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NASA NTRS2012

The Search for Life on Mars - Current Knowledge, Earth Analogues, and Principal Issues

For centuries, the planet Mars has been imagined as a possible abode for life. Serious searches for life's signatures began in the 19th century via ground-based visual astronomy that stimulated a vibrant fantasy literature but little lasting scientific knowledge. Modern scientific inquiry has emphasized the search for chemical signatures of life in the soil and rocks at the planet's surface, and via biomarker gases in the atmosphere. Today, investigations are based on high-resolution spectroscopy at Earth's largest telescopes along with planet orbiting and landed space missions. Methane has assumed central importance in these searches. Living systems produce more than 900/0 of Earth's atmospheric methane; the balance is of geochemical origin. Abundant methane is not expected in an oxidizing atmosphere such as Mars', and its presence would imply recent release - whether biological or geochemical. F or that reason, the quest for methane on Mars has been a continuing thread in the fabric of searches conducted since 1969. I will review aspects of the discovery and distribution of methane on Mars, and will mention ongoing extended searches for clues to its origin and destruction. On Earth, hydrogen (generated via serpentinization or radiolysis of water) provides an important 'fuel' for carbonate-reducing and sulphate-reducing biota (CH4 and H2S producers, respectively). Several such communities are known to reside at depth in continental domains (e.g., Lidy Hot Springs, Idaho; Witwatersrand Basin, S. Africa). If similar conditions exist in favourable locations on Mars, organisms similar to these could likely prosper there. Geologic (abiotic) production will also be mentioned, especially abiotic methane production associated with low-temperature serpentinization (e.g., terrestrial ophiolites). It is vitally important to pursue evidence for geochemical and biological production with equal vigour and intellectual weight lest unwanted and unintended bias contaminate the results. Finally, I will touch upon unresolved questions and issues posed by the methane detections.

Mumma, Michael J.↗

NASA NTRSDate not supplied

Phosphate Textural Diversity in CI Chondrites and C-Type Asteroids

Introduction: Apatite, Ca 5 (PO 4 ) 3 (CL/F/OH-), is a ubiquitous phosphate found throughout the solar system, including the most primitive solids, CI-chondrites [1,2] and related samples of carbonaceous asteroids Ryugu [3] and Bennu [4], returned by JAXA’s Hayabusa2 and NASA’s OSIRIS-REx missions, respectively. Apatite in these primitive solids is found as individual grains or mineral clusters and has been inferred to form from the hydrothermal sequence during cooling of their respective parent body or bodies. To better understand the formation history and reworking of these early phosphates we have undertaken a highly coordinated study of phosphate microstructures, geochemistry and U/Pb geochronology from a suite of CI meteorites and carbonaceous asteroid samples. These data have identified novel phosphate microstructures and complex relationships across a suite of apatite grains from the early solar system, indicating multiple episodes of growth and modification on the CI parent body(ies). Methods: Samples of CI chondrites, Alais, Ivuna, Orgueil, Oued Chebeika 002, Yamato (Y) 82162, Y980115, Y980134, and two chips of Hayabusa2 Ryugu particles (A0262 and C0263) have been acquired for analysis. The bulk texture of the samples were first scanned by X-ray Computed Tomography (XCT) using the Nikon XT H 320 within the XFACT facility at NASA JSC or the Xradia 620 Versa at the UTCT facility. Based on the identification of petrofabrics or features of interest from the XCT data, samples were chipped, oriented, potted in epoxy and thick sections were prepared. After anhydrously polishing the samples with silicon carbide and dry diamond powder down to 1 µm, the samples were ion polished using a Hitachi ArBlade. Energy dispersive Xray spectrometry (EDS) maps were collected to ID phosphates of interest using a JEOL 7900F SEM. The internal microstructures of identified phosphates were then mapped by electron backscatter diffraction (EBSD) using the JEOL 7900F. Based on the EDS and EBSD data, domains of interest were targeted for quantitative chemical analyses using a JEOL 8530 EPMA. Subsequently, in situ U-Pb and 207 Pb/ 206 Pb ages will be collected using a Cameca ims1290 secondary ion mass spectrometer at UCLA across a range of microstructures. Results: Apatite grains are ubiquitous throughout the CI chondrites and carbonaceous asteroid materials, found as individual grains, disseminated clusters or grain aggregates. Apatite grains are associated with serpentine, magnet-ite, and/or carbonate. Of particular interest, we have identified individual and aggregate polycrystalline grains ex-hibiting an internal ‘honeycomb’ texture (Fig. 1). Some of these grains appear overprinted by subsequent alteration while others remain unaltered. Apatite halogen sites are dominated by the missing component, assumed to be OH, and F, comparable to published values from Bennu, Ryugu and CM-chondrites [3-5]. However, the Yamato CI-like meteorites show a broader range of Cl values, and one grain from Alais is dominated by CL. Summary: Apatite growth features indicate a protracted and complex growth history, consistent with precipitation from an evolving fluid system. The ‘honeycomb’ texture identified in some CI meteorites is, to the best of our knowledge, the first report of such a microstructure in meteoritic phosphate. The microtextures and zoning will guide subsequent age analyses, to better constrain the formation and reworking of phosphate in CI(-like) materials. Acknowledgments: We thank the National Institute of Polar Research, Japan for samples of Y82162, 980115 and 980134 meteorites, ASU’s Buseck Center for Meteorite Studies for samples of Ivuna and Alais meteorites, and JAXA curation for chips of Ryugu material. This work was funded by NASA ROSES LARS grant 24-LARS24-0014. References: [1] Morlok et al., 2016, GCA 70:5371-5394. [2] Alfin g et al., 2019, Geochemistry 79:125532. [3] Nakamura et al. (2022) Science 379:1-15. [4] Seifert et al. (2026) MAPS 61:504-521. [5] Piralla et al. (2021) MAPS 56:809-828.

CI chondrites↗

NASA NTRS1999

Its a Wind, Its a Wave, Its Two Phenomena in One: Jerry Schubert, Superrotation, and the UV Markings on Venus

In the early 1970's, ground-based astronomers had already discovered that Ultraviolet (UV) cloud markings on Venus reappeared every 4 days. When radar evidence later revealed a 243-day rotation period for the solid planet, planetary scientists were faced with a quandary: Could the Venus atmosphere really move 60 times as fast as the planet below, or were the apparent movements of the UV features just an illusion caused by propagating waves? The former explanation seemed unlikely - a planet that hardly rotates should generate only a very sluggish circulation. The historical impact of Jerry Schubert's moving flame theory was twofold: It was the forerunner of current thermal tide explanations of the cloud-level superrotation, but it was also the first plausible mechanism for explaining a seemingly inconsistent set of observations. In 1974, Mariner 10 acquired UV images of the Venus clouds at unprecedented levels of detail. Although few have noted it, this began the shift of planetary atmospheric research primarily from the domain of astronomy to that of meteorology. Jerry was among the first scientists to apply terrestrial meteorology to the analysis of planetary data. At that time a young UCLA graduate student with plans to do research on mantle convection, but having flunked the solid earth geophysics section of his departmental comprehensive exam, was gently invited by Jerry to switch to atmospheric science. Jerry suggested that the Venus UV features could be revealing both superrotating winds and planetary-scale waves at the same time, and that we could distinguish the two by looking at motions on different spatial scales. This was my first science research lesson - the complexity of real geophysical systems. Over the next couple of years I was inculcated with Jerry's philosophy of a comprehensive, rigorous approach to research, which manifested itself as a scouring of the literature and the UCLA meteorology faculty to learn about every possible type of planetary-scale wave. The resulting identification of large-scale UV features on Venus as the product of Kelvin and Rossby-type wave motions was validated by extensive Pioneer Venus observations a decade later and remains one of the best examples of the use of terrestrial knowledge to understand other planets.

DelGenio, Anthony↗

NASA NTRS2000

Mineralogy, Petrology, Chemistry, and Ar-39 - Ar-40 and Ages of the Caddo County IAB Iron: Evidence for Early Partial Melt Segregation of a Gabbro Area Rich in Plagioclase-Diopside

We found coarse-grained gabbroic material rich in plagioclase and diopside in the Caddo County IAB iron meteorite. The polished thin sections studied were made from areas rich in Al and Ca detected by a micro-focus X-ray fluorescence (XRF) mapping technique. The gabbro is not a clast within a breccia, but rather this area is located mainly at silicate-metal boundaries only a few cm away from an area with fine-grained, ultramafic silicate similar to winonaites. Medium-grained orthopyroxene and olivine are found in transitional areas showing no disturbance of their crystalline textures. A vein-like region, starting at the area rich in fine-grained mafic silicate, extends towards the gabbroic area with a gradual increase in abundance of plagioclase and diopside. This texture and our accumulated knowledge of the formation mechanism of IAB/winonaltes meteorites, suggest that the gabbroic materials were formed by inhomogeneous segregation of partial melts of chondritic source materials. Compositional data on two mineralogically distinct samples of the gabbro-rich portion of the inclusion were obtained by INAA. Compared to an average of LAB silicate inclusions or winonaites, the Caddo County gabbro is enriched in the incompatible lithophile elements Na, Ca, Sc, REE and Hf, which is consistent with a melt origin for the gabbro. The cosmogenic space exposure age of Caddo County (511 Ma) is significantly younger than exposure ages of some other IAB meteorites, An 39Ar-40Ar age determination of the gabbroic material indicates a series of upward steps in age from 4.516 Ga to 4.523 Ga, with a few high temperature ages up to 4.54 Ga. The older age could approximate the primary recrystallization age of silicates. The stepped Ar age spectrum may indicate differences in Ar closure temperatures during slow cooling of -2-20'C/Myr in the parent body. Alternatively, the younger Ar-Ar ages may date a shock event which occurred while Caddo County was hot and which also created textures such as a linear metal vein with rounded zigzag walls in a diopside crystal and slightly miss-oriented rounded plagioclase domain.

Takeda, Hiroshi↗

NASA NTRS2008

Ground-based SMART-COMMIT Measurements for Studying Aerosol and Cloud Properties

From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations cover large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite data sets. The development and deployment of SMARTCOMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile facilities are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instruments fall into three categories: flux radiometer, radiance sensor and in-situ probe. In this paper, we will demonstrate the capability of SMART-COMMIT in recent field campaigns (e.g., CRYSTAL-FACE, UAE 2, BASEASIA, NAMMA) that were designed and executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., biomass-burning smoke, airborne dust) and cirrus clouds. We envision robust approaches in which well-collocated ground-based measurements and space-borne observations will greatly advance our knowledge of extensive aerosols and clouds.

Tsay, Si-Chee↗

NASA NTRS2014

Forecasting Sensorimotor Adaptability from Baseline Inter-Trial Correlations

One of the greatest challenges surrounding adaptation to the spaceflight environment is the large variability in symptoms, and corresponding functional impairments, from one crewmember to the next. This renders preflight training and countermeasure development difficult, as a "one-size-fits-all" approach is inappropriate. Therefore, it would be highly advantageous to know ahead of time which crewmembers might have more difficulty adjusting to the novel g-levels inherent to spaceflight. Such knowledge could guide individually customized countermeasures, which would enable more efficient use of crew time, both preflight and inflight, and provide better outcomes. The primary goal of this project is to look for a baseline performance metric that can forecast sensorimotor adaptability without exposure to an adaptive stimulus. We propose a novel hypothesis that considers baseline inter-trial correlations, the trial-to-trial fluctuations in motor performance, as a predictor of individual sensorimotor adaptive capabilities. To-date, a strong relationship has been found between baseline inter-trial correlations and adaptability in two oculomotor systems. For this project, we will explore an analogous predictive mechanism in the locomotion system. METHODS: Baseline Inter-trial Correlations: Inter-trial correlations specify the relationships among repeated trials of a given task that transpire as a consequence of correcting for previous performance errors over multiple timescales. We can quantify the strength of inter-trial correlations by measuring the decay of the autocorrelation function (ACF), which describes how rapidly information from past trials is "forgotten." Processes whose ACFs decay more slowly exhibit longer-term inter-trial correlations (longer memory processes), while processes whose ACFs decay more rapidly exhibit shorterterm inter-trial correlations (shorter memory processes). Longer-term correlations reflect low-frequency activity, which is more easily measured in the frequency domain. Therefore, we use the power spectrum (PS), which is the Fourier transform of the ACF, to describe our inter-trial correlations. The decay of the PS yields a straight line on a log-log frequency plot, which we quantify by Beta = - (slope of PS on log-log axes). Hence, Beta is a measure of the strength of inter- trial correlations in the baseline data. Larger Beta values are indicative of longer inter-trial correlations. Experimental Approach: We will begin by performing a retrospective analysis of treadmill-gait adaptation data previously collected by Dr. Bloomberg and colleagues. Specifically, we will quantify the strength of inter-trial correlations in the baseline step cadence and heart rate data and compare it to the locomotor adaptability performance results already described by these investigators. Incorporating these datasets will also allow us to explore the applicability of (and potential limitations surrounding) the use of Beta in forecasting physiological performance. We will also perform a new experiment, in which Beta will be derived from baseline data collected during over-ground (non-treadmill) walking, which will enable us to consider locomotor performance, through the parameter Beta, under the most functionallyrelevant, natural gait condition. This experiment will incorporate two baseline and five post-training over-ground locomotion tests to explore the consistency and potential adaptability of the Beta values themselves. HYPOTHESES: We hypothesize that the strength of baseline inter-trial correlations of step cadence and heart rate will relate to locomotor adaptability. Specifically, we anticipate that individuals who show weaker longer-term inter-trial correlations in baseline step cadence data will be the better adaptors, as step cadence can be modified in real-time (i.e., online corrections are an inherent property of the locomotor system; analogous to results observed in the VOR). Conversely, because heart rate is not altered mid-beat, we expect that individuals who demonstrate stronger longer-term correlations in heart rate will be the better adaptors (analogous to results observed in the saccadic system). CONCLUSIONS: At the conclusion of this project we hope to uncover a baseline predictor of locomotor adaptability. If our hypotheses hold true, our results will demonstrate that the temporal structure of baseline behavioral data contains important information that may aid in forecasting adaptive capacities. The ability to predict such adaptability in the sensorimotor system has significant implications for spaceflight, where astronauts must adjust their motor programs following a change in g-level to retain movement accuracy.

Beaton, K. H.↗

NASA NTRSDate not supplied

Cognitive Engineering in Training: Monitoring and Pilot-Automation Coordination in Complex Environments

This paper reports our investigation of flight path monitoring in aviation. We interviewed experienced pilots to understand the knowledge and skills underlying effective monitoring and we developed an example learning environment to improve these skills. We explore how design of pilot training and learning, like the design of interfaces and of the underlying automation, benefits from cognitive engineering methods and perspective. In aviation, monitoring and managing flight path are critical activities. The influences on flight path are complex and come from the autoflight system, from control actions by the pilot, and from external factors, including weather and Air Traffic Control (ATC). Indeed, inadequate flight path monitoring is a current aviation concern as it has been implicated in accidents and incidents. Effective piloting depends on strategies for noticing, understanding, and anticipating these influences to monitor and manage flight path. Lack of such skills reduces pilots' ability to maintain safety margin and resilience. Although flightdeck automation is intended to aid pilot understanding and prediction, the Fight Management Systems (FMS) can mislead as well as aid the pilot's understanding and projection of what will happen. In dynamic conditions, FMS predictions may be based on old or incomplete information. Understanding such vulnerabilities is an important part of pilot-autoflight coordination. The learning environment we developed is designed to help pilots proactively monitor and manage flight path. We consider how a broad cognitive engineering approach might inform the "what" and "how" of learning in dynamic work domains.

pilot-monitoring↗

NASA NTRS2019

Deep Learning Method for Detecting Precursors to Adverse Events

With the recent advancements in Deep Learning methods, the ability to model large complex heterogeneous data sets are fundamentally changing industry and research. Coupled with hardware improvements, and ease of implementation, a wide variety of deep neural network architectures can quickly be developed to solve a sweeping range of problems such as: object detection in images, automatic healthcare diagnosis using heterogenous data sources, real time language translating and sentence prediction, upscaling low resolution images, and forecasting of multivariate timeseries. Generally, many of these architectures outperform classical machine learning approaches in their respective tasks, however, this typically comes at a cost of interpretability. These black box algorithms generally suffer from lack of transparency in both model complexity as well as the rationale behind the prediction. This lack of comprehension, is driving an emerging area of interest in “Explainable AI”. An algorithm called: “Deep Temporal Multiple Instance Learning”1 was a recently developed to identify precursors to adverse events and has been applied in the aviation domain. The deep learning architecture is designed to capture the evolution of the probability of the outcome over the time preceding the adverse event using a multiple instance learning approach as illustrated in Figure 1. Precursors are defined when the probability of the event has exceeded a threshold at some point in the timeseries, at which point, a sensitivity analysis is performed to determine contributing factors. The contributing factors are used to explain and define the precursor during the periods where the probability score is high. The identified contributing factors are then presented to subject matter experts to provide objective insights into the leading factors associated with the particular adverse event. The algorithm has been tested on flight data from a commercial airline and has the ability to discover precursors to known adverse events that take the form of safety critical operations, such as unstable approach events on final approach. Apart from detecting precursors to adverse events, the converse can also be leveraged to discover corrective actions. These positive actions manifest themselves as periods in the timeseries when the precursor score has been lowered from an elevated state; meaning that if the system had been left uncorrected, it would have eventually reached the adverse event state. Characterizing these state changes can help identify successful interventions that may not have been known before. Policy makers and procedure designers can use this additional knowledge to craft more safety and efficient resilient procedures for future operations and therefore improve the overall performance of the National Airspace.

Matthews, Bryan L.↗

NASA NTRS2019

Soil Moisture Data Assimilation to Estimate Irrigation Water Use

Knowledge of irrigation is essential to support food security, manage depleting water resources, and comprehensively understand the global water and energy cycles. Despite the importance of understanding irrigation, little consistent information exists on the amount of water that is applied for irrigation. In this study, we develop and evaluate a new method to predict daily to seasonal irrigation magnitude using a particle batch smoother data assimilation approach, where land surface model soil moisture is applied in different configurations to understand how characteristics of remotely sensed soil moisture may impact the performance of the method. The study employs a suite of synthetic data assimilation experiments, allowing for systematic diagnosis of known error sources. Assimilation of daily synthetic soil moisture observations with zero noise produces irrigation estimates with a seasonal bias of 0.66% and a correlation of 0.95 relative to a known truth irrigation. When synthetic observations were subjected to an irregular overpass interval and random noise similar to the Soil Moisture Active Passive satellite (0.04 cm(exp 3) cm(exp -3)), irrigation estimates produced a median seasonal bias of <1% and a correlation of 0.69. When systematic biases commensurate with those between NLDAS‐2 land surface models and Soil Moisture Active Passive are imposed, irrigation estimates show larger biases. In this application, the particle batch smoother outperformed the particle filter. The presented framework has the potential to provide new information into irrigation magnitude over spatially continuous domains, yet its broad applicability is contingent upon identifying new method(s) of determining irrigation schedule and correcting biases between observed and simulated soil moisture, as these errors markedly degraded performance.

R Abolafia-Rosenzweig↗

NASA NTRS2015

Human Systems Integration (HSI) Practitioner's Guide

The NASA/SP-2015-3709, Human Systems Integration (HSI) Practitioner's Guide, also known as the "HSIPG," provides a tool for implementing HSI activities within the NASA systems engineering framework. The HSIPG is written to aid the HSI practitioner engaged in a program or project (P/P), and serves as a knowledge base to allow the practitioner to step into an HSI lead or team member role for NASA missions. Additionally, this HSIPG is written to address the role of HSI in the P/P management and systems engineering communities and aid their understanding of the value added by incorporating good HSI practices into their programs and projects. Through helping to build a community of knowledgeable HSI practitioners, this document also hopes to build advocacy across the Agency for establishing strong, consistent HSI policies and practices. Human Systems Integration (HSI) has been successfully adopted (and adapted) by several federal agencies-most notably the U.S. Department of Defense (DoD) and the Nuclear Regulatory Commission (NRC)-as a methodology for reducing system life cycle costs (LCCs). These cost savings manifest themselves due to reductions in required numbers of personnel, the practice of human-centered design, decreased reliance on specialized skills for operations, shortened training time, efficient logistics and maintenance, and fewer safety-related risks and mishaps due to unintended human/system interactions. The HSI process for NASA establishes how cost savings and mission success can be realized through systems engineering. Every program or project has unique attributes. This HSIPG is not intended to provide one-size-fits-all recommendations for HSI implementation. Rather, HSI processes should be tailored to the size, scope, and goals of individual situations. The instructions and processes identified here are best used as a starting point for implementing human-centered system concepts and designs across programs and projects of varying types, including manned and unmanned, human spaceflight, aviation, robotics, and environmental science missions. The practitioner using this guide should have expertise in Systems Engineering or other disciplines involved in producing systems with anticipated human interactions. (See section 1.6 of this guide for further discussion on HSI discipline domains.) The HSIPG provides an "HSI layer" to the NASA Systems Engineering Engine (SEE), detailed in NASA Procedural Requirement (NPR) 7123.1B, NASA Systems Engineering Processes and Requirements, and further explained in NASA/SP-2007-6105, Systems Engineering Handbook (see HSIPG Table 2.2-1, NASA Documents with HSI Content, for specific references and document versions).

Zumbado, Jennifer Rochlis↗

NASA NTRS2002

The D3 Middleware Architecture

DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid-dynamics) model executions. DARWIN captures, stores and indexes data; manages derived knowledge (such as visualizations across multiple datasets); and provides an environment for designers to collaborate in the analysis of test results. DARWIN is an interesting application because it supports high-volumes of data. integrates multiple modalities of data display (e.g., images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and views of data. Here we provide an overview of the architecture of D3, the third generation of DARWIN. Earlier versions of DARWIN were characterized by browser-based interfaces and a hodge-podge of server technologies: CGI scripts, applets, PERL, and so forth. But browsers proved difficult to control, and a proliferation of computational mechanisms proved inefficient and difficult to maintain. D3 substitutes a pure-Java approach for that medley: A Java client communicates (though RMI over HTTPS) with a Java-based application server. Code on the server accesses information from JDBC databases, distributed LDAP security services, and a collaborative information system. D3 is a three tier-architecture, but unlike 'E-commerce' applications, the data usage pattern suggests different strategies than traditional Enterprise Java Beans - we need to move volumes of related data together, considerable processing happens on the client, and the 'business logic' on the server-side is primarily data integration and collaboration. With D3, we are extending DARWIN to handle other data domains and to be a distributed system, where a single login allows a user transparent access to test results from multiple servers and authority domains.

Walton, Joan↗

NASA NTRSDate not supplied

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. Crew members operating independently during long duration space exploration missions will require a clinical decision support system (CDSS) to increase autonomy by augmenting their knowledge, skills and abilities in different scenarios. Significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities are needed to increase crew autonomy and self-reliance in decision making and task performance. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. Clinical decision support (CDS) presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. A comprehensive crew health and performance CDSS is required to augment crew capability and will be used in different scenarios for several reasons. In general, the CDSS’s role is to assist the crew in prevention, detection, diagnosis and treatment of crew health and performance related conditions that may arise in exploration spaceflight. For example, CDSS would assist a high acuity scenario such as a heart attack by supplying clear instructions, vital signs and treatment reminders. A lower severity scenario such as kidney stone risk could interface to vehicle systems and display more complex predictive data during a diagnosis. A CDSS needs to contribute to successful missions by maintaining a high performing crew who can potentially exhibit countless medical conditions related to derangements from the space environment (sleep, cognition, nutrition and exercise) as well as conditions intrinsic to humans anywhere. While supporting the crew’s ability to make sound clinical decisions is desirable in any mission, it is essential for exploration missions with significant communication delays, no evacuation capability, and extended exposure to the flight environment. Such missions correspond with medical Level of Care V (LOC V), the highest level specified in NASA-STD-3001. The project focuses on CDS implementation research to derive requirements for LOC V, where the need for increased autonomy results in new practices and the inclusion of non-clinical data, such as vehicle environmental measures and physical exercise results, from other human and vehicle domains and advanced analytics. The CDS project describes how the CDSS is intended to be used by defining concepts of operations (ConOps). The process to derive ConOps focuses on increased autonomy that reduces the likelihood and consequences of accepted medical conditions. These crew health and performance inputs are grouped by common datasets and analysis models. Use cases are derived to research new clinical scenarios, architectural development and workflows. Implementation research is conducted with protypes to inform assumptions and derive requirements. The project also establishes how externally developed analysis and approaches can be added to expand a clinical decision support system and thus highlight how a comprehensive system can be globally developed with collaborators. This presentation will cover example scenarios from the CDS ConOps and the method to derive them. One example scenario will be CDSS alerting an increased kidney stone risk during a mission, with diagnosis and treatment options provided during the intervention.

clinical decision support↗

NASA NTRSDate not supplied

Clinical Decision Support - Concepts of Operation

clinical decision support↗

NASA NTRS2009

Reaction Wheel Disturbance Model Extraction Software - RWDMES

The RWDMES is a tool for modeling the disturbances imparted on spacecraft by spinning reaction wheels. Reaction wheels are usually the largest disturbance source on a precision pointing spacecraft, and can be the dominating source of pointing error. Accurate knowledge of the disturbance environment is critical to accurate prediction of the pointing performance. In the past, it has been difficult to extract an accurate wheel disturbance model since the forcing mechanisms are difficult to model physically, and the forcing amplitudes are filtered by the dynamics of the reaction wheel. RWDMES captures the wheel-induced disturbances using a hybrid physical/empirical model that is extracted directly from measured forcing data. The empirical models capture the tonal forces that occur at harmonics of the spin rate, and the broadband forces that arise from random effects. The empirical forcing functions are filtered by a physical model of the wheel structure that includes spin-rate-dependent moments (gyroscopic terms). The resulting hybrid model creates a highly accurate prediction of wheel-induced forces. It accounts for variation in disturbance frequency, as well as the shifts in structural amplification by the whirl modes, as the spin rate changes. This software provides a point-and-click environment for producing accurate models with minimal user effort. Where conventional approaches may take weeks to produce a model of variable quality, RWDMES can create a demonstrably high accuracy model in two hours. The software consists of a graphical user interface (GUI) that enables the user to specify all analysis parameters, to evaluate analysis results and to iteratively refine the model. Underlying algorithms automatically extract disturbance harmonics, initialize and tune harmonic models, and initialize and tune broadband noise models. The component steps are described in the RWDMES user s guide and include: converting time domain data to waterfall PSDs (power spectral densities); converting PSDs to order analysis data; extracting harmonics; initializing and simultaneously tuning a harmonic model and a wheel structural model; initializing and tuning a broadband model; and verifying the harmonic/broadband/structural model against the measurement data. Functional operation is through a MATLAB GUI that loads test data, performs the various analyses, plots evaluation data for assessment and refinement of analysis parameters, and exports the data to documentation or downstream analysis code. The harmonic models are defined as specified functions of frequency, typically speed-squared. The reaction wheel structural model is realized as mass, damping, and stiffness matrices (typically from a finite element analysis package) with the addition of a gyroscopic forcing matrix. The broadband noise model is realized as a set of speed-dependent filters. The tuning of the combined model is performed using nonlinear least squares techniques. RWDMES is implemented as a MATLAB toolbox comprising the Fit Manager for performing the model extraction, Data Manager for managing input data and output models, the Gyro Manager for modifying wheel structural models, and the Harmonic Editor for evaluating and tuning harmonic models. This software was validated using data from Goodrich E wheels, and from GSFC Lunar Reconnaissance Orbiter (LRO) wheels. The validation testing proved that RWDMES has the capability to extract accurate disturbance models from flight reaction wheels with minimal user effort.

Blaurock, Carl↗

NASA NTRS2017

A New Architecture for Visualization: Open Mission Control Technologies

Open Mission Control Technologies (MCT) is a new architecture for visualisation of mission data. Driven by requirements for new mission capabilities, including distributed mission operations, access to data anywhere, customization by users, synthesis of multiple data sources, and flexibility for multi-mission adaptation, Open MCT provides users with an integrated customizable environment. Developed at NASAs Ames Research Center (ARC), in collaboration with NASAs Advanced Multimission Operations System (AMMOS) and NASAs Jet Propulsion Laboratory (JPL), Open MCT is getting its first mission use on the Jason 3 Mission, and is also available in the testbed for the Mars 2020 Rover and for development use for NASAs Resource Prospector Lunar Rover. The open source nature of the project provides for use outside of space missions, including open source contributions from a community of users. The defining features of Open MCT for mission users are data integration, end user composition and multiple views. Data integration provides access to mission data across domains in one place, making data such as activities, timelines, telemetry, imagery, event timers and procedures available in one place, without application switching. End user composition provides users with layouts, which act as a canvas to assemble visualisations. Multiple views provide the capability to view the same data in different ways, with live switching of data views in place. Open MCT is browser based, and works on the desktop as well as tablets and phones, providing access to data anywhere. An early use case for mobile data access took place on the Resource Prospector (RP) Mission Distributed Operations Test, in which rover engineers in the field were able to view telemetry on their phones. We envision this capability providing decision support to on console operators from off duty personnel. The plug-in architecture also allows for adaptation for different mission capabilities. Different data types and capabilities may be added or removed using plugins. An API provides a means to write new capabilities and to create data adaptors. Data plugins exist for mission data sources for NASA missions. Adaptors have been written by international and commercial users. Open MCT is open source. Open source enables collaborative development across organizations and also makes the product available outside of the space community, providing a potential source of usage and ideas to drive product design and development. The combination of open source with an Apache 2 license, and distribution on GitHub, has enabled an active community of users and contributors. The spectrum of users for Open MCT is, to our knowledge, unprecedented for mission software. In addition to our NASA users, we have, through open source, had users and inquires on projects ranging from Internet of Things, to radio hobbyists, to farming projects. We have an active community of contributors, enabling a flow of ideas inside and outside of the space community.

Trimble, Jay↗

NASA NTRSDate not supplied

Nancy Grace Roman Space Telescope Observatory Implementation and Challenges

NASA’s Nancy Grace Roman Space Telescope (Roman), previously referred to as Wide Field Infrared Survey Telescope (WFIRST), was named after Dr. Nancy Grace Roman, an astronomer and NASA pioneer of modern space-based astronomy who is known as the “mother of the Hubble Space Telescope”. Roman is a deep space infrared observatory with a Hubble-sized telescope and wide field of view instrument (greater than 100 times that of Hubble’s) that will conduct a high latitude time-domain survey, a high latitude imaging and spectroscopic survey, and a galactic bulge time-domain survey to characterize dark energy and expand the census of exoplanets in our galaxy while allowing a broad range of astrophysics research. Roman will also demonstrate exoplanet coronagraphy with active wave front control technology and provide general investigator programs for the science community. Roman is finishing the critical design phase and is planning for launch in 2026. It will operate in a quasi-halo orbit about Sun-Earth L2, 1.5 million kilometers from Earth, for a five-year primary mission life. The Observatory features an Optical Telescope Assembly with an existing, repurposed 2.4m primary mirror, a Wide Field Instrument with a focal plane array comprised of 18 HgCdTe near-infrared detectors and a grism, prism and filter elements for imaging and spectroscopy in support of the primary surveys, as well as a Coronagraph instrument technology demonstration with starlight suppression technology for direct imaging and spectroscopy of exoplanets. The telescope is mounted to the Instrument Carrier composite truss structure which also optically meters each instrument, includes a Launch Load and Vibration Isolation System to provide passive isolation of spacecraft jitter sources while also supporting the payload during launch and is attached to the Spacecraft Bus. The Spacecraft also includes a Solar Array Sunshield ,Deployable Aperture Cover, Lower Instrument Sunshade, High Gain Antenna System, and Outer Barrel Assembly. Figure 1 shows an overview of the Roman Observatory. When fully integrated, Roman will be the largest Observatory assembled and tested at NASA’s Goddard Space Flight Center. Figure 1. Roman Observatory Overview Development of scientific satellites is challenging by nature, as the pursuit to broaden scientific knowledge always pushes the boundary of what has come before. The implementation of the Roman mission is a prime example and expected challenges have been augmented by the foundational decision to use the existing telescope components, developed in the early 2000s by another Government agency for a different application. Other unique aspects of the Roman mission, such as its survey nature, the vast amount of data required to meet science objectives, and packaging of the Observatory elements around the existing telescope components, create constrained design spaces that drive competing requirements across Observatory subsystems. Given these challenges, systems engineering has been a critical discipline in balancing implementation decisions for the Roman mission and will continue to play a key role going forward. This paper will discuss details of the Roman Observatory configuration, as well as some of the systems engineering challenges and the decision-making process used to mature the Roman Space Telescope preliminary design to implementation.

Lisa Ml Bartusek↗

NASA NTRS1994

Technology Benefit Estimator (T/BEST): User's Manual

The Technology Benefit Estimator (T/BEST) system is a formal method to assess advanced technologies and quantify the benefit contributions for prioritization. T/BEST may be used to provide guidelines to identify and prioritize high payoff research areas, help manage research and limited resources, show the link between advanced concepts and the bottom line, i.e., accrued benefit and value, and to communicate credibly the benefits of research. The T/BEST software computer program is specifically designed to estimating benefits, and benefit sensitivities, of introducing new technologies into existing propulsion systems. Key engine cycle, structural, fluid, mission and cost analysis modules are used to provide a framework for interfacing with advanced technologies. An open-ended, modular approach is used to allow for modification and addition of both key and advanced technology modules. T/BEST has a hierarchical framework that yields varying levels of benefit estimation accuracy that are dependent on the degree of input detail available. This hierarchical feature permits rapid estimation of technology benefits even when the technology is at the conceptual stage. As knowledge of the technology details increases the accuracy of the benefit analysis increases. Included in T/BEST's framework are correlations developed from a statistical data base that is relied upon if there is insufficient information given in a particular area, e.g., fuel capacity or aircraft landing weight. Statistical predictions are not required if these data are specified in the mission requirements. The engine cycle, structural fluid, cost, noise, and emissions analyses interact with the default or user material and component libraries to yield estimates of specific global benefits: range, speed, thrust, capacity, component life, noise, emissions, specific fuel consumption, component and engine weights, pre-certification test, mission performance engine cost, direct operating cost, life cycle cost, manufacturing cost, development cost, risk, and development time. Currently, T/BEST operates on stand-alone or networked workstations, and uses a UNIX shell or script to control the operation of interfaced FORTRAN based analyses. T/BEST's interface structure works equally well with non-FORTRAN or mixed software analysis. This interface structure is designed to maintain the integrity of the expert's analyses by interfacing with expert's existing input and output files. Parameter input and output data (e.g., number of blades, hub diameters, etc.) are passed via T/BEST's neutral file, while copious data (e.g., finite element models, profiles, etc.) are passed via file pointers that point to the expert's analyses output files. In order to make the communications between the T/BEST's neutral file and attached analyses codes simple, only two software commands, PUT and GET, are required. This simplicity permits easy access to all input and output variables contained within the neutral file. Both public domain and proprietary analyses codes may be attached with a minimal amount of effort, while maintaining full data and analysis integrity, and security. T/BESt's sotware framework, status, beginner-to-expert operation, interface architecture, analysis module addition, and key analysis modules are discussed. Representative examples of T/BEST benefit analyses are shown.

Generazio, Edward R.↗

NASA NTRS2012

PheniX: A New Vision for the Hard X-ray Sky

We are proposing a mission devoted to high energy X-ray astronomy that is based on a focusing telescope operating in the 1-200 keV energy range but optimized for the hard X-ray range. The main scientific topics concern: Physics of compact objects: The proximity of compact objects provides a unique laboratory to study matter and radiation in extreme conditions of temperature and density in strong gravitational environment. The emission of high energy photons from these objects is far from being understood. The unprecedented sensitivity in the high energy domain will allow a precise determination of the non-thermal processes at work in the vicinity of compact objects. The full 1-200 keV energy coverage will be ideal to disentangle the emission processes produced in the spacetime regions most affected by strong-gravity, as well as the physical links: disk-thermal emission-iron line-comptonisation-reflection-non-thermal emission-jets. Neutron stars-magnetic field-cyclotron lines: Time resolved spectroscopy (and polarimetry) at ultra-high sensitivity of AXP, milliseconds pulsars and magnetars will give new tools to study the role of the synchrotron processes at work in these objects. Cyclotron lines-direct measurement of magnetic filed-equation of state constraints-short bursts-giant flares could all be studied with great details. AGN: The large sensitivity improvement will provide detailed spectral properties of the high energy emission of AGN's. This will give a fresh look to the connection between accretion and jet emission and will provide a new understanding of the physical processes at work. Detection of high-redshift active nuclei in this energy range will allow to introduce an evolutionary aspect to high-energy studies of AGN, probing directly the origin of the Cosmic X-ray Background also in the non-thermal range (> 20 keV). Element formation-Supernovae: The energy resolution achievable for this mission (<0.5 keV) and a large high energy effective area are ideally suited for the 44Ti line study (68 and 78 keV). This radioactive nuclei emission will give an estimate of their quantities and speed in their environment. In addition the study of the spatial structure and spectral emission of SNR will advance our knowledge of the dynamics of supernovae explosions, of particles acceleration mechanisms and how the elements are released in the interstellar medium. Instrumental design: The progress of X-ray focusing optics techniques allows a major step in the instrumental design: the collecting area becomes independent of the detection area. This drastically reduces the instrumental background and will open a new era. The optics will be based on depth-graded multi-layer mirrors in a Wolter I configuration. To obtain a significant effective area in the hundred of keV range a focal length in the 40-50 meters range (attainable with a deployable mast) is needed. In addition such a mission could benefit from recent progress made on mirror coating. We propose to cover the 1-200 keV energy range with a single detector, a double-sided Germanium strip detector operating at 80 K. The main features will be: (a) good energy resolution (.150 keV at 5 keV and <.5 keV at 100 keV), (b) 3 dimensional event localization with a low number of electronic chains, (c) background rejection by the 3D localization, (d) polarisation capabilities in the Compton regime.

PHENIX↗