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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Component testing for dynamic model verification

Dynamic model verification is the process whereby an analytical model of a dynamic system is compared with experimental data, adjusted if necessary to bring it into agreement with the data, and then qualified for future use in predicting system response in a different dynamic environment. These are various ways to conduct model verification. The approach taken here employs Bayesian statistical parameter estimation. Unlike curve fitting, whose objective is to minimize the difference between some analytical function and a given quantity of test data (or curve), Bayesian estimation attempts also to minimize the difference between the parameter values of that funciton (the model) and their initial estimates, in a least squares sense. The objectives of dynamic model verification, therefore, are to produce a model which: (1) is in agreement with test data; (2) will assist in the interpretation of test data; (3) can be used to help verify a design; (4) will reliably predict performance; and (5) in the case of space structures, will facilitate dynamic control.

Hasselman, T. K.↗
NASA NTRS1993

Explosive component acceptance tester using laser interferometer technology

Acceptance testing of explosive components requires a reliable and simple to use testing method that can discern less than optimal performance. For hot-wire detonators, traditional techniques use dent blocks or photographic diagnostic methods. More complicated approaches are avoided because of their inherent problems with setup and maintenance. A recently developed tester is based on using a laser interferometer to measure the velocity of flying plates accelerated by explosively actuated detonators. Unlike ordinary interferometers that monitor displacement of the test article, this device measures velocity directly and is commonly used with non-spectral surfaces. Most often referred to as the VISAR technique (Velocity Interferometer System for Any Reflecting Surface), it has become the most widely-accepted choice for accurate measurement of velocity in the range greater than 1 mm/micro-s. Traditional VISAR devices require extensive setup and adjustment and therefore are unacceptable in a production-testing environment. This paper describes a new VISAR approach which requires virtually no adjustments, yet provides data with accuracy comparable to the more complicated systems. The device, termed the Fixed-Cavity VISAR, is currently being developed to serve as a product verification tool for hot-wire detonators and slappers. An extensive data acquisition and analysis computer code was also created to automate the manipulation of raw data into final results.

Wickstrom, Richard D.↗
NASA NTRS2001

International Space Station Increment-2 Quick Look Report

The objective of this quick look report is to disseminate the International Space Station (ISS) Increment-2 reduced gravity environment preliminary analysis in a timely manner to the microgravity scientific community. This report is a quick look at the processed acceleration data collected by the Microgravity Acceleration Measurement System (MAMS) during the period of May 3 to June 8, 2001. The report is by no means an exhaustive examination of all the relevant activities, which occurred during the time span mentioned above for two reasons. First, the time span being considered in this report is rather short since the MAMS was not active throughout the time span being considered to allow a detailed characterization. Second, as the name of the report implied, it is a quick look at the acceleration data. Consequently, a more comprehensive report, the ISS Increment-2 report, will be published following the conclusion of the Increment-2 tour of duty. NASA sponsors the MAMS and the Space Acceleration Microgravity System (SAMS) to support microgravity science experiments, which require microgravity acceleration measurements. On April 19, 2001, both the MAMS and the SAMS units were launched on STS-100 from the Kennedy Space Center for installation on the ISS. The MAMS unit was flown to the station in support of science experiments requiring quasisteady acceleration data measurements, while the SAMS unit was flown to support experiments requiring vibratory acceleration data measurement. Both acceleration systems are also used in support of the vehicle microgravity requirements verification. The ISS reduced gravity environment analysis presented in this report uses mostly the MAMS acceleration data measurements (the Increment-2 report will cover both systems). The MAMS has two sensors. The MAMS Orbital Acceleration Research Experiment Sensor Subsystem, which is a low frequency range sensor (up to 1 Hz), is used to characterize the quasi-steady environment for payloads and vehicle. The MAMS High Resolution Acceleration Package is used to characterize the ISS vibratory environment up to 100 Hz. This quick look report presents some selected quasi-steady and vibratory activities recorded by the MAMS during the ongoing ISS Increment-2 tour of duty.

Jules, Kenol↗
NASA NTRS1987

A computer program for model verification of dynamic systems

Dynamic model verification is the process whereby an analytical model of a dynamic system is compared with experimental data, and then qualified for future use in predicting system response in a different dynamic environment. There are various ways to conduct model verification. The approach adopted in MOVER II employs Bayesian statistical parameter estimation. Unlike curve fitting whose objective is to minimize the difference between some analytical function and a given quantity of test data (or curve), Bayesian estimation attempts also to minimize the difference between the parameter values of that function (the model) and their initial estimates, in a least squares sense. The objectives of dynamic model verification, therefore, are to produce a model which: (1) is in agreement with test data, (2) will assist in the interpretation of test data, (3) can be used to help verify a design, (4) will reliably predict performance, and (5) in the case of space structures, facilitate dynamic control.

Chrostowski, J. D.↗
DOE OSTI2025

Progress Towards the Validation of a new RELAP5-3D model of the High Temperature Test Facility

Validation is a key step in the development of any type of systems model. As the next generation of reactors approaches, the need for codes that have been validated for these new types of systems continues to grow. An example of a prominent option is the Reactor Excursion Leak Analysis Program (RELAP5-3D), developed by Idaho National Laboratory. This code was developed for the purpose of systems level thermal-hydraulic modeling of light water reactors (LWRS) and postulated transients that can occur in LWRS.RELAP5-3D has been substantially validated against LWR data. Due to its long history as a reactor safety analysis tool, there has been an effort to adapt RELAP5-3D for the purposes of advanced reactor concepts such as prismatic high-temperature gas-cooled reactors (HTGRs). However, RELAP5-3D has not nearly been validated and verified for HTGRs to the degree of LWRs, warranting verification and validation opportunities with computational benchmarks and existing experimental facilities. Examples of such facilities include the modular high-temperature gas-cooled reactor (MHTGR) 350 and the high temperature engineering test reactor (HTTR) from Japan. The MHTGR 350 is a benchmark design concept for code-to-code verification purposes; therefore, it does not provide any experimental data for validation opportunities The HTTR provides useful multiphysics validation data but does not have the in-core instruments to generate thermal-hydraulic experimental data to help with RELAP5-3D validation. Consequently, a facility that could provide key in-core temperatures for thermal-hydraulic validation was still needed. The High Temperature Test Facility (HTTF) is an integral effects facility for HTGR thermal hydraulics developed and operated by Oregon State University. HTTF represents ¼ length scale of the General Atomics MHTGR and is rated for a total power of 2.2 MW. Axially, the core consists of an upper and lower reflector and 10 blocks, numbered from bottom to top (Block 1 is right above lower reflector). The core is heated via graphite resistive heater rods, with respective channels distributed throughout the core. The primary coolant is helium and heat can radiate out of the core to the reactor cavity cooling system (RCCS), which is cooled by water. The primary purpose of the facility is to investigate pressurized conduction cooldown (PCC) and depressurized conduction cooldown (DCC) transients, which are also referred to as the pressurized and depressurized loss of forced cooling respectively. Two experiments were chosen to perform the validation study with a RELAP5-3D model of HTTF. These experiments are PG-27 (PCC) and PG-29 (DCC). These were chosen based off of the quality of available experimental data before and during the experiment which led to their inclusion in the HTGR Thermal Hydraulics Benchmark.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Baseline Characterization Database Verification Report – 2114 Billet A20568

This ECAR provides the results of a validity evaluation of the physical and mechanical property data collected on a billet of nuclear-grade graphite (i.e., 2114 Billet A20568) in support of the ART Baseline Graphite Characterization Program.1,2 Millions of raw data points have been collected during testing and quantification analyses for these billets. The summary scalar property values and supplementary traceability data are collected into comprehensive spreadsheets. Data sets are composed of single billets of graphite for any given grade, organized by mechanical test-specimen type, and further subdivided into individual spreadsheet tabs according to the specific test or evaluation being performed. A direct analysis of properties was not conducted, and this report does not provide information on the validity or performance characteristics of the graphite itself. Rather, this report is intended as a verification of the completeness of actual data collected in accordance with PLN-3467, “Baseline Graphite Characterization Plan: Electromechanical Testing,”3 and their representation of the measurement and test results with sole regard to the graphite billets under evaluation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2005

Performance Evaluation of a Data Validation System

Online data validation is a performance-enhancing component of modern control and health management systems. It is essential that performance of the data validation system be verified prior to its use in a control and health management system. A new Data Qualification and Validation (DQV) Test-bed application was developed to provide a systematic test environment for this performance verification. The DQV Test-bed was used to evaluate a model-based data validation package known as the Data Quality Validation Studio (DQVS). DQVS was employed as the primary data validation component of a rocket engine health management (EHM) system developed under NASA's NGLT (Next Generation Launch Technology) program. In this paper, the DQVS and DQV Test-bed software applications are described, and the DQV Test-bed verification procedure for this EHM system application is presented. Test-bed results are summarized and implications for EHM system performance improvements are discussed.

Wong, Edmond↗
NASA NTRS2022

Analysis of the MODIS Above-Cloud Aerosol Retrieval Algorithm Using MCARS

The Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS) presently produces synthetic radiance data from Goddard Earth Observing System version 5 (GEOS-5) model output as if the Moderate Resolution Imaging Spectroradiometer (MODIS) was viewing a combination of atmospheric column inclusive of clouds, aerosols and a variety of gases and land/ocean surface at a specific location. In this paper we use MCARS to study the MODIS Above-Cloud AEROsol retrieval algorithm (MOD06ACAERO). MOD06ACAERO is presently a regional research algorithm able to retrieve aerosol optical thickness over clouds, in particular absorbing biomass burning aerosols overlying marine boundary layer clouds in the Southeastern Atlantic Ocean. The algorithm’s ability to provide aerosol information in cloudy conditions makes it a valuable source of information for modeling and climate studies n an area where current clear sky-only operational MODIS aerosol retrievals effectively have a data gap between the months of June and October. We use MCARS for a verification and closure study of the MOD06ACAERO algorithm. The purpose of this study is to develop a set of constraints a model developer might use during assimilation of MOD06ACAERO data. Our simulations indicate that the MOD06ACAERO algorithm performs well for marine boundary layer clouds in the SE Atlantic provided some specific screening rules are observed. For the present study, a combination of five simulated MODIS data granules was used for a dataset of 13.5 million samples with known input conditions. When pixel retrieval uncertainty was less than 30%, optical thickness of the underlying cloud layer was greater than 4 and scattering angle range within the cloud bow was excluded, MOD06ACAERO retrievals agreed with the underlying ground truth (GEOS-5 cloud and aerosol profiles used to generate the synthetic radiances) with a slope of 0.913, offset of 0.06, and RMSE=0.107. When only near-nadir pixels were considered (view zenith angle within +/-20 degrees) the agreement with source data further improved (0.977, 0.051 and 0.096 respectively). Algorithm closure was examined using a single case out of the five 38 used for verification. For closure, the MOD06ACAERO code was modified to use GEOS-5 temperature and moisture profiles as ancillary. Agreement of MOD06ACAERO retrievals with source data for the closure study had a slope of 0.996 with offset -0.007 and RMSE of 0.097 at pixel uncertainty level of less than 40%, illustrating the benefits of high-quality ancillary atmospheric data for such retrievals.

MODIS↗
NASA NTRS2017

Reusing JPSS Ground System Components to Process Aura Ozone Monitoring Instrument Science Products

New Earth observation instruments are planned to enable advancements in Earth science research over the next decade. Diversity of Earth observing instruments and their observing platforms will continue to increase as new instrument technologies emerge and are deployed as part of National programs such as Joint Polar Satellite System (JPSS), Geostationary Operational Environmental Satellite system (GOES), Landsat as well as the potential for many CubeSat and aircraft missions. The practical use and value of these observational data often extends well beyond their original purpose. The practicing community needs intuitive and standardized tools to enable quick unfettered development of tailored products for specific applications and decision support systems. However, the associated data processing system can take years to develop and requires inherent knowledge and the ability to integrate increasingly diverse data types from multiple sources. This paper describes the adaptation of a large-scale data processing system built for supporting JPSS algorithm calibration and validation (CalVal) node to a simplified science data system for rapid application. The new configurable data system reuses scalable JAVA technologies built for the JPSS Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) system to run within a laptop environment and support product generation and data processing of AURA Ozone Monitoring Instrument (OMI) science products. Of particular interest are the root requirements necessary for integrating experimental algorithms and Hierarchical Data Format (HDF) data access libraries into a science data production system. This study demonstrates the ability to reuse existing Ground System technologies to support future missions with minimal changes.

Science Data Systems↗
NASA NTRS1991

COBE navigation with one-way return-link Doppler in the post-helium-venting phase

The results of a navigation experiment with one way return link Doppler tracking measurements for operational orbit determination of the Cosmic Background Explorer (COBE) spacecraft are presented. The frequency of the tracking signal for the one way measurements was stabilized with an Ultrastable Oscillator (USO), and the signal was relayed by the Tracking and Data Relay Satellite System (TDRSS). The study achieved three objectives: space qualification of TDRSS noncoherent one way return link Doppler tracking; determination of flight performance of the USO coupled to the second generation TDRSS compatible user transponder; and verification of algorithms for navigation using actual one way tracking data. Orbit determination and the inflight USO performance evaluation results are presented.

Dunham, Joan↗
DOE OSTI2023

High-Resolution Synthetic Solar Irradiance Sequence Generation: An LSTM-Based Generative Adversarial Network

The rapid growth of renewable energy resources penetration is bringing more challenges to power system planning and operation. Relevant renewable energy integration studies, such as the capability and dynamic performance of inverter-based resources' primary frequency response and fast frequency response, require high-resolution renewable generation output data that are representative of renewable energy resources. This paper focuses on creating synthetic but realistic solar irradiance data and proposes a long short-term memory-based generative adversarial network to generate high-resolution (second-level) solar irradiance sequences from low-resolution (minute-level) measurements. Combined with a classifier to recognize the solar irradiance patterns, the proposed model is trained using multi-loss functions to accurately capture the temporal correlations among both high-resolution and low-resolution sequences. Verification of the proposed approach is performed on the data set of the Oahu Solar Measurement Grid collected through the National Renewable Energy Laboratory. The results of the case studies demonstrate the proposed approach's capability to capture the statistical characteristics of different solar irradiance patterns and to generate high-quality synthetic solar irradiance sequences in high resolution.

dynamic scheduling↗
DOE OSTI2020

SCALE capabilities for high temperature gas-cooled reactor analysis

The SCALE code system’s ability to address stochastic distributions of fuel particles within a graphite matrix has been revisited in both multigroup (MG) features and continuous-energy (CE) Monte Carlo methods. Furthermore, this paper describes current and emergent SCALE capabilities within the CSAS sequence to address double-heterogeneous systems and presents verification and validation studies of these methods and data. Good agreement was obtained for a high temperature gas-cooled reactor (HTGR) fuel pebble model between CSAS MG eigenvalue calculations and corresponding CE reference solutions. Code-to-code comparisons for this HTGR pebble model showed good agreement of CSAS-KENO and CSAS-Shift CE calculations and the Serpent and MCNP codes in terms of eigenvalues and reaction rate ratios. Validation studies based on two HTGR experiments resulted in good agreement between MG and CE results, as well as between experiment and calculation, although the level of agreement was significantly influenced by the applied ENDF/B nuclear data library.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

The liquid-conduction, vapor-flow heat pipe model in Sockeye

A single-phase heat pipe flow model implemented in the heat pipe application Sockeye is described. This model solves one-dimensional, compressible flow equations for the vapor phase in the center of a heat pipe, which are coupled to the two-dimensional heat conduction equation for the wick, liquid, and cladding, as well as to an ordinary differential equation tracking the working fluid inventory in the evaporator section of the heat pipe. This model is demonstrated with several test problems, including comparisons to analytic solutions for the vapor flow fields, analytic curves for sonic and capillary limitations of heat pipe operation, and some experimental data. The numerical solution gives excellent agreement for verification problems and good agreement with experimental results. Also, demonstrations show that the model is very robust, allowing for full simulations of heat pipe transients, including frozen startup, sonic-limited (supersonic) flow, and heat pipe shutdown.

42 ENGINEERING↗
DOE OSTI2023

Accurate prediction of carbon dioxide capture by deep eutectic solvents using quantum chemistry and a neural network

Carbon dioxide (CO 2 ) emissions from fossil fuel combustion are a significant source of greenhouse gas, contributing in a major way to global warming and climate change. Carbon dioxide capture and sequestration is gaining much attention as a potential method for controlling these greenhouse gas emissions. Among the environmentally friendly solvents, deep eutectic solvents (DESs) have demonstrated the potential capability for carbon capture. To establish a theoretical framework for DES activity, thermodynamics modeling and solubility predictions are significant factors to anticipate and understand the system behavior. Here, in this study, we combine the COSMO-RS model with machine learning techniques to predict the solubility of CO 2 in various deep eutectic solvents. A comprehensive data set was established comprising 1973 CO 2 solubility data points in 132 different DESs at a variety of temperatures, pressures, and DES molar ratios. This data set was then utilized for the further verification and development of the COSMO-RS model. The CO 2 solubility (ln(x CO 2 )) in DESs calculated with the COSMO-RS model differs significantly from the experiment with an average absolute relative deviation (AARD) of 23.4%. A multilinear regression model was developed using the COSMO-RS predicted solubility and a temperature-pressure dependent parameter, which improved the AARD to 12%. Finally, a machine learning model using COSMO-RS-derived features was developed based on an artificial neural network algorithm. The results are in excellent agreement with the experimental CO 2 solubilities, with an AARD of only 2.72%. The ML model will be a potentially useful tool for the design and selection of DESs for CO 2 capture and utilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Multidimensional Numerical Modeling of Combustion Dynamics in a Non-Premixed Rotating Detonation Engine With Adaptive Mesh Refinement

In the present work, a novel computational fluid dynamics (CFD) methodology was developed to simulate full-scale non-premixed rotating detonation engines (RDEs). A unique feature of the modeling approach was the incorporation of adaptive mesh refinement (AMR) to achieve a good trade-off between model accuracy and computational expense. Here, unsteady Reynolds-averaged Navier–Stokes (RANS) simulations were performed for an Air Force Research Laboratory (AFRL) non-premixed RDE configuration with hydrogen as fuel and air as the oxidizer. The finite-rate chemistry model, along with a ten-species detailed kinetic mechanism, was employed to describe the H 2 -Air combustion chemistry. Three distinct operating conditions were simulated, corresponding to the same global equivalence ratio of unity but different fuel/air mass flowrates. For all conditions, the capability of the model to capture essential detonation wave dynamics was assessed. An exhaustive verification and validation study was performed against experimental data in terms of a number of waves, wave frequency, wave height, reactant fill height, oblique shock angle, axial pressure distribution in the channel, and fuel/air plenum pressure. The CFD model was demonstrated to accurately predict the sensitivity of these wave characteristics to the operating conditions, both qualitatively and quantitatively. A comprehensive heat release analysis was also conducted to quantify detonative versus deflagrative burning for the three simulated cases. The present CFD model offers a potential capability to perform rapid design space exploration and/or performance optimization studies for realistic full-scale RDE configurations.

42 ENGINEERING↗
DOE OSTI2025

Using a Large Language Model as a Building Block to Generate Usable Validation and Verification Suite for OpenMP

In the HPC area, both hardware and software move quickly. Often new hardware is developed and deployed, the corresponding software stack, including compilers and other tools, are under active development while leading edge software developers are working to port and tune their applications, all at the same time. While the software ecosystem is in flux, one of the key challenges for users is obtaining insight into the state of implementation of key features in the programming languages and models their applications are using – whether they have been implemented, and whether the implementation conforms to the specification, especially for newly implemented features (less tested by widespread use). OpenMP is one of the most prominent shared memory programming models used for on-node programming in HPC. With the shift towards accelerators (such as GPUs and FPGAs) and heterogeneous programming OpenMP features are getting more complex. It is natural to ask whether generative AI approaches, and large language models (LLMs) in particular, can help in producing validation and verification test suites to allow users better and faster insights into the availability and correctness of OpenMP features of interest. In this work, we explore the use of ChatGPT-4 to generate a suite of tests for OpenMP features. We have chosen a set of directives and clauses, a total of 78 combinations, which first appeared in OpenMP 3.0 (released in May 2008) but are also relevant for accelerators. We prompted ChatGPT to generate tests in the C and Fortran languages, for both host (CPU) and device (accelerator). On the Summit super-computer using the GNU implementation, we found that, of the 78 generated tests 67 C tests and 43 Fortran tests compiled successfully and fewer than those executed to completion. On further analysis we show that not all generated tests are valid. We document the process, results, and provide detailed analysis regarding the quality of tests generated. With the aim of providing input to a production quality validation and verification suite, we manually implement the corrections required to make the tests valid according to the current OpenMP specification. We quantify this effort as small, medium, or large, and record the lines of code changed to correct the invalid tests. With the corrected tests we validate recent implementations from HPE, AMD, and GNU on the Frontier supercomputer. Our experiment and subsequent analysis show that although LLMs are capable of producing HPC specific codes, they are limited by their understanding of the deeper semantics and restrictions of programming models such as OpenMP. Unsurprisingly more commonly used features have better support, while some OpenMP 3.0 directives such as sections and tasking are not universally supported on accelerators. We demonstrate that successful compilation and execution to completion are inadequate metrics for evaluating generated code and that, at this time, commodity LLMs require expert intervention for code verification. This points to gaps in the training data that is currently available for HPC. We demonstrate that with "small" effort 37% of generated invalid C tests and 63% of generated invalid Fortran tests could be corrected. This improves productivity of test generation as we circumvent writing from scratch and the common programming errors associated with it.

Pophale, Swaroop [ORNL] (ORCID:0000000185446367)↗
DOE OSTI2021

Implementation of Plot File Testing in the DYNA3D/ParaDyn Software Quality Assurance Suite

Automated testing of DYNA3D/ParaDyn plot files was added to the DYNA3D/ParaDyn software quality assurance (SQA) test suite. The new capability extracts select data from the plot files generated during each verification run and compares it to the same baseline answers used to verify the problem. Deviations between baseline answers and plot file values are reported in the same manner as solution discrepancies, and differences in precision levels between the baseline answers and plot file results are accounted for. The new testing leverages the existing SQA test suite framework and test problems and the Python Mili reader and minimally increases the overall run time (< 5%) of the SQA test suite. This new capability provides incremental end-toend testing of the most common DYNA3D/ParaDyn simulation workflows.

42 ENGINEERING↗
DOE OSTI2025

DMTN-101: Verifying LSST Calibration Data Products

A description of plans for verifying LSST's Calibration Data Products. This document covers our approach to verification element LVV-57, addressing requirement DMS-REQ-0130.

79 ASTRONOMY AND ASTROPHYSICS↗