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NASA NTRSDate not supplied

Planetary Protection at Marshall Space Flight Center

Introduction: NASA Marshall Space Flight Center (MSFC) is historically known for its role in propulsion. While this is still the mainstay of MSFC’s expertise, many unique capabilities exist at MSFC which pertain to Planetary Protection (PP), including 1) identifying PP threats, and 2) developing novel methods to neutralize those threats. Furthermore, because these capabilities exist among diverse groups at MSFC, this work promotes collaboration both within and outside MSFC to expand and develop PP studies related to a full spectrum of NASA research, design, manufacture, and test interests. This abstract describes the PP research ongoing at MSFC and describes how it contributes to NASA’s overall PP objectives. Microbial Identification in Cleanrooms: One of the greatest threats to successful implementation of PP requirements is recontamination post bioburden reduction. One method to prevent recontamination is to keep the spacecraft in clean environments (i.e. cleanrooms) as much as possible during assembly and integration. However, cleanrooms are not without their own sources of contamination, which is why NASA is interested in monitoring the cleanliness of cleanrooms and characterizing the microbial species present. Such information allows a greater understanding of the resistance of these microbes to cleaning methods, as well as the risk of their contaminating the targeted planetary body of a given mission. MSFC has multiple cleanrooms of various ISO cleanliness levels onsite. We sampled the air and surfaces of three of these rooms, isolated microbes, and then sequenced the 16S rRNA gene or ITS region of the 18S rRNA gene for bacterial and fungal isolates, respectively. This has resulted in a microbial library which currently includes nearly 100 isolates. Microbial Enumeration of Spacecraft Materials: Currently, there are only a couple bioburden reduction methods approved by NASA, and often the harshness of these methods presents additional concerns or risks related to material properties. The goal of this research is to assess the microbial content of solid rocket motor (SRM) materials potentially used for lander missions. This work aims to more accurately define the risk of planetary contamination by providing empirical data associated with commonly used SRM raw materials. In this study, we pulverized nonmetallic SRM materials using a cryogenic grinder, then analyzed the resulting substrate for microbial colony forming units (CFU). We found that many SRM nonmetallic materials do not harbor detectable bioburden, though a range existed depending on the material. The results from this work provide quantitative data to potentially reduce concerns of contamination, while also providing a foundation for follow up studies into additional sterilization methods and molecular identification of contaminating microbes. Space Environmental Effects on Microbial Survival: One potential area of microbial reduction is the space environment. Understanding the survivability of hardy microbes in space-like conditions is a crucial first step in answering how space may reduce bioburden and if it can be relied upon for adherence to PP requirements. This work studied the effects of ultraviolet (UV) and ionizing radiation on survival of Bacillus atrophaeus spores. Microbes were dried on relevant polymeric materials then exposed to space environmental stressors. Coupons were submerged in water, diluted, and plated to determine survival compared with controls. We found that both UV and ionizing radiation were capable of reducing viability by nearly 99%, but there were still survivors, some with changed morphology indicating resistance mechanisms within certain cells. Manufacturing credit: Finally, given the above-mentioned limitations of the NASA-approved bioburden reduction methods, there is interest in understanding if manufacturing processes may provide enough bioburden reduction without additional PP-specific bakeouts. For instance, some material additives may be antimicrobial. Given this, we investigated the effects of several commonly used rubber additives on the growth of B. atrophaeus spores. We found that some of the materials inhibited growth of the spores, possibly supporting the use of these additives on missions with PP constraints. Future work into manufacturing credit for bioburden reduction includes inoculation of green insulation with B. atrophaeus spores, followed by a typical cure. Thermal profiles will be verified for appropriate temperature and durations to meet PP requirements, and cured samples will be analyzed using a cryogenic grinder to determine survivability of spores.

Chelsi D. Cassilly↗

NASA NTRS1998

An Experimental Investigation of Transverse Tension Fatigue Characterization of IM6/3501-6 Composite Materials Using a Three-Point Bend Test

As composites are introduced into more complex structures with out-of-plane loadings, a better understanding is needed of the out-of-plane, matrix-dominated failure mechanisms. This work investigates the transverse tension fatigue characteristics of IM6/3501 composite materials. To test the 90 degree laminae, a three-point bend test was chosen, potentially minimizing handling and gripping issues associated with tension tests. A finite element analysis was performed of a particular specimen configuration to investigate the influence of specimen size on the stress distribution for a three-point bend test. Static testing of 50 specimens of 9 different sized configurations produced a mean transverse tensile strength of 61.3 Mpa (8.0 ksi). The smallest configuration (10.2 mm wide, Span-to-thickness ratio of 3) consistently exhibited transverse tensile failures. A volume scale effect was difficult to discern due to the large scatter of the data. Static testing of 10 different specimens taken from a second panel produced a mean transverse tensile strength of 82.7 Mpa (12.0 ksi). Weibull parameterization of the data was possible, but due to variability in raw material and/or manufacturing, more replicates are needed for greater confidence. Three-point flex fatigue testing of the smallest configuration was performed on 59 specimens at various levels of the mean static transverse tensile strength using an R ratio of 0.1 and a frequency of 20 Hz. A great deal of scatter was seen in the data. The majority of specimens failed near the center loading roller. To determine whether the scatter in the fatigue data is due to variability in raw material and/or the manufacturing process, additional testing should be performed on panels manufactured from different sources.

Peck, Ann W.↗

NASA NTRSDate not supplied

The NASA Open Science Data Repository: Biomedical Fair Data, Analysis Tools, User Communities, Publications, and Discoveries for Deep Space Missions

Increased biomedical risks and challenges associated with deep space missions require new knowledge discovery, new health countermeasures, and development of novel ecosystems, life support, crop production, and biomedical support capabilities. To meet NASA’s Moon to Mars strategic program goals for Human and Biological Sciences, findable, accessible, interoperable, reusable (FAIR), and maximally open-access data is going to be required to enable humanity to thrive in deep space. Indeed, this cornerstone perspective on FAIR and maximally open access data was also recommended in the recent 2023-2032 Decadal Survey from the National Academies of Sciences, Engineering, and Medicine. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database, and meets various scientific, technical, and operational spaceflight needs. It offers public users and submitters the ability to upload, download, search, share, analyze, and visualize data across ‘omics, physiological, phenotypic, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive, and the NASA Biological Institutional Scientific Collection. OSDR has >455 studies with datasets from model organisms and non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets have raw FASTQ and FASTA files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) which was developed based on industry norms. OSDR also recently began a collaboration with the European Space Agency (ESA) to scientifically curate and make available >200 terabytes of human and model organism space-relevant data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics assay data types, and ~50 physiological-phenotypic-imaging assay data types, spanning ultrasonography, micro-computed tomography, histology, morphometric photography, rebound tonometry, gait analysis, optical coherence tomography, novel object recognition, flow cytometry, and immunohistochemistry. A suite of analysis tools are available for OSDR users including: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, which compiles radiation measurements relevant to human spaceflight and provides tools for accessing and manipulating the data, and 3) a Multi-study visualization tool which enables users to look across and combine GeneLab’s omics datasets across different experiments and missions. There are ~600 volunteer OSDR Analysis Working Group (AWG) members who: 1) provide feedback on scientific standards for reuse (subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability), and 2) collaborate to mine-reuse OSDR data conducting scientific analysis. OSDR has enabled 60 publications as of September 2023, many directly from AWG collaborations most notably the Cell Press package in 2020. Lastly, there are at least 15 articles which mine OSDR data part of a package of ~50 articles across Nature Portfolio with research stemming from I4, the Japan Aerospace Exploration Agency, NASA Space Biology, and the NASA Human Research Program.

space biology↗

NASA NTRSDate not supplied

NASA Open Science Data Repository: Biomedical FAIR Data, Analysis Tools, User Communities, and Discoveries for Deep Space Missions

open access↗

NASA NTRS1978

Flying-hot-wire study of two-dimensional mean flow past an NACA 4412 airfoil at maximum lift

Hot-wire measurements have been made in the boundary layer, the separated region, and the near wake for flow past an NACA 4412 airfoil at maximum lift. The Reynolds number based on chord was about 1,500,000. The main instrumentation was a hot-wire probe mounted on the end of a rotating arm. A digital computer was used to control synchronized sampling of hot-wire data at closely spaced points along the probe arc. Ensembles of data were obtained at several thousand locations in the flow field. The data include intermittency, two components of mean velocity, and twelve mean values for double, triple, and quadruple products of two velocity fluctuations. The data are available on punched cards in raw form and also after use of smoothing and interpolation routines to obtain values on a fine rectangular grid aligned with the airfoil chord. The data are displayed in the paper as contour plots.

Coles, D.↗

NASA NTRS2003

A Treatment of Measurements of Heptane Droplet Combustion Aboard MSL-1

Results of measurements on the burning of free n-heptane droplets (that is, droplets without fiber supports) performed in Spacelab during the flights of the first Microgravity Science Laboratory (MSL-1) are presented. The droplet combustion occurred in oxidizing atmospheres which were at an ambient temperature within a few degrees of 300 K. A total of 34 droplets were burned in helium-oxygen atmospheres having oxygen mole fractions ranging from 20 to 50 percent, at pressures from 0.25 to 1.00 bar. In addition, four droplets were burned in air at 1.00 bar, bringing the total number of droplets for which combustion data were secured to 38; two of these four air tests were fiber-supported to facilitate comparisons with other fiber-support experiments, results of which also are given here. Initial diameters of free droplets ranged from about 1 to 4 mm. The primary data obtained were histories of droplet diameters, recorded in backlight on 35 mm film at 80 frames per second, and histories of flame diameters, inferred from emissions through a narrow-band interference filter centered at the 310 micron OH chemiluminescent ultraviolet band, recorded at 30 frames per second by a intensified-array camera. These data are reported here both in raw form and in a smoothed form with estimated error bars. In addition, summaries are presented of measured burning-rate constants, final droplet diameters, and final flame diameters. Both diffusive and radiative extinctions were exhibited under different conditions. Although some interpretations are reported and conclusions drawn concerning the combustion mechanisms, the principal intent of this report is to provide a complete, documented data set for future analysis.

Ackerman, M. D.↗

NASA NTRS2012

NASA IMAGESEER: NASA IMAGEs for Science, Education, Experimentation and Research

A number of web-accessible databases, including medical, military or other image data, offer universities and other users the ability to teach or research new Image Processing techniques on relevant and well-documented data. However, NASA images have traditionally been difficult for researchers to find, are often only available in hard-to-use formats, and do not always provide sufficient context and background for a non-NASA Scientist user to understand their content. The new IMAGESEER (IMAGEs for Science, Education, Experimentation and Research) database seeks to address these issues. Through a graphically-rich web site for browsing and downloading all of the selected datasets, benchmarks, and tutorials, IMAGESEER provides a widely accessible database of NASA-centric, easy to read, image data for teaching or validating new Image Processing algorithms. As such, IMAGESEER fosters collaboration between NASA and research organizations while simultaneously encouraging development of new and enhanced Image Processing algorithms. The first prototype includes a representative sampling of NASA multispectral and hyperspectral images from several Earth Science instruments, along with a few small tutorials. Image processing techniques are currently represented with cloud detection, image registration, and map cover/classification. For each technique, corresponding data are selected from four different geographic regions, i.e., mountains, urban, water coastal, and agriculture areas. Satellite images have been collected from several instruments - Landsat-5 and -7 Thematic Mappers, Earth Observing-1 (EO-1) Advanced Land Imager (ALI) and Hyperion, and the Moderate Resolution Imaging Spectroradiometer (MODIS). After geo-registration, these images are available in simple common formats such as GeoTIFF and raw formats, along with associated benchmark data.

Le Moigne, Jacqueline↗

NASA NTRSDate not supplied

Nearest-Neighbor Machine Learning Feature Selection for Interpretation of Microbial Molecular Signatures from Isotope Ratio Mass Spectrometry Data

Mass spectrometry (MS) promises to be a powerful tool for potential biosignature detection during astrobiological missions on ocean worlds in our solar system. Accurate and generalizable machine learning methods could enhance science return on investment by predicting seawater chemistry and classifying isotopic biosignatures, either as a signature consistent with microbial life (biotic) or as a novelty (unclassified/unique). However, machine learning models are likely to be complex and involve interactions between MS features, making biosignatures difficult to interpret. Feature selection methods provide biological and chemical context that help interpret the mechanisms of machine learning models, but these methods also need the ability to detect complex interactions. Previously, we developed a machine learning feature selection algorithm called nearest-neighbor projected distance regression (NPDR) that has the ability to identify important model features that involve complex interactions and automatically reduce correlation and the dimensionality in a high-dimensional variable space. The standard distance metrics used in NPDR – Manhattan and Euclidean – assume the multivariate data are isotropic, which is often violated in real data due to differences in the covariance between variables. Thus, we extend NPDR to include a random forest distance, and other anisotropic distance metrics, for computing nearest neighbors. We also augment the isotope-ratio MS data with time-series features from the raw MS signal to improve biotic classification. We test NPDR on our novel experimental ocean world seawater analog MS data. We measure isotope fractionations of volatile CO 2 that could be measured in exospheres or plumes. Samples include baseline abiotic conditions using a range of possible seawater chemistry consistent with Europa and Enceladus, and biotic samples that include microbes in these seawaters. We use penalized NPDR with random forest proximity to identify interpretable microbial molecular signatures. We compare features with random forest importance, and we train a classifier that discriminates between biotic and abiotic samples with high accuracy. These ML-trained ocean-world analog MS data could be used to assist in identifying biosignatures during future missions.

geochemistry↗

NASA NTRS2005

Investigation of Solar Radiation Properties at the Battleship Promontory Area, Antarctica

JPL scientists in January 2005 visited the unique Battleship Promontory Area of the Antarctic Dry Valleys at 76 deg. 54 min. S one of the few places on the Antarctic continent home to viable life. Cryptoendolithic microorganisms manage to survive on and inside rocks in Antarctica's harsh conditions of extreme dryness and cold that are not So different from the past and present conditions on Mars. We are investigating the physical properties of these biological creatures through analysis of optical spectra collected from a variety of rock samples over the deep UV, visible, and near-infrared regions with the intent of gaining key insights into the environmental factors that make such a habitat viable for life. The LabView programming environment is equipped with the tools necessary to create an interface to visualize, manipulate, and normalize extensive raw reflectance and corresponding incident spectral data. We are determining the meaning of the colors observed and their relationship to the ability to acquire energy and investigating differences between the photosynthetic processes in full sunlight and diffuse/shadow lighting. Comparisons between spectral data collected in the field and from returned samples in the lab validate the accuracy of our field collection methodology.

VanNortwick, Sara S.↗

NASA NTRS2014

Design and Development of the SMAP Microwave Radiometer Electronics

The SMAP microwave radiometer will measure land surface brightness temperature at L-band (1413 MHz) in the presence of radio frequency interference (RFI) for soil moisture remote sensing. The radiometer design was driven by the requirements to incorporate internal calibration, to operate synchronously with the SMAP radar, and to mitigate the deleterious effects of RFI. The system design includes a highly linear super-heterodyne microwave receiver with internal reference loads and noise sources for calibration and an innovative digital signal processor and detection system. The front-end comprises a coaxial cable-based feed network, with a pair of diplexers and a coupled noise source, and radiometer front-end (RFE) box. Internal calibration is provided by reference switches and a common noise source inside the RFE. The RF back-end (RBE) downconverts the 1413 MHz channel to an intermediate frequency (IF) of 120 MHz. The IF signals are then sampled and quantized by high-speed analog-to-digital converters in the radiometer digital electronics (RDE) box. The RBE local oscillator and RDE sampling clocks are phase-locked to a common reference to ensure coherency between the signals. The RDE performs additional filtering, sub-band channelization, cross-correlation for measuring third and fourth Stokes parameters, and detection and integration of the first four raw moments of the signals. These data are packetized and sent to the ground for calibration and further processing. Here we discuss the novel features of the radiometer hardware particularly those influenced by the need to mitigate RFI.

radio frequency interference↗

NASA NTRS1998

Feature Extraction of Event-Related Potentials Using Wavelets: An Application to Human Performance Monitoring

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many f ree parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation,-, algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance.

Trejo, Leonard J.↗

NASA NTRS1999

Feature extraction of event-related potentials using wavelets: an application to human performance monitoring

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many free parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance. Copyright 1999 Academic Press.

Evoked Potentials↗

NASA NTRS2017

A Trilateration Scheme for Relative Positioning

We introduce a trilateration scheme that evaluates the 3-dimensional (3-D) relative position between a reference spacecraft and a target spacecraft using raw-range measurements from a distance baseline of known locations, which we call “anchors”. The anchors can be antennas of a ground-based network (e.g., Deep Space Network (DSN) or Near Earth Network (NEN) stations), or satellites of a spacebased network (e.g., global positioning system (GPS) or tracking and data relay satellite (TDRS)). We define raw-range as the range that includes all the systematic errors that occur during range measurements. A unique feature of this approach is that accurate relative position is derived from a “differencing function” of raw-range measurements of the reference spacecraft and target spacecraft, thereby eliminating most of the systematic errors, such as media effects, ephemeris errors, instrument delays, clock bias, etc. There can be an arbitrary number of target spacecraft, and relative positioning of target spacecraft with respect to the reference spacecraft can be done simultaneously. In this paper, we first assume an idealized system in which clocks on the reference and target spacecraft are synchronized, with clocks of the anchors synchronized as well. We develop a novel iterative algorithm that computes the relative position of the target spacecraft with respect to the reference spacecraft. We illustrate the relative positioning method using the scenario of a network of three ground stations (i.e., the anchors) at Goldstone, California, USA, Madrid, Spain, and Marlargue, Argentina tracking two spacecraft at geosynchronous orbit distance. We demonstrate that the algorithm converges to submeter accuracy in estimating the relative position, in the presence of random errors and systematic errors in raw-range measurements, and in the presence of angular errors in estimating the pointing vectors between the anchors and the reference spacecraft. Next, we relax the requirement of perfect time synchronization between spacecraft, and show that by using an additional anchor, one can estimate and remove the clock biases between the reference and target spacecraft. We add a ground station at Kourou to the above example of three ground stations of Goldstone, Madrid, and Marlargue, and demonstrate that the updated algorithm also converges to meter-level accuracy (submeter in some cases) in the presence of clock biases in addition to the random errors, systematic errors, and angular errors as shown in the above case. We compare this scheme with a similar trilateration scheme for relative positioning scheme first proposed by Montenbruck in 2002.

Cheung, Kar-Ming↗

NASA NTRS2021

Scaling photosynthetic function and CO2 dynamics from leaf to canopy level for maize – dataset combining diurnal and seasonal measurements of vegetation fluorescence, reflectance and vegetation indices with canopy gross ecosystem productivity

Recent advances in leaf fluorescence measurements and canopy proximal remote sensing currently enable the non-destructive collection of rich diurnal and seasonal time series, which are required for monitoring vegetation function at the temporal and spatial scales relevant to the natural dynamics of photosynthesis. Remote sensing assessments of vegetation function have traditionally used actively excited foliar chlorophyll fluorescence measurements, canopy optical reflectance data and vegetation indices (VIs), and only recently passive solar induced chlorophyll fluorescence (SIF) measurements. In general, reflectance data are more sensitive to the seasonal variations in canopy chlorophyll content and foliar biomass, while fluorescence observations more closely relate to the dynamic changes in plant photosynthetic function. With this dataset we link leaf level actively excited chlorophyll fluorescence, canopy proximal reflectance and SIF, with eddy covariance measurements of gross ecosystem productivity (GEP). The dataset was collected during the 2017 growing season on maize, using three automated systems (i.e., Monitoring Pulse-Amplitude-Modulation fluorimeter, Moni-PAM; Fluorescence Box, FloX; and from eddy covariance tower). The data were quality checked, filtered and collated to a common 30 minutes timestep. We derived vegetation indices related to canopy functioning (e.g., Photochemical Reflectance Index, PRI; Normalized Difference Vegetation Index, NDVI; Chlorophyll Red-edge, Clre) to investigate how SIF and VIs can be coupled for monitoring vegetation photosynthesis. The raw datasets and the filtered and collated data are provided to enable new processing and analyses.

Petya Campbell↗

NASA NTRS1978

Large-scale Gulf Stream frontal study using GEOS 3 radar altimeter data

From data obtained by the GEOS 3 radar altimeter, sea surface heights are found by both editing and filtering the raw sea surface height measurements and then referencing these processed data to a 5 foot by 5 foot geoid. Any trend between the processed data and the geoid is removed by subtracting out a linear fit to the residuals in the open ocean. Data from individual passes are further processed by applying a minimum variance technique at the subsatellite crossing points to produce surface topography maps for the 6 months and an overall mean map which reveal important details about the Gulf Stream system. The differences between the monthly mean and the overall mean are calculated for each of the 6 months to show the temporal and spatial changes of the Gulf Stream front and spawned eddies. The standard deviation map is even more informative and shows preferred locations of Gulf Stream meanders.

Huang, N. E.↗

NASA NTRS2010

Presearch Data Conditioning in the Kepler Science Operations Center Pipeline

We describe the Presearch Data Conditioning (PDC) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this component are to correct systematic and other errors, remove excess flux due to aperture crowding, and condition the raw flux light curves for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) targets across the focal plane array. Long cadence corrected flux light curves are subjected to a transiting planet search in a subsequent pipeline module. We discuss the science algorithms for long and short cadence PDC: identification and correction of unexplained (i.e., unrelated to known anomalies) discontinuities; systematic error correction; and excess flux removal. We discuss the propagation of uncertainties from raw to corrected flux. Finally, we present examples of raw and corrected flux time series for flight data to illustrate PDC performance. Corrected flux light curves produced by PDC are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and will be made available to the general public in accordance with the NASA/Kepler data release policy.

Twicken, Joseph D.↗

NASA NTRS2018

Displaying multiple data types in the GeoGateway Public Mapping System: including a system for rapid surface fracture detection in raw and unwrapped radar interferograms

UNKNOWN

Wang, Jun↗

NASA NTRS1977

The vehicle design evaluation program - A computer-aided design procedure for transport aircraft

The vehicle design evaluation program is described. This program is a computer-aided design procedure that provides a vehicle synthesis capability for vehicle sizing, external load analysis, structural analysis, and cost evaluation. The vehicle sizing subprogram provides geometry, weight, and balance data for aircraft using JP, hydrogen, or methane fuels. The structural synthesis subprogram uses a multistation analysis for aerodynamic surfaces and fuselages to develop theoretical weights and geometric dimensions. The parts definition subprogram uses the geometric data from the structural analysis and develops the predicted fabrication dimensions, parts material raw stock buy requirements, and predicted actual weights. The cost analysis subprogram uses detail part data in conjunction with standard hours, realization factors, labor rates, and material data to develop the manufacturing costs. The program is used to evaluate overall design effects on subsonic commercial type aircraft due to parameter variations.

Oman, B. H.↗