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NASA NTRSDate not supplied

Autogenous Pressurization of a Cryogenic Tank using Computational Fluid Dynamics

Well-validated simulation tools can be used to predict long-term storage and transfer of cryogenic propellants, which are essential to NASA’s mission plan to return to the Moon and continue to Mars. Autogenous pressurization of propellant tanks is used to supply rocket engine turbopumps with pressurized liquid fuel and oxidizer, preventing cavitation. Additionally, autogenous pressurization can be used to pressurize propellant tanks to support on-orbit propellant transfer. In lieu of expensive tests conducted on-orbit, accurate predictive computational models of these processes can be used to reduce system and propellant mass as well as mission risk. Using simulation tools also reduces the cost of analyzing and developing this technology. This study presents a multiphase computational fluid dynamics model capable of simulating autogenous pressurization of a large cryogenic tank using the commercial code STAR-CCM+. Experimental data from a full-scale tank pressurization test under terrestrial gravity is compared to simulation results using transient error metrics. Comparisons show good agreement and give confidence in using these and other validated simulation tools to develop cryogenic pressurization systems. Note: There is no audio file included or available for this presentation.

cryogenics↗
NASA NTRSDate not supplied

On the use of DSCOVR EPIC to monitor the visible calibration stability of polar orbiting imagers to improve the next edition of the CERES climate data record.

The NASA CERES project has provided the climate quality observed TOA and computed surface fluxes to the scientific community. CERES instruments are onboard the Terra, Aqua, NPP, and NOAA-20 spacecraft. CERES uses MODIS and VIIRS imagers to retrieve cloud properties needed to convert CERES footprint radiance observations into fluxes using empirically derived angular directional models obtained during early CERES record. CERES utilizes geostationary sensors to infer the regional diurnal fluxes in between Terra and Aqua CERES observations. The imagers are also used to radiometrically scale the geostationary sensors (GEO) radiances to the imager calibration reference to ensure that the GEO derived cloud properties and broadband TOA fluxes are consistent in both space and time. Both the imager and GEO retrieved cloud properties are used to compute the surface fluxes. The Aqua-MODIS, SNPP-VIIRS, and NOAA-20 VIIRS afternoon imagers will also need to be radiometrically scaled to the same common calibration reference. Although all three imagers employ onboard solar diffusers, the calibration is not consistent over time due to instrument anomalies and ageing of the onboard calibrators. The CERES imager and GEO calibration group (IGCG) has been tasked to remove the imager channel calibration drifts for the next CERES reprocessing effort. The team will rely primarily on deep convective clouds, desert, and polar ice invariant targets to monitor the imager channel stability. The team uses ray-matched radiance pairs to radiometrically scale the SNPP and NOAA-20 VIIRS sensors to Aqua-MODIS. The radiometric scaling is further validated using geostationary imagers as transfer radiometers. The DSCOVR satellite was launched on February 25, 2015 and orbits around the L1 Lagrange point directly between the Earth and the sun. The EPIC instrument onboard DSCOVR employs a CCD array to image the Earth approximately every 2-hours. The EPIC sensor contains no onboard calibration systems. However, multiple inter-calibration studies have shown that the EPIC imager is very stable in time. This is likely due to the DSCOVR satellite being located about a 1.5M km from the Earth, where very little Earth reflected solar radiation degrades the optics. The excellent radiometric stability of EPIC allows the CERES IGCG to utilize the EPIC observations as a stable reference for monitoring the calibration stability of the three afternoon imagers, as well as to validate the radiometric scaling factors between them. Examples of the imager relative calibration using EPIC before and after radiometric scaling will be shown along with the results from the use of invariant targets to remove imager calibration drifts.

DSCOVR-EPIC↗
NASA NTRS2021

Land-Use Harmonization Datasets for Global Carbon Budget 2019 and Beyond

Land-use change has been the dominant source of anthropogenic carbon emissions for most of the historical period, and is currently one of the largest and most uncertain components of the global carbon cycle. Advancing the scientific understanding on this topic requires that the best data be used as input to the best models in well-organized scientific assessments. The Land-Use Harmonization dataset (LUH2), previously developed and used as input for CMIP6 simulations, has been updated annually to provide required input to land models in the annual Global Carbon Budget (GCB) assessment. These annual LUH2-GCB updates and extensions have incorporated annual FAO wood harvest data updates for dataset years after 2015 and HYDE gridded agriculture area data updates (based on annual FAO agricultural area data updates) for dataset years after 2012, along with extrapolations to the current year due to a lag of one or more years in the FAO data releases. The resulting updated LUH2-GCB datasets have provided global, annual gridded land-use and land-use change data relating toagricultural expansion, deforestation, wood harvesting, shifting cultivation, regrowth and afforestation, and crop rotationsand pasture managementand are used by both book-keeping models and Dynamic Global Vegetation Models (DGVMs) for the GCB. For GCB 2019,a more significant update to LUH2 was produced (LUH2-GCB2019) to correct cropland and grazing area errors in the underlying input datasets for the globally important region of Brazil, as far back as 1950. From 1951-2012 the LUH2-GCB2019 dataset begins to diverge from the LUH2 v2hdataset, with peak differences in Brazil in the year 2000 for grazing land (difference of 100,000 km2) and in the year 2009 for cropland (difference of 77,000 km2), along with significant sub-national reorganization of agricultural land-use patterns within Brazil. These LUH2-GCB2019 corrections for Brazil provide the base for future LUH2-GCB updates including the recent LUH2-GCB2020 dataset, and present a starting point for operationalizing the creation of these datasets toreduce time-lags due to the multiple input dataset and model latencies.

L Chini↗
NASA NTRS2021

Exploring Sentinel-1 and Sentinel-2 diversity for Flood inundation mapping using deep learning

Identification of flood water extent from satellite images has historically relied on either synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to cloud free conditions, whereas SAR imagery is plagued by noise-like speckle. Prior studies that use combinations of MS and SAR data to overcome individual limitations of these sensors have not fully examined sensitivity of flood mapping performance to different combinations of SAR and MS derived spectral indices or band transformations in color space. This study explores the use of diverse bands of Sentinel 2 (S2) through well-established water indices and Sentinel 1 (S1) derived SAR imagery along with their combinations to assess their capability for generating accurate flood inundation maps. The robustness in performance of S-1 and S-2 band combinations was evaluated using 446 hand labeled flood inundation images spanning across 11 flood events from Sen1Floods11 dataset which are highly diverse in terms of land cover as well as location. A modified K-fold cross validation approach is used to evaluate the performance of 32 combinations of S1 and S2 bands using a fully connected deep convolutional neural network known as U-Net. Our results indicated that usage of elevation information has improved the capability of S1 imagery to produce more accurate flood inundation maps. Compared to a median F1 score of 0.62 when using only S1 bands, the combined use of S1 and elevation information led to an improved median F1 score of 0.73. Water extraction indices based on S2 bands have a statistically significant superior performance in comparison to S1. Among all the band combinations, HSV (Hue, Saturation, Value) transformation of S2 bands provides a median F1 score of 0.9, outperforming the commonly used water spectral indices owing to HSV’s transformation’s superior contrast distinguishing abilities. Additionally, U-Net algorithm was able to learn the relationship between raw S2 based water extraction indices and their corresponding raw S2 bands, but not of HSV owing to relatively complex computation involved in the latter. Results of the paper establishes important benchmarks for the extension of S1 and S2 data-based flood inundation mapping efforts over large spatial extents.

Goutam Konapala↗
NASA NTRS2020

Case Study of Using Flocad to Model a Ground Test Station Ln2 Heat Exchanger

This paper presents a case study of using FLOCAD to model the heat transfer and boiling flow behavior of a Liquid Nitrogen (LN2) ground station equipment heat exchanger. The unique aspect of this work is that is one of very few studies documenting the use of FLOCAD in the spacecraft thermal control community. The results of the simulations described herein were used to guide and plan the execution of thermal vacuum testing spacecraft hardware using a ground test heat exchanger such as the one modeled herein. The paper will review the theory of two-phase boiling flow and correlations used by SINDA/FLUINT as well as the terminology and nomenclature used within Thermal Desktop / FLOCAD regarding two-phase boiling flow heat transfer modeling and simulation. Results for using the ground station heat exchanger as a heat sink in a thermal vacuum test set up are shown in order to demonstrate the set-up and execution of a typical FLOCAD model. Results indicate that properly modeling of the two-phase behavior is critical in order to ascertain the time constant associated with the heat exchanger, as well as understanding the temperature distribution across the test equipment and prediction of required LN2 flowrates to be used during testing. The paper is meant to augment the FLOCAD user’s manual and serve as a tutorial for thermal engineers and analysts wishing to learn and apply FLOCAD to industrial problems.

Anderson, Kevin R.↗
NASA NTRS2022

Identifying Chemical Aerosol Signatures Using Optical Suborbital Observations: How Much Can Optical Properties Tell us about Aerosol Composition?

Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation. We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).

Meloe S F Kacenelenbogen↗
NASA NTRS2021

What it Takes to Compute Highly Accurate Rovibrational Line Lists for Use in Astrochemistry

We review the Best Theory + Reliable High-resolution Experiment (BTRHE) strategy for obtaining highly accurate molecular rovibrational line lists with InfraRed (IR) intensities. The need for highly accurate molecular rovibrational line lists is two-fold: a) assignment of the many rovibrational lines for common stable molecules especially those that exhibit a large amplitude motion, such as NH3, or have a high density of states such as SO2; and b) characterization of the atmospheres of exoplanets which will be one of the main areas of research in astronomy in the coming decades. The first motivation arises due to the need to eliminate lines due to common molecules in an astronomical observation in order to identify lines from new molecules, while the second motivation arises due to the need to obtain accurate molecular opacities in order to characterize the atmosphere of an exoplanet. The BTRHE strategy first consists of using high quality ab initio quantum chemical methods to obtain a global potential energy surface (PES) and dipole moment surface (DMS) that contains the proper physics. The global PES is then refined using a subset of the reliable high-resolution experimental data. The refined PES then gives energy level predictions to an accuracy similar to the reproduction accuracy of the experimental data used in the refinement step in the interpolation region (i.e., within the range of the experimental data used in the refinement step). The accuracy of the energy levels will slowly degrade as they are extrapolated to spectral regions beyond the high-resolution experimental data used in the refinement step. However, because the degradation is slow, the predicted energy levels can be used to assign new high-resolution experiments, and the data from these can then be used in a subsequent refinement step. In this way, the global PES eventually can yield highly accurate energy levels for all desired spectral regions including to very high energies and high J values. We show that IR intensities computed with the BTRHE rovibrational wavefunctions and the DMS can be very accurate provided one has minimized the fitting error of the DMS and tested the completeness of the DMS. Some examples of our work on NH3, CO2, and SO2 are given to highlight the usefulness of the BTRHE strategy and to provide ideas on how to further improve its predictive power in the future. In particular, it is shown how successive refinement steps, once new high-resolution data is available, can lead to PESs that yield highly accurate transition energies to larger spectral regions. The importance of including non-adiabatic corrections to reduce the J-dependence of errors for H-containing molecules is shown with work on NH3. Another very important aspect of the BTRHE approach is the consistency across isotopologues, which allows for highly accurate line lists for any isotopologue once one is obtained for the main isotopologue (which has more high-resolution data available for refinement).

Xinchuan Huang↗
NASA NTRS2022

Analysis of the MODIS Above-Cloud Aerosol Retrieval Algorithm Using MCARS

The Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS) presently produces synthetic radiance data from Goddard Earth Observing System version 5 (GEOS-5) model output as if the Moderate Resolution Imaging Spectroradiometer (MODIS) was viewing a combination of atmospheric column inclusive of clouds, aerosols and a variety of gases and land/ocean surface at a specific location. In this paper we use MCARS to study the MODIS Above-Cloud AEROsol retrieval algorithm (MOD06ACAERO). MOD06ACAERO is presently a regional research algorithm able to retrieve aerosol optical thickness over clouds, in particular absorbing biomass burning aerosols overlying marine boundary layer clouds in the Southeastern Atlantic Ocean. The algorithm’s ability to provide aerosol information in cloudy conditions makes it a valuable source of information for modeling and climate studies n an area where current clear sky-only operational MODIS aerosol retrievals effectively have a data gap between the months of June and October. We use MCARS for a verification and closure study of the MOD06ACAERO algorithm. The purpose of this study is to develop a set of constraints a model developer might use during assimilation of MOD06ACAERO data. Our simulations indicate that the MOD06ACAERO algorithm performs well for marine boundary layer clouds in the SE Atlantic provided some specific screening rules are observed. For the present study, a combination of five simulated MODIS data granules was used for a dataset of 13.5 million samples with known input conditions. When pixel retrieval uncertainty was less than 30%, optical thickness of the underlying cloud layer was greater than 4 and scattering angle range within the cloud bow was excluded, MOD06ACAERO retrievals agreed with the underlying ground truth (GEOS-5 cloud and aerosol profiles used to generate the synthetic radiances) with a slope of 0.913, offset of 0.06, and RMSE=0.107. When only near-nadir pixels were considered (view zenith angle within +/-20 degrees) the agreement with source data further improved (0.977, 0.051 and 0.096 respectively). Algorithm closure was examined using a single case out of the five 38 used for verification. For closure, the MOD06ACAERO code was modified to use GEOS-5 temperature and moisture profiles as ancillary. Agreement of MOD06ACAERO retrievals with source data for the closure study had a slope of 0.996 with offset -0.007 and RMSE of 0.097 at pixel uncertainty level of less than 40%, illustrating the benefits of high-quality ancillary atmospheric data for such retrievals.

MODIS↗
NASA NTRSDate not supplied

Using Open Standards and NASA Open Source Simulation Tools to Model Artemis Base Camp Mission Timelines

The United States’ National Aeronautics and Space Administration (NASA) has announced that the Artemis Program will return humans to the Moon, establishing a persistent presence with the Artemis Base Camp (ABC), and extend human exploration to Mars. The NASA Exploration Systems Simulations (NExSyS) team at NASA’s Johnson Space Center is using internationally developed simulation interoperability standards and NASA open source simulation tools to support Artemis concept, analysis, designs, development, training, and ultimately operations. The NExSyS team has been tasked to support early ABC architecture and mission analysis using mission time lines developed by the crew operations mission planning team. The NExSyS team is developing a distributed simulation framework with initial Artemis element implementations to model the ABC mission timelines using the international simulation interoperability standard High Level Architecture (HLA), the Simulation Interoperability Standards Organization’s Space Reference Federation Object Model (SpaceFOM), the NASA open source Trick Simulation Environment, and another NASA open source interface package called TrickHLA. The ABC architecture is composed of a number of key surface elements and resources. Some examples of modeled elements (also known as entities) are landers, habitats, rovers, logistics carriers, and astronauts. Some examples of modeled transferable and consumable resources are power, water, oxygen, nitrogen, scientific samples, and food. These entities and resources are modeled in a collection of individual simulations called Federates. A coordinated collection of interoperable federates is called a Federation and when these federates are tied together in a coordinated simulation run, it is referred to as a Federation Execution. The federates communicate through HLA using data exchange formats defined by a collection of machine readable files called Federation Object Models (FOMs). These FOM files are based on extensions to the SpaceFOM. This enables the instantiation and sharing of objects and interactions between federates in the federation. These provide for entity and resource tracking, object transfer, and data collection. Federate interactions are used to trigger events and notify federates of entity or resource transfers. For the initial implementation, the constituent federates are Trick-based simulations that use TrickHLA to provide the required HLA-base interoperability. These Trick-based simulations provide the required modeling for the individual Artemis elements along with the associated element resources. These federates provide a means to explore traverses between surface elements and exploration sites as scheduled in a mission timeline and explore the affects traverse times have on the overall mission timeline. The mission time lines are modeled using a Trick input file event handling capabilities. Each timeline operation is handled as individual simulation events, and triggered based on previous event status, time of operation, and simulated task completions. In addition, the ABC Federation can be used to perform Monte Carlo analysis. The Monte Carlo tool can vary the inputs, timings, and malfunctions to show how various contingencies in the mission can affect the mission timeline.

Keaton Craig Dodd↗
NASA NTRS2022

An Adaptation of ISO 11204 using Customized Correction Grades to Mitigate Ambient Noise Effects when Computing Sonic Boom Loudness Levels

A spectral-based correction adapted from ISO 11204 [1] is investigated here to mitigate the effects of ambient noise contamination of sonic booms recorded by noise monitors during field tests. The algorithm from sections 5.4.2 and 7 of ISO 11204 is customized using six nonstandard correction grades in addition to implementing the two standardized grades described in ISO 11204. The six nonstandard grades allow for more aggressive correction of the levels of the sonic boom spectrum when they are proximate to the ambient spectrum. Of the eight correction grades, the most aggressive custom correction grade, termed “Custom F” here, performed best under the conditions that were studied. Consequently, “Custom F” is recommended for use when processing in-field recordings of X-59 sonic booms. To evaluate the eight correction grades, mock X-59 acoustic recordings were generated using predicted ground-level X-59 sonic booms. These ground-level waveforms were created by Doebler [2] by propagating nearfield CFD solutions of the X-59 C612A configuration to the ground using PCBoom [3] (please see Acknowledgements and Refs. [4, 5, 2, 6]). To generate the mock acoustic recordings from those ground-level waveforms, they were further modified using turbulence filters developed during the NASA SonicBAT effort [7], post boom noise audio clips from the NASA SonicBAT tests [7], and ambient noise from the NASA QSF18 test [8, 9]. These mock acoustic recordings enabled evaluation of the ambient noise mitigation methods since the proper loudness levels of the X-59 waveforms in absence of ambient noise are known. Specifically, these known levels provide a benchmark against which the corrected loudness levels are compared, where the corrected loudness levels are computed when ambient noise is present within the waveforms. Importantly, similar analyses using in-field recordings are not possible since the proper loudness levels of the sonic boom waveforms in absence of ambient noise are unknowable when analyzing in-field recordings. Consequently, if additional analyses of ambient noise mitigation methods are needed, then use of mock recordings like those used here is recommended.

Sonic boom↗
NASA NTRSDate not supplied

An Evaluation of Extended Reality Technologies for Use in Verification Testing at NASA 2024 HRP IWS Abstract

BACKGROUND At NASA, verification testing is the formal process of ensuring that a product conforms to requirements set by a project or program. Some verification methods, such as Demonstrations and Test, require either the end product or a mockup of the product with sufficient fidelity to stand-in for the product during the test. Traditionally, these mockups have been physical (e.g., foam-core and wood) but there is growing interest in exploring new methods for testing with these mockups. These methods include virtual reality (VR), mixed reality, and augmented reality which are collectively referred to as eXtended Reality (XR) technologies. VR has already been adopted and used by many in the aerospace industry as a tool for use in early design phases (e.g., developmental testing) and may have the most potential for use in verification tests. Benefits of using VR mockups offer cost effectiveness, ease of iteration, simulation of hazardous conditions (e.g., an egress through a hatch with smoke obscuring vision), and the ability to simulate microgravity conditions, which are challenging to do with physical mockups. However, the validity of test results obtained from VR mockup demonstrations or testing, compared to the current gold standard of physical mockups, remains uncertain. It is unlikely that there is one clean answer as there are many different types of verification outcomes and each XR technology must be evaluated on its own merits. This is not an issue during developmental testing as the design is still in flux and the total success of the design is not dependent upon the results of a developmental test. Verification tests, however, only happen once, assuming no change to the design, and the results are used to certify the product. Therefore, establishing the validity of XR mockup-based verification outcomes is essential before considering them for any use in verification tests. OBJECTIVE AND METHOD To address this concern, the Human Research Program has funded a project to explore and qualify how XR technologies might be used in verification demonstration and testing at NASA. Currently, we are conducting a review of the literature on the utilization of XR mockups for design activities, prototyping, and user testing. We are employing the Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis method to identify the pros, cons, and barriers to adoption of XR technologies for verification testing at NASA. Additionally, we are developing a framework to guide the deployment of XR mockups for verification tests. Building upon available evidence from the literature and subject-matter expert feedback, our goal for the framework is to provide guidelines for which forms of XR mockups are suitable for a given verification test, when only physical mockups should be employed and to highlight areas for which more evidence is needed. To further refine our framework and to contribute to the body of evidence, we are planning a lab-based experiment comparing a VR mockup to a physical twin for a set of select verification outcomes. ANTICIPATED RESULTS In this presentation, we will present the work we conducted to evaluate XR technologies for use in verification tests at NASA. We will summarize and report our findings from the SWOT analysis and our lab-based study, and we will present the current state of the XR Technologies for Verification Testing framework. We will conclude by summarizing remaining work and future directions for the project. Technologies for Verification Testing framework. We will conclude by summarizing remaining work and future directions for the project.

Extended Reality↗
NASA NTRSDate not supplied

Human-AI Collaboration Among Engineering and Design Professionals: Three Strategies of Generative AI Use

Designers are increasingly using Generative Artificial Intelligence (GenAI) in design processes; however, knowing how designers use GenAI--especially in professional design practice--is under-explored. This paper presents an ethnographic study of a design team at NASA that explores the natural variation of GenAI use across team members during a speculative design workflow. We aimed to uncover when, how, and why GenAI tools were or were not employed using ethnographic observations to map the team's speculative design process and follow-up interviews to provide deeper insights into team members' interactions (or lackthereof) with GenAI. Through inductive qualitative coding, our analysis revealed three strategies of GenAI use observed among professional engineers and designers--intimate co-design with GenAI, selective delegation to GenAI, and minimal use of GenAI--as well as factors that appeared to influence their decisions whether or not to use GenAI. This study proposes new theory in human-AI collaboration that sheds light on the strategies, rationale, and circumstances under which design professionals use GenAI. Future work that builds upon these insights include examining a larger sample size of engineering and design professionals in uncontrolled design process experiences and exploring the impact that design tasks, goals, and constraints have on a participants decision to leverage GenAI tools.

design practice↗
NASA NTRSDate not supplied

Observation of Deep Convective Cloud-Top Height and Vertical Temperature Structure of Hurricane Using Hyperspectral Infrared Sounder and its Single-Field-View Retrieval Products

Hurricanes, severe tropical cyclones (TC), or typhoons are significant natural disasters that often result in substantial loss of life and property damage. Numerous studies have indicated that changes in TC intensity are closely linked to deep convective clouds (DCC), with stronger TCs typically exhibiting higher cloud top heights (CTH) compared to weaker TCs. The CTH can help determine if a tropical depression is at the onset of rapid intensification based on case studies. Therefore, accurate determination of TC CTH will be greatly helpful for monitoring TC development and studying TC dynamics. One traditional and most common method to derive CHT from satellite observations is using the thermal brightness temperature in atmospheric channels to match the sounding temperature profile. However, it was found that thermally derived CTH has a lower bias of approximately 1 km, and this bias tends to worsen for the tallest clouds. A new method using the hyperspectral infrared sounder will be presented. From the measurements of Cross-track Infrared Sounder (CrIS) on S-NPP and J-1, along with radiative transfer simulations, we identified the inverted-V spectral feature in the ozone (O3) band (near 9.6 μm) corresponding to high clouds. The depth of the inverted-V can be used to estimate the CTH. Since the depth is computed using the peak absorption O3 channel and the nearby most transparent O3 channel in this O3 band, the uncertainties associated with cloud emissivity and scattering by cloud particles in the traditional method can be ignored. From several hurricane case studies, we found that the CHT derived using this method can accurately capture the structure of the cloud tops in the eyewall, spiral rainbands, and surrounding regions. For example, Hurricane Dorian on September 2, 2019, showed a nicely outward-sloping and circular shape eye cloud in the early morning, but the circular shape of the eyewall cloud became distorted in the afternoon. For various hurricanes we examined, the distribution of CHT for the eyewall clouds differed significantly. To better study the thermodynamic structure of hurricane clouds, this research will analyze the vertical temperature profiles from a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP), derived using CrIS and the Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1. SiFSAP has a spatial resolution of 15 km at nadir, which surpasses most global weather and climate models and other current operational sounding products. The combined use of ATMS and CrIS allows for retrievals near hurricane eyewalls and spiral rainbands. Wind fields from NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize transport, and comparisons between the model temperature and water vapor profiles with the corresponding SiFSAP products will also be provided.

SiFSAP↗
NASA NTRS2024

Shape Servoing of Deformable Objects Using Model Estimation and Barrier Lyapunov Function

An adaptive shape servoing control method is presented in this article to manipulate a deformable object into a desired shape in 3-D. A finite-point-based representation of the deformable object is used and the deformation Jacobian matrix is approximated using Fourier series basis functions. The unknown parameters of the deformation Jacobian are learned by using the velocity applied to a control point on the object and corresponding change of positions of the points describing the entire object. An integral concurrent learning (ICL)-based parameter update law is designed along with a constrained controller to satisfy the state constraints on the motion of the control point using Barrier Lyapunov function analysis. ICL-based parameter update law uses data history of velocity and corresponding positions of the points along with their current values. An efficient algorithm to update the history stack using singular value maximization is proposed based on the structure of the regressor matrix. Simulations using a physical simulator and experiments using a robot platform are performed to validate the performance of the proposed controller on two different deformable objects.

Vrithik Raj Guthikonda↗
NASA NTRS1975

CARETS: A prototype regional environmental information system. Volume 3: Toward a national land use information system

It is recommended that a national land use information system be established by an agency of the Federal Government. This recommendation comes at a time of increasing demand for scientific information in support of environmentally relevant land use planning and management at all levels of government. It is also a time when new airborne and spaceborne remote sensors, tested in cooperation with the National Aeronautics and Space Administration (NASA) and the Earth Resources Observation Systems (EROS) Program of the Department of the Interior, make possible the gathering of land use information rapidly and on an unprecedented scale. Furthermore, information handling technology is developing toward a capability to receive, store, and disseminate the huge quantities of data that would be involved. The recommendation for the national land use information system is based upon careful analysis of the results of remote sensing experiments funded by NASA, EROS, and the Geography Program of the Geological Survey, with specific examples drawn from the demonstration project known as the Central Atlantic Regional Ecological Test Site (CARETS). CARETS is cast in the framework of a regional land use information system, channeling the flow bf information generated in response to users' declaration of their needs, through stages dealing with remote sensing data gathering systems, data processing and land mensuration, calibration in-terms of environmental impact, and evaluation with feedback from users. The proposed system would develop and implement a unified approach to the description and interpretation of the changing uses of the nation's land resources, building upon the base of interagency and intergovernmental cooperation already achieved in the experimental work to date. The land use data base that is being derived from high-altitude aerial color infrared photography would be the initial component of the recommended system. High-altitude photographic coverage would immediately be extended to as much of the nation as possible as technological developments and economic considerations permit. The system would later expand to include multiple-sensor, multiple-platform data sources. Six system characteristics are recommended: (1) High capacity storage of data available for quick retrieval, inexpensive processing, and update, (2) provision of accuracy appropriate to the scale of survey or to the level of detail dictated by different types of management and decision requirements; (3) permanent, publicly accessible sensor records for historical interpretation; (4) compatibility of the recording, storage, and retrieval system with all types of inputs, from ground observer to satellite; (5) products of diverse formats and scales, responsive to user feedback; (6) and standardization of formats, scales, and storage inputs to permit nationwide comparability.

Land use mapping↗
NASA NTRS2013

Remaining Useful Life Estimation in Prognosis: An Uncertainty Propagation Problem

The estimation of remaining useful life is significant in the context of prognostics and health monitoring, and the prediction of remaining useful life is essential for online operations and decision-making. However, it is challenging to accurately predict the remaining useful life in practical aerospace applications due to the presence of various uncertainties that affect prognostic calculations, and in turn, render the remaining useful life prediction uncertain. It is challenging to identify and characterize the various sources of uncertainty in prognosis, understand how each of these sources of uncertainty affect the uncertainty in the remaining useful life prediction, and thereby compute the overall uncertainty in the remaining useful life prediction. In order to achieve these goals, this paper proposes that the task of estimating the remaining useful life must be approached as an uncertainty propagation problem. In this context, uncertainty propagation methods which are available in the literature are reviewed, and their applicability to prognostics and health monitoring are discussed.

Uncertainty Quantification↗
NASA NTRS2014

An Analysis of Earth Science Data Analytics Use Cases

The increase in the number and volume, and sources, of globally available Earth science data measurements and datasets have afforded Earth scientists and applications researchers unprecedented opportunities to study our Earth in ever more sophisticated ways. In fact, the NASA Earth Observing System Data Information System (EOSDIS) archives have doubled from 2007 to 2014, to 9.1 PB (Ramapriyan, 2009; and https:earthdata.nasa.govaboutsystem-- performance). In addition, other US agency, international programs, field experiments, ground stations, and citizen scientists provide a plethora of additional sources for studying Earth. Co--analyzing huge amounts of heterogeneous data to glean out unobvious information is a daunting task. Earth science data analytics (ESDA) is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. It can include Data Preparation, Data Reduction, and Data Analysis. Through work associated with the Earth Science Information Partners (ESIP) Federation, a collection of Earth science data analytics use cases have been collected and analyzed for the purpose of extracting the types of Earth science data analytics employed, and requirements for data analytics tools and techniques yet to be implemented, based on use case needs. ESIP generated use case template, ESDA use cases, use case types, and preliminary use case analysis (this is a work in progress) will be presented.

data analytics↗
NASA NTRS2019

Multimodel Analysis of Future Land Use and Climate Change Impacts on Ecosystem Functioning

Land use and climate changes both affect terrestrial ecosystems. Here, we used three combinations of Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1xRCP26, SSP3xRCP60, and SSP5xRCP85) as input to three dynamic global vegetation models to assess the impacts and associated uncertainty on several ecosystem functions: terrestrial carbon storage and fluxes, evapotranspiration, surface albedo, and runoff. We also performed sensitivity simulations in which we kept either land use or climate (including atmospheric CO2) constant from year 2015 on to calculate the isolated land use versus climate effects. By the 2080–2099 period, carbon storage increases by up to 87 ± 47 Gt (SSP1xRCP26) compared to present day, with large spatial variance across scenarios and models. Most of the carbon uptake is attributed to drivers beyond future land use and climate change, particularly the lagged effects of historic environmental changes. Future climate change typically increases carbon stocks in vegetation but not soils, while future land use change causes carbon losses, even for net agricultural abandonment (SSP1xRCP26). Evapotranspiration changes are highly variable across scenarios, and models do not agree on the magnitude or even sign of change of the individual effects. A calculated decrease in January and July surface albedo (up to −0.021 ± 0.007 and −0.004 ± 0.004 for SSP5xRCP85) and increase in runoff (+67 ± 6 mm/year) is largely driven by climate change. Overall, our results show that future land use and climate change will both have substantial impacts on ecosystem functioning. However, future changes can often not be fully explained by these two drivers and legacy effects have to be considered.

land use change↗