Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “validation data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Preservation of Provenance and Context to Ensure Future Understandability of Airborne Earth Observations and Derived Data Products

Open-source science goes beyond making data from scientific projects (e.g., on-orbit/satellite missions, airborne and field investigations, and other data producing activities) openly available after they are generated, but involves and open sharing of information throughout the project lifecycle. Preservation of the data and associated information required for understanding and reusing the data well after the scientific projects is a contributor to open-source science as well. Considering the high investment in the on-orbit/satellite missions, we had developed a document titled “NASA Earth Science Data Preservation Content Specification (PCS)” in 2011. This document has been used as a requirement for recent on-orbit/satellite missions by NASA. Recently it became clear that the specifications should be applied to other scientific projects as well. Therefore, the document was revised to cover other types of projects, and a Preservation Content Implementation Guidance (PCIG) document was also developed. The revised PCS, and the PCIG, were published in 2022. The purpose of this presentation is to highlight the contents of these documents as they apply to suborbital/airborne investigations. The PCS calls for content preservation in eight general categories - Measuring Instrument/Platform Description, Instrument and Science Data Products and Metadata, Science Raw Data, Product and Algorithm Documentation, Instrument Calibration, Science Algorithm Software, Science Data Product Algorithm Inputs, Science Data Product Validation, and Science Data Access and Analysis Tools. While all these categories apply to various types of projects, a few clarifying sentences have been added to the descriptions of contents in each of the categories to show which categories are especially important to airborne and field investigations and where some contents are not applicable (or difficult to obtain). The PCIG document provides some general guidance applicable to all types of projects and specific guidance in a separate section for airborne and field investigations. This section calls out typical artifacts produced during such investigations that can meet the spirit of the various PCS categories.

remote sensing↗
DOE OSTI2022

Using Calibrated Water Data for Preliminary Validation of the SRT Code for Advanced Reactors

Recent interest and corresponding progress worldwide regarding advanced nuclear reactors has renewed focus on their performance and related safety assessments. Specifically, the U.S. Nuclear Regulatory Commission has emphasized the importance of mechanistic approaches to source term analysis for advanced reactor licensing applications, which attempt to realistically account radionuclide transport and retention phenomena. Further model development is required due to the numerous and complex physical and chemical phenomena associated with mechanistic source term analyses. Reflecting the need for modeling advancement, Argonne National Laboratory developed a mechanistic source term analysis tool for sodium fast reactors. The Simplified Radionuclide Transport (SRT) code describes fuel pin failure (for simulating the initial condition at the point of fuel pin breach), bubble scrubbing, deposition, leakage and following environmental impact. In the current work, a validation study of the SRT bubble scrubbing model is performed using a water-loop experiment performed at the University of Wisconsin-Madison. Through the analysis, the approach and fundamental bubble scrubbing models in SRT, which examine the removal of aerosols within the bubble as it is transported through a pool, have been widely evaluated. The results of the assessment demonstrate a high level of agreement in the regions of greater aerosol size. In the parameter range of minimal aerosol removal, the simulation slightly underpredicts the experiment results; however, considering the scale of plots and huge uncertainties inherently included, the deviation can be judged to be minor and would produce a conservative result. In addition, uncertainty analysis has been further refined to reflect the experimental distribution of parameters including aerosol sizes, which induces a span of performance for each representative aerosol size. Based upon the initial validation results along with uncertainty effects, SRT is expected to provide meaningful insights for the analysis of bubble scrubbing. Future sodium-loop tests will provide further validation basis.

Kam, Dong Hoon↗
DOE OSTI2025

Using Calibrated Sodium Data for Preliminary Validation of the SRT Code for Advanced Reactors

Various types of non-light water reactors are currently engaged in the U.S. licensing process. Because of inherent differences compared with well-established large light water reactors, appropriate assessment tools are needed. Specifically, source term analysis, which determines environmental dose impacts from potential accident scenarios, is a crucial part of design and licensing. The U.S. Nuclear Regulatory Commission has emphasized the importance of mechanistic source term analysis for advanced reactor deployments. To align with these needs, Argonne National Laboratory has developed the Simplified Radionuclide Transport (SRT) source term analysis code for metal fuel Sodium-cooled Fast Reactors (SFRs) and microreactors. SRT conducts time-dependent radionuclide transport and retention in SFRs for core and ex-core radionuclide source accident sequences. The main objective of SRT is to provide rapid sensitivity and uncertainty analyses, incorporating parametric uncertainties and summarizing probabilistic results. As part of the code validation process, a study focused on the bubble scrubbing module was performed using an experiment recently carried out by the University of Wisconsin-Madison. Based on the analysis, the modeling approach in SRT provides accurate results for small and large aerosols, while slight underprediction of radionuclide aerosol removal are observed for medium sized aerosols. However, the deviation is minor, considering the highly uncertain phenomenon and range of results, and is in the conservative direction. In addition, uncertainty information derived from the experiments is further implemented, reflecting the actual span of parameters, which leads to enhanced agreement with code predictions. The results demonstrate that SRT provides reasonable predictions for the bubble scrubbing process in sodium pool.

Kam, Dong Hoon↗
NASA NTRS2003

Validation of Envisat Ozone Data Products using Satellite and Ground Based Data

The Envisat chemistry instruments provide an opportunity to continue the ozone data sets produced by TOMS, SBUV, HALOE, and SAGE. These data sets have already been extensively validated and are assured to be of high accuracy. Continuity and consistency of data sets among the various satellite instruments as well as ground networks is essential for detecting an ozone recovery and climate change. Our objective, as part of the Envisat CaWal program, is to validate SCIAMACHY, MIPAS, and GOMOS ozone products using these heritage instruments. In addition we plan to validate SCIAMACHY Level 1 radiance using heritage satellite data and ground observations using a radiative transfer model. Ground based data included US ozonesonde profiles and a double monochromator Brewer instrument located at Goddard Space Flight Center. To date we have tested our intercomparisons algorithms using available Envisat data compared with SBW/2 and the ground based observations. We analyzed the comparisons with respect to ozone amounts and latitude and found the differences that were expected based on the initial release of Envisat data, which had known deficiencies. We will present our latest results based on the most current release of Envisat ozone data products.

Hilsenrath, E.↗
NASA NTRS2017

Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may soon enable unique insight into which measured phenomena correlate to biological mechanisms that are truly affected by spaceflight conditions; which are most likely to be confounded by other variables; and which are insufficiently characterized, significantly increasing existing and future science return from ISS and spaceflight missions.

Gentry, Diana↗
NASA NTRS1991

Validating a large geophysical data set - Experiences with satellite-derived cloud parameters

The goal of this study is to validate the global cloud parameters derived from the satellite-borne HIRS2 and MSU atmospheric sounding instrument measurements, and to use the analysis of these data as one prototype for studying large geophysical data sets in general. The HIRS2/MSU data set contains a total of 40 physical parameters, filling 25 MB/day; raw HIRS2/MSU data are available for a period exceeding 10 years. Validation involves developing a quantitative sense for the physical meaning of the derived parameters over the range of environmental conditions sampled. This is accomplished by comparing the spatial and temporal distributions of the derived quantities with similar measurements made using other techniques, and with model results. The need to work with Level 2 (point) data, rather than Level 3 (gridded) data for validation purposes is discussed, and some techniques developed for charting the assumptions made in deriving an algorithm and generating a code to produce geophysical quantities from measured radiances are presented.

Kahn, Ralph↗
DOE OSTI2024

Californium-252 production at the High Flux Isotope Reactor - I: Validation study using campaign data

This paper presents a series of 252 Cf production validation and code-to-code comparison studies performed based on data from the production campaigns at the High Flux Isotope Reactor (HFIR). These studies support efforts to convert HFIR from using highly enriched uranium (HEU) fuel to low-enriched uranium (LEU) fuel. HFIR must maintain its world-class performance and missions following this conversion, and because 252 Cf is a vital neutron-emitting radioisotope used for a variety of high-impact applications (e.g., reactor startup, cancer treatment), the ability to efficiently produce 252 Cf must be preserved. In this work, the HFIRCON, Shift, ORIGEN, and TCOMP codes were deployed, and several sets of data libraries were investigated to better understand the calculation codes and the data biases. As-loaded target composition data, as-run irradiation history data, and post-irradiation measurements from recent multi-cycle irradiation campaigns of the HEU core were used to validate and determine methodology biases. Further, the findings demonstrated a good agreement, with results falling within 3 standard deviations of measurements. This paper lays the ground work for the second paper, which evaluates and compares 252 Cf production and safety metrics with the HEU core and a proposed LEU core.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Statistical Validation of Multiple Related Data Sets—Case Study Using Interstellar Boundary Explorer Satellite Data

Abstract Space scientists often face the question of whether data collected by different instruments are measurements of the same source population. This paper proposes a statistical validation method for evaluating the agreement between such related data sets. It offers a detailed case study focused on validating a new data set from the Interstellar Boundary Explorer (IBEX) mission, which serves as a practical how-to guide for similar analyses. Since 2008, the IBEX satellite has been gathering data on heliospheric energetic neutral atoms (ENAs) while being exposed to various sources of background noise, such as cosmic rays and solar energetic particles. The IBEX mission initially released only a qualified triple-coincidence (qABC) data product, which was designed to provide observations of ENAs free of background contamination. Further measurements revealed that the qABC data were in fact susceptible to contamination, having relatively low ENA counts and high background rates. To mitigate this issue, the mission team recently considered releasing a certain qualified double-coincidence (qBC) data product, which has roughly twice the detection rate of the qABC data product. This paper presents a simulation-based validation of the new qBC data product against the already-released qABC data product. The results show that the qBCs can plausibly be said to be measuring the same source population as the qABCs up to an average absolute deviation of 3.6%. Visual diagnostics provide additional confirmation of source rate coherence across data products. The framework introduced here is general and can be applied to other validation problems both within and outside the field of space physics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2010

A Comprehensive Validation Methodology for Sparse Experimental Data

A comprehensive program of verification and validation has been undertaken to assess the applicability of models to space radiation shielding applications and to track progress as models are developed over time. The models are placed under configuration control, and automated validation tests are used so that comparisons can readily be made as models are improved. Though direct comparisons between theoretical results and experimental data are desired for validation purposes, such comparisons are not always possible due to lack of data. In this work, two uncertainty metrics are introduced that are suitable for validating theoretical models against sparse experimental databases. The nuclear physics models, NUCFRG2 and QMSFRG, are compared to an experimental database consisting of over 3600 experimental cross sections to demonstrate the applicability of the metrics. A cumulative uncertainty metric is applied to the question of overall model accuracy, while a metric based on the median uncertainty is used to analyze the models from the perspective of model development by analyzing subsets of the model parameter space.

Norman, Ryan B.↗
DOE OSTI2020

Recursive Dynamic Compressive Sensing in Smart Distribution Systems

With a transition to a smarter grid, we are witnessing a significant growth in smart metering infrastructure and sensor deployment in the distribution system. The underlying communication infrastructure is stressed due to the large volume of data that is generated by the smart meters/sensors. Furthermore, real time operations such as state estimation and control are impaired due to the lack of reliable aggregation of the data. In this paper, we exploit the underlying sparsity in grid data to implement two recursive dynamic compressive sensing (CS) approaches-streaming modified weighted-`1 CS and Kalman filtered CS. These approaches aim to reconstruct the sparse signal using the current underdetermined measurements and the prior information about the sparse signal and its support set. Slow signal and support change is in distribution grid data is validated using Pecan Street data. Both the IEEE 34 node test feeder system and PecanStreet data are considered as two examples to validate the superior performance of the two recursive CS techniques relative to classic CS.

Karimi, Hazhar Sufi↗
NASA NTRS2001

Development and Validation of High Performance Unshrouded Centrifugal Impeller

The feasibility of using a two-stage unshrouded impeller turbopump to replace the current three-stage reusable launch vehicle engine shrouded impeller hydrogen pump has been evaluated from the standpoint of turbopump weight reduction and overall payload improvement. These advantages are a by-product of the higher tip speeds that an unshrouded impeller can sustain. The issues associated with the effect of unshrouded impeller tip clearance on pump efficiency and head have been evaluated with one-dimensional tools and full three-dimensional rotordynamic fluid reaction forces and coefficients have been established through time dependent computational fluid dynamics (CFD) simulation of the whole 360 degree impeller with different rotor eccentricities and whirling ratios. Unlike the shrouded impeller, the unshrouded impeller forces are evaluated as the sum of the pressure forces on the blade and the pressure forces on the hub using the CFD results. The turbopump axial thrust control has been optimized by adjusting the first stage impeller backend wear ring seal diameter and diverting the second stage backend balance piston flow to the proper location. The structural integrity associated with the high tip speed has been checked by analyzing a 3D-Finite Element Model at maximum design conditions (6% higher than the design speed). This impeller was fabricated and tested in the NASA Marshall Space Flight Center water-test rig. The experimental data will be compared with the analytical predictions and presented in another paper. The experimental data provides validation data for the numerical design and analysis methodology. The validated numerical methodology can be used to help design different unshrouded impeller configurations.

Chen, Wei-Chung↗
NASA NTRS1988

Calibration support for the Earth Observing System Project

The Earth Observing System Project (EOS) program guidelines establishes significantly more stringent requirements on calibrations of instruments. This requirement is driven by the need for long-term continuity of acquired data sets and the use of measurements in interdisciplinary investigations. Personnel from the Standards and Calibration Office have been supporting the Program and Project in interpreting these goals into specific requirements. Contributions to EOS have included participation in the Panel of Experts which produced a list of consensus items necessary for accomplishing an accurate calibration and suggested EOS Project Calibration Policy, and drafting the announcement of opportunity and bidders information package positions on instrument calibration and data product validation. Technical staffing was provided to the NASA delegates to the Committee on Earth Orbiting Satellites (club of space-faring nations) for the standing working group on Calibration and Data Validation.

Guenther, B. W.↗
DOE OSTI2025

Thermal Hydraulics Validation Activities in the ART-GCR Campaign

The Advanced Reactor Technologies - Gas Cooled Reactor Campaign (ART-GCR) is part of the United States Department of Energy - Office of Nuclear Energy's Advanced Reactor Technologies program aimed at developing a High Temperature Gas-cooled Reactor (HTGR) which will offer enhancements in safety and efficiency. The Design, Methods, and Validation arm of the ART-GCR program provides experience and advanced tools for HTGR design and analysis. The Methods and Validation arm is developing data to validate predictions of decay heat removal through an extensive experimental campaign the Natural Convection Shutdown Heat Removal Test Facility at Argonne National Laboratory. In-core thermal hydraulics validation is being facilitated through the OECD/NEA's Thermal Hydraulic Code Validation Benchmark for High Temperature Gas-Cooled Reactors using HTTF Data. That benchmark contains code-to-code and code-to-data comparisons for 3 sets of HTGR thermal hydraulics phenomena. This ongoing benchmark activity has 16 participants from 9 countries developing leading insights into HTGR thermal hydraulics code validation. The ART-GCR campaign is also working on the development of state-of-the-art MOOSE-based models of the High Temperature Engineering Test Reactor (HTTR). Through the OECD/NEA's HTTR Loss of Forced Cooling (LOFC) program, the ART-GCR campaign is developing a multiphysics transient code validation benchmark based on 3 HTTR experiments that will provide an opportunity for international collaboration on multiphysics code validation.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1999

Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

Duque, Earl P. N.↗
NASA NTRS2023

A GeoNEX-Based High-Spatiotemporal-Resolution Product of Land Surface Downward Shortwave Radiation and Photosynthetically Active Radiation

Surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) play critical roles in the Earth’s surface processes. As the main inputs of various ecological, hydrological, carbon, and solar photovoltaic models, increasing requirements for high-spatiotemporal-resolution DSR and PAR es- timation with high accuracy have been observed in recent years. However, few existing products satisfy all of these requirements. This study employed a well-established physical-based lookup table (LUT) approach to the GeoNEX gridded top-of-atmosphere bidirectional reflectance factor data acquired by the Advanced Hi- mawari Imager (AHI) and Advanced Baseline Imager (ABI) sensors. It produced a data product of DSR and PAR over both AHI and ABI coverage at an hourly temporal step with a 1 km spatial resolution. GeoNEX DSR data were validated over 63 stations, and GeoNEX PAR data were validated over 27 stations. The vali- dation showed that the new GeoNEX DSR and PAR products have accuracy higher than other existing prod- ucts, with root mean square error (RMSE) of hourly GeoNEX DSR achieving 74.3Wm−2 (18.0%), daily DSR estimation achieving 18.0 W m−2 (9.2 %), hourly GeoNEX PAR achieving 34.9 W m−2 (19.6 %), and daily PAR achieving 9.5 W m−2 (10.5 %). The study also demonstrated the application of the high-spatiotemporal- resolution GeoNEX DSR product in investigating the spatial heterogeneity and temporal variability of surface solar radiation. The data product can be freely accessed through the NASA Advanced Supercomputing Division GeoNEX data portal: https://data.nas.nasa.gov/geonex/geonexdata/GOES16/GEONEX-L2/DSR-PAR/ (last ac- cess: 12 March 2023) and https://data.nas.nasa.gov/geonex/geonexdata/HIMAWARI8/GEONEX-L2/DSR-PAR/ (last access: 12 March 2023) (https://doi.org/10.5281/zenodo.7023863; Wang and Li, 2022).

Surface downward shortwave radiation (DSR)↗
DOE OSTI2021

Development and Application of a Data-Driven Methodology for Validation of Risk-Informed Safety Margin Characterization Models

The document is the Final Technical Progress Report for the Nuclear Energy University Program’s Integrated Research Project (IRP) on “Development and Application of a Data-Driven Methodology for Validation of Risk-Informed Safety Margin Characterization Models” that supports the LWR Sustainability Program’s RISMC R&D Pathway. The project goal is to develop and demonstrate a data-driven methodology for validation of advanced computer models used in nuclear power plant safety analysis. Specifically, the advanced computer models are those in the toolkit developed to support risk-informed safety margin characterization (RISMC), an integrated deterministic/probabilistic safety analysis methodology developed in the Department of Energy’s Light Water Reactor Sustainability (LWR-S) program. The report reflects the progress made towards the project’s stated goal by contributions by researchers and graduate students from universities, with support from researchers from national laboratories and industry companies. The project organization, effort coordination and technical implementation are summarized, followed by discussion of main findings, issues, and path forward. Selected chapters provide a more detailed description of tasks, approaches and respective findings and recommendations. Noteworthy are contributions that serve as guidelines for methodology development. It is also noted that this report is complemented by other milestone reports (as stand-alone deliverables) that provide detailed discussion of the technical developments. The project results have been documented in a number (12) dissertations and these, 50+ peer-reviewed publications in technical journals and conference proceedings.

42 ENGINEERING↗
NASA NTRS1988

On the appropriateness of applying chi-square distribution based confidence intervals to spectral estimates of helicopter flyover data

The validity of applying chi-square based confidence intervals to far-field acoustic flyover spectral estimates was investigated. Simulated data, using a Kendall series and experimental acoustic data from the NASA/McDonnell Douglas 500E acoustics test, were analyzed. Statistical significance tests to determine the equality of distributions of the simulated and experimental data relative to theoretical chi-square distributions were performed. Bias and uncertainty errors associated with the spectral estimates were easily identified from the data sets. A model relating the uncertainty and bias errors to the estimates resulted, which aided in determining the appropriateness of the chi-square distribution based confidence intervals. Such confidence intervals were appropriate for nontonally associated frequencies of the experimental data but were inappropriate for tonally associated estimate distributions. The appropriateness at the tonally associated frequencies was indicated by the presence of bias error and noncomformity of the distributions to the theoretical chi-square distribution. A technique for determining appropriate confidence intervals at the tonally associated frequencies was suggested.

Rutledge, Charles K.↗