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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 OSTI2022

Development of Training Materials for Pathologists to Provide Machine Learning Validation Data of Tumor-Infiltrating Lymphocytes in Breast Cancer

The High Throughput Truthing project aims to develop a dataset for validating artificial intelligence and machine learning models (AI/ML) fit for regulatory purposes. The context of this AI/ML validation dataset is the reporting of stromal tumor-infiltrating lymphocytes (sTILs) density evaluations in hematoxylin and eosin-stained invasive breast cancer biopsy specimens. After completing the pilot study, we found notable variability in the sTILs estimates as well as inconsistencies and gaps in the provided training to pathologists. Using the pilot study data and an expert panel, we created custom training materials to improve pathologist annotation quality for the pivotal study. We categorized regions of interest (ROIs) based on their mean sTILs density and selected ROIs with the highest and lowest sTILs variability. In a series of eight one-hour sessions, the expert panel reviewed each ROI and provided verbal density estimates and comments on features that confounded the sTILs evaluation. We aggregated and shaped the comments to identify pitfalls and instructions to improve our training materials. From these selected ROIs, we created a training set and proficiency test set to improve pathologist training with the goal to improve data collection for the pivotal study. We are not exploring AI/ML performance in this paper. Instead, we are creating materials that will train crowd-sourced pathologists to be the reference standard in a pivotal study to create an AI/ML model validation dataset. The issues discussed here are also important for clinicians to understand about the evaluation of sTILs in clinical practice and can provide insight to developers of AI/ML models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Dataset for ASME VVUQ Symposium Workshop on Regression of Validation Data to an Application Point

This dataset consists of a collection of Excel spreadsheets that contain output from analysis specified in the workshop. The analysis involves ASME V&V 20-style validation as well as the application of a supplement methodology for regression of validation comparison error and validation uncertainty to application points where experimental data does not exist for comparison. The simulation results and experimental data are provided by the workshop organizers and a NASA report, respectively.

Kirsch, Jared Roelof [Sandia National Laboratories↗
NASA NTRS2001

MODIS Observation of Aerosols over Southern Africa During SAFARI 2000: Data, Validation, and Estimation of Aerosol Radiative Forcing

Aerosol properties, including optical thickness and size parameters, are retrieved operationally from the MODIS sensor onboard the Terra satellite launched on 18 December 1999. The predominant aerosol type over the Southern African region is smoke, which is generated from biomass burning on land and transported over the southern Atlantic Ocean. The SAFARI-2000 period experienced smoke aerosol emissions from the regular biomass burning activities as well as from the prescribed burns administered on the auspices of the experiment. The MODIS Aerosol Science Team (MAST) formulates and implements strategies for the retrieval of aerosol products from MODIS, as well as for validating and analyzing them in order to estimate aerosol effects in the radiative forcing of climate as accurately as possible. These activities are carried out not only from a global perspective, but also with a focus on specific regions identified as having interesting characteristics, such as the biomass burning phenomenon in southern Africa and the associated smoke aerosol, particulate, and trace gas emissions. Indeed, the SAFARI-2000 aerosol measurements from the ground and from aircraft, along with MODIS, provide excellent data sources for a more intensive validation and a closer study of the aerosol characteristics over Southern Africa. The SAFARI-2000 ground-based measurements of aerosol optical thickness (AOT) from both the automatic Aerosol Robotic Network (AERONET) and handheld Sun photometers have been used to validate MODIS retrievals, based on a sophisticated spatio-temporal technique. The average global monthly distribution of aerosol from MODIS has been combined with other data to calculate the southern African aerosol daily averaged (24 hr) radiative forcing over the ocean for September 2000. It is estimated that on the average, for cloud free conditions over an area of 9 million square kin, this predominantly smoke aerosol exerts a forcing of -30 W/square m C lose to the terrestrial surface and -10 W/square m at the top of the atmosphere (TOA). While cooling the surface and Earth system, the difference of 20 W/square m is energy that heats the atmosphere.

Ichoku, Charles↗
NASA NTRS2003

Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

Spectral band synthesis is a key step in the process of creating a simulated multispectral image from hyperspectral data. In this step, narrow hyperspectral bands are combined into broader multispectral bands. Such an approach has been used quite often, but to the best of our knowledge accuracy of the band synthesis simulations has not been evaluated thus far. Therefore, the main goal of this paper is to provide validation of the spectral band synthesis algorithm used in the ART software. The next section contains a description of the algorithm and an example of its application. Using spectral responses of AVIRIS, Hyperion, ALI, and ETM+, the following section shows how the synthesized spectral bands compare with actual bands, and it presents an evaluation of the simulation accuracy based on results of MODTRAN modeling. In the final sections of the paper, simulated images are compared with data acquired by actual satellite sensors. First, a Landsat 7 ETM+ image is simulated using an AVIRIS hyperspectral data cube. Then, two datasets collected with the Hyperion instrument from the EO-1 satellite are used to simulate multispectral images from the ALI and ETM+ sensors.

Blonski, Slawomir↗
NASA NTRS1994

Measurements of stratospheric NO, NO2, and N2O5 by ISAMS: Preliminary observations and data validation

The Improved Stratospheric and Mesospheric Sounder (ISAMS) is a multichannel radiometer and forms part of the science payload of the Upper Atmosphere Research Satellite (UARS). ISAMS measures infrared emissions from the Earth's atmosphere in several wavelength bands. Three such bands include emission from nitric oxide, nitrogen dioxide, and dinitrogen pentoxide. In this paper, we briefly discuss how the ISAMS instrument measures NO, NO2, and N2O5. We also present preliminary data from these channels and describe preliminary validation work.

Kerridge, Brian J.↗
DOE OSTI2025

Verified, Archived Library of Inputs and Data (VALID) Online Repository [Slides]

VALID continues to serve as a library of high-quality models used for evaluating SCALE and nuclear data. Large number of cases are in the pipeline. Online repository is available for use. Future plans include simplifying the process for adding cases, including additional models outside the ICSBEP Handbook (HTC models, DNCSH models, International Handbook of Evaluated Reactor Physics Benchmark Experiments [IRPhE], SINBAD, etc.), and increasing the availability of models and results for external users.

KENO↗
NASA NTRS1999

Operational Processing of Ground Validation Data for the Tropical Rainfall Measuring Mission

The Tropical Rainfall Measuring Mission (TRMM) satellite was successfully launched in November 1997. A primary goal of TRMM is to sample tropical rainfall using the first active spaceborne precipitation radar. To validate TRMM satellite observations, a comprehensive Ground Validation (GV) Program has been implemented for this mission. A key component of GV is the analysis and quality control of meteorological ground-based radar data from four primary sites: Melbourne, FL; Houston, TX; Darwin, Australia; and Kwajalein Atoll, RMI. As part of the TRMM GV effort, the Joint Center for Earth Systems Technology (JCET) at the University of Maryland, Baltimore County, has been tasked with developing and implementing an operational system to quality control (QC), archive, and provide data for subsequent rainfall product generation from the four primary GV sites. This paper provides an overview of the JCET operational environment. A description of the QC algorithm and performance, in addition to the data flow procedure between JCET and the TRNM science and Data Information System (TSDIS), are presented. The impact of quality-controlled data on higher level rainfall and reflectivity products will also be addressed, Finally, a brief description of JCET's expanded role into producing reference rainfall products will be discussed.

Kulie, Mark S.↗
NASA NTRS1986

Downward longwave surface radiation from sun-synchronous satellite data - Validation of methodology

An extensive study has been carried out to validate a satellite technique for estimating downward longwave radiation at the surface. The technique, mostly developed earlier, uses operational sun-synchronous satellite data and a radiative transfer model to provide the surface flux estimates. The satellite-derived fluxes were compared directly with corresponding ground-measured fluxes at four different sites in the United States for a common one-year period. This provided a study of seasonal variations as well as a diversity of meteorological conditions. Dome heating errors in the ground-measured fluxes were also investigated and were corrected prior to the comparisons. Comparison of the monthly averaged fluxes from the satellite and ground sources for all four sites for the entire year showed a correlation coefficient of 0.98 and a standard error of estimate of 10 W/sq m. A brief description of the technique is provided, and the results validating the technique are presented.

Darnell, W. L.↗
DOE OSTI2023

An Alternative to Solution Experiments for Nuclear Data Validation: Reflection and Interaction of Juxtaposed Uranium (RAIJU) Experiment Design

The need for solution experiments was thoroughly discussed at the recent NCERC (National Criticality Experiments Research Center) Futures Meeting in September 2022 for multiple applications including criticality safety, training, and nuclear data. However, this capability does not exist anywhere in the United States. NCERC, located at the Nevada National Security Site and operated by LANL (Los Alamos National Laboratory) is the only general-purpose critical experiments laboratory in the United States. However, solution experiments are not authorized at NCERC, and obtaining that authorization would be too time consuming and costly to happen in the foreseeable future. An alternative is needed – an experimental configuration with the homogeneity of liquid experiments, but without being a liquid. This project, Reflection and Interaction of Juxtaposed Uranium (RAIJU) will fill the gap in capability within LANL, the U.S. Department of Energy, and the international community and will support current and future nuclear material processing needs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2005

GOES Satellite Data Validation Via Hand-held 4 LED Sun Photometer at Norfolk State University

Sun photometry is a passive means of measuring a quantity of light radiation. The GIFTS- IOMI/GLOBE Water Vapor/Haze Sun photometer contains four light emitting diodes (LEDs), which are used to convert photocurrent to voltage. The intensity of the incoming and outgoing radiation as detected on the Earth s surface can be affected by aerosols and gases in the atmosphere. The focus of this research is primarily on aerosol and water vapor particles that absorb and reemit energy. Two LEDs in the photometer correspond to light scattered at 530 nm (green spectrum) and 620 nm (red spectrum). They collect data pertaining to aerosols that scatter light. The other two LEDs detect the light scattered by water vapor at wavelengths of 820 nm and 920 nm. The water vapor measurements will be compared to data collected by the Geostationary Observation Environmental Satellite (GOES). Before a comparison can be made, the extraterrestrial constant (ET), which is intrinsic to each sun photometer, must be measured. This paper will present determination of the ET constant, from which the aerosol optical thickness (AOT) can be computed for comparison to the GOES satellite to ascertain the reliability of the sun photometer.

Reynolds, Arthur, Jr.↗
DOE OSTI2020

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

CORAL: A framework for rigorous self-validated data modeling and integrative, reproducible data analysis

Abstract Background Many organizations face challenges in managing and analyzing data, especially when relevant datasets arise from multiple sources and methods. Analyzing heterogeneous datasets and additional derived data requires rigorous tracking of their interrelationships and provenance. This task has long been a Grand Challenge of data science and has more recently been formalized in the FAIR principles: that all data objects be Findable, Accessible, Interoperable, and Reusable, both for machines and for people. Adherence to these principles is necessary for proper stewardship of information, for testing regulatory compliance, for measuring the efficiency of processes, and for facilitating reuse of data-analytical frameworks. Findings We present the Contextual Ontology-based Repository Analysis Library (CORAL), a platform that greatly facilitates adherence to all 4 of the FAIR principles, including the especially difficult challenge of making heterogeneous datasets Interoperable and Reusable across all parts of a large, long-lasting organization. To achieve this, CORAL's data model requires that data generators extensively document the context for all data, and our tools maintain that context throughout the entire analysis pipeline. CORAL also features a web interface for data generators to upload and explore data, as well as a Jupyter notebook interface for data analysts, both backed by a common API. Conclusions CORAL enables organizations to build FAIR data types on the fly as they are needed, avoiding the expense of bespoke data modeling. CORAL provides a uniquely powerful platform to enable integrative cross-dataset analyses, generating deeper insights than are possible using traditional analysis tools.

97 MATHEMATICS AND COMPUTING↗