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NASA NTRSDate not supplied

TriTruss Packaging and Deployment Trade Study

An architecture and feasibility study of next generation In-Space Assembled Telescopes (iSAT) concluded that robotic in-space assembly of modular components is necessary to enable large (>15-meter diameter) primary apertures. The iSAT study recommended that the foundational structure be assembled from modular TriTruss modules that are packaged for launch, deployed on-orbit and robotically assembled into the final configuration. This paper will describe and summarize the results of a trade study that investigated viable concept of operations (ConOps) for the packaging and deployment (P&D) of individual planar TriTruss modules that could be assembled to form a large aperture iSAT. The ideal TriTruss P&D concept is defined as one that: allows for efficient packaging; has sufficient geometric versatility to be launch vehicle independent; provides a stiff and lightweight structure; has low mechanical complexity; and has component modularity. The P&D concept should allow for prelaunch subsystem or utility integration if required. The concept would be kinematically simple and be robotically deployed using a minimum number of specialized tools. In this first phase of an ongoing more comprehensive trade study, concepts were proposed and then evaluated based on initial metrics representing features of an ideal P&D concept. The P&D concepts evaluated are categorized as: core collapse, face collapse, and erectable structures. Sub-scale models were constructed to help understand the kinematics and mechanical complexity required to enable P&D. Based on a weighting scale, the most promising candidate P&D concepts have selected and will undergo more rigorous structural design, analysis, and testing in the study’s next phase. The ultimate goal of the comprehensive trade study will be to recommend a single TriTruss design and associated P&D concept that will be built and evaluated at NASA Langley Research Center’s In-Space Assembly Laboratory.

in-space assembly (ISA)↗
NASA NTRS2020

An Analysis of COVID-19’s Impact on U.S. Aviation

To better understand the effects of COVID-19 and prepare for crises in the future, the changes in the aviation industry during the pandemic were analyzed. Data was gathered on airlines’ economic status, passenger travel, air cargo, avionics manufacturing, and the environment. It was found that passenger air travel was severely depressed, dropping 96% in April 2020 compared to April 2019 [1]. Air cargo and manufacturing also felt the effects of the decrease in air traffic. In comparison to the previous year, air cargo capacity in July 2020 was down 28% [2], and manufacturing companies, such as Boeing, have seen more than a 10% decrease in revenue [3]. Many companies have adapted to the pandemic with new protocols and procedures, such as social distancing guidelines and using passenger planes as cargo planes. Based on these actions taken guidelines were created for future crises. The objective is to facilitate a faster recovery and a more prepared airspace system. Lastly, health guidelines and areas of research that are relevant after a global pandemic are outlined.

Trishala Jain↗
NASA NTRSDate not supplied

An Analysis of COVID-19’s Impact on U.S. Aviation

To better understand the effects of COVID-19 and prepare for crises in the future, the changes in the aviation industry during the pandemic were analyzed. Data was gathered on airlines’ economic status, passenger travel, air cargo, avionics manufacturing, and the environment. It was found that passenger air travel was severely depressed, dropping 96% in April 2020 compared to April 2019. Air cargo and manufacturing also felt the effects of the decrease in air traffic. In comparison to the previous year, air cargo capacity in July 2020 was down 28%, and manufacturing companies, such as Boeing, have seen more than a 10% decrease in revenue. Many companies have adapted to the pandemic with new protocols and procedures, such as social distancing guidelines and using passenger planes as cargo planes. Based on these actions taken guidelines were created for future crises. The objective is to facilitate a faster recovery and a more prepared airspace system. Lastly, health guidelines and areas of research that are relevant after a global pandemic are outlined.

Trishala Madhu Jain↗
NASA NTRSDate not supplied

How to Educate Decision Makers on the Value and Necessity of Modal Testing and Model Correlation: Tips for Young Engineers

Engineers need to effectively communicate the justification and value of their modal testing and model correlation in terminology familiar to decision makers as it relates to the program’s risk tolerance. This communication must relate to the program’s risk tolerance and the metrics used to judge the performance of both the program and individual decision makers. The challenge is the terminologies familiar to engineers and decision makers are quite different and seemingly unrelated. The engineering profession has developed a specific terminology to solve highly technical issues, which are many times themselves unique to very specific engineering problems. It is all too easy for engineers to believe that everyone in their organization, including the decision makers, has an intrinsic understanding of what they do and the value it brings to the program’s success. This is especially true for young engineers who have recently spent the last four plus years in an academic engineering learning environment, which has a highly technical research oriented atmosphere. Effective communication with decision makers is increasingly important as the technical breadth and practical program and project experience level for up and coming decision makers diminishes. It is not unusual for the decision makers to have technical knowledge in a domain different from structural dynamics (e.g., electronics or systems). Competition among satellite manufactures has increased the focus on programmatic cost and ability to deliver on schedule. NASA programs are also seeing more restrictive programmatic cost and schedule constraints, which impact both analysis and testing. It should also be noted that a comprehensive suite of tests are required to verify a satellite’s design capability with some margin. These tests include static strength verification tests, shock, acoustic, and vibration tests (sine and random) of systems, subsystems, and components. Each of these verification tests provide opportunities for model correlation and risk reduction. It is important to recognize dynamic loads/modal test models may not include all of the flight hardware (i.e., harness, coax, waveguides, connectors, etc.) and the previously mentioned tests are still required for qualification/verification of the design. This paper provides tips to young engineers on how to bridge this communications gap, have a better understanding of the environment in which decision makers operate, and assist them to better support successful missions. While this paper primarily focuses on modal testing and model correlation as related to spacecraft missions, the concepts and recommendations presented here are equally applicable to other fields such as aeronautics, automotive, power generation, etc.

Decision Maker↗
NASA NTRSDate not supplied

How to Educate Decision Makers on the Value and Necessity of Modal Testing and Model Correlation: Tips for Young Engineers

Engineers need to effectively communicate the justification and value of their modal testing and model correlation in terminology familiar to decision makers as it relates to the program’s risk tolerance. This communication must relate to the program’s risk tolerance and the metrics used to judge the performance of both the program and individual decision makers. The challenge is the terminologies familiar to engineers and decision makers are quite different and seemingly unrelated. The engineering profession has developed a specific terminology to solve highly technical issues, which are many times themselves unique to very specific engineering problems. It is all too easy for engineers to believe that everyone in their organization, including the decision makers, has an intrinsic understanding of what they do and the value it brings to the program’s success. This is especially true for young engineers who have recently spent the last four plus years in an academic engineering learning environment, which has a highly technical research oriented atmosphere. Effective communication with decision makers is increasingly important as the technical breadth and practical program and project experience level for up and coming decision makers diminishes. It is not unusual for the decision makers to have technical knowledge in a domain different from structural dynamics (e.g., electronics or systems). Competition among satellite manufactures has increased the focus on programmatic cost and ability to deliver on schedule. NASA programs are also seeing more restrictive programmatic cost and schedule constraints, which impact both analysis and testing. It should also be noted that a comprehensive suite of tests are required to verify a satellite’s design capability with some margin. These tests include static strength verification tests, shock, acoustic, and vibration tests (sine and random) of systems, subsystems, and components. Each of these verification tests provide opportunities for model correlation and risk reduction. It is important to recognize dynamic loads/modal test models may not include all of the flight hardware (i.e., harness, coax, waveguides, connectors, etc.) and the previously mentioned tests are still required for qualification/verification of the design. This paper provides tips to young engineers on how to bridge this communications gap, have a better understanding of the environment in which decision makers operate, and assist them to better support successful missions. While this paper primarily focuses on modal testing and model correlation as related to spacecraft missions, the concepts and recommendations presented here are equally applicable to other fields such as aeronautics, automotive, power generation, etc.

Decision Maker↗
NASA NTRS2023

Non-Gaussian Ensemble Filtering and Adaptive Inflation for Soil Moisture Data Assimilation

The rank histogram filter (RHF) and the ensemble Kalman filter (EnKF) are assessed for soil moisture estimation using perfect model (identical twin) synthetic data assimilation experiments. The primary motivation is to gauge the impact on analysis quality attributable to the consideration of non-Gaussian forecast error distributions. Using the NASA Catchment land surface model, the two filters are compared at 18 globally-distributed single-catchment locations for a 10-year experiment period. It is shown that both filters yield adequate estimates of soil moisture, with the RHF having a small but significant performance advantage. Most notably, the RHF systematically increases the normalized information contribution (NIC) score of the mean absolute bias by 0.05 over that of the EnKF for surface, root-zone and profile soil moisture. The RHF also increases the NIC score for the anomaly correlation of surface soil moisture by 0.02 over that of the EnKF (at a 5% significance level). Results also demonstrate that the performance of both filters is somewhat improved when the ensemble priors are adaptively inflated to offset the negative effects of systematic errors.

Soil moisture↗
NASA NTRS2022

Determining the Spectral Content of MOSES Images

The Multi-Order Solar Extreme Ultraviolet Spectrograph (MOSES) sounding rocket was launched from White Sands Missile Range on 2006 February 8th, to capture images of the Sun in the He ii 303.8 Å emission line. MOSES is a slitless spectrograph that forms images in multiple spectral orders simultaneously using a concave diffraction grating in an effort to measure line profiles over a wide field of view from a single exposure. Early work on MOSES data showed evidence of solar features composed of neither He ii 303.8 Å nor the nearby Si xi 303.3 Å spectral lines. We have built a forward model that uses cotemporal EIT images and the Chianti atomic database to fit synthetic images with known spectra to the MOSES data in order to quantify this additional spectral content. Our fit reveals a host of dim lines that alone are insignificant but combined contribute a comparable intensity to MOSES images as Si xi 303.3 Å. In total, lines other than He ii 303.8 Å and Si xi 303.3 Å contribute approximately 10% of the total intensity in the MOSES zero order image. This additional content, if not properly accounted for, could significantly impact the analysis of MOSES and similar slitless spectrograph data, especially those using a zero-order (undispersed) image. More broadly, this serves as a reminder that multilayer EUV imagers are sensitive to a host of weak contaminant lines.

Solar transition region↗
NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

Validation↗
NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

Validation↗
NASA NTRSDate not supplied

Non-Gaussian Ensemble Filtering and Adaptive Inflation for Soil Moisture Data Assimilation

The rank histogram filter (RHF) and the ensemble Kalman filter (EnKF) are assessed for soil moisture estimation using perfect model (identical twin) synthetic data assimilation experiments. The primary motivation is to gauge the impact on analysis quality attributable to the consideration of non-Gaussian forecast error distributions. Using the NASA Catchment land surface model, the two filters are compared at 18 globally distributed single-catchment locations for a 10-yr experiment period. It is shown that both filters yield adequate estimates of soil moisture, with the RHF having a small but significant performance advantage. Most notably, the RHF consistently increases the normalized information contribution (NIC) score of the mean absolute bias by 0.05 over that of the EnKF for surface, root-zone, and profile soil moisture. The RHF also increases the NIC score for the anomaly correlation of surface soil moisture by 0.02 over that of the EnKF (at a 5% significance level). Results additionally demonstrate that the performance of both filters is somewhat improved when the ensemble priors are adaptively inflated to offset the negative effects of systematic errors.

Rolf Reichle↗
NASA NTRS2012

Improved Impact of Atmospheric Infrared Sounder (AIRS) Radiance Assimilation in Numerical Weather Prediction

Improvements to global and regional numerical weather prediction (NWP) have been demonstrated through assimilation of data from NASA s Atmospheric Infrared Sounder (AIRS). Current operational data assimilation systems use AIRS radiances, but impact on regional forecasts has been much smaller than for global forecasts. Retrieved profiles from AIRS contain much of the information that is contained in the radiances and may be able to reveal reasons for this reduced impact. Assimilating AIRS retrieved profiles in an identical analysis configuration to the radiances, tracking the quantity and quality of the assimilated data in each technique, and examining analysis increments and forecast impact from each data type can yield clues as to the reasons for the reduced impact. By doing this with regional scale models individual synoptic features (and the impact of AIRS on these features) can be more easily tracked. This project examines the assimilation of hyperspectral sounder data used in operational numerical weather prediction by comparing operational techniques used for AIRS radiances and research techniques used for AIRS retrieved profiles. Parallel versions of a configuration of the Weather Research and Forecasting (WRF) model with Gridpoint Statistical Interpolation (GSI) that mimics the analysis methodology, domain, and observational datasets for the regional North American Mesoscale (NAM) model run at the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) are run to examine the impact of each type of AIRS data set. The first configuration will assimilate the AIRS radiance data along with other conventional and satellite data using techniques implemented within the operational system; the second configuration will assimilate AIRS retrieved profiles instead of AIRS radiances in the same manner. Preliminary results of this study will be presented and focus on the analysis impact of the radiances and profiles for selected cases.

Zavodsky, Bradley↗
NASA NTRS1984

Geological rhythms and cometary impacts

Time series analysis reveals two dominant, long-term periodicities approximately equal to 32 and 260 million years in the known series of geological and biological upheavals during the Phanerozoic Eon. The cycles of these episodes agree in period and phase with the cycles of impact cratering on Earth, suggesting that periodic comet impacts strongly influence Earth processes.

Rampino, M. R.↗
NASA NTRS1982

An analysis of the physical, chemical, optical, and historical impacts of the 1908 Tunguska meteor fall

An analysis is presented of the physical characteristics and photochemical aftereffects of the 1908 Tunguska explosive cometary meteor, whose physical manifestations are consistent with a five million ton object's entry into the earth's atmosphere at 40 km/sec. Aerodynamic calculations indicate that the shock waves emanating from the falling meteor could have generated up to 30 million tons of nitric oxide in the stratosphere and mesosphere. A fully interactive one-dimensional chemical-kinetics model of atmospheric trace constituents is used to estimate the photochemical consequences of such a large NO injection. The 35-45% hemispherical ozone depletion predicted by the model is in keeping with the 30 + or - 15% ozone variation reported for the first year after the Tunguska fall. Attention is also given to the optical anomalies which followed the event for indications of NO(x)-O(x) chemiluminescent emissions, NO2 solar absorption, and meteoric dust turbidity, along with possible climate changes due to the nearly one million tons of pulverized dust deposited in the mesosphere and stratosphere by the meteor.

Turco, R. P.↗
NASA NTRS2010

Finding Interstellar Particle Impacts on Stardust Aluminium Foils: The Safe Handling, Imaging, and Analysis of Samples Containing Femtogram Residues

Impact ionisation detectors on a suite of spacecraft have shown the direction, velocity, flux and mass distribution of smaller ISP entering the Solar System. During the aphelion segments of the Stardust flight, a dedicated collector surface was oriented to intercept ISP of beta = 1, and returned to Earth in January 2006. In this paper we describe the probable appeareance and size of IS particle craters from initial results of experimental impacts and numerical simulation, explain how foils are being prepared and mounted for crater searching by automated acquisition of high magnification electron images (whilst avoiding contamination of the foils) and comment on appropriate analytical techniques for Preliminary Examination (PE).

Kearsley, A. T.↗