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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

Past methods of predicting net heat input needed to be validated. Validation effort pursued with several paths including improving model inputs, using test hardware to provide validation data, and validating high fidelity models. Validation test hardware provided direct measurement of net heat input for comparison to predicted values. Predicted value of net heat input was 1.7 percent less than measured value and initial calculations of measurement uncertainty were 2.1 percent (under review). Lessons learned during validation effort were incorporated into convertor modeling approach which improved predictions of convertor efficiency.

Wilson, Scott D.↗
NASA NTRS2013

Develop a Model Component

During my internship at NASA, I was a model developer for Ground Support Equipment (GSE). The purpose of a model developer is to develop and unit test model component libraries (fluid, electrical, gas, etc.). The models are designed to simulate software for GSE (Ground Special Power, Crew Access Arm, Cryo, Fire and Leak Detection System, Environmental Control System (ECS), etc. ~.) before they are implemented into hardware. These models support verifying local control and remote software for End-Item Software Under Test (SUT). The model simulates the physical behavior (function, state, limits and 110) of each end-item and it's dependencies as defined in the Subsystem Interface Table, Software Requirements & Design Specification (SRDS), Ground Integrated Schematic (GIS), and System Mechanical Schematic.(SMS). The software of each specific model component is simulated through MATLAB's Simulink program. The intensiv~ model development life cycle is a.s follows: Identify source documents; identify model scope; update schedule; preliminary design review; develop model requirements; update model.. scope; update schedule; detailed design review; create/modify library component; implement library components reference; implement subsystem components; develop a test script; run the test script; develop users guide; send model out for peer review; the model is sent out for verific~tionlvalidation; if there is empirical data, a validation data package is generated; if there is not empirical data, a verification package is generated; the test results are then reviewed; and finally, the user. requests accreditation, and a statement of accreditation is prepared. Once each component model is reviewed and approved, they are intertwined together into one integrated model. This integrated model is then tested itself, through a test script and autotest, so that it can be concluded that all models work conjointly, for a single purpose. The component I was assigned, specifically, was a fluid component, a discrete pressure switch. The switch takes a fluid pressure input, and if the pressure is greater than a designated cutoff pressure, the switch would stop fluid flow.

Ensey, Tyler S.↗
NASA NTRS2021

T0TEM - T0 Test Evaluation Module Development and Verification

Transition temperature testing of ferritic steels evaluates the ductile to brittle transition temperature, where the behavior of the steel changes from controlled ductile tearing to uncontrollable brittle fracture. This testing is governed by ASTM (American Society of Testing and Materials) E1921 standard. The calculations and plots required by this standard are iterative in nature and require significant effort to produce by standard hand calculations. In addition to analysis of a complete data set, intermediate analysis during testing is beneficial to determine optimal test temperatures. Given the exhaustive nature of calculating the transition temperature, being able to quickly update target temperatures is a significant benefit to not only the quality of tests, but the number of required tests as well. T0 Test Evaluation Module (T0TEM) v1.5 is a software application created under the Layered Pressure Vessel (LPV) certification effort. To reduce the analysis time of transition temperature test data sets producedfor this effort, T0TEM was created to calculate the E1921 Master Curve along with all required data and validity checks. By creating this program, hundreds of hours of analysis time were saved. In addition, the creation of a standard program provided a significant improvement in the consistency with which results were reported. T0TEM also calculates the results and plots required for the E1921 inhomogeneity annex to determine whether a material behaves in a homogenous manner. This program was created by Levi Shelton and Cameron Bosley at NASA, with input and review from the E1921 committee. The results generated by T0TEM were compared to the validation data sets provided by ASTM with good concurrence. ASTM committee members have reviewed and applied T0TEM to other data sets with satisfactory results. T0TEM was originally released to the NASA Software Repository and publicly via SourceForge in May of 2020. Version 1.5 was released in April of 2021 with minor functionality updates and additional statistical analysis methods.

Levi Shelton↗
NASA NTRS2006

System and method for forward error correction

A system and method are provided for transferring a packet across a data link. The packet may include a stream of data symbols which is delimited by one or more framing symbols. Corruptions of the framing symbol which result in valid data symbols may be mapped to invalid symbols. If it is desired to transfer one of the valid data symbols that has been mapped to an invalid symbol, the data symbol may be replaced with an unused symbol. At the receiving end, these unused symbols are replaced with the corresponding valid data symbols. The data stream of the packet may be encoded with forward error correction information to detect and correct errors in the data stream.

Cole, Robert M.↗
NASA NTRS2007

System and method for transferring data on a data link

A system and method are provided for transferring a packet across a data link. The packet may include a stream of data symbols which is delimited by one or more framing symbols. Corruptions of the framing symbol which result in valid data symbols may be mapped to invalid symbols. If it is desired to transfer one of the valid data symbols that has been mapped to an invalid symbol, the data symbol may be replaced with an unused symbol. At the receiving end, these unused symbols are replaced with the corresponding valid data symbols. The data stream of the packet may be encoded with forward error correction information to detect and correct errors in the data stream.

Cole, Robert M.↗
NASA NTRS2000

Earth Radiation Measurement Science

This document is the final report for NASA Grant NAG1-1959, 'Earth Radiation Measurement Science'. The purpose of this grant was to perform research in this area for the needs of the Clouds and Earth Radiant Energy System (CERES) project and for the Earth Radiation Budget Experiment (ERBE), which are bing conducted by the Radiation and Aerosols Branch of the Atmospheric Sciences Division of Langley Research Center. Earth Radiation Measurement Science investigates the processes by which measurements are converted into data products. Under this grant, research was to be conducted for five tasks: (1) Point Response Function Measurements; (2) Temporal Sampling of Outgoing Longwave Radiation; (3) Spatial Averaging of Radiation Budget Data; (4) CERES Data Validation and Applications; and (5) ScaRaB Data Validation and Application.

Smith, G. Louis↗
NASA NTRS1995

Utilization of UARS Data in Validation of Photochemical and Dynamical Mechanism in Stratospheric Models

UARS data sets provide global coverage for the distributions of trace gases, which gives us an excellent chance to utilize the data set for model-data intercomparison studies. In the past three months, we have been working on the comparisons of the UARS data between 1992 (a half year after the Pinatubo eruption) and 1993 (one and a half year after the eruption) in an attempt to see how the Pinatubo volcanic eruption may have impacted stratospheric chemistry.

Rodriquez, Jose M.↗
NASA NTRS2017

The Mars Science Laboratory Curiosity Rover Mastcam Instruments: Preflight and In-Flight Calibration, Validation, and Data Archiving

The NASA Curiosity rover Mast Camera (Mastcam) system is a pair of fixed-focal length, multispectral, color CCD imagers mounted approximately 2 m above the surface on the rover's remote sensing mast, along with associated electronics and an onboard calibration target. The left Mastcam (M-34) has a 34 mm focal length, an instantaneous field of view (IFOV) of 0.22 mrad, and a FOV of 20 deg × 15 deg over the full 1648 × 1200 pixel span of its Kodak KAI-2020 CCD. The right Mastcam (M-100) has a 100 mm focal length, an IFOV of 0.074 mrad, and a FOV of 6.8 deg × 5.1 deg using the same detector. The cameras are separated by 24.2 cm on the mast, allowing stereo images to be obtained at the resolution of the M-34 camera. Each camera has an eight-position filter wheel, enabling it to take Bayer pattern red, green, and blue (RGB) 'true color' images, multispectral images in nine additional bands spanning approximately 400-1100 nm, and images of the Sun in two colors through neutral density-coated filters. An associated Digital Electronics Assembly provides command and data interfaces to the rover, 8 Gb of image storage per camera, 11 bit to 8 bit companding, JPEG compression, and acquisition of high-definition video. Here we describe the preflight and in-flight calibration of Mastcam images, the ways that they are being archived in the NASA Planetary Data System, and the ways that calibration refinements are being developed as the investigation progresses on Mars. We also provide some examples of data sets and analyses that help to validate the accuracy and precision of the calibration.

MSL Mastcam; quantitative multispectral↗
NASA NTRS2010

Obtaining Valid Safety Data for Software Safety Measurement and Process Improvement

We report on a preliminary case study to examine software safety risk in the early design phase of the NASA Constellation spaceflight program. Our goal is to provide NASA quality assurance managers with information regarding the ongoing state of software safety across the program. We examined 154 hazard reports created during the preliminary design phase of three major flight hardware systems within the Constellation program. Our purpose was two-fold: 1) to quantify the relative importance of software with respect to system safety; and 2) to identify potential risks due to incorrect application of the safety process, deficiencies in the safety process, or the lack of a defined process. One early outcome of this work was to show that there are structural deficiencies in collecting valid safety data that make software safety different from hardware safety. In our conclusions we present some of these deficiencies.

Basili, Victor r.↗
NASA NTRS2004

Validation and Analysis of SRTM and VCL Data Over Tropical Volcanoes

The focus of our investigation was on the application of digital topographic data in conducting first-order volcanological and structural studies of tropical volcanoes, focusing on the Java, the Philippines and the Galapagos Islands. Kilauea volcano, Hawaii, served as our test site for SRTM data validation. Volcanoes in humid tropical environments are frequently cloud covered, typically densely vegetated and erode rapidly, so that it was expected that new insights into the styles of eruption of these volcanoes could be obtained from analysis of topographic data. For instance, in certain parts of the world, such as Indonesia, even the regional structural context of volcanic centers is poorly known, and the distribution of volcanic products (e.g., lava flows, pyroclastic flows, and lahars) are not well mapped. SRTM and Vegetation Canopy Lidar (VCL) data were expected to provide new information on these volcanoes. Due to the cancellation of the VCL mission, we did not conduct any lidar studies during the duration of this project. Digital elevation models (DEMs) such as those collected by SRTM provide quantitative information about the time-integrated typical activity on a volcano and allow an assessment of the spatial and temporal contributions of various constructional and destructional processes to each volcano's present morphology. For basaltic volcanoes, P_c?w!m-d and Garbed (2000) have shown that gradual slopes (less than 5 deg.) occur where lava and tephra pond within calderas or in the saddles between adjacent volcanoes, as well as where lava deltas coalesce to form coastal plains. Vent concentration zones (axes of rift zones) have slopes ranging from 10 deg. to 12 deg. Differential vertical growth rates between vent concentration zones and adjacent mostly-lava flanks produce steep constructional slopes up to 40". The steepest slopes (locally approaching 90 deg.) are produced by fluvial erosion, caldera collapse, faulting, and catastrophic avalanches, all of which are usually identifiable. Due to the delay in the release of the SRTM data following the February 2000 flight, a significant part of our effort was devoted to the analog studies of the SRTM topographic data using topographic data from airborne interferometric radars. As part of the original SRTM Science Team, we proposed four study sites (Kilauea, Hawaii; Mt. Pinatubo, Philippines; Cerro Am1 and Femandina volcanoes, Galapagos Islands; and Tengger caldera, Java) where we could conduct detailed geologic studies to evaluate the uses of SRTM data for the analysis of lava flows, lahars, erosion of ash deposits, and an evaluation of the structural setting of the volcanoes. Only near the end of this project was one of these SRTM Science Team products (Luzon Island, the Philippines) released to the community, and we only had limited time to work on these data.

Mouginis-Mark, Peter J.↗
NASA NTRS1995

Utilization of UARS Data in Validation of Photochemical and Dynamical Mechanism in Stratospheric Models

We proposed model-data intercomparison studies for UARS data. In the past three months, we have been working on constructing analysis tools to diagnose the UARS data. The 'Trajectory mapping' technique, which was developed by Morris (1994), is adaptable to generate synoptic maps of trace gas data from asynoptic observations. An in-house trajectory model (kinematic methods following Merrill et al., 1986 and Pickering et al., 1994) has been developed in AER under contract with NASA/ACMAP and the trajectory mapping tool has been applied to analyze UARS measurement.

Rodriquez, Jose M.↗
NASA NTRS2020

TESS Data Release Notes: Sector 21 DR 29

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel les, light curve les, collateral pixel les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD)1. The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2017).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.

Michael M. Fausnaugh↗
NASA NTRS2016

Experience with Aero- and Fluid-Dynamic Testing for Engineering and CFD Validation

Ever since computations have been used to simulate aerodynamics the need to ensure that the computations adequately represent real life has followed. Many experiments have been performed specifically for validation and as computational methods have improved, so have the validation experiments. Validation is also a moving target because computational methods improve requiring validation for the new aspect of flow physics that the computations aim to capture. Concurrently, new measurement techniques are being developed that can help capture more detailed flow features pressure sensitive paint (PSP) and particle image velocimetry (PIV) come to mind. This paper will present various wind-tunnel tests the author has been involved with and how they were used for validation of various kinds of CFD. A particular focus is the application of advanced measurement techniques to flow fields (and geometries) that had proven to be difficult to predict computationally. Many of these difficult flow problems arose from engineering and development problems that needed to be solved for a particular vehicle or research program. In some cases the experiments required to solve the engineering problems were refined to provide valuable CFD validation data in addition to the primary engineering data. All of these experiments have provided physical insight and validation data for a wide range of aerodynamic and acoustic phenomena for vehicles ranging from tractor-trailers to crewed spacecraft.

experiment↗
NASA NTRS2020

TESS Data Release Notes: Sector 24, DR35

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel fi les, light curve fi les, collateral pixel fi les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml fi les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD). The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2019).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.

TESS↗
NASA NTRS2000

Flow Duct Data for Validation of Acoustic Liner Codes for Impedance Eduction

The objective of the study reported here was to acquire acoustic and flow data with hard and lined duct wall duct sections for validation of a liner prediction code being developed at NASA LaRC. Both the mean flowfield and acoustic flowfields were determined in a cross-plane of the rectangular duct. A flow duct facility with acoustic drivers connected to a rectangular (4.7 x 2.0 inch) source section and a linear acoustic liner mounted downstream of the source section was used in this study. The liner section was designed to allow liner materials to be placed on all 4 walls of the duct. The test liner was of the locally-reacting type and was made from a ceramic material. The material, consisting of a tubular structure, was provided by NASA LaRC. The liner was approximately 8.89 cm (3.5 inches) thick. For the current study, only the two "short" sides of the duct were lined with liner material. The other two sides were hard walls. Two especially built instrumentation sections were attached on either sides of the liner section to allow acoustic and flow measurements to be made upstream and downstream of the liner. The two instrumentation duct sections were built to allow measurement of acoustic and flow properties at planes perpendicular to flow upstream and downstream of the liner section. The instrumentation section was also designed to provide a streamwise gradient in acoustic (complex) pressure from which the acoustic particle velocity, needed for the model validation, can be computed. Flow measurements included pressure, temperature, and velocity profiles upstream of the liner section. The in-flow sound pressure levels and phases were obtained with a microphone probe equipped with a nose cone in two cross planes upstream of the liner and two cross plane downstream of the liner. In addition to the acoustic measurements at the cross planes. axial centerline acoustic data was acquired using an axially traversing microphone probe which was traversed from a location upstream of the liner to some distance downstream of the liner. All probes used here had to be calibrated with respect to a standard microphone equipped with a nose cone to allow for the effects of flow.

Ahuja, K. K.↗
NASA NTRS2017

Assessment of NASA Airborne Laser Altimetry Data Using Ground-Based GPS Data near Summit Station, Greenland

A series of NASA airborne lidars have been used in support of satellite laser altimetry missions. These airbornelaser altimeters have been deployed for satellite instrument development, for spaceborne data validation, and to bridge the data gap between satellite missions. We used data from ground-based Global Positioning System (GPS) surveys of an 11 km long track near Summit Station, Greenland, to assess the surface elevation bias and measurement precision of three airborne laser altimeters including the Airborne Topographic Mapper (ATM), the Land, Vegetation, and Ice Sensor (LVIS), and the Multiple Altimeter Beam Experimental Lidar (MABEL). Ground-based GPS data from the monthly ground-based traverses, which commenced in 2006, allowed for the assessment of nine airborne lidar surveys associated with ATM and LVIS between 2007 and 2016. Surface elevation biases for these altimeters over the flat, ice-sheet interior are less than 0.12 m, while assessments of measurement precision are 0.09 m or better. Ground-based GPS positions determined both with and without differential post-processing techniques provided internally consistent solutions. Results from the analyses of ground-based and airborne data provide validation strategy guidance for the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) elevation and elevation-change data products.

Summit Station↗