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NASA NTRS1977

Rocket exhaust effluent modeling for tropospheric air quality and environmental assessments

The various techniques for diffusion predictions to support air quality predictions and environmental assessments for aerospace applications are discussed in terms of limitations imposed by atmospheric data. This affords an introduction to the rationale behind the selection of the National Aeronautics and Space Administration (NASA)/Marshall Space Flight Center (MSFC) Rocket Exhaust Effluent Diffusion (REED) program. The models utilized in the NASA/MSFC REED program are explained. This program is then evaluated in terms of some results from a joint MSFC/Langley Research Center/Kennedy Space Center Titan Exhaust Effluent Prediction and Monitoring Program.

Stephens, J. B.↗

NASA NTRS2010

Examples L-Band Interference will be Presented and Discussed, as well as the Importance of L-Band Soil Moisture Observations

Examples of L-band interference will be presented and discussed, as well as the importance of L-band soil moisture observations, as part of this one-day GEOSS workshop XXXVII on "Data Quality and Radio Spectrum Allocation Impact on Earth Observations" will address the broad challenges of data quality and the impact of generating reliable information for decision makers who are Earth data users but not necessarily experts in the Earth observation field. GEO has initiated a data quality assessment task (DA-09-01a) and workshop users will review and debate the directions and challenges of this effort. Radio spectrum allocation is an element of data availability and data quality, and is also associated with a GEO task (AR-06-11). A recent U.S. National Research Council report on spectrum management will be addressed as part of the workshop. Key representatives from industry, academia, and government will provide invited talks on these and related issues that impact GEOSS implementation.

Kim, Edward↗

DOE OSTI2025

Common practices for quantifying methane emissions from plumes detected by remote sensing

This document provides a set of community-accepted practices for quantifying methane emissions based on plumes detected via spectroscopic remote sensing. Its primary goal is to promote consistency in the generation, validation, reporting, and quality assessment of methane emission estimates derived from remote sensing radiances. Developed by subject matter experts with deep experience across all stages of the measurement process, this guidance reflects a critical evaluation of current methodologies and highlights key practices needed to produce reliable, interoperable, and traceable products. The focus is specifically on methane emissions quantified from distinct plumes originating from localized sources, rather than diffuse emissions spread over large regions, which are beyond the scope of this work. This document is intended to serve both data producers and users. For producers, it offers a framework for aligning with field-recognized standards to ensure their outputs meet rigorous quality and transparency criteria. For users, it provides a reference to assess dataset fitness-for-purpose by highlighting essential metadata, assumptions, and methodological choices that underpin emission estimates. By fostering a shared understanding of best practices, this work aims to enhance comparability, confidence, and utility of remotely sensed methane emission products.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

Ninth Annual NASA/Contractors Conference on Quality and Productivity. World Class Excellence: The Journey Continues. Conference presentations

The topics covered include the following: The George M. Low Trophy; total quality assessment and measurement; using award criteria to improve organizational effectiveness; results--keeping an eye on the bottom line; capturing customer satisfaction; moving from management to leadership; leadership versus management; transforming the management team; leadership success stories; success stories in the quest for excellence; small business successes; education success stories; government success stories; tools and techniques for total quality management (TQM) integration; planning and organizing for TQM integration; successful stories for implementing system level TQM/CI tools; assessing TQM results; establishing an environment for continuous improvement at NASA; empowerment; synergism of partnering; and partnerships in education.

Templeton, Geoffrey B.↗

NASA NTRS2012

Assess Calibration Consistency of MODIS and AVHRR Thermal Infrared Bands Using SNO Observations Corrected for Atmospheric Effects

Monitoring environmental changes from space requires extremely well-calibrated observations to achieve the necessary high accuracy and stability. The calibration differences between the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High Resolution Radiometer (AVHRR) thermal bands provide a valuable quality assessment of the instrument performance. This letter compares the calibration differences between the Aqua MODIS and NOAA-18 AVHRR bands at 11.0 and 12.0 /Lm using simultaneous nadir overpass observations obtained in nearly parallel orbits. Impacts due to the relative spectral-response differences between the two sensors are estimated by MODTRAN simulations with real-time atmospheric profiles of temperature, water vapor, atmospheric pressure and ozone, and surface skin temperatures. Results show that the temperature difference after the removal of atmospheric impacts is within 0.30 K (or 0.40% in radiance) across the effective calibration range (or the 1l.0 l'm band/channel. For the 12.0 pm band, the differences are OAO K (or 0.50%) at the typical radiance and up to 0.70 K (or 0.90%) close to the maximum radiance, indicating an excellent calibration consistency between MODIS and AVHRR for both bands.

Wu, Aisheng↗

NASA NTRS2004

6S Return Samples: Assessment of Air Quality in the International Space Station (ISS) Based on Solid Sorbent Air Sampler (SSAS) and Formaldehyde Monitoring Kit (FMK) Analyses

The toxicological assessments of SSAS and FMK analytical results are reported. Analytical methods have not changed from earlier reports. Surrogate standard recoveries from the SSAS tubes were 66-76% for 13C-acetone, 85-96% for fluorobenzene, and 73-89% for chlorobenzene. Post-flight flows were far below pre-flight flows and an investigation of the problem revealed that the reduced flow was caused by a leak at the interface of the pump inlet tube and the pump head. This resulted in degradation of pump efficiency. Further investigation showed that the problem occurred before the SSAS was operated on orbit and that use of the post-flight flows yielded consistent and useful results. Recoveries from formaldehyde control badges were 86 to 104%. The two general criteria used to assess air quality are the total-non-methane-volatile organic hydrocarbons (NMVOCs) and the total T-value (minus the CO2 and formaldehyde contributions). The T values will not be reported for these data due to the flow anomaly. Control of atmospheric alcohols is important to the water recovery system engineers, hence total alcohols (including acetone) are also shown for each sample. Octafluoropropane (OFP) is not efficiently trapped by the sorbents used in the SSAS. Because formaldehyde is quantified from sorbent badges, its concentration is also listed separately. These five indices of air quality are summarized.

James, John T.↗

NASA NTRSDate not supplied

Composites From in-Situ Consolidation Automated Fiber Placement of Thermoplastics for High-Rate Aircraft Manufacturing

The National Aeronautics and Space Administration (NASA) project Hi-Rate Composites Aircraft Manufacturing (HiCAM) aims to significantly increase commercial aircraft composite structures manufacturing rate. Thermoplastic composites offer attractive solutions to rapid manufacturing due to their ability to be formed and consolidated quickly. NASA has a particular interest in assessing composite structure manufacturing utilizing an in-situ consolidation automated fiber placement (AFP) of thermoplastics (ICAT) process employing current state-of-the-art laser heating systems. Three semi-crystalline polyaryletherketone (PAEK) thermoplastic tape materials were characterized to ascertain the ICAT process parameters. The required laser power settings were determined at Electroimpact, Inc., measuring material temperatures utilizing a forward looking infrared (FLIR) thermal imaging camera and thermocouples. The material temperature, tool temperature, and placement speed were varied for resulting consolidation quality assessment. The resulting temperature data were also utilized to calibrate thermal analysis models under development at NASA. The experimental temperature data confirmed analytical results. The quality of the resulting test panels was evaluated by both non-destructive evaluation as well as destructively by photo-microscopy. The effect on interlaminar strength was determined by short beam strength testing. Test results of carbon fiber laminates fabricated by ICAT using polyetheretherketone (PEEK), polyetherketoneketone (PEKK), and low-melt polyaryletherketone (LM-PAEK) at various placement temperatures and placement speeds are presented.

thermoplastic composites↗

NASA NTRSDate not supplied

Data Quality Challenges for Analysis Ready Data (ARD)

Data quality plays a critical role in research and applications. The Earth Science Information Partners (ESIP) Information Quality Cluster (IQC) defines four aspects of information quality: Science, Product, Stewardship, and Services. The ESIP IQC has become internationally recognized as an authoritative and responsive resource of information and guidance to data producers and distributors on how to implement data quality standards and best practices for their science data systems, datasets, and data/metadata dissemination services. In recent years, cloud computing environments have provided scale-up capabilities such as data archives and services, enabling interdisciplinary science and applications. More value-added products are expected from data service providers, including Analysis Ready Data (ARD). ARD refers to data that has been preprocessed into a form that allows immediate analysis by the end user, processed to a minimum set of requirements and provides interoperability over time and across multiple datasets. Once a dataset has been developed from its original form to produce ARD, what quality characteristics should the derived dataset or ARD possess? Also, is it safe to assume that the quality of the ARD is consistent with the quality of the source data, or are there special attributes to an ARD that would warrant a secondary, independent quality assessment? What provenance (also called “data lineage”) information needs to be included in ARD? It is important to answer these questions, especially given the ease of use of ARD, and the consequent temptation by users to trust ARD without understanding the limitations or possible variations in quality compared to the source data. In this presentation, we will discuss data quality challenges for ARD products and services and introduce IQC for participation.

data quality↗

NASA NTRS2003

Assessment of Air Quality in the International Space Station (ISS) and Space Shuttle Based on Samples Returned Aboard STS-ll1 (UF2) in June 2002

The toxicological assessments of grab sample canisters (GSCs) and 2 solid sorbent air samplers (SSASs) returned aboard STS-111 are reported. Analytical methods have not changed from earlier reports. Surrogate standard recoveries from the GSCs were 86-106% and 62% to 136 % from the SSASs; 2 tubes with low surrogate recoveries were not reported. Pressure tracking indicated no leaks in the canisters during analysis. Recoveries from lab and trip controls for formaldehyde analyses ranged from 87 to 96%. The two general criteria used to assess air quality are the total-non-methane-volatile organic hydrocarbons (NMVOCs) and the total T-value (minus the CO2 and formaldehyde contributions). Because of the inertness of Freon 218 (octafluoropropane, OFP), Its contribution to the NMVOC is subtracted and tabulated separately. Control of atmospheric alcohols is important to the water recovery system engineers, hence total alcohols (including acetone) are also shown for each sample. Because formaldehyde is quantified from sorbent badges, its concentration is listed separately. The table shows that the air quality in general was acceptable for crew respiration; however, certain values shown in bold require further explanation. The 1.05 T value on 2/28/02 was caused by an unusually high measurement ofhexamethylcyc1otrisiloxane (T value = 0.50), which is not a concern. The MPLM T value of 1.42 and the alcohol level of 7.5 mg/cu m were due to an overall polluted atmosphere, which was expected at first entry. The major T-value component was carbon monoxide at a contribution of 0.44 units. Since the crew was only exposed momentarily to the polluted atmosphere, no health effects are expected. The formaldehyde value of 0.060 mg/cu m found in the Lab sample from 3/27/02 is cause for concern because the Lab consistently shows higher concentrations of formaldehyde than the SM and occasionally the concentrations are above the acceptable guideline. Levels of OFP have remained low, suggesting that no further leaks of the SM air conditioner have occurred.

James, John T.↗

NASA NTRS2018

Snowex 2017 Community Snow Depth Measurements: A Quality-Controlled, Georeferenced Product

Snow depth was one of the core ground measurements required to validate remotely-sensed data collected during SnowEx Year 1, which occurred in Colorado. The use of a single, common protocol was fundamental to produce a community reference dataset of high quality. Most of the nearly 100 Grand Mesa and Senator Beck Basin SnowEx ground crew participants contributed to this crucial dataset during 6-25 February 2017. Snow depths were measured along ~300 m transects, whose locations were determined according to a random-stratified approach using snowfall and tree-density gradients. Two-person teams used snowmobiles, skis, or snowshoes to travel to staked transect locations and to conduct measurements. Depths were measured with a 1-cm incremented probe every 3 meters along transects. In shallow areas of Grand Mesa, depth measurements were also collected with GPS snow-depth probes (a.k.a. MagnaProbes) at ~1-m intervals. During summer 2017, all reference stake positions were surveyed with <10 cm accuracy to improve overall snow depth location accuracy. During the campaign, 193 transects were measured over three weeks at Grand Mesa and 40 were collected over two weeks in Senator Beck Basin, representing more than 27,000 depth values. Each day of the campaign depth measurements were written in waterproof field books and photographed by National Snow and Ice Data Center (NSIDC) participants. The data were later transcribed and prepared for extensive quality assessment and control. Common issues such as protocol errors (e.g., survey in reverse direction), notebook image issues (e.g., halo in the center of digitized picture), and data-entry errors (sloppy writing and transcription errors) were identified and fixed on a point-by-point basis. In addition, we strove to produce a georeferenced product of fine quality, so we calculated and interpolated coordinates for every depth measurement based on surveyed stakes and the number of measurements made per transect. The product has been submitted to NSIDC in csv format. To educate data users, we present the study design and processing steps that have improved the quality and usability of this product. Also, we will address measurement and design uncertainties, which are different in open vs. forest areas.

Brucker, L.↗

NASA NTRS2002

Assessment of Air Quality in the International Space Station (ISS) and Space Shuttle Based on Samples Returned Aboard STS-110 (ISS-8A) in April 2002

The toxicological assessment of grab sample canisters (GSCs) returned aboard STS-110 is reported. Analytical methods have not changed from earlier reports, and surrogate standard recoveries from the GSCs were 77-121%, with one exception. Pressure tracking indicated no leaks in the canisters. Recoveries from lab and trip controls for formaldehyde analyses ranged from 87 to 96%. The two general criteria used to assess air quality are the total-non-methane-volatile organic hydrocarbons (NMVOCs) and the total T-value (minus the CO2 and formaldehyde contributions). Because of the inertness of Freon 218 (octafluoropropane, OFP), its contribution to the NMVOC is subtracted and tabulated separately. Control of atmospheric alcohols is important to the water recovery system engineers, hence total alcohols are also shown for each sample. Because formaldehyde is quantified from sorbent badges, its concentration is listed separately. These five indices of air quality are summarized.

James, John T.↗

NASA NTRS2016

Assessment of SNPP VIIRS VIS NIR Radiometric Calibration Stability Using Aqua MODIS and Invariant Surface Targets

The first Visible Infrared Imaging Radiometer Suite (VIIRS) is onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. As a primary sensor, it collects imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans in the spectral regions from visible (VIS) to long-wave infrared. NASA's National Polar-orbiting Partnership (NPP) VIIRS Characterization Support Team has been actively involved in the VIIRS radiometric and geometric calibration to support its Science Team Principal Investigators for their independent quality assessment of VIIRS Environmental Data Records. This paper presents the performance assessment of the radiometric calibration stability of the VIIRS VIS and NIR spectral bands using measurements from SNPP VIIRS and Aqua MODIS simultaneous nadir overpasses and over the invariant surface targets at the Libya-4 desert and Antarctic Dome Concordia snow sites. The VIIRS sensor data records (SDRs) used in this paper are reprocessed by the NASA SNPP Land Product Evaluation and Analysis Tool Element. This paper shows that the reprocessed VIIRS SDRs have been consistently calibrated from the beginning of the mission, and the calibration stability is similar to or better than MODIS. Results from different approaches indicate that the calibrations of the VIIRS VIS and NIR spectral bands are maintained to be stable to within 1% over the first three-year mission. The absolute calibration differences between VIIRS and MODIS are within 2%, with an exception for the 0.865-m band, after correction of their spectral response differences.

Wu, Aisheng↗

NASA NTRS2003

STS-113/11A: Assessment of Air Quality in the International Space Station (ISS) and Space Shuttle Based on Samples Returned in December 2002 and in May 2003 aboard Soyuz 5

The toxicological assessments of grab sample canisters (GSCs) returned aboard STS-l13 and Soyuz 5 are reported. Analytical methods have not changed from earlier reports. Surrogate standard recoveries from the GSCs were 79-120% except as noted in the table. One sample was returned with the valve opened. The two general criteria used to assess air quality are the total-non-methane-volatile organic hydrocarbons (NMVOCs) and the total T-value (minus the CO2 and formaldehyde contributions). Control of atmospheric alcohols is important to the water recovery system engineers, hence total alcohols (including acetone) are also shown for each sample. Octafluoropropane (OFP) has leaked from heat-exchange units in large quantities, so its concentration is tracked separately. Because formaldehyde is quantified from sorbent badges, its concentration is also listed separately. The table shows that the air quality in general was acceptable for crew respiration through the middle of December 2002. No conclusions can be made about the air quality after that date due to NASA's inability to return air samples from the ISS . Alcohols are not being controlled to the recently lowered guideline of 5 mg/m3, which was recommended to protect the water recovery systems. The airlock sample was taken during the regeneration of Met ox canisters in the adjacent Node. The trace pollutants were not increased above background; however, inspection of table 1 in the appendix shows a CO2 concentration of 17,000 mg/cu m, which is a relatively high concentration, but still below the 24-hour SMAC of23,000 mg/cu m. The control of OFP continues to be adequate at least through December 2002. Formaldehyde concentrations suggest that the high levels that were being found in the Lab atmosphere have subsided. This is probably attributable to the restoration of IMV in early February 2003 . Before the obstructing material was removed from ducts the Lab formaldehyde concentrations approached 0.06 mg/cu m, whereas after the repair the levels were near 0.04 mg/m3 . This does not mean that local sources in the Lab have been reduced, only that the excess of formaldehyde produced in the Lab is distributed into the whole volume of the ISS.

James, John T.↗

NASA NTRS2002

A Study of Uncertainties for MODIS Cloud Retrievals of Optical Thickness and Effective Radius

The investigation spanned four linked components as summarized in section III, each relating to some aspect of uncertainty assessment in the retrieval of cloud optical and microphysical properties using solar reflectance algorithms such as the MODIS operational cloud product (product IDS MOD06, MDY06 for Terra and Aqua, respectively). As discussed, three of these components have been fully completed (items (l), (2), and (3) while item (4) has been partially completed. These efforts have resulted in peer-reviewed publications and/or information delivered to the MODIS P.I. (M. D. King) for inclusion in the cloud product Quality Assessment (QA) output, a portion of the product output used, in part, for retrieval error assignments. This final report begins with a synopsis of the proposed investigation (section III) followed by a summary of work performed up through the last report including updates (section IV). Section V describes new activities. Publications from the efforts are listed in section VI. Figures (available in powerpoint format) are found in section VII.

Platnick, Steven↗

DOE OSTI2025

Anomaly Detection in Seismic Data with Deep Learning: Application for Instrument Failure Detection and Forecasting

Seismic data quality assessment (QA) is the first and one of the most important steps before conducting any further data analysis. Traditional methods involve checking various metrics, such as spike detection and power spectral density, by setting strict thresholds or comparing data against synthetic benchmarks. However, these approaches often rely on pre-existing knowledge and assumptions about data anomalies, leading to potential misclassification of unusual cases. Here, in this study, we propose a deep autoencoder model, an unsupervised learning approach that evaluates data quality without making assumptions about normal and anomalous data, which can be used to identify deviations in recorded data that may indicate nascent instrument failure. We test the model with the U.S. International Monitoring System (IMS) seismic stations and demonstrate the capability of detecting anomalies on a monthly scale. This could prompt station operators to examine potential problems early, allowing sufficient time for instrument maintenance to prevent data outages. In addition, we use a new manually selected testing dataset to compare our model performance against two supervised machine learning (ML) approaches and a standard QA package, as baseline models. When applied to the dataset containing known data anomalies, performance of the supervised and unsupervised ML approaches is similar, with an accuracy of 88.1% for our model compared to ∼90% for the supervised ML approach and 78.2% for the standard QA package. Our model outperforms the baseline models when applied to new stations, where new types of data anomalies can be station-specific and not included in the training dataset. Finally, we show model transferability by training the model with data from the Global Seismograph Network only and applying it to the IMS network data. The results suggest that our model is generalizable and can be applied to new stations with good accuracy.

Lin, Jiun-Ting [Lawrence Livermore National Labora↗

NASA NTRSDate not supplied

In-Situ Consolidation Automated Fiber Placement of Thermoplastic Composites for High-Rate Aircraft Manufacturing

The National Aeronautics and Space Administration (NASA) initiated the Hi-Rate Composites Aircraft Manufacturing (HiCAM) project in 2021 with the goal of significantly increasing composite structures manufacturing rate in the commercial aircraft industry. The technologies currently under investigation include resin infusion and automated fiber placement (AFP) of novel thermoset materials and thermoplastic composites. Thermoplastic composites offer attractive solutions to rapid manufacturing due to their ability to be formed and consolidated quickly. NASA is particularly focused on assessing composite structure manufacturing utilizing an in-situ consolidation AFP of thermoplastics (ICAT) process employing a recently developed laser heating system. Two semi-crystalline polyaryletherketone thermoplastic tape materials were characterized to ascertain the ICAT process parameters at AFP placement speeds approaching 423 mm/s. The required laser power settings were determined at Electroimpact, measuring material temperatures utilizing a forward looking infrared (FLIR) thermal imaging camera and thermocouples. The material temperature, tool temperature, and placement speed were varied for resulting consolidation quality assessment. The resulting temperature data were also utilized to calibrate thermal analysis models under development at NASA. The experimental temperature data confirmed analytical results. An overview of the HiCAM project as well as initial data from ICAT process characterizations are described.

thermoplastic composites↗

NASA NTRS2022

In-Situ Consolidation Automated Fiber Placement of Thermoplastic Composites for High-Rate Aircraft Manufacturing

laser heating↗

NASA NTRS2008

Provenance in Data Interoperability for Multi-Sensor Intercomparison

As our inventory of Earth science data sets grows, the ability to compare, merge and fuse multiple datasets grows in importance. This requires a deeper data interoperability than we have now. Efforts such as Open Geospatial Consortium and OPeNDAP (Open-source Project for a Network Data Access Protocol) have broken down format barriers to interoperability; the next challenge is the semantic aspects of the data. Consider the issues when satellite data are merged, cross-calibrated, validated, inter-compared and fused. We must match up data sets that are related, yet different in significant ways: the phenomenon being measured, measurement technique, location in space-time or quality of the measurements. If subtle distinctions between similar measurements are not clear to the user, results can be meaningless or lead to an incorrect interpretation of the data. Most of these distinctions trace to how the data came to be: sensors, processing and quality assessment. For example, monthly averages of satellite-based aerosol measurements often show significant discrepancies, which might be due to differences in spatio- temporal aggregation, sampling issues, sensor biases, algorithm differences or calibration issues. Provenance information must be captured in a semantic framework that allows data inter-use tools to incorporate it and aid in the intervention of comparison or merged products. Semantic web technology allows us to encode our knowledge of measurement characteristics, phenomena measured, space-time representation, and data quality attributes in a well-structured, machine-readable ontology and rulesets. An analysis tool can use this knowledge to show users the provenance-related distrintions between two variables, advising on options for further data processing and analysis. An additional problem for workflows distributed across heterogeneous systems is retrieval and transport of provenance. Provenance may be either embedded within the data payload, or transmitted from server to client in an out-of-band mechanism. The out of band mechanism is more flexible in the richness of provenance information that can be accomodated, but it relies on a persistent framework and can be difficult for legacy clients to use. We are prototyping the embedded model, incorporating provenance within metadata objects in the data payload. Thus, it always remains with the data. The downside is a limit to the size of provenance metadata that we can include, an issue that will eventually need resolution to encompass the richness of provenance information required for daata intercomparison and merging.

Lynnes, Chris↗