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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 109 records · Page 6

Pollutant emissions from flat-flame burners at high pressures

Maximum flame temperatures and pollutant emission measurements for NOx, CO, and UHC (unburned hydrocarbons) are reported for premixed methane air flat flames at constant total mass flow rate over the pressure range from 1.9 to 30 atm and for equivalence ratios from 0.84 to 1.12. For any given pressure, maxima typically occur in both the temperature and NOx emissions curves slightly to the lean side of stoichiometric conditions. The UHC emissions show minima at roughly the same equivalence ratios. The CO emissions, however, increase continually with increasing equivalence ratio. Flame temperature and NOx emissions decrease with increasing pressure, while the opposite is true for the CO and UHC emissions. The NOx data correlate reasonably well as a function of flame temperature only. Four flameholders, differing only slightly, were used. In general, the temperature and emissions data from these four flameholders are similar, but some differences also exist. These differences appear to be related to minor variations in the condition of the flameholder surfaces.

Maahs, H. G.↗

Optical data transmission technology for fixed and drag-on STS payloads umbilicals. Volume 1: Executive summary

The feasibility of using optical data handling methods to transmit payload checkout and telemetry is discussed. Optical communications are superior to conventional communication systems for the following reasons: high data capacity optical channels; small and light weight optical cables; and optical signal immunity to electromagnetic interference. Task number one analyzed the ground checkout data requirements that may be expected from the payload community. Task number two selected the optical approach based on the interface requirements, the location of the interface, the amount of time required to reconfigure hardware, and the method of transporting the optical signal. Task number three surveyed and selected optical components for the two payload data link. Task number four makes a qualitative comparison of the conventional electrical communication system and the proposed optical communication system.

St.denis, R. W.↗

Search for an Anomalous Production of Charged-Current 𝜈 𝑒 Interactions without Visible Pions across Multiple Kinematic Observables in MicroBooNE

This Letter presents an investigation of low-energy electron-neutrino interactions in the Fermilab Booster Neutrino Beam by the MicroBooNE experiment, motivated by the excess of electron-neutrino-like events observed by the MiniBooNE experiment. This is the first measurement to use data from all five years of operation of the MicroBooNE experiment, corresponding to an exposure of 1.11 × 10 21 protons on target, a 70% increase on past results. Two samples of electron neutrino interactions without visible pions are used, one with visible protons and one without any visible protons. The MicroBooNE data show reasonable agreement with the nominal prediction, with 𝑝 values ≥26.7% when the two 𝜈 𝑒 samples are combined, though the prediction exceeds the data in limited regions of phase space. The data are further compared to two empirical models that modify the predicted rate of electron-neutrino interactions in different variables in the simulation to match the unfolded MiniBooNE low energy excess. In the first model, this unfolding is performed as a function of electron neutrino energy, while the second model aims to match the observed shower energy and angle distributions of the MiniBooNE excess. This measurement excludes an electronlike interpretation of the MiniBooNE excess based on these models at >99% CLs in all kinematic variables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Vehicle-Level Reasoning Systems: Integrating System-Wide Data to Estimate the Instantaneous Health State

At the aircraft level, a Vehicle-Level Reasoning System (VLRS) can be developed to provide aircraft with at least two significant capabilities: improvement of aircraft safety due to enhanced monitoring and reasoning about the aircrafts health state, and also potential cost savings by enabling Condition Based Maintenance (CBM). Along with the benefits of CBM, an important challenge facing aviation safety today is safeguarding against system and component failures and malfunctions. Faults can arise in one or more aircraft subsystem their effects in one system may propagate to other subsystems, and faults may interact.

system-wide data↗

Predicting the evolution of biomass bulk density through feedstock preprocessing: Discrete element modeling, regression analysis, and pilot-scale validation

Bulk density is an important material property of biomass feedstocks, influencing handling, storage, transport costs, and conversion efficiency. In this study, predictive regression models for loose and tapped bulk densities of Alamo and Cave-in-Rock switchgrass are developed using a comprehensive dataset generated via calibrated bonded-sphere discrete element method (DEM) simulations. Here, a key contribution of this study is the use of a DEM-based approach, which correlates density with moisture content and particle size distribution parameters and enables analysis across a continuous particle size range, overcoming limitations of purely experimental data. For comparison, regression models are also developed using only experimental data from pilot-scale runs at the Biomass Feedstock National User Facility at Idaho National Laboratory. Validation against pilot-scale data showed reasonable prediction accuracy for both model types, particularly for smaller particle sizes (post-secondary grinding). While the experimental model showed slightly better performance matching the validation data in some cases, the DEM-based model benefits from a much larger dataset, reduced predictor multicollinearity, and continuous parameter coverage, highlighting the utility of validated simulation models for developing robust predictive tools for biomass preprocessing applications.

09 - BIOMASS FUELS↗

Anomaly detection of turbopump vibration in Space Shuttle Main Engine using statistics and neural networks

The statistical and neural networks methods have been applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. The anomalies are detected based on the amplitude of peaks of fundamental and harmonic frequencies in the power spectral density. These data are reduced to the proper format from sensor data measured by strain gauges and accelerometers. Both methods are feasible to detect the vibration anomalies. The statistical method requires sufficient data points to establish a reasonable statistical distribution data bank. This method is applicable for on-line operation. The neural networks method also needs to have enough data basis to train the neural networks. The testing procedure can be utilized at any time so long as the characteristics of components remain unchanged.

Lo, C. F.↗

A geometric modeler based on a dual-geometry representation polyhedra and rational b-splines

For speed and data base reasons, solid geometric modeling of large complex practical systems is usually approximated by a polyhedra representation. Precise parametric surface and implicit algebraic modelers are available but it is not yet practical to model the same level of system complexity with these precise modelers. In response to this contrast the GEOMOD geometric modeling system was built so that a polyhedra abstraction of the geometry would be available for interactive modeling without losing the precise definition of the geometry. Part of the reason that polyhedra modelers are effective is that all bounded surfaces can be represented in a single canonical format (i.e., sets of planar polygons). This permits a very simple and compact data structure. Nonuniform rational B-splines are currently the best representation to describe a very large class of geometry precisely with one canonical format. The specific capabilities of the modeler are described.

Klosterman, A. L.↗

Creep rupture of polymer-matrix composites

The time-dependent creep-rupture process in graphite-epoxy laminates is examined as a function of temperature and stress level. Moisture effects are not considered. An accelerated characterization method of composite-laminate viscoelastic modulus and strength properties is reviewed. It is shown that lamina-modulus master curves can be obtained using a minimum of normally performed quality-control-type testing. Lamina-strength master curves, obtained by assuming a constant-strain-failure criterion, are presented along with experimental data, and reasonably good agreement is shown to exist between the two. Various phenomenological delayed failure models are reviewed and two (the modified rate equation and the Larson-Miller parameter method) are compared to creep-rupture data with poor results.

Brinson, H. F.↗

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden C. Szeto↗

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden Szeto↗

Transition in a disturbed environment

The title of this presentation is the title of our research grant. While transition study is the objective of the work, the results to date are principally on the properties of turbulent boundary layers at low Reynolds numbers are discussed. Testing was done in a small return wind tunnel. Mean boundary layer development is given. The skin friction behavior of the turbulent points are considered. No standard laminar flow was observed. Furthermore, the turbulent mean flow data seem reasonable for the elevated disturbance levels of the tests in the sense that there is no discernible wake component to any of the profiles and that the variation of skin friction with R sub theta is consistent with zero wake strength. The no-grid data are in all likelihood transitional.

Reshotko, E.↗

Aerosol optical depth retrievals over the Konza Prairie

The aerosol optical depth over the Konza Prairie, near Manhattan, Kansas, was recorded at various locations by five separate teams. These measurements were made in support of the First ISLSCP Field Experiment (FIFE) and used to correct imagery from a variety of satellite and aircraft sensors for the effects of atmospheric scattering and absorption. The results from one instrument are reported here for 26 days in 1987 and for 7 in 1989. Daily averages span a range of 0.05 to 0.28 in the midvisible wavelengths. In addition, diurnal variations are noted in which the afternoon optical depths are greater than those of the morning by as much as 0.07. A comparison between instruments and processing techniques used to determine these aerosol optical depths is provided. The first comparisons are made using summer 1987 data. Differences of as much as 0.05 (midvisible) are observed. Although these data allow reasonable surface reflectance retrievals, they do not agree to within the performance limits typically associated with these types of instruments. With an accuracy goal of 0.02 a preseason calibration/comparison experiment was conducted at a mountain site prior to the final field campaign in 1989. Good calibration data were obtained, and good agreement (0.01, midvisible) was observed in the retrieved optical depth acquired over the Konza. By comparing data from the surface instruments at different locations, spatial inhomogeneities are determined. Then, data from the airborne tracking sunphotometer allow one to determine variations as a function of altitude. Finally, a technique is proposed for using the in situ data to establish an instrument calibration.

Bruegge, Carol J.↗

Airborne Aerosol Closure Studies During PRIDE

The Puerto Rico Dust Experiment (PRIDE) was conducted during June/July of 2000 to study the properties of Saharan dust aerosols transported across the Atlantic Ocean to the Caribbean Islands. During PRIDE, the NASA Ames Research Center six-channel (380 - 1020 nm) airborne autotracking sunphotometer (AATS-6) was operated aboard a Piper Navajo airplane alongside a suite of in situ aerosol instruments. The in situ aerosol instrumentation relevant to this paper included a Forward Scattering Spectrometer Probe (FSSP-100) and a Passive Cavity Aerosol Spectrometer Probe (PCASP), covering the radius range of approx. 0.05 to 10 microns. The simultaneous and collocated measurement of multi-spectral aerosol optical depth and in situ particle size distribution data permits a variety of closure studies. For example, vertical profiles of aerosol optical depth obtained during local aircraft ascents and descents can be differentiated with respect to altitude and compared to extinction profiles calculated using the in situ particle size distribution data (and reasonable estimates of the aerosol index of refraction). Additionally, aerosol extinction (optical depth) spectra can be inverted to retrieve estimates of the particle size distributions, which can be compared directly to the in situ size distributions. In this paper we will report on such closure studies using data from a select number of vertical profiles at Cabras Island, Puerto Rico, including measurements in distinct Saharan Dust Layers. Preliminary results show good agreement to within 30% between mid-visible aerosol extinction derived from the AATS-6 optical depth profiles and extinction profiles forward calculated using 60s-average in situ particle size distributions and standard Saharan dust aerosol refractive indices published in the literature. In agreement with tendencies observed in previous studies, our initial results show an underestimate of aerosol extinction calculated based on the in situ size distributions relative to the extinction obtained from the sunphotometer measurements. However, a more extensive analysis of all available AATS-6 and in situ size distribution data is necessary to ascertain whether the preliminary results regarding the degree of extinction closure is representative of the entire range of dust conditions encountered in PRIDE. Finally, we will compare the spectral extinction measurements obtained in PRIDE to similar data obtained in Saharan dust layers encountered above the Canary Islands during ACE-2 (Aerosol Characterization Experiment) in July 1997. Thus, the evolution of Saharan dust spectral properties during its transport across the Atlantic can be investigated, provided the dust origin and microphysical properties are found to be comparable.

Redemann, Jens↗

Use NASA Earthdata in the Cloud

With the impending arrival of new, high-data-volume Earth observation missions, NASA’s ability to effectively ingest, process, and archive large amounts of data requires the most cost-effective, flexible, and scalable data-management architectures and technologies. To meet these demands, NASA's Earth Science Data Systems (ESDS) Program is implementing a strategic vision to develop and operate multiple components of NASA's Earth Observing System Data and Information System (EOSDIS) in a commercial cloud environment. As more earth observing data is moved into the cloud, NASA EOSDIS wants to share our reasoning for moving data into the commercial cloud, as well as demonstrate how end-users can take advantage of both data in the cloud and cloud-deployed services. This presentation explains the enterprise reasons for moving data into the cloud, specifically the scalability of cloud systems, the flexibility to pivot to the most optimal language/system/architecture, and the reduced redundancy of a common architecture. Then we primarily focus on the user-driven reasons for moving to the cloud. Equal access to high performance computing helps all parties, especially users that don't have access to their own on-premise computing infrastructure. Rapid deployment allows users to spin up their own systems without needing the extensive platform previously required for large scale development. Cost effectiveness allows users a wide breadth of computing options, from super computer ability to small scale development, which can help underserved communities. Finally we link to internal resources that users can utilize to begin their cloud based development journey without having to be an expert in the field.

Nicholas Doty↗

Efficacy of FTIR Analysis in Determining CO2 Loading on Diglycolamine

In support of advanced air revitalization technologies to enable human spaceflight beyond low earth orbit, performance studies have been conducted using a liquid amine, Diglycolamine (DGA) between teams at NASA?s Johnson Spaceflight Center (JSC) and Ames Research Center (ARC). Liquid amines have been used in regenerable earth-based systems to remove CO2 from industrial systems as well as for closed-environment air revitalization because they can be regenerated at lower temperatures than solid sorbent systems. As an additional advantage to solid sorbent based systems, liquid sorbents can be cycled between an adsorbing contactor and degassing chamber, thereby reducing system complexity by operation in a continuous loop. In an effort to inform a regeneration system design for micro-gravity applications, ARC has performed a number of tests to characterize the degas mechanics of DGA. In order to accurately measure the amount of CO2 captured or released by the amine, methods such as gravimetric weighing and chemical decomposition are reasonable, however the initial design for a scaled down degas system required analysis on small sample sizes. In order to accomplish CO2 loading measurements with a sample size of approximately 500µL, Fourier-transform infrared spectroscopy (FTIR) was used. Calibration against acid decomposition showed relatively good correlation and test data showed reasonable adherence to expected trends, however more extensive testing should be conducted to fully validate the usage of FTIR to determine CO2 loading on DGA.

Diglycolamine↗

A numerical evaluation of TIROS-N and NOAA-6 analyses in a high resolution limited area model

Vertical temperature profiles derived from TIROS-N and NOAA-6 radiance measurements were used to create separate analyses for the period 0000 GMT 6 January to 0000 GMT 7 January 1980. The 0000 GMT 6 January satellite analyses and a conventional analysis were used to initialize and run the University of Wisconsin's version of the Australian Region Primitive Equations model. Forecasts based on conventional analyses were used to evaluate the forecasts based only on satellite upper air data. The forecasts based only on TIROS-N or NOAA-6 data did reasonably well in locating the main trough and ridge positions. The satellite initial analyses and forecasts revealed errors correlated to the synoptic situation. The trough in both TIROS-N and NOAA-6 forecasts which was initially too warm remained too warm as it propagated eastward during the forecast period. Thus, it is unlikely that the operational satellite data will improve forecasts in a data dense region. However, in regions of poor data coverage, the satellite data should have a beneficial effect on numerical forecasts.

Derber, J. C.↗

Efficacy of FTIR Analysis in Determining CO2 Loading on Diglycolamine

In support of advanced air revitalization technologies to enable human spaceflight beyond low earth orbit, performance studies have been conducted using a liquid amine, Diglycolamine (DGA) between teams at NASA's Johnson Spaceflight Center (JSC) and Ames Research Center (ARC). Liquid amines have been used in regenerable earth-based systems to remove CO2 from industrial systems as well as for closed-environment air revitalization because they can be regenerated at lower temperatures than solid sorbent systems. As an additional advantage to solid sorbent-based systems, liquid sorbents can be cycled between an adsorbing contactor and degassing chamber, thereby reducing system complexity by operation in a continuous loop. In an effort to inform a regeneration system design for micro-gravity applications, ARC has performed a number of tests to characterize the degas mechanics of DGA. In order to accurately measure the amount of CO2 captured or released by the amine, methods such as gravimetric weighing and chemical desorption are reasonable, however the first iteration test setup for a scaled down degas system required analysis on small sample sizes. Fourier-transform infrared spectroscopy (FTIR) analysis was experimentally evaluated to analyze CO2 concentration because it can produce measurements with sample sizes on the order of 100's of μL. Calibration against chemical desorption showed relatively good correlation and test data showed reasonable adherence to expected trends, however more extensive testing should be conducted to fully validate the usage of FTIR to determine CO2 loading on DGA.

Diglycolamine↗

Estimating Temperature Retrieval Accuracy Associated With Thermal Band Spatial Resolution Requirements for Center Pivot Irrigation Monitoring and Management

This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.

Ryan, Robert E.↗