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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Scientist-in-the-Loop Data Analytics Framework for Intelligent Simulation Model Tuning and Validation

This project developed a scientist-in-the-loop data analytics framework for intelligent simulation model tuning and validation, targeting the Weather Research and Forecasting (WRF) model and its solar energy variant, WRF-Solar-BNL. Domain experts, such as climate scientists, depend on large-scale numerical simulations for knowledge discovery and decision-making, yet the complexity of parameter tuning and the disconnect between automated optimization and domain expertise pose significant challenges. We extended an interactive visual analytics framework that enables domain experts to observe and intervene in the computational steering process by identifying disagreements between the simulation model, surrogate model, and the expert’s domain knowledge. Using Bayesian Optimization with Gaussian Process Regression as the surrogate model, our system allows users to probe parameter relationships, analyze correlation patterns, and adjust tuning parameters in real time. We developed use cases for solar irradiance forecasting through sustained collaboration with Brookhaven National Laboratory, resolving critical model configuration challenges and achieving meaningful reductions in prediction error. The project supported one PhD student, one MS student, and eight undergraduate students across three Data Science Capstone projects, resulting in one master’s thesis.

Dasgupta, Aritra [New Jersey Institute of Technolo↗
NASA NTRS1992

A toy model linking atmospheric thermal radiation and sea ice growth

A simplified analytical model of sea ice growth is presented where the atmosphere is in thermal radiative equilibrium with the ice. This makes the downwelling longwave radiation reaching the ice surface an internal variable rather than a specified forcing. Analytical results demonstrate how the ice state depends on properties of the ice and on the externally specified climate.

Thorndike, A. S.↗
NASA NTRS2007

Science in Exploration: From the Moon to Mars and Back Home to Earth

NASA is embarking on a grand journey of exploration that naturally integrates the past successes of the Apollo missions to the Moon, as well as robotic science missions to Mars, to Planet Earth, and to the broader Universe. The US Vision for Space Exporation (VSE) boldly lays out a plan for human and robotic reconnaissance of the accessible Universe, starting with the surface of the Moon, and later embracing the surface of Mars. Sustained human and robotic access to the Moon and Mars will enable a new era of scientific investigation of our planetary neighbors, tied to driving scientific questions that pertain to the evolution and destiny of our home planet, but which also can be related to the search habitable worlds across the nearby Universe. The Apollo missions provide a vital legacy for what can be learned from the Moon, and NASA is now poised to recapture the lunar frontier starting with the flight of the Lunar Reconnaissance Orbiter (LRO) in late 2008. LRO will provide a new scientific context from which joint human and robotic exploration will ensue, guided by objectives some of which are focused on the grandest scientific challenges imaginable : Where did we come from? Are we alone? and Where are we going? The Moon will serve as an essential stepping stone for sustained human access and exploration of deep space and as a training ground while robotic missions with ever increasing complexity probe the wonders of Mars. As we speak, an armada of spacecraft are actively investigating the red planet both from orbit (NASA's Mars Reconnaissance Orbiter and Mars Odyssey Orbiter, plus ESA's Mars Express) and from the surface (NASA's twin Mars Exploration Rovers, and in 2008 NASA's Phoenix polar lander). The dramatically changing views of Mars as a potentially habitable world, with its own flavor of global climate change and unique climate records, provides a new vantage point from which to observe and question the workings of our own planet Earth. By 2010 NASA will have its first mobile analytical laboratory operating on the surface of Mars (Mars Science Laboratory) in search of potentially subtle expressions of past life or at least of life-hospitable environments. Meanwhile back here on Planet Earth, NASA will be continuing to implement an increasingly comprehensive program of robotic missions that address major issues associated with global climate variability, and the "state variables" that affect the quality of human life on our home planet. Ultimately, the fmits of NASA's emergent program of Exploration (VSE) will provide never-beforepossible opportunities for scientific leadership and advancement, culminating in a new state of awareness from which to better plan for the sustainability of life on Earth and for extending Earth life to the Moon and eventually to Mars. As NASA nears its 50th anniversary, the unimaginable and unexpected wealth of strategic knowledge its missions have generated about Earth, the Universe, and our local Solar System boggles the mind and serves as a legacy of knowledge for Educators to inspire future generations.

Garvin, James B.↗
NASA NTRS1982

Climatic influence of background and volcanic stratosphere aerosol models

A simple modelization of the earth atmosphere system including tropospheric and stratospheric aerosols has been derived and tested. Analytical expressions are obtained for the albedo variation due to a thin stratospheric aerosol layer. Also outlined are the physical procedures and the respective influence of the main parameters: aerosol optical thickness, single scattering albedo and asymmetry factor, and sublayer albedo. The method is applied to compute the variation of the zonal and planetary albedos due to a stratospheric layer of background H2SO4 particles and of volcanic ash.

Deschamps, P. Y.↗
DOE OSTI2025

Data for Photosynthetic responses to temperature across the tropics: a meta-analytic approach

This data package contains raw data, data output, and code of photosynthetic temperature response curves from tropical forests. Data are used in "Photosynthetic responses to temperature across the tropics: a meta-analytic approach". The research investigates how photosynthetic optimum temperatures and shapes of photosynthetic temperature response curves varies across tropical forest climates and growth conditions. Growth climate variables include mean annual temperature, max and max temperature, diurnal temperature range, and aridity index. Meta-analysis combines 18 datasets with representation from Africa, Oceana, North American, and South America. Growth conditions analyzed considers deciduousness, successional status, light conditions, and whether plants are grown in situ or ex situ. All files, except for the raw datafile (Tropical_MetaAnalysis_Master_3.8.22_Edit.csv), have been processed using R code, which is provided.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Scaling Laws for Impact Craters in Water

Tsunami waves from asteroid impacts into water are of concern from asteroids in the 200 m to 1 km diameter range because this spans the range from asteroids that will likely hit the surface and not airburst, but also be small enough that global climate effects will hopefully be minimal. Current estimates of impact tsunamis depend on either hydrocode simulations or on semi-analytical models. Unfortunately there is significant disagreement between these methods. One of the main reasons for the disparity is that the semi-analytical models such as Holsapple (1993) rely on experimental impacts into deep water. However for asteroids in the 200 - 1000 m range even the deep ocean basins can appear as shallow water impacts where the crater formed in the water reaches all the way to the sea floor. Another reason for the disparity arises from the linear interpolation of data across many orders of magnitude difference between Froude number (ratio of kinetic to gravitational energy) used in the laboratory experiments and what would be seen in an asteroid impact. The Gault & Sonett (1982) experiment shot millimeter sized glass spheres into water at 1 to 6 km/s and the Olevson (1969) experiment dropped millimeter sized water drops at a few meters per second. The goal of this work was to fill in the gaps and conduct experiments and simulations at the correct Froude numbers of interest, and in both deep and shallow water, to help resolve the disparity and extend the semi-analytical models.

Robertson, Darrel↗
DOE OSTI2024

An analytic theory for the degree of Arctic Amplification

Arctic Amplification (AA), the amplified surface warming in the Arctic relative to the global mean, is a robust and impactful feature of climate change. While the basic physical picture of AA has been depicted, a clear understanding of how the degree of AA is determined has not been established. Here, by deciphering the intricate role of atmospheric heat transport (AHT), we build a two-box energy-balance model of AA and derive that the degree of AA is a simple nonlinear function of the Arctic and global feedbacks, the meridional heterogeneity in radiative forcing, and the partial sensitivities of AHT to global mean warming and meridional warming gradient. The formula captures the varying degree of AA in individual climate models and attributes the variation to specific physical factors. It further conveys a concise picture of how essential physics mutually determine the degree of AA and limit the range within 1.5~3.5. Our results articulate AHT as both forcing and feedback to AA, highlighting its partial sensitivities instead of total change as the key parameters for understanding AA. We also find that the effect of lapse rate feedback, a widely-recognized major contributor to AA, is fully offset by the effect of water vapor feedback.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

ML/AI Applications to the Atmosphere Science Data and Simulations (Demonstration and Vision)

Artificial Intelligence has been recognized as one of the most powerful tools for scientific research. It has a wide range of applications in atmospheric science and plays a significant role in advancing our understanding of the Earth-Atmosphere system, as well as improving our ability to monitor, predict, and respond to atmospheric observations and simulations. Different AI architectures can help us handle various problems according to our research goals. In this presentation, we will introduce several use cases and models for applying computer vision to active remote sensing data from CALIOP, analyzing cloud dynamical relationships for climate model parameterizations, and building surrogate models for lidar simulations. The presentation will highlight the advantages that AI offers compared to traditional analytical methods. By assembling pieces of the multidimensional atmospheric science puzzle, we can integrate our knowledge from observations to simulations.

Shan Zeng↗
DOE OSTI2025

The potential for New Mexico basalts to sequester CO 2 with a focus on critical element mobility

This study evaluates the potential of New Mexico basaltic rocks and mafic mine waste for CO₂ sequestration via mineral carbonation. Batch experiments up to 200 days at 40°C simulated CO₂-bearing fluid interactions with various crushed basaltic materials at different grain sizes. Results showed that 70–80% of injected CO₂ was mineralized, with the finest grain sizes showing the most rapid and effective drawdown. The experiments also assessed the mobility of critical metals (Cu, Ni, Zn, Co), revealing trends tied to mineral dissolution and secondary mineral formation. The findings support the dual potential of mine waste for CO₂ sequestration and critical element recovery, informing future carbon capture and resource upcycling strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1987

U-238-U-234-Th-230-Th-232 systematics and the precise measurement of time over the past 500,000 years

A method is presented for the high-precision measurement of the Th-230 abundance in corals by isotope-dilution mass spectrometry using techniques developed by Chen and Wasserburg (1980, 1981) and Chen et al. (1986). It is shown that 6 x 10 to the 8th atoms of Th-230 can be measured to + or - 30 percent (2 sigma) and 2 x 10 to the 10th atoms of Th-230 to + or - 2 percent. The time over which useful age data on corals can be obtained ranges from a few years to about 500 ky, with the uncertainty in age ranging from 5 y for a 180-y-old coral, to 44 y for a 8294-y-old coral, to 1.1 ky for a 123.1-ky-old coral. Ages were determined with high analytical precision for several corals that grew during high sea-level stands about 120 ky ago, supporting the view that the dominant cause of Pleistocene climate change was Milankovitch forcing.

Edwards, R. Lawrence↗
NASA NTRS2014

Analytical Techniques for Retrieval of Atmospheric Composition with the Quadrupole Mass Spectrometer of the Sample Analysis at Mars Instrument Suite on Mars Science Laboratory

The Sample Analysis at Mars (SAM) instrument suite is the largest scientific payload on the Mars Science Laboratory (MSL) Curiosity rover, which landed in Mars׳ Gale Crater in August 2012. As a miniature geochemical laboratory, SAM is well-equipped to address multiple aspects of MSL׳s primary science goal, characterizing the potential past or present habitability of Gale Crater. Atmospheric measurements support this goal through compositional investigations relevant to martian climate evolution. SAM instruments include a quadrupole mass spectrometer, a tunable laser spectrometer, and a gas chromatograph that are used to analyze martian atmospheric gases as well as volatiles released by pyrolysis of solid surface materials (Mahaffy et al., 2012). This report presents analytical methods for retrieving the chemical and isotopic composition of Mars׳ atmosphere from measurements obtained with SAM׳s quadrupole mass spectrometer. It provides empirical calibration constants for computing volume mixing ratios of the most abundant atmospheric species and analytical functions to correct for instrument artifacts and to characterize measurement uncertainties. Finally, we discuss differences in volume mixing ratios of the martian atmosphere as determined by SAM (Mahaffy et al., 2013) and Viking (Owen et al., 1977, Oyama and Berdahl, 1977) from an analytical perspective. Although the focus of this paper is atmospheric observations, much of the material concerning corrections for instrumental effects also applies to reduction of data acquired with SAM from analysis of solid samples.

quadropole mass spectometer↗
NASA NTRS1991

Biological production models as elements of coupled, atmosphere-ocean models for climate research

Process models of phytoplankton production are discussed with respect to their suitability for incorporation into global-scale numerical ocean circulation models. Exact solutions are given for integrals over the mixed layer and the day of analytic, wavelength-independent models of primary production. Within this class of model, the bias incurred by using a triangular approximation (rather than a sinusoidal one) to the variation of surface irradiance through the day is computed. Efficient computation algorithms are given for the nonspectral models. More exact calculations require a spectrally sensitive treatment. Such models exist but must be integrated numerically over depth and time. For these integrations, resolution in wavelength, depth, and time are considered and recommendations made for efficient computation. The extrapolation of the one-(spatial)-dimension treatment to large horizontal scale is discussed.

Platt, Trevor↗
NASA NTRS2013

The Ocean Colour Climate Change Initiative: III. A Round-Robin Comparison on In-Water Bio-Optical Algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situ Rrs as input to the models, the performance of eleven semianalytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

Phytoplankton↗
DOE OSTI2024

Neural network representations of multiphase Equations of State

Abstract Equations of State model relations between thermodynamic variables and are ubiquitous in scientific modelling, appearing in modern day applications ranging from Astrophysics to Climate Science. The three desired properties of a general Equation of State model are adherence to the Laws of Thermodynamics, incorporation of phase transitions, and multiscale accuracy. Analytic models that adhere to all three are hard to develop and cumbersome to work with, often resulting in sacrificing one of these elements for the sake of efficiency. In this work, two deep-learning methods are proposed that provably satisfy the first and second conditions on a large-enough region of thermodynamic variable space. The first is based on learning the generating function (thermodynamic potential) while the second is based on structure-preserving, symplectic neural networks, respectively allowing modifications near or on phase transition regions. They can be used either “from scratch” to learn a full Equation of State, or in conjunction with a pre-existing consistent model, functioning as a modification that better adheres to experimental data. We formulate the theory and provide several computational examples to justify both approaches, highlighting their advantages and shortcomings.

Science & Technology - Other Topics↗
DOE OSTI2026

Historic climate, cosmogenic 10Be, denudation-rate, and geospatial datasets from the Pikes Peak region, Colorado, USA

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of elevation-dependent denudation rates on Pikes Peak in the Front Range of the Rocky Mountains, Colorado, USA. The package includes GIS layers used to produce the study-area map, including sample locations, sample watershed boundaries, the Pikes Peak batholith, Pleistocene glacier extent, weather station locations, and elevation and hillshade rasters, together with comma-separated value (CSV) tables and matching CSV data dictionaries. These mapped layers provide the geographic framework for interpreting denudation patterns across the Pikes Peak region and for relating sample locations to watershed geometry, bedrock setting, glacial history, and nearby climate stations. The first group of tables reports climate and geospatial context for the study area. These files include station-based temperature and precipitation data used to characterize elevational gradients in mean annual climate and monthly climate seasonality, sample locations, denudation-rate and topographic metrics, fixed frost-cracking model parameters, frost-cracking intensity and precipitation-frequency metrics, and stream-power inversion results. Together, these data provide the basis for evaluating how denudation varies with elevation, climate, and landscape form across sampled catchments on Pikes Peak. The second group of tables reports cosmogenic nuclide and erosion-model results used in the denudation analysis. Included files contain accelerator mass spectrometry (AMS) measurements for in situ-produced cosmogenic beryllium-10 (10Be), including sample identifiers, measured 10Be:9Be ratios, analytical uncertainties, carrier mass, quartz mass, blank corrections, blank-group statistics, and calculated 10Be concentrations and uncertainties. Additional tables summarize stream-power-law inversion results for sampled catchments, including optimized model parameters, predicted erosion rates, residual metrics, channel-pixel counts, and convergence status, as well as regression equations and summary statistics used to evaluate relationships among elevation, climate, frost cracking, precipitation forcing, and denudation rate. The package contains GIS files, comma-separated value files (.csv), Microsoft Excel files (.xlsx), CSV data dictionaries, a file-level metadata table, and a readme text file.

10Be cosmogenic nuclides↗
DOE OSTI2025

Establishing nationwide power system vulnerability index across US counties using interpretable machine learning

Power outages have become increasingly frequent, intense, and prolonged in the US due to climate change, aging electrical grids, and rising energy demand. However, largely due to the absence of granular spatiotemporal outage data, we lack data-driven evidence and analytics-based metrics to quantify power system vulnerability. This limitation has hindered the ability to effectively evaluate and address vulnerability to power outages in US communities. Here, in this work, we collected ∼179 million power outage records at 15-min intervals across 3022 US contiguous counties (96.15 % of the area) from 2014 to 2023. We developed a power system vulnerability assessment framework based on three dimensions (intensity, frequency, and duration) and applied interpretable machine learning models (XGBoost and SHAP) to compute Power System Vulnerability Index (PSVI) at the county level. Our analysis reveals a consistent increase in power system vulnerability across the US counties over the past decade. We identified 318 counties across 45 states as hotspots for high power system vulnerability, particularly in the West Coast (California and Washington), the East Coast (Florida and the Northeast area), the Great Lakes megalopolis (Chicago-Detroit metropolitan areas), and the Gulf of Mexico (Texas). Our heterogeneity analysis indicates that urban counties and those located along regional transmission boundaries tend to exhibit significantly higher vulnerability. Our results highlight the significance of the proposed PSVI for evaluating the vulnerability of communities to power outages. The findings underscore the widespread and pervasive impact of power outages across the country and offer crucial insights to support infrastructure operators, policymakers, and emergency managers in formulating policies and programs aimed at enhancing the resilience of the US power infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Advancing a Low-Temperature, Low-Cost Direct Air Capture System Based on Organic Chemistry

Holocene Climate Corporation (Holocene) partnered with Oak Ridge National Laboratory (ORNL) to conduct bench-scale testing of a new optimized Direct Air Capture (DAC) process to assist the U.S. Department of Energy (DOE) in achieving the Carbon Negative Shot target of under $\$$100/net tonne CO₂ removed by 2031. Holocene’s DAC process for carbon dioxide (CO₂) removal uses amino acids and guanidine compounds, an ORNL-invented chemical process and licensed by Holocene. Holocene will use this novel chemistry to develop a new process and deploy the technology commercially.

36 MATERIALS SCIENCE↗