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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

LANDSAT-4 Radiometric and Geometric Correction and Image Enhancement Results

Techniques were developed or improved to calibrate, enhance, and geometrically correct LANDSAT-4 satellite data. Statistical techniques to correct data radiometry were evaluated and were found to minimize striping and banding. Conventional techniques cause striping even with perfect calibration parameters. Intensity enhancement techniques were improved to display image data with large variation in intensity or brightness. Data were geometrically corrected to conform to a 1:100,000 map reference and image products produced with the map overlay. It is shown that these products can serve as accurate map products. A personal computer was experimentally used for digital image processing.

Bernstein, R.↗
DOE OSTI2025

Auger@TA: In-situ Cross-Calibration of the World's Largest Cosmic Ray Observatories

The Pierre Auger Observatory (Auger) and the Telescope Array (TA) are the world's two largest ultra-high-energy cosmic ray (UHECR) observatories. They operate in the Southern and Northern hemispheres, respectively, at similar latitudes but with distinct surface detector (SD) designs. A significant challenge in studying UHECR physics across the full sky is the apparent discrepancy in flux measurements between the two experiments. This discrepancy could arise from astrophysical differences and/or systematic effects related to their detector designs and sensitivities to extensive air shower components. To address this, the Auger@TA working group aims to cross-calibrate the two observatories with a self-triggering micro-Auger array within the TA array. This micro-array consists of eight Auger Surface Detector (SD) stations equipped with Water Cherenkov Detectors (WCDs) and AugerPrime Surface Scintillator Detectors. Seven SD stations, configured with a centered-1-PMT design, are arranged in a hexagonal pattern with one station in the center, with 1.5 km spacing, mirroring the Auger layout. The eighth station, which features a standard 3-PMT Auger station, is located in conjunction with a TA detector at the center of the hexagon, forming a triplet for high-statistics and low-uncertainty cross-calibration. A custom communication system that uses readily available components enables seamless communication between stations and remote access to each station through a central computer. The micro-array is now fully deployed, and initial data-taking is about to start. This presentation will detail the instrumentation, communication systems, central data acquisition system, expected performance of the micro-array, and preliminary results as appropriate.

Mocellin, Adriel G.B. [Colorado School of Mines]↗
NASA NTRS1992

An examination of the assumptions in the POLCAL cross-talk removal algorithm

The POLCAL crosstalk removal algorithm is based on the statistical properties of the image background and does not need any corner reflector or active radar calibrator deployed in the scene. The advantage of being able to remove the crosstalk contamination without using external calibration targets gives rise to the consideration of algorithms based on clutter statistics in polarimetric synthetic aperture radar (SAR) images in more detail. The basic assumption of the POLCAL procedure is the decorrelation of copolarized and cross-polarized backscatter, which is valid for natural targets with azimuthal symmetry. This assumption and others regarding the properties of the imaged surface are examined. An improved version called POLCALII is presented, and its performance is compared with POLCAL.

Zink, M.↗
DOE OSTI2026

Unprecedented Shifts in Hydrology Are Emerging Across California's Critical Basins: An Evaluation From 0.5 to 3.5°C

With advances in climate models and downscaling techniques, stakeholders anticipate high-resolution analysis to inform regional to local changes in water management. Here, we produce hydrologic projections from an ensemble of Earth System Models (ESMs) that were selected and downscaled to support California's 5th Climate Assessment. An ensemble of 19 ESMs was downscaled to a 3-km resolution across California using a statistical-dynamical downscaling approach and subsequently run through two calibrated hydrology models. Although California has been extensively studied in the context of climate change, we provide the first evaluation of the warming thresholds at which hydroclimate metrics demonstrate statistically significant shifts. We show that present-day to near-term warming levels in Klamath and Northern Sierra Nevada basins, which serve as a critical source of water for California, show statistically significant decreases in snowfall and peak snowpack and associated decreases in summer snowmelt and runoff. More generally, shifts in these hydroclimate metrics occur for intermediate elevation basins ranging from 1,315 to 1,455 m (4,314.3–4,773.6 ft), while the warming level of emergence is delayed for lower and higher elevation basins. We also find that several basins already demonstrate significant increases in 5- to 100-year runoff intensities, primarily due to the increasing influence of precipitation falling as rain. Hydroclimate metrics with trends that demonstrate near-term warming levels of emergence are reflected in reanalysis-based observations, suggesting California is entering a fundamentally different hydroclimate regime. While this will likely stress California's water management, the research provided can support when to implement adaptation efforts.

Bass, B. [Univ. of California, Los Angeles, CA (Un↗
DOE OSTI2026

A Framework for Parametric and Predictive Uncertainty Quantification in the E3SM Land Model: Assessing Site and Observable Generalizability

Quantifying parametric uncertainty using observations from individual sites provides a critical foundation for Earth system modeling, serving as a necessary first step before scaling up to regional or global applications. This study introduces a novel computational framework designed to enhance model predictability by reducing parametric uncertainty and assessing site and observable generalizability using various observational constraints. The framework integrates five components: Model Simulation, Statistical Emulation, Global Sensitivity Analysis (GSA), Model Calibration, and Model Prediction. Using the E3SM land model, we simulated site-level land-atmosphere carbon and energy fluxes from 2003 to 2007 across five evergreen needleleaf FLUXNET sites, perturbing 26 vegetation-related model parameters. Gaussian process emulators were employed to expedite GSA and model calibration. Four critical parameters that strongly influence selected land-atmosphere fluxes were identified by GSA. Bayesian approaches were used to infer parameter probability distributions leveraging synthetic data and FLUXNET observations. The results reveal that posterior parameter distributions vary significantly across different sites and observables within the same plant functional type. Probabilistic predictions indicate that parameters calibrated at one site can enhance predictive accuracy at other sites, although site heterogeneity may sometimes outweigh parametric uncertainty. Additionally, the probabilistic predictions demonstrate that calibration for one variable can also improve predictability for other variables, thereby maximizing predictive capabilities with limited observations. This framework provides a powerful approach for reducing parametric uncertainty in Earth system models and deepening our understanding of carbon dynamics and energy cycles. Its adaptability makes it a valuable tool for broader applications in Earth system modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Evaluation of usefulness of Skylab EREP S-190 and S-192 imagery in multistage forest surveys

The author has identified the following significant results. The digital timber volume prediction system was tested with another test area in the Trinity Alps. The estimated gain in precision was somewhat lower than the estimate for the first test area (35%). A combined interpretation of the two areas was made, yielding an estimated gain of 44%, with high statistical significance. This interpretation was used to calibrate the system for an interpretation of 43 primary sample units distributed over 1600 square miles. Preliminary results indicate that a gain of 35% can be realized over this large area in northern California.

Langley, P. G.↗
NASA NTRS1974

SIRU utilization. Volume 1: Theory, development and test evaluation

The theory, development, and test evaluations of the Strapdown Inertial Reference Unit (SIRU) are discussed. The statistical failure detection and isolation, single position calibration, and self alignment techniques are emphasized. Circuit diagrams of the system components are provided. Mathematical models are developed to show the performance characteristics of the subsystems. Specific areas of the utilization program are identified as: (1) error source propagation characteristics and (2) local level navigation performance demonstrations.

Musoff, H.↗
NASA NTRS1981

AgRISTARS. Supporting research: MARS x-band scatterometer

The design, construction, and data collection procedures of the mobile agricultural radar sensor (MARS) x band scatterometer are described. This system is an inexpensive, highly mobile, truck mounted FM-CW radar operating at a center frequency of 10.2 GHz. The antennas, which allow for VV and VH polarizations, are configured in a side looking mode that allows for drive by data collection. This configuration shortens fieldwork time considerably while increasing statistical confidence in the data. Both internal calibration, via a delay line, and external calibration with a Luneberg lens are used to calibrate the instrument in terms of sigma(o). The radar scattering cross section per unit area, sigma(o), is found using the radar equation.

Ulaby, F. T.↗
NASA NTRS2004

Performance Evaluation of Fiber Bragg Gratings at Elevated Temperatures

The development of integrated fiber optic sensors for smart propulsion systems demands that the sensors be able to perform in extreme environments. In order to use fiber optic sensors effectively in an extreme environment one must have a thorough understanding of the sensor s limits and how it responds under various environmental conditions. The sensor evaluation currently involves examining the performance of fiber Bragg gratings at elevated temperatures. Fiber Bragg gratings (FBG) are periodic variations of the refractive index of an optical fiber. These periodic variations allow the FBG to act as an embedded optical filter passing the majority of light propagating through a fiber while reflecting back a narrow band of the incident light. The peak reflected wavelength of the FBG is known as the Bragg wavelength. Since the period and width of the refractive index variation in the fiber determines the wavelengths that are transmitted and reflected by the grating, any force acting on the fiber that alters the physical structure of the grating will change what wavelengths are transmitted and what wavelengths are reflected by the grating. Both thermal and mechanical forces acting on the grating will alter its physical characteristics allowing the FBG sensor to detect both temperature variations and physical stresses, strain, placed upon it. This ability to sense multiple physical forces makes the FBG a versatile sensor. This paper reports on test results of the performance of FBGs at elevated temperatures. The gratings looked at thus far have been either embedded in polymer matrix materials or freestanding with the primary focus of this paper being on the freestanding FBGs. Throughout the evaluation process, various parameters of the FBGs performance were monitored and recorded. These parameters include the peak Bragg wavelength, the power of the Bragg wavelength, and total power returned by the FBG. Several test samples were subjected to identical test conditions to allow for statistical analysis of the data. Test procedures, calibrations, and referencing techniques are presented in the paper along with directions for future research.

Juergens, Jeffrey↗
NASA NTRS2005

Thermal Evaluation of Fiber Bragg Gratings at Extreme Temperatures

The development of integrated fiber optic sensors for use in aerospace health monitoring systems demands that the sensors be able to perform in extreme environments. In order to use fiber optic sensors effectively in an extreme environment one must have a thorough understanding of the sensor's capabilities, limitations, and performance under extreme environmental conditions. This paper reports on our current sensor evaluation examining the performance of freestanding fiber Bragg gratings (FBG) at extreme temperatures. While the ability of FBGs to survive at extreme temperatures has been established, their performance and long term survivability is not well documented. At extreme temperatures the grating structure would be expected to dissipate, degrading the sensors performance and eventually ceasing to return a detectable signal. The fiber jacket will dissipate leaving a brittle, unprotected fiber. For FBGs to be used in aerospace systems their performance and limitations need to be thoroughly understood at extreme temperatures. As the limits of the FBGs performance are pushed the long term survivability and performance of the sensor comes into question. We will not only examine the ability of FBGs to survive extreme temperatures but also look at their performance during many thermal cycles. This paper reports on test results of the performance of thermal cycling commercially available FBGs, at temperatures up to 1000 C, seen in aerospace applications. Additionally this paper will report on the performance of commercially available FBGs held at 1000 C for hundreds of hours. Throughout the evaluation process, various parameters of the FBGs performance were monitored and recorded. Several test samples were subjected to identical test conditions to allow for statistical analysis of the data. Test procedures, calibrations, referencing techniques, performance data, and interpretations and explanations of results are presented in the paper along with directions for future research.

Juergens, Jeffrey↗
NASA NTRS2017

Effective Assimilation of SMAP Observations Using Statistical Techniques

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, the need for bias correction prior to an assimilation of these estimates is reduced, which could result in a more effective use of the independent information provided by the satellite observations. In this study, a statistical neural network (NN) retrieval algorithm is calibrated using SMAP brightness temperature observations and modeled soil moisture estimates (similar to those used to calibrate the SMAP Level 4 DA system). Daily values of surface soil moisture are estimated using the NN and then assimilated into the NASA Catchment model. The skill of the assimilation estimates is assessed based on a comprehensive comparison to in situ measurements from the SMAP core and sparse network sites as well as the International Soil Moisture Network. The NN retrieval assimilation is found to significantly improve the model skill, particularly in areas where the model does not represent processes related to agricultural practices. Additionally, the NN method is compared to assimilation experiments using traditional bias correction techniques. The NN retrieval assimilation is found to more effectively use the independent information provided by SMAP resulting in larger model skill improvements than assimilation experiments using traditional bias correction techniques.

Kolassa, J.↗
NASA NTRS2024

Flaring Activity for Low-mass Stars in the β Pictoris Moving Group

Stellar flares from K and M dwarfs release panchromatic radiation characterized by a significantly higher brightness temperature (∼9–20 kK) than the star. The increased frequency of magnetic activity on young low-mass stars results in the energy released during flaring events becoming a notable contributor to the radiation environment. This study focuses on the β Pictoris moving group (βPMG; 24 ± 3 Myr) for the analysis of young low-mass star flaring rates within the framework of larger flare studies. The calibration of long-term optical flare statistics is crucial to updating flare activity–age relations and the interpretation of exoplanet atmosphere observations. Using the βPMG, we develop a modular flare-extraction pipeline sensitive to low-mass stellar flares in observations from the Transiting Exoplanet Survey Satellite (TESS). This pipeline is built to characterize the flare properties of these stars such as total energy and cumulative flare rate. Consistent with previous studies, this sample (N = 49) shows higher cumulative flare rates than early-type and old field stars by at least an order of magnitude. Fitted flare frequency distributions for both early- and late-type M dwarfs show an average slope of 1.58 ± 0.23, with earlier stars flaring with lower or similar rates to late types. A typical member in this sample has daily (∼1 day−1) flares with TESS band energies of 1032–1033 erg. The optical flare rates and energies for this group provide essential context into the coevolution of host stars and associated planets.

Jordan Ealy↗
DOE OSTI2025

A Computational Workflow of Elucidating Viral Impact on Mediating Microbial Response to In-situ Experimental Warming: Bridging microbial modeling to carbon and mineral modeling

Viruses are abundant in soils and shape microbial communities in ways that can potentially influence ecosystem processes, yet their contributions to carbon cycling and mineral transformations remain poorly understood. Here we present a multi-phase framework that links virus-host interactions to soil biogeochemistry by combining ecological simulations, genome- and community-scale metabolic modeling, and statistical and machine-learning analyses. We first calibrated microbial abundance profiles under explicit infection scenarios to capture how viral pressure alters community structure, then explored alternative interaction strategies, including kill-the-winner, piggyback-the-winner, and mixed lytic-lysogenic modes, through forward simulations. These ecological shifts were translated into metabolic consequences using exchange fluxes summarized into biologically meaningful categories, while integrated statistical and machine-learning screens elevated subtle but consistent signals. Application of this framework revealed that viral infections shift the balance between organic and inorganic fluxes, redirecting metabolism from diffuse organic transformations toward inorganic pools such as protons and CO 2 , directly linking viral regulation to respiration and soil carbon balance. The roll-up analysis also isolated perturbations in critical mineral ions, including magnesium, manganese, zinc, and copper, which serve as essential enzymatic cofactors. In piggyback-the-winner scenarios, uptake of these ions was strongly suppressed. Contrasting viral strategies produced distinct community structures and metabolic outcomes, from broad suppression under kill-the-winner dynamics to dramatic redistributions under high-lytic and high-gain lysogenic regimes that collapsed vulnerable microbial populations while promoting opportunists. Together, these results provide a tractable path to trace viral perturbations from host abundance shifts to metabolic flux adjustments and ecosystem-scale processes, offering a practical way to include viruses in earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. Validation on simulations

Beyond-two-point statistics contain additional information on cosmological as well as astrophysical and observational (systematics) parameters. In this methodology paper we provide an end-to-end simulationbased analysis of a set of Gaussian and non-Gaussian weak lensing statistics using detailed mock catalogs of the Dark Energy Survey (DES). Here, we implement: 1) second and third moments; 2) wavelet phase harmonics (WPH); 3) the scattering transform (ST). Our analysis is fully based on simulations, it spans a space of seven $νw$CDM cosmological parameters, and it forward models the most relevant sources of systematics of the data (masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration). We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a likelihood-free-inference approach. We validate the pipeline extensively, and we find that WPH exhibits the strongest performance when combined with second moments, followed by ST, and then by third moments. The combination of all the different statistics further enhances constraints with respect to second moments, up to 25 percent, 15 percent, and 90 percent for S 8 , Ω m , and the figure-of-merit FoM S8;Ωm , respectively. We further find that non-Gaussian statistics improve constraints on w and on the amplitude of intrinsic alignment with respect to second moments constraints. The methodological advances presented here are suitable for application to Stage IV surveys from Euclid, Rubin-LSST, and Roman with additional validation on mock catalogs for each survey. In a companion paper we present an application to DES Year 3 data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Application of Linear Additive Conditions for Near-Infrared Diffuse Reflectance Absorption Spectroscopy

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.

Feng, Zhiyue↗
DOE OSTI2025

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. II. cosmological results

Here, we present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years of the Dark Energy Survey. We implement the following: (1) second and third moments; (2) wavelet phase harmonics; (3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven 𝑤 Cold Dark Matter (𝑤⁢ CDM) cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the figure of merit (𝑆 8 , Ω m ) is improved by 70% (Λ ⁢CDM) and 90% (𝑤 ⁢CDM). When all the summary statistics are combined, we achieve a 2% constraint on the amplitude of fluctuations parameter 𝑆 8 ≡ 𝜎 8 ⁢(Ω m /0.3) 0.5 , obtaining 𝑆 8 = 0.794 ±0.017 (Λ⁢ CDM) and 𝑆 8 = 0.817 ±0.021 (𝑤 ⁢CDM), and a ∼10% constraint on Ω m , obtaining Ω m =0.259 ±0.025 (Λ ⁢CDM) and Ω m = 0.273 ±0.029 (𝑤⁢ CDM). In the context of the 𝑤⁢ CDM scenario, these statistics also strengthen the constraints on the parameter 𝑤, obtaining 𝑤 <−0.72. The constraints from different statistics are shown to be internally consistent (with a 𝑝-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the first three years of the Dark Energy Survey data, finding good consistency; we also compare with results from external datasets, such as planck constraints from the cosmic microwave background, finding statistical agreement, with discrepancies no greater than <2.2⁢𝜎.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

The Comsat 13 and 18 GHz propagation experiment

The ATS-6 Comsat Propagation Experiment, designed to gather statistical data on attenuation by rain and snow at 13 and 18 GHz, is discussed. Signals from unattended ground transmitters at 25 locations in the eastern U.S. operating at 18 GHz and 13 GHz were transmitted to ATS-6, where the transponder converted the carriers to frequencies around 4150 MHz. These signals were then transmitted to the Comsat large horn antenna/data acquisition and receiving facility at Bangor, Maine, where each carrier was calibrated and digitally recorded once per second. Attenuation statistics for 40 carriers have been plotted. The experiment was conducted from July 1974 to May 1975 with excellent performance of the transponder.

King, J. L.↗
DOE OSTI2020

Calibration of energy density functionals with deformed nuclei

Nuclear density functional theory is the prevalent theoretical framework for accurately describing nuclear properties at the scale of the entire chart of nuclides. Given an energy functional and a many-body scheme (e.g., single- or multireference level), the predictive power of the theory depends strongly on how the parameters of the energy functionals have been calibrated with experimental data. Expanded algorithms and computing power have enabled recent optimization protocols to include data in deformed nuclei in order to optimize the coupling constants of the energy functional. The primary motivation of this work is to test the robustness of such protocols with respect to some of the technical and numerical details of the underlying calculations, especially when the calibration explores a large parameter space. To this end, we quantify the effect of these uncertainties on both the optimization and statistical emulation of composite objective functions. We also emphasize that Bayesian calibration can provide better estimates of the theoretical errors used to define objective functions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗