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NASA NTRSDate not supplied

Natural Language Processing (NLP) Analysis of NOTAMs for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized. Video is an mp4 download, with a play time of 9 min 35 secs.

Natural Language Processing↗
NASA NTRS2014

H Diffusion in Olivine and Pyroxene from Peridotite Xenoliths and a Hawaiian Magma Speedometer

Hydrogen is present as a trace element in olivine and pyroxene and its content distribution in the mantle results from melting and metasomatic processes. Here we examine how these H contents can be disturbed during decompression. Hydrogen was analyzed by FTIR in olivine and pyroxene of spinel peridotite xenoliths from Salt Lake Crater (SLC) nephelinites which are part of the rejuvenated volcanism at Oahu (Hawaii) [1,2]. H mobility in pyroxene resulting from spinel exsolution during mantle upwelling Most pyroxenes in SLC peridotites exhibit exsolutions, characterized by spinel inclusions. Pyroxene edges where no exsolution are present have less H then their core near the spinel. Given that H does not enter spinel [3], subsolidus requilibration may have concentrated H in the pyroxene adjacent to the spinel exsolution during mantle upwelling. H diffusion in olivine during xenolith transport by its host magma and host magma ascent rates Olivines have lower water contents at the edge and near fractures compared to at their core, while the concentrations of all other chemical elements appear homogeneous. This suggests that some of the initial water has diffused out of the olivine. Water loss from the olivine is thought to occur during host-magma ascent and xenolith transport to the surface [4-6]. Diffusion modeling matches best the data when the initial water content used is that measured at the core of the olivines, implying that mantle water contents are preserved at the core of the olivines. The 3225 cm(sup -1) OH band at times varies independantly of other OH bands, suggesting uneven H distribution in olivine defects likely acquired during mantle metasomatism just prior to eruption and unequilibrated. Diffusion times (1-48 hrs) combined with depths of peridotite equilibration or of magma start of degassing allow to calculate ascent rates for the host nephelinite of 0.1 to 27 m/s.

Peslier, A. H.↗
NASA NTRS1975

Project Fog Drops 5. Task 1: A numerical model of advection fog. Task 2: Recommendations for simplified individual zero-gravity cloud physics experiments

A two-dimensional numerical model was used to investigate the formation of marine advection fog. The model predicts the evolution of potential temperature, horizontal wind, water vapor content, and liquid water content in a vertical cross section of the atmosphere as determined by vertical turbulent transfer and horizontal advection, as well as radiative cooling and drop sedimentation. The model is designed to simulate the formation, development, or dissipation of advection fog in response to transfer of heat and moisture between the atmosphere and the surface as driven by advection over horizontal discontinuities in the surface temperature. Results from numerical simulations of advection fog formation are discussed with reference to observations of marine fog. A survey of candidate fog or cloud microphysics experiments which might be performed in the low gravity environment of a shuttle-type spacecraft in presented. Recommendations are given for relatively simple experiments which are relevent to fog modification problems.

Rogers, C. W.↗
NASA NTRS1999

Improving Reanalyses Using TRMM and SSM/I-Derived Precipitation and Total Precipitable Water Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of rainfall and total precipitable water (TPW) observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve these fields in reanalyses. The DAO has developed a "1+1"D procedure to assimilate 6-hr averaged rainfall and TPW into the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS. The "1+1" designation refers to one spatial dimension plus one temporal dimension. The scheme minimizes the least-square differences between the satellite-retrieved rain rates and those produced by the column model over the 6-hr analysis window. The control variables are analysis increments of moisture within the Incremental Analysis Update (IAU) framework of the GEOS DAS. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but differs in its choice of the control variable. Instead of estimating the initial condition at the beginning of the assimilation cycle, it estimates the constant IAU forcing applied over a 6-hr assimilation cycle. In doing so, it imposes the forecast model as a weak constraint in a manner similar to the variational continuous assimilation techniques. We present results from an experiment in which the observed rain rate and TPW are assumed to be "perfect". They show that assimilating the TMI and SSM/I-derived surface precipitation and TPW observations improves not only the precipitation and moisture fields but also key climate parameters directly linked to convective activities such as clouds, the outgoing longwave radiation, and the large-scale circulation in the tropics. In particular, assimilating these data types reduce the state-dependent systematic errors in the assimilated products. The improved analysis also leads to a better short-range forecast, but the impact is modest compared with improvements in the time-averaged fields. These results suggest that, in the presence of biases and other errors of the forecast model, it is possible to improve the time-averaged "climate content" in the assimilated data without comparable improvements in the short-range forecast skill. Results of this experiment provide a useful benchmark for evaluating error covariance models for optimal use of these data types.

Hou, Arthur Y.↗
NASA NTRS2024

Effects of Water on the Density and Elevation of Tesserae on Venus

While the current conditions on Venus are inhospitable, with surface temperatures of ~ 470 °C, pressures of 92 bars, and a CO 2 dominated atmosphere, early Venus may have had a more temperate climate with water on the surface. Water is not only crucial to understanding the habitability potential of Venus, but also has major implications for the tectonic regime and thermal evolution of a planet. Tesserae are believed to be the oldest exposed features on the surface of Venus and may have formed during a period with higher water content. Some of this water might have been preserved as hydrous minerals in the Venusian subsurface. The presence of these minerals has an effect on the density profiles and isostatic behaviour of the tesserae and therefore requires a more detailed investigation. Here we will present results of phase equilibria and isostasy modelling on a range of Tesserae-analogue rock compositions with varying water content and along a range of potential thermal gradients. We compare our results to anhydrous models performed previously under similar thermal regime to constrain the conditions (rock composition, thermal gradient, and water content) needed for tesserae stability.

A R Baker↗
DOE OSTI2021

Automatic enhancement in 6D supergravity and F-theory models

We observe that in many F-theory models, tuning a specific gauge group G and matter content M under certain circumstances leads to an automatic enhancement to a larger gauge group G ' ⊂ G and matter content M ' ⊂ M . We propose that this is true for any theory G, M whenever there exists a containing theory G ' , M ' that cannot be Higgsed down to G, M . We give a number of examples including non-Higgsable gauge factors, nonabelian gauge factors, abelian gauge factors, and exotic matter. In each of these cases, tuning an F-theory model with the desired features produces either an enhancement or an inconsistency, often when the associated anomaly coefficient becomes too large. This principle applies to a variety of models in the apparent 6D supergravity swampland, including some of the simplest cases with U(1) and SU( N ) gauge groups and generic matter, as well as infinite families of U(1) models with higher charges presented in the prior literature, potentially ruling out all these apparent swampland theories.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Converting 2D Nanofiber Membranes to 3D Hierarchical Assemblies with Structural and Compositional Gradients Regulates Cell Behavior

Abstract New methods are described for converting 2D electrospun nanofiber membranes to 3D hierarchical assemblies with structural and compositional gradients. Pore‐size gradients are generated by tuning the expansion of 2D membranes in different layers with incorporation of various amounts of a surfactant during the gas‐foaming process. The gradient in fiber organizations is formed by expanding 2D nanofiber membranes composed of multiple regions collected by varying rotating speeds of mandrel. A compositional gradient on 3D assemblies consisting of radially aligned nanofibers is prepared by dripping, diffusion, and crosslinking. Bone mesenchymal stem cells (BMSCs) on the 3D nanofiber assemblies with smaller pore size show significantly higher expression of hypoxia‐related markers and enhanced chondrogenic differentiation compared to BMSCs cultured on the assemblies with larger pore size. The basic fibroblast growth factor gradient can accelerate fibroblast migration from the surrounding area to the center in an in vitro wound healing model. Taken together, 3D nanofiber assemblies with gradients in pore sizes, fiber organizations, and contents of signaling molecules can be used to engineer tissue constructs for tissue repair and build biomimetic disease models for studying disease biology and screening drugs, in particular, for interface tissue engineering and modeling.

Chen, Shixuan↗
NASA NTRS2011

New Challenges of Cloud Remote Sensing from Space

Clouds are recognized as a major source of uncertainties in predicting climate change. Lack of observational constraints on cloud processes has hindered the development of more reliable climate and weather models. With the advanced NASA EOS and A-Train sensors, we now have better knowledge about vertical distribution, water content, and occurrence frequency of global cloudiness. New ice water content (IWC) measurements from CloudSat and MLS have led to several improvements in model physics and parameterization schemes. MISR and GPS high-resolution data start to reveal deep insights on cloud processes and dynamicS in the planetary boundary layer (PBL). However, Earth sciences are still facing urgent needs to measure cloud microphysical properties, interactions between clouds and aerosol/precipitation, and processes that are coupled in 3-D space but not adequately sampled by the A-Train curtains or by the 2-D imageries. Submillimeter- wave, multi-angle imaging, and GPS radio occultation have emerged as promising remote sensing techniques to meet the challenges and enable new sciences for mid-tropospheric and PBL clouds.

Wu, Dong L.↗
DOE OSTI2026

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 1. Evaluating Above- and Below-ground Controls of Flow Persistence in a Forested Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.

ATS↗
NASA NTRS1991

Model rotor icing tests in the NASA. Lewis Icing Research Tunnel

Tests of a lightly instrumented two bladed teetering rotor and a heavily instrumented subscale articulated main rotor were conducted in the NASA Lewis Icing Research Tunnel (IRT). The first was an OH-58 tail rotor which had a diameter of 1.575 m and a blade chord of 0.133 m, and was mounted on a NASA designed test rig. The second, a four bladed articulated rotor, had a diameter of 1.83 m with 0.124 m chord blades specifically fabricated for the experiment. This rotor was mounted on a Sikorsky Aircraft Powered Force Model, which enclosed a rotor balance and other measurement systems. The models were exposed to variations in temperature, liquid water content, and medium droplet diameter, and were operated over ranges of advance ratio, shaft angle, tip Mach number (rotor speed), and weight coefficient to determine the effect of these parameters on ice accretion. In addition to strain gage and balance data, the test was documented with still, video, and high speed photography, ice profile tracing, and ice molds. The sensitivity is presented of the model rotors to the test parameter and a comparison of the results to theoretical predictions.

Flemming, Robert J.↗
NASA NTRS1991

The hemispherical asymmetry of the residual polar caps on Mars

A model of the polar caps of Mars was created which allows: (1) for light penetration into the cap; (2) ice albedo to vary with age, latitude, hemisphere, dust content, and solar zenith angle; and (3) for diurnal variability. The model includes the radiative effects of clouds and dust, and heat transport as represented by a thermal wind. The model reproduces polar cap regression data very well, including the survival of CO2 frost at the south pole and reproduces the general trend in the Viking Lander pressure data.

Lindner, Bernhard Lee↗
NASA NTRS1999

Predicting Decade-to-Century Climate Change: Prospects for Improving Models

Recent research has led to a greatly increased understanding of the uncertainties in today's climate models. In attempting to predict the climate of the 21st century, we must confront not only computer limitations on the affordable resolution of global models, but also a lack of physical realism in attempting to model key processes. Until we are able to incorporate adequate treatments of critical elements of the entire biogeophysical climate system, our models will remain subject to these uncertainties, and our scenarios of future climate change, both anthropogenic and natural, will not fully meet the requirements of either policymakers or the public. The areas of most-needed model improvements are thought to include air-sea exchanges, land surface processes, ice and snow physics, hydrologic cycle elements, and especially the role of aerosols and cloud-radiation interactions. Of these areas, cloud-radiation interactions are known to be responsible for much of the inter-model differences in sensitivity to greenhouse gases. Recently, we have diagnostically evaluated several current and proposed model cloud-radiation treatments against extensive field observations. Satellite remote sensing provides an indispensable component of the observational resources. Cloud-radiation parameterizations display a strong sensitivity to vertical resolution, and we find that vertical resolutions typically used in global models are far from convergence. We also find that newly developed advanced parameterization schemes with explicit cloud water budgets and interactive cloud radiative properties are potentially capable of matching observational data closely. However, it is difficult to evaluate the realism of model-produced fields of cloud extinction, cloud emittance, cloud liquid water content and effective cloud droplet radius until high-quality measurements of these quantities become more widely available. Thus, further progress will require a combination of theoretical and modeling research, together with intensified emphasis on both in situ and space-based remote sensing observations.

Somerville, Richard C. J.↗
NASA NTRS1973

A field investigation and numerical simulation of coastal fog

A field investigation of the microphysical and micrometeorological features of fogs occurring near Los Angeles and Vandenberg, California was conducted. Observations of wind speed and direction, temperature, dew point, vertical wind velocity, dew deposition, drop-size distribution, liquid water content, and haze and cloud nucleus concentration were obtained. These observations were initiated in late evening prior to fog formation and continued until the time of dissipation in both advection and radiation fogs. Data were also acquired in one valley fog and several dense haze situations. The behavior of these parameters prior to and during fog are discussed in detail. A two-dimensional numerical model was developed to investigate the formation and dissipation of advection fogs under the influence of horizontal variations in surface temperature. The model predicts the evolution of potential temperature, water vapor content, and liquid water content in a vertical plane as determined by vertical turbulent transfer and horizontal advection. Results are discussed from preliminary numerical experiments on the formation of warm-air advection fog and dissipation by natural and artificial heating from the surface.

Mack, E. J.↗
NASA NTRS1991

Model rotor icing tests in the NASA Lewis icing research tunnel

Tests of a lightly instrumented two-bladed teetering rotor and a heavily instrumented sub-scale articulated main rotor were conducted in the NASA Lewis Research Center Icing Research Tunnel (IRT) in August 1988 and September and November 1989. The first was an OH-58 tail rotor which had a diameter of 1.575 m and a blade chord of 0.133 m, and was mounted on a NASA designed test rig. The second, a four bladed articulated rotor, had a diameter of 1.83 m with 0.124 m chord blades specially fabricated for the experiment. This rotor was mounted on a Sikorsky Aircraft Powered Force Model, which enclosed a rotor balance and other measurement systems. The models were exposed to variations in temperature, liquid water content, and medium droplet diameter, and were operated over ranges of advance ratio, shaft angle, tip Mach number (rotor speed), and weight coefficient to determine the effect of these parameters on ice accretion. In addition to strain gage and balance data, the test was documented with still, video, and high speed photography, ice profile tracing, and ice molds. Presented here are the sensitivity of the model rotors to the test parameters and a comparison of the results to theoretical predictions.

Flemming, Robert J.↗
DOE OSTI2021

The Role of Oxidation Resistance in High Temperature Alloy Selection for a Future with Green Hydrogen

Hydrogen is being considered integral to the future energy landscape but there is limited mechanistic understanding and a lack of predictive models to describe the combined effects of alloy and gas composition, temperature, thermal cycling and water vapor contents on the oxidation behavior of high-temperature materials. Experimental evaluations were combined with coupled thermodynamic-kinetic modeling to investigate the oxidation behavior of five representative Ni-based superalloys in two water vapor contents (10%, 60% H 2 O) under thermal cycling (1-h, 100-h cyles) conditions at 800°C and 1000°C. The alloy with the highest Ti content demonstrated the poorest cyclic oxidation behavior while the alloy with highest Cr and Al contents was expected to continue to support protective formation of a compact Al 2 O 3 scale. Finally, accelerated degradation of the chromia-forming alloys was observed in the higher water vapor content but the impact on transient oxidation of the alumina-forming alloys needs further investigations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates

ABSTRACT: Variation in the genome of Pseudomonas aeruginosa , an important pathogen, can have dramatic impacts on the bacterium’s ability to cause disease. We therefore asked whether it was possible to predict the virulence of P. aeruginosa isolates based on their genomic content. We applied a machine learning approach to a genetically and phenotypically diverse collection of 115 clinical P. aeruginosa isolates using genomic information and corresponding virulence phenotypes in a mouse model of bacteremia. We defined the accessory genome of these isolates through the presence or absence of accessory genomic elements (AGEs), sequences present in some strains but not others. Machine learning models trained using AGEs were predictive of virulence, with a mean nested cross-validation accuracy of 75% using the random forest algorithm. However, individual AGEs did not have a large influence on the algorithm’s performance, suggesting instead that virulence predictions are derived from a diffuse genomic signature. These results were validated with an independent test set of 25 P. aeruginosa isolates whose virulence was predicted with 72% accuracy. Machine learning models trained using core genome single-nucleotide variants and whole-genome k-mers also predicted virulence. Our findings are a proof of concept for the use of bacterial genomes to predict pathogenicity in P. aeruginosa and highlight the potential of this approach for predicting patient outcomes. IMPORTANCE Pseudomonas aeruginosa is a clinically important Gram-negative opportunistic pathogen. P. aeruginosa shows a large degree of genomic heterogeneity both through variation in sequences found throughout the species (core genome) and through the presence or absence of sequences in different isolates (accessory genome). P. aeruginosa isolates also differ markedly in their ability to cause disease. In this study, we used machine learning to predict the virulence level of P. aeruginosa isolates in a mouse bacteremia model based on genomic content. We show that both the accessory and core genomes are predictive of virulence. This study provides a machine learning framework to investigate relationships between bacterial genomes and complex phenotypes such as virulence.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1985

Modeling canopy reflectance and microwave backscattering coefficient

Various approaches to model canopy reflectance (CR) in the visible/infrared region and backscattering coefficient (BSC) in the microwave region are compared and contrasted. It is noted that BSC can be related to CR in the source direction (the 'hot spot' direction). By assuming a frequency dependent leaf reflectance and transmittance it is shown that the observed dependence of BSC on leaf area index, leaf angle distribution, angle of incidence, soil moisture content, and frequency can be simulated by a CR model. Thus both BSC and CR can, in principle, be calculated using a single model which has essentially the same parameters as many CR models do.

Goel, N. S.↗
NASA NTRS1996

Computer Modeling of Non-Isothermal Crystallization

A realistic computer model for simulating isothermal and non-isothermal phase transformations proceeding by homogeneous and heterogeneous nucleation and interface-limited growth is presented. A new treatment for particle size effects on the crystallization kinetics is developed and is incorporated into the numerical model. Time-dependent nucleation rates, size-dependent growth rates, and surface crystallization are also included. Model predictions are compared with experimental measurements of DSC/DTA peak parameters for the crystallization of lithium disilicate glass as a function of particle size, Pt doping levels, and water content. The quantitative agreement that is demonstrated indicates that the numerical model can be used to extract key kinetic data from easily obtained calorimetric data. The model can also be used to probe nucleation and growth behavior in regimes that are otherwise inaccessible. Based on a fit to data, an earlier prediction that the time-dependent nucleation rate in a DSC/DTA scan can rise above the steady-state value at a temperature higher than the peak in the steady-state rate is demonstrated.

Kelton, K. F.↗