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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Dark Energy Bedrock All-sky Supernova Program: Cross Calibration, Simulations, and Cosmology Forecasts

Type Ia supernovae (SNe Ia) have been essential for probing the nature of dark energy; however, most SN analyses rely on the same low-redshift sample, which may lead to shared systematics. In a companion paper, we introduce the Dark Energy Bedrock All-Sky Supernova (DEBASS) program, which has already collected more than 500 low-redshift SNe Ia on the Dark Energy Camera, and present an initial release of 77 SNe Ia within the Dark Energy Survey (DES) footprint observed between 2021 and 2024. Here, we examine the systematics, including photometric calibration and selection effects. We find agreement at the 10 mmag level among the tertiary standard stars of DEBASS, DES, and Pan-STARRS1. Our simulations reproduce the observed distributions of DEBASS SN light-curve properties, and we measure a bias-corrected Hubble residual scatter of 0.08 mag, which, while small, is found in 10% of our simulations. We compare the DEBASS SN distances to the Foundation sample and find consistency with a median residual offset of 0.016 ± 0.019 mag. Selection effects have negligible impacts on distances, but a different photometric calibration solution shifts the median residual −0.015 ± 0.019 mag, highlighting calibration sensitivity. Using conservative simulations, we forecast that replacing historical low-redshift samples with the full DEBASS sample will improve the statistical uncertainties on dark energy parameters w 0 and w a by 30% and 24%, respectively, enhance the dark energy Figure of Merit by up to 60%, and enable a measurement of fσ 8 at the 25% level.

Acevedo, Maria [Duke Univ., Durham, NC (United Sta↗
DOE OSTI2026

A Unified Photometric Redshift Calibration for Weak Lensing Surveys Using the Dark Energy Spectroscopic Instrument

The effective redshift distribution n(z) of galaxies is a critical component in the study of weak gravitational lensing. Here, we introduce a new method for determining n(z) for weak lensing surveys based on high-quality redshifts and neural-network-based importance weights. Additionally, we present the first unified photometric redshift calibration of the three leading stage-III weak lensing surveys, the Dark Energy Survey (DES), the Hyper Suprime-Cam (HSC) survey, and the Kilo-Degree Survey (KiDS), with state-of-the-art spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We verify our method using a new, data-driven approach and obtain n(z) constraints with statistical uncertainties of the order of $σ_z$ ~ 0.01 and smaller. Our analysis is largely independent of previous photometric redshift calibrations and, thus, provides an important cross-check in light of recent cosmological tensions. Overall, we find excellent agreement with previously published results on the DES Y3 and HSC Y1 data sets, while there are some differences on the mean redshift with respect to the previously published KiDS-1000 results. We attribute the latter to mismatches in photometric noise properties in the COSMOS field compared to the wider KiDS self-organizing map-gold catalog. At the same time, the new n(z) estimates for KiDS do not significantly change estimates of cosmic structure growth from cosmic shear. Finally, we discuss how our method can be applied to future weak lensing calibrations with DESI data.

Lange, J. U. [American Univ., Washington, DC (Unit↗
DOE OSTI2026

DESI EDR: Calibrating the Tully–Fisher Relationship with the DESI Peculiar Velocity Survey

We calibrate the Tully–Fisher relation (TFR) with data from the DESI Peculiar Velocity (PV) Survey taken during the Survey Validation (SV) period of the DESI galaxy redshift survey. Placing spectroscopic fibers on the centers and major axes of spatially extended spiral galaxies identified in the 2020 Siena Galaxy Atlas using the DESI Legacy Surveys, we measure the rotational velocities at 0.33R 26 for 1155 (1128 + 27 dwarf) spiral galaxies observed during SV. Using 39 spiral galaxies observed in the Coma cluster, we find a slope for the TFR of −8.32 ± 0.15 AB mag in the r band, with a scatter about the TFR of 1.12 ± 0.03 AB mag. We calibrate the zero-point of the TFR using galaxies with independent distances measured using type Ia supernovae (SNe Ia) via the cosmological distance ladder. From the SN Ia distances, we measure a zero-point of $-19.21^{+0.30}_{-0.31}$ AB mag in the r band. We produce a public catalog of the distances to these 1128 spiral galaxies observed during DESI SV as part of the DESI PV Survey with our calibrated TFR. This is, to our knowledge, the first catalog of TFR distances produced with velocities measured at a single point in the disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Korean VLBI Network Calibrator Survey (KVNCS). 1. Source Catalog of KVN Single-dish Flux Density Measurement in the K and Q Bands

We present the catalog of the KVN Calibrator Survey (KVNCS). This first part of the KVNCS is a single-dish radio survey simultaneously conducted at 22 ( K band) and 43 GHz ( Q band) using the Korean VLBI Network (KVN) from 2009 to 2011. A total of 2045 sources are selected from the VLBA Calibrator Survey with an extrapolated flux density limit of 100 mJy at the K band. The KVNCS contains 1533 sources in the K band with a flux density limit of 70 mJy and 553 sources in the Q band with a flux density limit of 120 mJy; it covers the whole sky down to −32.°5 in decl. We detected 513 sources simultaneously in the K and Q bands; ∼76% of them are flat-spectrum sources (−0.5 ≤ α ≤ 0.5). From the flux–flux relationship, we anticipated that most of the radiation of many of the sources comes from the compact components. The sources listed in the KVNCS therefore are strong candidates for high-frequency VLBI calibrators.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Physically Motivated Deep Learning to Superresolve and Cross Calibrate Solar Magnetograms

Abstract Superresolution (SR) aims to increase the resolution of images by recovering detail. Compared to standard interpolation, deep learning-based approaches learn features and their relationships to leverage prior knowledge of what low-resolution patterns look like in higher resolution. Deep neural networks can also perform image cross-calibration by learning the systematic properties of the target images. While SR for natural images aims to create perceptually convincing results, SR of scientific data requires careful quantitative evaluation. In this work, we demonstrate that deep learning can increase the resolution and calibrate solar imagers belonging to different instrumental generations. We convert solar magnetic field images taken by the Michelson Doppler Imager (resolution ∼2″ pixel −1 ; space based) and the Global Oscillation Network Group (resolution ∼2.″5 pixel −1 ; ground based) to the characteristics of the Helioseismic and Magnetic Imager (resolution ∼0.″5 pixel −1 ; space based). We also establish a set of performance measurements to benchmark deep-learning-based SR and calibration for scientific applications.

Muñoz-Jaramillo, Andrés (ORCID:0000000247160840)↗
DOE OSTI2019

First M87 Event Horizon Telescope Results. III. Data Processing and Calibration

We present the calibration and reduction of Event Horizon Telescope (EHT) 1.3 mm radio wavelength observations of the supermassive black hole candidate at the center of the radio galaxy M87 and the quasar 3C 279, taken during the 2017 April 5–11 observing campaign. These global very long baseline interferometric observations include for the first time the highly sensitive Atacama Large Millimeter/submillimeter Array (ALMA); reaching an angular resolution of 25 μas, with characteristic sensitivity limits of ~1 mJy on baselines to ALMA and ~10 mJy on other baselines. The observations present challenges for existing data processing tools, arising from the rapid atmospheric phase fluctuations, wide recording bandwidth, and highly heterogeneous array. In response, we developed three independent pipelines for phase calibration and fringe detection, each tailored to the specific needs of the EHT. The final data products include calibrated total intensity amplitude and phase information. They are validated through a series of quality assurance tests that show consistency across pipelines and set limits on baseline systematic errors of 2% in amplitude and 1° in phase. The M87 data reveal the presence of two nulls in correlated flux density at ~3.4 and ~8.3 Gλ and temporal evolution in closure quantities, indicating intrinsic variability of compact structure on a timescale of days, or several light-crossing times for a few billion solar-mass black hole. These measurements provide the first opportunity to image horizon-scale structure in M87.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Comparing the Photometric Calibration of DESI Imaging and Gaia Synthetic Photometry

Abstract The relative photometric calibration errors in the DESI Legacy Imaging Surveys (LS), which are used for DESI target selection, can leave imprints on the DESI target densities and bias the resulting cosmological measurements. We characterize the LS calibration systematics by comparing the LS stellar photometry with Gaia DR3 synthetic photometry. We find the stellar photometry of LS DR9 and Gaia has an rms difference of 4.7, 3.7, 4.4 mmag in DECam grz bands, respectively, when averaged over an angular scale of 27 ′ . There are distinct spatial patterns in the photometric offset resembling the Gaia scan patterns (most notably in the synthesized g -band) which indicate systematics in the Gaia spectrophotometry, as well as honeycomb patterns due to LS calibration systematics. We also find large and smoothly varying photometric offsets at decl. < −29.°25 in LS DR9 which are fixed in DR10.

Zhou, Rongpu (ORCID:0000000153814372)↗
DOE OSTI2018

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

Data-model integration plays a critical role in assessing and improving our capacity to predict ecosystem dynamics. Similarly, the ability to attach quantitative statements of uncertainty around model forecasts is crucial for model assessment and interpretation and for setting field research priorities. Bayesian methods provide a rigorous data assimilation framework for these applications, especially for problems with multiple data constraints. However, the Markov chain Monte Carlo (MCMC) techniques underlying most Bayesian calibration can be prohibitive for computationally demanding models and large datasets. We employ an alternative method, Bayesian model emulation of sufficient statistics, that can approximate the full joint posterior density, is more amenable to parallelization, and provides an estimate of parameter sensitivity. Analysis involved informative priors constructed from a meta-analysis of the primary literature and specification of both model and data uncertainties, and it introduced novel approaches to autocorrelation corrections on multiple data streams and emulating the sufficient statistics surface. We report the integration of this method within an ecological workflow management software, Predictive Ecosystem Analyzer (PEcAn), and its application and validation with two process-based terrestrial ecosystem models: SIPNET and ED2. In a test against a synthetic dataset, the emulator was able to retrieve the true parameter values. A comparison of the emulator approach to standard brute-force MCMC involving multiple data constraints showed that the emulator method was able to constrain the faster and simpler SIPNET model's parameters with comparable performance to the brute-force approach but reduced computation time by more than 2 orders of magnitude. The emulator was then applied to calibration of the ED2 model, whose complexity precludes standard (brute-force) Bayesian data assimilation techniques. Both models are constrained after assimilation of the observational data with the emulator method, reducing the uncertainty around their predictions. Performance metrics showed increased agreement between model predictions and data. Our study furthers efforts toward reducing model uncertainties, showing that the emulator method makes it possible to efficiently calibrate complex models.

58 GEOSCIENCES↗
DOE OSTI2019

Calibration and analysis of the uncertainty in downscaling global land use and land cover projections from GCAM using Demeter (v1.0.0)

Demeter is a community spatial downscaling model that disaggregates land use and land cover changes projected by integrated human–Earth system models. Demeter has not been intensively calibrated, and we still lack good knowledge about its sensitivity to key parameters and parameter uncertainties. We used long-term global satellite-based land cover records to calibrate key Demeter parameters. The results identified the optimal parameter values and showed that the parameterization substantially improved the model's performance. The parameters of intensification ratio and selection threshold were the most sensitive and needed to be carefully tuned,especially for regional applications. Further, small parameter uncertainties after calibration can be inflated when propagated into future scenarios,suggesting that users should consider the parameterization equifinality to better account for the uncertainties in Demeter-downscaled products. Our study provides a key reference for Demeter users and ultimately contributes to reducing the uncertainties in Earth system model simulations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Effect of soil property uncertainties on permafrost thaw projections: A calibration-constrained analysis

Here, the effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21$^{st}$ century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of intra-annual uncertainty due to soil properties and the inter-annual variability due to year to year differences in CESM climate forcings. After calibrating to borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant intra-annual uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Intra-annual uncertainties in projected soil moisture content and Stefan number are small. A volume and time integrated Stefan number decreases significantly in the future climate, indicating that latent heat of phase change becomes more important than heat conduction in future climates. Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.

58 GEOSCIENCES↗
DOE OSTI2015

Effect of soil property uncertainties on permafrost thaw projections: A calibration-constrained analysis

The effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of intra-annual uncertainty due to soil properties and the inter-annual variability due to year to year differences in CESM climate forcings. After calibrating to borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant intra-annual uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Intra-annual uncertainties in projected soil moisture content and Stefan number are small. A volume and time integrated Stefan number decreases significantly in the future climate, indicating that latent heat of phase change becomes more important than heat conduction in future climates. Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Calibrated Hydrothermal Parameters, Barrow, Alaska, 2013

A model-observation-experiment process (ModEx) is used to generate three 1D models of characteristic micro-topographical land-formations, which are capable of simulating present active layer thickness (ALT) from current climate conditions. Each column was used in a coupled calibration to identify moss, peat and mineral soil hydrothermal properties to be used in up-scaled simulations. Observational soil temperature data from a tundra site located near Barrow, AK (Area C) is used to calibrate thermal properties of moss, peat, and sandy loam soil to be used in the multiphysics Advanced Terrestrial Simulator (ATS) models. Simulation results are a list of calibrated hydrothermal parameters for moss, peat, and mineral soil hydrothermal parameters drawn from literature and field observations at the NGEE-Arctic site. Find more details in the associated publication by Atchley, et.al, 2015.There is one data file as both a .xlsx and .csv. The datafile was transformed into a csv for interoperability, however some information might have been lost in the transformation.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Milone eTape Liquid Level Sensor Laboratory Calibration with a Commercial 12.2 cm HS-Flume and 3D Printed 4 cm Micro-HS-Flumes

The NGEE Arctic Rainfall Simulator (NARS) is a variable intensity rainfall simulator (RFS) with a frame design based on the Humphry et al. (2002) RFS and a water delivery system based on the Walnut Gulch (Paige et al., 2004) RFS. The NARS uses an aluminum frame that is fully deconstructable for transportation to field locations and a water system that enables variable rain intensity. Prior to field deployment, H-flume discharge and the corresponding Milone eTape Liquid Level Sensor (eTape) resistance values were measured in the laboratory so that discharge measurements from the NGEE Arctic Rainfall Simulator could be automated. eTape resistance was measured with increasing fluid heights for the full range of the eTape to calculate sensor detection limits and resolution. The eTape was calibrated to both a commercially available 12.2 cm HS-flume and a 3D printed 4 cm Micro-HS-flume. This data package contains two .csv files, one for the eTape calibration and the other for the flume calibrations, and two .stl files to 3D print the 4 cm Micro-HS-Flume design with a 1 cm x 3.6 cm stilling well opening. The .stl files can be opened in most 3D printing or CAD programs/software. Two .kml files of the laboratory location and broader area where testing was conducted are also included in this data package.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Beyond pinball loss: Quantile methods for calibrated uncertainty quantification

Amongthemanywaysofquantifying uncertainty in a regression setting, specifying the full quantile function is attractive, as quantiles are amenable to interpretation and evaluation. A model that predicts the true conditional quantiles for each input, at all quantile levels, presents a correct and efficient representation of the underlying uncertainty. To achieve this, many current quantile-based methods focus on optimizing the pinball loss. However, this loss restricts the scope of applicable regression models, limits the ability to target many desirable properties (e.g. calibration, sharpness, centered intervals), and may produce poor conditional quantiles. In this work, we develop new quantile methods that address these shortcomings. In particular, we propose methods that can apply to any class of regression model, select an explicit balance between calibration and sharpness, optimize for calibration of centered intervals, and produce more accurate conditional quantiles. We provide a thorough experimental evaluation of our methods, which includes a high dimensional uncertainty quantification task in nuclear fusion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Calibration of Traceable Solid Mock 131 I Phantoms Used in an International SPECT Image Quantification Comparison

The International Atomic Energy Agency (IAEA) has organized an international comparison to assess Single Photon Emission Computed Tomography (SPECT) image quantification capabilities in 12 countries. Iodine-131 was chosen as the radionuclide for the comparison because of its wide use around the world, but for logistical reasons solid 133 Ba sources were used as a long-lived surrogate for 131 I. For this study, we designed a set of solid cylindrical sources so that each site could have a set of phantoms (having nominal volumes of 2 mL, 4 mL, 6 mL, and 23 mL) with traceable activity calibrations so that the results could be properly compared. We also developed a technique using two different detection methods for individually calibrating the sources for 133 Ba activity based on a National standard. This methodology allows for the activity calibration of each 133 Ba source with a standard uncertainty on the activity of 1.4 % for the high-level 2-, 4-, and 6-mL sources and 1.7 % for the lower-level 23 mL cylinders. This level of uncertainty allows for these sources to be used for the intended comparison exercise, as well as in other SPECT image quantification studies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Legacy Survey of Space and Time Data Preview 1: calibrations dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the calibrations dataset type. These are a collection of calibration datasets such as biases, darks, and flats used to construct the data release. This release contains 496 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1965

Volumetric system calibrates meters for large flow rates

Volumetric system calibrates meters used for large liquid flow rates. The system employs trip probes and equipment to time the flow of liquid from a tare vessel into a calibrated vessel. This calibration system is used in the petroleum and chemical industries.

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