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NASA NTRS2017

The First Twenty Years (1994 2014) of Ozone Soundings from Rapa Nui (27 deg S, 109 deg W, 51 m a.s.l.)

Ozone (O3) soundings have been performed on Easter Island or Rapa Nui (27 8S, 109 8W, 51 m a.s.l.) since 1994 as part of the Global Atmospheric Watch Programme of the World Meteorological Organization. In this work, we analyze 260 soundings compiled over the period 19942014, and make the data available for the international community. We characterize O3 profiles over this remote area of the Pacific by means of statistical analyses that consider, on the one hand, a traditional climatology that describes the data in terms of seasonal cycles based on monthly averages and, on the other hand, a process-oriented analysis based on self-organizing maps. Our analyses show the influence of both tropical and subtropical/mid-latitude air masses at Rapa Nui. The former occurs in summer and fall when convective conditions prevail, and the latter in late winter and spring when subsiding conditions are recurrent. The occurrence of stratospheric intrusions in late winter and spring in connection with deep troughs and the presence of the subtropical jet stream is also apparent in the data set. The tropospheric ozone column is in good agreement with the corresponding data derived from satellites but with a systematic overestimate of summer and fall values. There is evidence of an upward trend in ozone near the surface, which suggests the impact of local pollution. We look forward to an enhancement of the Rapa Nui observing site, given its location that offers a privileged position to observe climate change over the sparsely sampled and vast South Pacific Ocean.

tropical and subtropical/mid-latitude air masses↗
NASA NTRS2017

Time and Measurement Days

Questions in data analysis involving the concepts of time and measurement are often pushed into the background or reserved for a philosophical discussion. Some examples are: a) Is causality a consequence of the laws of physics, or can the arrow of time be reversed? b) Can we determine the arrow of time of an event? c) Do we need the continuum hypothesis for the underlying function in any measurement process? d) Can we say anything about the analyticity of the underlying process of an event? e) Would it be valid to model a non-analytical process as function of time? f) What are the implications of all these questions for classical Fourier techniques? However, in the age of big data gathered either from space missions supplying ultra-precise long time series, or e.g. LIGO data from the ground, the moment to bring these questions to the foreground seems arrived. The limitations of our understanding of some fundamental processes is emphasized by the lack of solution for problems open for more than 2 decades, such as the non-detection of solar g-modes, or the modal identification of main sequence stellar pulsators like delta Scuti stars. Flicker noise or 1/f noise, for example, attributed in solar-like stars to granulation, is analyzed mostly only to apply noise reduction techniques, neither considering the classical problem of 1/f noise that was introduced a 100 years ago, nor taking into account ergodic or non-ergodic solutions that make inapplicable spectral analysis techniques in practice. This topic was discussed by Nicholas W. Watkins during the ITISE meeting held in Granada in 2016. There he presented preliminary results of his research on Mandelbrot's related work. We reproduce here his quotation of Mandelbrot (1999) "There is a sharp contrast between a highly anomalous ("non-white") noise that proceeds in ordinary clock time and a noise whose principal anomaly is that it is restricted to fractal time", suggesting a connection with the above proposed topics that could be phrased as the following additional questions:a) Is self-organized criticality (SOC) frequent in astrophysical phenomena? b) Could all fractals in nature be considered stochastic? c) Could we establish mathematical/physical relationships between chaotic and fractal behaviors in time series? d) Could the differences between fractals and chaos in terms of analyticity be used to understand the residuals of the fitting of stellar light curves? In this meeting we would like to approximate these problems from a holistic and multidisciplinary perspective, taking into account not only technical issues but also the deeper implications. In particular the concept of connectivity (introduced in Pascual-Granado et al. A&A, 2015) could be used to implement, within the framework of ARMA processes, an "arrow of time" (see attached document), and so studying the possible implications in the concept of time as envisaged by Watkins.

data analysis↗
NASA NTRS2017

Ice Roughness and Thickness Evolution on a Swept NACA 0012 Airfoil

Several recent studies have been performed in the Icing Research Tunnel (IRT) at NASA Glenn Research Center focusing on the evolution, spatial variations, and proper scaling of ice roughness on airfoils without sweep exposed to icing conditions employed in classical roughness studies. For this study, experiments were performed in the IRT to investigate the ice roughness and thickness evolution on a 91.44-cm (36-in.) chord NACA 0012 airfoil, swept at 30-deg with 0deg angle of attack, and exposed to both Appendix C and Appendix O (SLD) icing conditions. The ice accretion event times used in the study were less than the time required to form substantially three-dimensional structures, such as scallops, on the airfoil surface. Following each ice accretion event, the iced airfoils were scanned using a ROMER Absolute Arm laser-scanning system. The resulting point clouds were then analyzed using the self-organizing map approach of McClain and Kreeger to determine the spatial roughness variations along the surfaces of the iced airfoils. The resulting measurements demonstrate linearly increasing roughness and thickness parameters with ice accretion time. Further, when compared to dimensionless or scaled results from unswept airfoil investigations, the results of this investigation indicate that the mechanisms for early stage roughness and thickness formation on swept wings are similar to those for unswept wings.

glaze icing↗
NASA NTRS2017

Solar Activity Across the Scales: From Small-Scale Quiet-Sun Dynamics to Magnetic Activity Cycles

Observations as well as numerical and theoretical models show that solar dynamics is characterized by complicated interactions and energy exchanges among different temporal and spatial scales. It reveals magnetic self-organization processes from the smallest scale magnetized vortex tubes to the global activity variation known as the solar cycle. To understand these multiscale processes and their relationships, we use a two-fold approach: 1) realistic 3D radiative MHD simulations of local dynamics together with high resolution observations by IRIS, Hinode, and SDO; and 2) modeling of solar activity cycles by using simplified MHD dynamo models and mathematical data assimilation techniques. We present recent results of this approach, including the interpretation of observational results from NASA heliophysics missions and predictive capabilities. In particular, we discuss the links between small-scale dynamo processes in the convection zone and atmospheric dynamics, as well as an early prediction of Solar Cycle 25.

Solar↗
NASA NTRS2018

Power-Law Statistics of Driven Reconnection in the Magnetically Closed Corona

Numerous observations have revealed that power-law distributions are ubiquitous in energetic solar processes. Hard X-rays, soft X-rays, extreme ultraviolet radiation, and radio waves all display power-law frequency distributions. Since magnetic reconnection is the driving mechanism for many energetic solar phenomena, it is likely that reconnection events themselves display such power-law distributions. In this work, we perform numerical simulations of the solar corona driven by simple convective motions at the photospheric level. Using temperature changes, current distributions, and Poynting fluxes as proxies for heating, we demonstrate that energetic events occurring in our simulation display power-law frequency distributions, with slopes in good agreement with observations. We suggest that the braiding-associated reconnection in the corona can be understood in terms of a self-organized criticality model driven by convective rotational motions similar to those observed at the photosphere.

Knizhnik, K. J.↗
NASA NTRS2018

Is Water Necessary for Life?

The universality of water as the solvent for life is usually justified by its role in supporting the rich organic chemistry. It has been pointed out, however, that even richer synthetic chemistry is possible in other organic solvents. Does it mean that water is not necessary for life? Here, other, essential criteria for solvent for life that have not been sufficiently considered are discussed. In biological systems, complex molecules are not only constantly synthesized but also degraded. Solvent-mediated degradation is essential for regulating cell content, preventing overcrowding and allowing for recycling organic material. Achieving a balance between synthetic and degradative processes is facile in water, but not in many other organic liquids. Thus, the so-called “water paradox” according to which water is both necessary to life and toxic to biopolymer synthesis might not be paradoxical at all. The machinery of life is based on non-covalent interactions that do not involve making or breaking chemical bonds. Their strength needs to be properly tuned. If they are too weak, there might be undesired response to natural fluctuations of physical or chemical parameters. If they are too strong, the kinetics and energetics of cellular processes could adversely influenced. The solvent must allow for balancing these interactions, which provides strong, universal constraints on the medium for life. Water influences non-covalent interactions mainly by two mechanisms. First, it reduces strong, electrostatic interactions between molecules, chemical groups or atoms carrying electric charge or dipole. Second, it induces the hydrophobic effect, the tendency to remove non-polar (hydrophobic) molecules and groups from direct contact with aqueous solution and, instead, interact with each other. In living systems, the hydrophobic effect is largely responsible for self-organization of molecules to more complex structures, such as aggregation of lipid molecules to form biological membranes and protein folding. Water exists as stable liquid in a large temperature range, and the hydrophobic effects are a consequence of the temperature insensitivity of essential properties of its liquid state. In summary, water accomplishes an amazing feat – it reduces strong interactions between dissolved species and simultaneously increases the strength of weak interactions, bringing all of them to the right range. Once we consider not only synthetic capabilities but also other required traits of the solvent for life, no viable alternative to water is currently known.

Life↗
NASA NTRS2018

Serious Gaming for Building a Basis of Certification via Trust and Trustworthiness of Autonomous Systems

Autonomous systems governed by a variety of adaptive and nondeterministic algorithms are being planned for inclusion into safety-critical environments, such as unmanned aircraft and space systems in both civilian and military applications. However, until autonomous systems are proven and perceived to be capable and resilient in the face of unanticipated conditions, humans will be reluctant or unable to delegate authority, remaining in control aided by machine-based information and decision support. Proving capability, or trustworthiness, is a necessary component of certification. Perceived capability is a component of trust. Trustworthiness is an attribute of a cyber-physical system that requires context-driven metrics to prove and certify. Trust is an attribute of the agents participating in the system and is gained over time and multiple interactions through trustworthy behavior and transparency. Historically, artificial intelligence and machine learning systems provide answers without explanation - without a rationale or insight into the machine “thinking”. In order to function as trusted teammates, machines must be able to explain their decisions and actions. This transparency is a product of both content and communication. NASA’s Autonomy Teaming & TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project seeks to build a basis for certification of autonomous systems via establishing metrics for trustworthiness and trust in multi-agent team interactions, using AI (Artificial Intelligence) explainability and persistent modeling and simulation, in the context of mission planning and execution, with analyzable trajectories. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ATTRACTOR modeling and simulation environment is similar to online gaming environments in which player (aka agent) participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual agent’s active participation. This persistent simulation environment will accommodate individual agents, groups of self-organizing agents, and large-scale infrastructure behavior. The effects of the emerging adaptation and coevolution can be observed and measured to building a basis of measurable trustworthiness and trust, toward certification of safety-critical autonomous systems.

Allen, B. Danette↗
NASA NTRS2017

Observations, Modeling, and Predictions of Solar Activity From the Deep Interior to the Corona

Solar activity is a manifestation of magnetic self-organization processes that involve complex dynamical coupling of various layers of the Sun acting over a broad range of spatial and temporal scales. Synergy of observational, theoretical, and modeling efforts is key to understanding solar activity variation, dynamics, and evolution and to developing reliable physics-based forecasts of long-term solar cycles and short-term activity manifestations, “seasons of solar activity”, such as periods of enhanced flaring and CME activity. The session welcomes observers, modelers, and theoreticians to share their results and ideas and to discuss current challenges, development of emerging fields (such as data assimilation), and the analysis of historical and modern observational data using theoretical modeling, interpretations, and predictions.

Deep Interior↗
NASA NTRS2020

Material Remodelling and Unconventional Gaits Facilitate Locomotion of a Robophysical Rover Over Granular Terrain

Autonomous robots and vehicles must occasionally recover from locomotion failure in loosely consolidated granular terrain. Recent mobility challenges led NASA Johnson Space Center to develop a prototype robotic lunar rover Resource Prospector 15 (RP15) capable of wheeled, legged, and crawling behavior. To systematically understand performance of such a device, we developed a scaled-down rover robot and studied its locomotion on slopes of dry and wet granular media. Addition of a cyclic legged gait to the robot’s wheel spinning action changes the robot dynamics from that of a wheeled vehicle to a locomotor paddling through frictional fluid. Granular drag force measurements and modified Resistive Force Theory facilitate modeling of such dynamics. A peculiar gait strategy that agitates and cyclically reflows grains under the robot allows it to ‘swim’ up loosely consolidated hills. Whereas substrate disturbance typically hinders locomotion in granular media, the multi-mode design of RP15 and a diversity of possible gaits facilitate formation of self-organized localized frictional fluids that enable effective robust transport.

Siddharth Shrivastava↗
NASA NTRSDate not supplied

Detecting And Characterizing Archetypes of Unintended Consequences in Engineered Systems

When designing engineered systems, the potential for unintended consequences of design policies or design decisions exists despite best intentions. Conditions that might cause the formation of unintended consequences are often known only in hindsight. However, since these conditions are associated with a single event, it is difficult to uncover the general patterns of conditions leading to unintended consequences. In this research, patterns of conditions associated with unintended consequences are learned from historical data and represented in the form of archetypes. While previous work using systems theoretic modeling has identified high-level archetypes, this work leverages a self-organizing map to learn archetypes of unintended consequences from human-tagged risk factors in a large data set of lessons learned from adverse events at NASA. The sixty-six identified archetypes contain patterns of conditions such as complexity and human-machine interaction associated with the formation of unintended consequences. To validate the archetypes, a sample of the archetypes is represented using system dynamics in order to illustrate that the identified archetypes are specialized versions of known high-level archetypes of unintended consequences. While the research is based upon a specific dataset, the archetypes apply to any engineered system and the pattern of leading indicators open a new path to manage unintended consequences and mitigate the magnitude of potentially adverse outcomes.

Hannah S Walsh↗
NASA NTRS2019

Improved assessment of mangrove forests in Sundarbans East Wildlife Sanctuary using WorldView 2 and TanDEM-X high resolution imagery

Recent developments of remote sensing techniques which can capture both the structure and function of the ecosystem provide a more representative view of the landscape. These unique Earth observations were used to help improve traditional forestry surveys by providing species-specific land cover classes for mangrove forests in the Sundarbans East Wildlife Sanctuary. By combining optical data from WorldView2 (WV2; 2 m pixel) and a canopy height model derived using radar data from TanDEM-X (TDX; 12 m pixel), we identified nine mangrove and five non-mangrove classes by following an Iterative Self-Organizing Data Analysis Algorithm. Three dominant mangrove species accounted for nearly 50% of the sanctuary. Heritieria fomes disproportionately covered the largest area at 43%, overturning previous field-based estimates of Excoecaria agallocha dominance. E. agallocha and Sonneratia apetala, covered 3% and 1.47% of the sanctuary, respectively. Four mixed species classes were also identified with clear vegetation zonation patterns that trended toward species homogeneity with increasing distance from shore. The overall land cover accuracy (WV2: 89.33%; WV2-TDX: 89.89%), the Kappa Coefficient (WV2:0.88; WV2-TDX: 0.89) and change statistics between WV2 and WV2-TDX landcover classifications indicate that the WV2 imagery can separate mangrove community types without structural data. The combination of the land cover classifications and the canopy height model indicated that H. fomes were not only the most dominant forest but also, on average, the tallest (12.3 m) among the other eight mangrove types. Our large-scale mapping with high resolution optical and radar platforms can capture subtle changes in mangrove vegetation and canopy structural gradients more accurately and be used to monitor biodiversity changes and Aichi Biodiversity Targets and Indicators, which would contribute to biodiversity policy updating.

Md Mizanur Rahman↗
NASA NTRS2022

Advances and Challenges in Observations and Modeling of the Global-Sun Dynamics and Dynamo

Computational heliophysics has shed light on the fundamental physical processes inside the Sun, such as the differential rotation, meridional circulation, and dynamo-generation of magnetic fields. However, despite the substantial advances, the current results of 3D MHD simulations are still far from reproducing helioseismic inferences and surface observations. The reason is the multi-scale nature of the solar dynamics, covering a vast range of scales, which can-not be solved with the current computational resources. In such a situation, significant progress has been achieved by the mean-field approach, based on the separation of small-scale turbulence and large-scale dynamics. The mean-field simulations can reproduce solar observations, qualitatively and quantitatively, and uncover new phenomena. However, they do not reveal the complex physics of large-scale convection, solar magnetic cycles, and the magnetic self-organization that causes sunspots and solar eruptions. Thus, developing a synergy of these approaches seems to be a necessary but very challenging task.

SMD↗
NASA NTRS2023

Adaptive Independent Verification and Validation (IV&V) Reduces Risk of Software Impacting Safety in Artemis Missions

The National Aeronautics and Space Administration (NASA) is asking more of its human spaceflight programs than ever before through the collective Artemis Missions. The NASA Independent Verification and Validation (IV&V) Program contributes to NASA’s human spaceflight goals by providing IV&V services for NASA’s critical spacecraft and ground software. The IV&V Program is tasked with providing assurance from both individual and integrated mission software perspectives. The Artemis IV&V organization is actively supporting six distinct development efforts: Orion, the Space Launch System (SLS), Exploration Ground Systems (EGS), Mission Control Center (MCC), the Lunar Gateway, and the Human Landing System (HLS), representing a wide diversity of developer organizations, management structures, and development approaches. With much of this extremely complex flight and ground software being essential to human safety both on the ground and in space, Artemis IV&V is likewise challenged to provide more value-added assurance to future Artemis missions within a constrained budget. To meet this challenge, Artemis IV&V employs a variety of novel and evolving “Adaptive IV&V” approaches for planning and executing IV&V analysis to increase both the efficiency and effectiveness of the IV&V Program’s assurance activities, and to address the difficulties imposed by assuring software for a large, highly integrated, multi-mission enterprise managed and executed by physically and organizationally distinct programs. Instilling agile principles like iterative planning cycles, self-organizing teams, and regular retrospectives, into IV&V planning and execution has led to a more rapid turnaround of a minimum viable assurance product and allowed for increased alignment of assurance activities with development progress. Adopting an assurance case methodology has led to greater consistency and clearer communication of assurance design and provided a foundation for long-term maintenance of assurance plans, products, and results across missions. The IV&V-developed Assurance / Safety Case Analytical Network (A-SCAN) framework and tool has enabled the quantification and tracking of system/software risk and confidence. These confidence measures provide a means to repeatedly express the impact of planned and completed assurance work and the remaining residual risk. Applied as part of a “Follow-the-Risk” organizational ethos, this allows consistent rightsizing of analysis rigor and intensity commensurate with the perceived risk of defects, as well as appropriate targeting of the highest risk areas of the software to find safety issues before they can manifest. Finally, the development of the IV&V Advanced Risk Reduction Integrated Software Test and Operations Tri-program Lightweight Environment (ARRISTOTLE), an integrated software-only simulation of Orion, SLS, and EGS systems, has made it possible to independently test integrated pad and flight scenarios and inject faults to observe how the Artemis multi-program, mission software behaves in degraded modes and in response to hazards. These adaptive IV&V investments have enabled Artemis IV&V to become more efficient and effective in IV&V planning and execution and respond more readily to changes in the risk landscape, increasing the breadth and depth of risk reduction possible within the available resources. Residual risk tracking allows IV&V to communicate more effectively with stakeholders, both internal and external at all levels, and inform key decision-making personnel. This evolving assurance design approach provides IV&V surety that work is performed in the highest risk, most value-added areas of the software, to keep our astronauts and ground crews safe and ensure mission success.

Gerek A Whitman↗
NASA NTRS2023

Adaptive Independent Verification and Validation (IV&V) Reduces Risk of Software Impacting Safety in Artemis Missions

The National Aeronautics and Space Administration (NASA) is asking more of its human spaceflight programs than ever before through the collective Artemis Missions. The NASA Independent Verification and Validation (IV&V) Program contributes to NASA’s human spaceflight goals by providing IV&V services for NASA’s critical spacecraft and ground software. The IV&V Program is tasked with providing assurance from both individual and integrated mission software perspectives. The Artemis IV&V organization is actively supporting six distinct development efforts: Orion, the Space Launch System (SLS), Exploration Ground Systems (EGS), Mission Control Center (MCC), the Lunar Gateway, and the Human Landing System (HLS), representing a wide diversity of developer organizations, management structures, and development approaches. With much of this extremely complex flight and ground software being essential to human safety both on the ground and in space, Artemis IV&V is likewise challenged to provide more value-added assurance to future Artemis missions within a constrained budget. To meet this challenge, Artemis IV&V employs a variety of novel and evolving “Adaptive IV&V” approaches for planning and executing IV&V analysis to increase both the efficiency and effectiveness of the IV&V Program’s assurance activities, and to address the difficulties imposed by assuring software for a large, highly integrated, multi-mission enterprise managed and executed by physically and organizationally distinct programs. Instilling agile principles like iterative planning cycles, self-organizing teams, and regular retrospectives, into IV&V planning and execution has led to a more rapid turnaround of a minimum viable assurance product and allowed for increased alignment of assurance activities with development progress. Adopting an assurance case methodology has led to greater consistency and clearer communication of assurance design and provided a foundation for long-term maintenance of assurance plans, products, and results across missions. The IV&V-developed Assurance / Safety Case Analytical Network (A-SCAN) framework and tool has enabled the quantification and tracking of system/software risk and confidence. These confidence measures provide a means to repeatedly express the impact of planned and completed assurance work and the remaining residual risk. Applied as part of a “Follow-the-Risk” organizational ethos, this allows consistent rightsizing of analysis rigor and intensity commensurate with the perceived risk of defects, as well as appropriate targeting of the highest risk areas of the software to find safety issues before they can manifest. Finally, the development of the IV&V Advanced Risk Reduction Integrated Software Test and Operations Tri-program Lightweight Environment (ARRISTOTLE), an integrated software-only simulation of Orion, SLS, and EGS systems, has made it possible to independently test integrated pad and flight scenarios and inject faults to observe how the Artemis multi-program, mission software behaves in degraded modes and in response to hazards. These adaptive IV&V investments have enabled Artemis IV&V to become more efficient and effective in IV&V planning and execution and respond more readily to changes in the risk landscape, increasing the breadth and depth of risk reduction possible within the available resources. Residual risk tracking allows IV&V to communicate more effectively with stakeholders, both internal and external at all levels, and inform key decision-making personnel. This evolving assurance design approach provides IV&V surety that work is performed in the highest risk, most value-added areas of the software, to keep our astronauts and ground crews safe and ensure mission success.

Gerek Whitman↗
NASA NTRSDate not supplied

Detection of CH 4 Hotspots from NASA’s GEOS Composition Analysis System

Recent research indicates that 8 to 12% of the global oil and gas production methane emissions could be attributed to ultra-emitters, which result in high concentration ‘hotspots’ near point sources. Identifying these emissions in near real time provides useful information to the policy makers and private industry, who are working to reduce their impact. To meet this need, scientists are increasingly analyzing satellite data from the TROPOspheric Monitoring Instrument (TROPOMI) instrument aboard ESA’s Sentinel 5-Precursor mission. While direct analysis of TROPOMI level 2 swath data has been successful in identifying some large emission events, identifying hotpots is challenging because of the imaging noise due to a variety of artifacts and limits in daily coverage. Here we explore possible methodologies to detect methane hotspots using a new, gap-filled, and temporally continuous methane product from NASA’s Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS), which assimilates column averaged methane mole fractions from the TROPOMI with capabilities to assimilate other remote sensing measurements. The CoDAS has been expanded from a heritage of stratospheric composition and carbon dioxide assimilation allowing for the support of regional modeling, validation with non-coincident operations, and merging variety of datasets. The current work mainly explores Observing System Simulation Experiments with methane GEOS simulations without assimilation to prepare the groundwork for further experiments with assimilated TROPOMI. First, known hotspots based on the known inventory are identified to demonstrate the capability of the system to point out emission hotspots. In the next step, a variety of machine learning techniques such as Self-Organizing Maps and Deep Learning are explored to automate detection of the plumes. Finally, a few approaches to quantify emissions from the identified hotspots are presented and are evaluated against the inventory. The effort is directed toward a future evaluation of the CoDAS based methane monitoring system’s ability to successfully detect and quantify hotspots.

Nikolay Balashov↗