfaces [6]. Second (Group B), there is the view holding to the remarkable property of carbon discovered in 1985. Carbon can curl up into closed geometries of hexagon- and pentagon-shaped carbon-ring configurations, a property ignored completely by Group A. Group B thinks of Q as a three-dimensional structure of endohedral carbon cages like fullerenes, carbon onions, or some class of carbon nanotubes [3, 4, 10]. Group B does not exclude Group A effects.

Wilson, T. L.↗

NASA NTRS2019

Solar Energetic Particles in the Inner Heliosphere: Status and Open Questions

Solar energetic particle (SEP) events are related to both solar flares and coronal mass ejections (CMEs) and they present energy spectra that span from a few keV up to several GeV. A wealth of observations from widely distributed spacecraft have revealed that SEPs fill very broad regions of the heliosphere, often all around the Sun. High energy SEPs can sometimes be energetic enough to penetrate all the way down to the surface of the Earth and thus be recorded on the ground as ground level enhancements (GLEs). The conditions of the radiation environment are currently unpredictable due to an as-yet incomplete understanding of solar eruptions and their corresponding relation to SEP events. This is because the complex nature and the interplay of the injection, acceleration and transport processes undergone by the SEPs in the solar corona and the interplanetary space prevent us from establishing an accurate understanding (based on observations and modelling). In this work, we review the current status of knowledge on SEPs, focusing on GLEs and multi-spacecraft events. We extensively discuss the forecasting and nowcasting efforts of SEPs, dividing these into three categories. Finally, we report on the current open questions and the possible direction of future research efforts. This article is part of the theme issue ‘Solar eruptions and their space weather impact’.

Anastasiadis, Anastasios↗

NASA NTRS2019

A new environment to simulate the dynamics in the close proximity of rubble-pile asteroids

This paper presents a new environment to simulate close-proximity dynamics around rubble-pile asteroids. The code provides methods for modeling the asteroid’s gravity field and surface through granular dynamics. It implements stateof-the-art techniques to model both gravity and contact interaction between particles: 1) mutual gravity as either direct N2 or Barnes-Hut GPU-parallel octree and 2) contact dynamics with a soft-body (force-based, smooth dynamics), hard-body (constraint-based, non-smooth dynamics), or hybrid (constraint-based with compliance and damping) approach. A very relevant feature of the code is its ability to handle complex-shaped rigid bodies and their full 6D motion. Examples of spacecraft close-proximity scenarios and their numerical simulations are shown.

Ferrari, Fabio↗

NASA NTRSDate not supplied

Development of a Consistent MODIS and VIIRS Cloud Detection Approach for CERES

A consistent cloud fraction record across various satellite platforms is essential for maintaining a long-term and stable climate data record of Earth's energy budget. With the Aqua satellite nearing the end of its operational lifetime, the continuation of this record relies on utilizing VIIRS observations from NOAA20 for cloud detection in NASA’s Clouds and Earth’s Radiant Energy System (CERES) project. However, integrating data from VIIRS and MODIS instruments poses challenges due to their distinct characteristics, such as varying spatial resolutions and different spectral channels. As a result, deriving consistent cloud properties from these two sensors without introducing artificial discontinuities in the time series remains a complex and challenging task. This paper will present progress toward developing a unified MODIS and VIIRS cloud mask using common channels to produce consistent cloud properties for CERES next edition (Ed5) Earth radiation budget data products. The fundamental approach taken in the CERES cloud mask is to compare the observed radiances to the expected background clear sky radiances. Therefore, one vital step is to compute clear sky radiances with a radiative transfer model that accurately accounts for satellite-specific, spectrally dependent surface reflectance, surface emission, and atmospheric absorption. Refined radiative transfer models and updated ancillary data inputs including surface emissivity maps, IGBP, snow and ice maps are incorporated into the processing framework to improve cloud detection consistency and accuracy. Pixel level cloud mask results and monthly global cloud fraction comparisons between MODIS and VIIRS will be presented to evaluate their consistency. Remaining challenges will be discussed. It is expected that this work will contribute consistent cloud properties for CERES that adequately bridges the MODIS and VIIRS imager data records.

CERES↗

NASA NTRSDate not supplied

LES-Based Analysis of Film Cooling in a High-Pressure Turbine Rotor Including Effects of Purge and Tip Flow

Accurate modeling of coolant airflows, which form protective films over turbine blades, is essential for designing fuel-efficient and environmentally sustainable gas turbine engines. Excessive coolant reduces thermal efficiency, while insufficient coolant leads to blade overheating and causes damage. Therefore, precise prediction of flow field interactions with cooling air is critical for optimizing turbine performance. This study numerically investigates the cooling effectiveness of purge and film cooling flows within a high-pressure turbine (HPT) rotor using Large Eddy Simulation (LES). The study utilizes NASA Glenn Research Center’s Glenn-HT solver. The simulation models ethe conditions of the Penn State University START rotating rig. A high-fidelity structured mesh comprising up to 800 million cells is employed to resolve high-Reynolds number flow (Re ≈ 350,000) and to capture intricate secondary flow structures, including tip leakage and purge-induced vortices. Film cooling effectiveness computations are highly sensitive to boundary conditions at the cooling holes and to grid resolution. Even with well-resolved grids and included plena, strong mixing challenges traditional eddy viscosity models. To address this, a simplified configuration is simulated: a truncated row of shaped holes on the suction side near the leading edge and a row on the pressure side, both fed from internal plena while the purge slot and tip clearance are also modeled. Two isothermal LES cases are conducted at two distinct wall temperatures, which yield the adiabatic wall temperature and the heat transfer coefficient. The definition and means of computation of the effectiveness is discussed in this paper. The simulations reveal detailed three-dimensional unsteady flow features, including coherent vortical structures and secondary flows originating from the purge cavity. Film cooling effectiveness and Nusselt number distributions are presented for both the blade surface and tip, highlighting regions of elevated heat transfer and complex thermal behavior. These findings underscore the importance of high-resolution LES and realistic boundary conditions in capturing the dynamics of purge and film cooling, offering valuable insights for improving turbine blade design and thermal management strategies.

Secondary Flows↗

NASA NTRSDate not supplied

A GPU-based Approach for Turbomachinery Application

Gas Turbine↗

DOE OSTI2022

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗

NASA NTRS1991

Creep behavior of copper at intermediate temperatures. II - Surface microstructural observations. III - A comparison with theory

Three different types of microstructural slip features are noted to occur during the creep of Cu at 0.46-0.72 of absolute melting point. While single slip is associated with higher temperatures and lower stresses, complex wavy slip features are observed at higher temperatures and higher stresses as well as with increasing strains: suggesting the importance of cross-slip mechanisms. At lower temperatures and higher stresses the multiple-slip morphologies observed indicate that cross-slip mechanisms may control the creep of polycrystalline Cu only over a limited stress and temperature range. A phenomenological model is proposed which assumes that (1) cell boundaries within subgrains act as both sources of, and obstacles to, gliding dislocations, and (2) dislocation annihilation occurs at the cell boundaries by climb and cross-slip.

Raj, S. V.↗

DOE OSTI2026

Modeling rf sheath formation in turbulent tokamak boundary plasma

During ICRF antenna operation, complex interactions between turbulent density profiles, nonlinear RF sheaths, and RF-induced convective transport are observed to alter plasma density in the tokamak edge [D’Ippolito et al., Nucl. Fusion 38, 1543 (1998)]. In this work, we explore the physics of such interactions via numerical modeling, using a nonlinear EM/plasma/sheath code (VSim) and profiles obtained from a fluid plasma turbulence code (Hermes) in a 3D slab domain containing biased side-wall limiters. RF-rectified sheath formation on antenna and limiter surfaces is observed as electromagnetic waves launched by the antenna are refracted through the turbulent density profile. On transport timescales, such sheath potentials have been shown to influence both the mean species density and its RMS fluctuation spectrum [Smithe et al., these proceedings]. On the faster RF timescales, we demonstrate that the converse is also true – regions of high plasma density near material surfaces give rise to the highest sheath potential amplitudes. When density is turbulent and spatially nonuniform, localized regions of high sheath potential (hotspots) may develop where high-density filaments intersect material surfaces. Such hotspots are of particular concern as sources of impurity sputtering, and we explore their behavior in response to changes both to the local plasma density and to antenna operating parameters and structure. Related results exploring the role of Faraday shields and/or enclosing structures in suppressing high sheath potentials for other devices (e.g. SPARC) will also be shown.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Instrumentation development and testing of a wind turbine blade for sub-scale wake studies

Wind turbine blade aerodynamics and the resulting wake flow are complex, and wind tunnel testing of these flows can provide critical insight. The data from such tests are also valuable for validation of numerical models. For experiments using sub-scale turbines to be useful, the blade aerodynamics and wakes must exhibit the important features observed in utility-scale turbine flows. In this work, ~1 m blades designed to produce physics relevant to larger scale turbines were manufactured and affixed to an existing turbine. One of the blades was instrumented for blade surface pressure measurements. Time-dependent surface pressure measurements coupled with instantaneous measurements of the inflow with Cobra probes and the wake with particle image velocimetry allowed for characterization of the inflow, blade flow, and near wake. The results demonstrate that the instrumentation was effective in characterizing the blade loading and the flow field. For the one test case discussed in this paper, the measurements of inflow, blade loading, and wake properties facilitate understanding of the wake's behavior.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initialization

Obtaining lightweight and accurate approximations of discretized objective functional Hessians in inverse problems governed by partial differential equations (PDEs) is essential to make both deterministic and Bayesian statistical large-scale inverse problems computationally tractable. The cubic computational complexity of dense linear algebraic tasks, such as Cholesky factorization, that provide a means to sample Gaussian distributions and determine solutions of Newton linear systems is a computational bottleneck at large-scale. These tasks can be reduced to log-linear complexity by utilizing hierarchical off-diagonal low-rank (HODLR) matrix approximations. In this work, we show that a class of Hessians that arise from inverse problems governed by PDEs are well approximated by the HODLR matrix format. In particular, we study inverse problems governed by PDEs that model the instantaneous viscous flow of ice sheets. In these problems, we seek a spatially distributed basal sliding parameter field such that the flow predicted by the ice sheet model is consistent with ice sheet surface velocity observations. Here, we demonstrate the use of HODLR Hessian approximation to efficiently sample the Laplace approximation of the posterior distribution with covariance further approximated by HODLR matrix compression. Computational studies are performed which illustrate ice sheet problem regimes for which the Gauss–Newton data-misfit Hessian is more efficiently approximated by the HODLR matrix format than the low-rank (LR) format. We then demonstrate that HODLR approximations can be favorable, when compared to global LR approximations, for large-scale problems by studying the data-misfit Hessian associated with inverse problems governed by the first-order Stokes flow model on the Humboldt glacier and Greenland ice sheet.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

X-Band Radar and Surface-Based Observations of Cold-Season Precipitation in Western Colorado’s Complex Terrain

Abstract Hydrologic processes associated with intermountain cold-season precipitation in the Upper Colorado River basin have important impacts on avalanche forecasting and water resource management. However, traditional weather radar networks struggle with observations in this complex terrain. Data collected during the Study of Precipitation, the Lower Atmosphere, and the Surface for Hydrometeorology (SPLASH) and its sister campaign, Surface Atmosphere Integrated Field Laboratory (SAIL) in the East River watershed of western Colorado, are used to examine a multistorm period from 23 December 2021 to 1 January 2022 that contributed 35% of the total winter precipitation in this watershed. Dual-polarization X-band radar and disdrometer measurements show ∼30-mm differences in precipitation amount at two sites in proximity over four distinct storm events within the period. Wind patterns, synoptic forcings, microphysical characteristics of precipitation, and surface meteorology are analyzed to explain the observed spatial variability of cold-season precipitation in complex mountainous terrain. Analysis shows that differences over time within this event are mainly accounted for by synoptic forcings, such as frontal passages; differences between sites are accounted for by the impact of variations in local wind patterns on precipitation microphysics. Patterns of surface precipitation intensity are compared and found to be correlated with X-band radar signatures; a relationship between a strong dendritic growth stage and intense low-density surface precipitation is reinforced by this study. This relationship demonstrates the importance of particle growth mechanisms on surface snowfall patterns in high-altitude complex terrain, underscoring the importance of realistic microphysical parameterizations. Significance Statement The amount and density of snowpack from western Colorado winter storms have significant impacts on water resources in the Upper Colorado River basin. Snowpack characteristics are affected by small-scale differences in how snow forms in the atmosphere. These differences are hard to study in the complex terrain of the Rockies, but data from the SPLASH and SAIL field campaigns allows us to investigate how snow crystal formation and mountain-driven wind patterns affect snow near the surface. Our study finds that snow crystal growth varies over small space and time scales and is likely controlled by the terrain beneath a given location and resultant local wind patterns. These results imply that predicting snowpack in the Rockies requires properly representing local wind patterns and crystal growth processes in models.

Heflin, Stella↗

DOE OSTI2021

Development of Explainable, Knowledge-Guided AI Models to Enhance the E3SM Land Model Development and Uncertainty Quantification

Focal Area(s): (2)Predictive modeling using AI techniques and AI-derived model components; use of AI and other tools to design a prediction system comprising of a hierarchy of models. (3) Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge- guided AI. Science Challenge: The Energy Exascale Earth System Model (E3SM) is a fully coupled, state-of-the-science Earth system model that uses code optimized for DOE's advanced computers to address the most critical scientific questions facing our nation and society (Golaz et al., 2019). The E3SM Land model (ELM) is designed to understand how the changes in terrestrial land surfaces will interact with other Earth system components and has been used to understand hydrologic cycles, biogeophysics, and ecosystem dynamics. In spite of great successes, the ELM has several known issues that restrain rapid improvements. For example, the ELM uses equilibrium models to simulate dynamic land-climate interactions and it requires long model spin-up time to identify suitable initial conditions for transient simulations. The ELM lacks built-in uncertainty mechanisms that can improve the robustness of model predictions. The ELM is a holistic, deterministic model system with a rigid design, and in many situations, it is hard to modify the ELM system to incorporate new theory/hypothesis and new data across scales to address emerging science problems (such as predicting the impacts of water cycle extremes). In addition, The ELM is technically optimized for traditional CPU-centric computers and it cannot fully utilize the current and incoming leadership computers for model simulations and uncertainty quantification (UQ). The success of artificial intelligence (AI) has inspired scientists to use AI models to discover intrinsic features from simulation data (Chattopadhyay et al., 2020) and observational data (Reichstein et al., 2019) to gain further process understanding of Earth science problems. However, autonomous AI model training through deep learning usually requires a huge amount of annotated data. To overcome the limitations from the data and computing resources, knowledge-guided AI models are necessary where human-knowledge is ingested in model construction (Banino et al., 2018) and training process (Silver et al., 2016) for efficient learning. Herein, we present a new way that leverages the process understanding from the ELM to guide AI model development for the ELM enhancement and UQ. We hope this study can inspire further Earth and environmental system model developments and transformations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1989

The use of models to predict potential contamination aboard orbital vehicles

A model of fungal growth on air-exposed, nonnutritive solid surfaces, developed for utilization aboard orbital vehicles is presented. A unique feature of this testable model is that the development of a fungal mycelium can facilitate its own growth by condensation of water vapor from its environment directly onto fungal hyphae. The fungal growth rate is limited by the rate of supply of volatile nutrients and fungal biomass is limited by either the supply of nonvolatile nutrients or by metabolic loss processes. The model discussed is structurally simple, but its dynamics can be quite complex. Biofilm accumulation can vary from a simple linear increase to sustained exponential growth, depending on the values of the environmental variable and model parameters. The results of the model are consistent with data from aquatic biofilm studies, insofar as the two types of systems are comparable. It is shown that the model presented is experimentally testable and provides a platform for the interpretation of observational data that may be directly relevant to the question of growth of organisms aboard the proposed Space Station.

Boraas, Martin E.↗