Results for “environmental context” — Page 13

NASA NTRS2017

A Water Rich Mars Surface Mission Scenario

In an on-going effort to make human Mars missions more affordable and sustainable, NASA continues to investigate the innovative leveraging of technological advances in conjunction with the use of accessible Martian resources directly applicable to these missions. One of the resources with the broadest utility for human missions is water. Many past studies of human Mars missions assumed a complete lack of water derivable from local sources. However, recent advances in our understanding of the Martian environment provides growing evidence that Mars may be more "water rich" than previously suspected. This is based on data indicating that substantial quantities of water are mixed with surface regolith, bound in minerals located at or near the surface, and buried in large glacier-like forms. This paper describes an assessment of what could be done in a "water rich" human Mars mission scenario. A description of what is meant by "water rich" in this context is provided, including a quantification of the water that would be used by crews in this scenario. The different types of potential feedstock that could be used to generate these quantities of water are described, drawing on the most recently available assessments of data being returned from Mars. This paper specifically focuses on sources that appear to be buried quantities of water ice. (An assessment of other potential feedstock materials is documented in another paper.) Technologies and processes currently used in terrestrial Polar Regions are reviewed. One process with a long history of use on Earth and with potential application on Mars - the Rodriguez Well - is described and results of an analysis simulating the performance of such a well on Mars are presented. These results indicate that a Rodriguez Well capable of producing the quantities of water identified for a "water rich" human mission are within the capabilities assumed to be available on the Martian surface, as envisioned in other comparable Evolvable Mars Campaign assessments. The paper concludes by capturing additional findings and describing additional simulations and tests that should be conducted to better characterize the performance of the identified terrestrial technologies for accessing subsurface ice, as well as the Rodriguez Well, under Mars environmental conditions.

Hoffman, Stephen J.↗

NASA NTRS2024

Crew Health and Performance Integrated Data Architecture (CHP-IDA) Project

BACKGROUND: Future Human Exploration missions introduce a new paradigm as crews move further from the resupply and near real-time ground support typical of Low Earth Orbit missions today. Without immediate support from ground-based personnel, exploration crews will be more reliant on inflight data and technology to respond to emergencies and anomalies. A data architecture to support a new generation of technologies, employing advanced analytical and predictive modeling techniques, is needed to enable crew autonomy. OVERVIEW: The Crew Health and Performance Integrated Data Architecture (CHP-IDA) project funded by NASA’s Exploration Medical Integrated Product Team (XMIPT) is laying a foundation for future in-flight informatics by providing a back-end architecture for collecting, storing, and integrating multiple sources of data generated by and around the crew. CHP-IDA provides a platform for common data models and Application Programming Interfaces to access, integrate, process, and display CHP data (e.g., environmental, exercise, medical, sleep, performance, etc.). This will facilitate the increased situation awareness and decision support required by the crew and remote support of exploration missions. This presentation will describe the currently ongoing effort to develop and evaluate a path-to-flight concept of the CHP-IDA software and its core capabilities. Current integrations will be discussed, including analytics for Extravehicular Activity metabolic rate and data ingestion from a multi-functional integrated medical device. The presentation will also provide examples of scenarios used to demonstrate the CHP-IDA through human-in-the-loop test bed activities as well as examples of appropriate system performance metrics. DISCUSSION: Today, in-flight data is often siloed, unsynchronized, and largely inaccessible in real time. Many data sets require manual entry and/or data transfer between vehicles and the ground. These issues contribute to risks in supporting exploration medical capabilities. The CHP-IDA is a back-end data system providing core capabilities needed for timely and meaningful data insights across CHP domains to crew and remote personnel to enable increased crew autonomy. Future work includes collaboration with additional CHP domains, new technology integrations, and further demonstrations of the IDA within different vehicle and communication latency contexts. LEARNING OBJECTIVES 1. The audience will understand that the CHP-IDA is a back-end system, providing a platform to facilitate access, promote decision tools, and provide meaningful insights to crew and to remote stakeholders during exploration missions. 2. The audience will gain insight into human-centered research and activities used to discover CHP domain data needs and pain points and how this information is used to guide development of the IDA.

Exploration↗

NASA NTRS2004

Monitoring Change in Temperate Coniferous Forest Ecosystems

The primary goal of this research was to improve monitoring of temperate forest change using remote sensing. In this context, change includes both clearing of forest due to effects such as fire, logging, or land conversion and forest growth and succession. The Landsat 7 ETM+ proved an extremely valuable research tool in this domain. The Landsat 7 program has generated an extremely valuable transformation in the land remote sensing community by making high quality images available for relatively low cost. In addition, the tremendous improvements in the acquisition strategy greatly improved the overall availability of remote sensing images. I believe that from an historical prespective, the Landsat 7 mission will be considered extremely important as the improved image availability will stimulate the use of multitemporal imagery at resolutions useful for local to regional mapping. Also, Landsat 7 has opened the way to global applications of remote sensing at spatial scales where important surface processes and change can be directly monitored. It has been a wonderful experience to have participated on the Landsat 7 Science Team. The research conducted under this project led to contributions in four general domains: I. Improved understanding of the information content of images as a function of spatial resolution; II. Monitoring Forest Change and Succession; III. Development and Integration of Advanced Analysis Methods; and IV. General support of the remote sensing of forests and environmental change. This report is organized according to these topics. This report does not attempt to provide the complete details of the research conducted with support from this grant. That level of detail is provided in the 16 peer reviewed journal articles, 7 book chapters and 5 conference proceedings papers published as part of this grant. This report attempts to explain how the various publications fit together to improve our understanding of how forests are changing and how to monitor forest change with remote sensing. There were no new inventions that resulted from this grant.

Williams, Darrel↗

NASA NTRSDate not supplied

The INSTEP Monitoring Network: Merging High-and-Low Cost Measurements to Characterize California Wildfires

Despite challenges with data quality and scope, low-cost sensor networks have skyrocketed in popularity over the last 15 years, making air quality data available on refined spatial scales. More recently, studies have leveraged both high and low-quality instruments to create stronger “hybrid” models, with most studies focusing on particulate matter. Low-cost measurements typically represent ground-level emissions only, providing context for human health issues from climate change-driven events such as wildfires. Since low-cost sensors’ capabilities are localized, daily events and microclimates tend to dominate the data rather than larger regional or atmospheric trends. Likewise, their low cost explains their high uncertainty. In contrast, some regulatory-grade instruments produce column measurements as well, providing reliable information on a broader scope. To bridge this gap while expanding into gas-phase measurements, we deployed 12 air quality sensor packages in California, USA during the 2022 wildfire season. These INSTEP (Inexpensive Network Sensor Technology Exploring Pollution) monitors measure carbon monoxide (CO), carbon dioxide (CO2), ozone (O3), nitrogen dioxide (NO2), and several hydrocarbons including methane (CH4) and formaldehyde (HCHO). Half of the monitors were co-located with remote sensing spectrometers: NASA Pandora and Total Column Carbon Observing Network (TCCON). The overlap in pollutants includes NO2, O3, and HCHO between the INSTEP monitors and the Pandora column measurements. TCCON covers column CO, CO2, and CH4, rounding out our comparison. Most of the monitors were distributed throughout the San Francisco Bay area, and an additional three were located within 100 km of Los Angeles. The sites ranged in geographic and population characteristics, including desert, mountainous, coastal, and urban locations. Since varying environmental conditions such as temperature and pressure are known to challenge sensor performance, we will apply newer sensor “calibration” techniques meant to combat this. We will normalize our sensor signals by z-scoring them prior to applying a single calibration model in the form of multivariate linear regression or an artificial neural network. While this technique has been validated for the hydrocarbon and ozone sensor types (metal oxide), it has not yet been tested on electrochemical and non-dispersive infrared sensors, which are also used in the INSTEP monitors. This will serve as a test to see if this normalization technique – or another – is most effective in accounting for environmental differences among sensors. Related data analysis efforts have found success with a variety of geospatial analysis techniques, including weighted network models in which high-quality instruments are given higher weights than their low-cost counterparts. Our preliminary analysis will focus on kriging, which uses a Gaussian algorithm to assign weights, providing estimated pollution levels at locations between monitors. Smoke trajectory and evolution will also be considered using both measurement types. We also aim to baseline subtract our emission estimates from each region to determine which portion of emissions are regional and local, further characterizing burn differences in northern and southern California fires. Future directions include using INSTEP jointly with TEMPO satellite data, and mobile deployments on aircraft and uncrewed aerial vehicles (UAV).

Low-cost sensors↗

NASA NTRS2013

Evidence Report: Risk of Inadequate Human-Computer Interaction

Human-computer interaction (HCI) encompasses all the methods by which humans and computer-based systems communicate, share information, and accomplish tasks. When HCI is poorly designed, crews have difficulty entering, navigating, accessing, and understanding information. HCI has rarely been studied in an operational spaceflight context, and detailed performance data that would support evaluation of HCI have not been collected; thus, we draw much of our evidence from post-spaceflight crew comments, and from other safety-critical domains like ground-based power plants, and aviation. Additionally, there is a concern that any potential or real issues to date may have been masked by the fact that crews have near constant access to ground controllers, who monitor for errors, correct mistakes, and provide additional information needed to complete tasks. We do not know what types of HCI issues might arise without this "safety net". Exploration missions will test this concern, as crews may be operating autonomously due to communication delays and blackouts. Crew survival will be heavily dependent on available electronic information for just-in-time training, procedure execution, and vehicle or system maintenance; hence, the criticality of the Risk of Inadequate HCI. Future work must focus on identifying the most important contributing risk factors, evaluating their contribution to the overall risk, and developing appropriate mitigations. The Risk of Inadequate HCI includes eight core contributing factors based on the Human Factors Analysis and Classification System (HFACS): (1) Requirements, policies, and design processes, (2) Information resources and support, (3) Allocation of attention, (4) Cognitive overload, (5) Environmentally induced perceptual changes, (6) Misperception and misinterpretation of displayed information, (7) Spatial disorientation, and (8) Displays and controls.

Kritina Holden↗

NASA NTRS2020

A Quantitative Hydroclimatic Context for the European Great Famine of 1315–1317

The European Great Famine of 1315–1317 triggered one of the worst population collapses in European history and ranks as the single worst European famine in mortality as a proportion of population. Historical records point to torrential rainfall, land saturation, crop failure, and prolonged flooding as important causes of the famine. Here we use the tree-ring based Old World Drought Atlas (OWDA) to show that the average of each growing season preceding the Great Famine years (1314–1316) was the fifth wettest over Europe from 1300 to 2012 C.E. The spatial and temporal characteristics of our OWDA-estimated anomalies are in excellent agreement with available historical accounts. We also characterize a mode of European hydroclimate variability that is associated with the Great Famine, which we term the “Great Famine mode.” This mode emerges as the leading mode of European hydroclimate variability from 1300–2012 and is strongly associated with extreme wet and dry events in Europe over the last millennium.

Environmental impact↗

NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗

NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗

NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

Current Environmental Control and Life Support System (ECLSS) development and test activities are not generating data fast enough to provide statistically-supportable precise Orbital Replacement Unit (ORU) failure rate estimates for future missions. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches – namely regular resupply and rapid abort capabilities – will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of operations on board the International Space Station (ISS), a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass for future missions. A Bayesian failure rate estimation approach, such as the one currently implemented by the ISS Program, can help reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior failure rate estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, these subjective (and often inaccurate) prior estimates currently have a strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Supportability↗

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

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 NTRS1997

An Undergraduate Intern Program at PACES

The University of Texas at El Paso (UTEP) established the Pan American Center for Earth and Environmental Studies (PACES) in 1995 to conduct basic and applied research that contributes to NASA's Mission to Planet Earth. Specifically, PACES provides a repository of remote sensing and other information that supports investigations into an improved understanding of geological, ecological and environmental processes occurring in the southwestern United States and Northern Mexico. Approximately 85% of UTEP's students come from El Paso County, a fast growing urban region representative of many large cities in the Southwest that have, or will soon have, a majority of their population composed of groups currently underrepresented in the scientific and technical workforce. UTEP's student population has an ethnic distribution (63% Hispanic, 32% Anglo, 3% African American, 1.5 % Asian American, and less than 1% Native American) that closely matches the demographics of the region it serves. Thus, UTEP has a mission to serve a multicultural population where minority students comprise the majority. Most Hispanic students at UTEP are primarily of Mexican origin. A large number are first or second-generation U.S. citizens. Characteristics that unite Hispanic students, in particular those of Mexican-origin, are a strong sense of family loyalty and a belief that all family members are responsible for contributing to the economic stability and well-being of the family. Most of their families are larger in number than the national average, and a variety of generations live together or share considerable resources. Thus, many young people feel an obligation and a desire to go to work at a young age and to continue working while in college, thereby assisting their parents and other family members. Older siblings understand that they have responsibilities to do household chores, to aid their younger siblings economically, and to assist elderly family members. This "work ethic" within the context of family responsisilities is often viewed as being as important as higher education aspirations by both parents and university students. As a consequence, much effort at UTEP has been placed in recent years upon creating opportunities for students to earn income while working on campus as undergraduate research assistants on research projects related to their majors. Work assignments of this sort serve to promote retention efforts, to introduce students with the possibility of graduate study and to develop students professionally. Also, the involvement of students in group-oriented research projects at UTEP which require frequent oral and written reports has been proven beneficial at promoting communication skills of students. Because an estimated 60% of UTEP's students are first-generation college students, many are often uncertain graduate education.

Starks, Scott A.↗

NASA NTRS2003

Energy Requirements of Hydrogen-utilizing Microbes: A Boundary Condition for Subsurface Life

Microbial ecosystems based on the energy supplied by water-rock chemistry carry particular significance in the context of geo- and astrobiology. With no direct dependence on solar energy, lithotrophic microbes could conceivably penetrate a planetary crust to a depth limited only by temperature or pressure constraints (several kilometers or more). The deep lithospheric habitat is thereby potentially much greater in volume than its surface counterpart, and in addition offers a stable refuge against inhospitable surface conditions related to climatic or atmospheric evolution (e.g., Mars) or even high-energy impacts (e.g., early in Earth's history). The possibilities for a deep microbial biosphere are, however, greatly constrained by life s need to obtain energy at a certain minimum rate (the maintenance energy requirement) and of a certain minimum magnitude (the energy quantum requirement). The mere existence of these requirements implies that a significant fraction of the chemical free energy available in the subsurface environment cannot be exploited by life. Similar limits may also apply to the usefulness of light energy at very low intensities or long wavelengths. Quantification of these minimum energy requirements in terrestrial microbial ecosystems will help to establish a criterion of energetic habitability that can significantly constrain the prospects for life in Earth's subsurface, or on other bodies in the solar system. Our early work has focused on quantifying the biological energy quantum requirement for methanogenic archaea, as representatives of a plausible subsurface metabolism, in anoxic sediments (where energy availability is among the most limiting factors in microbial population growth). In both field and laboratory experiments utilizing these sediments, methanogens retain a remarkably consistent free energy intake, in the face of fluctuating environmental conditions that affect energy availability. The energy yields apparently required by methanogens in these sediment systems for sustained metabolism are about half that previously thought necessary. Lowered energy requirements would imply that a correspondingly greater proportion of the planetary subsurface could represent viable habitat for microorganisms.

Hoehler, Tori M.↗

NASA NTRSDate not supplied

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-meador↗

NASA NTRSDate not supplied

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-Meador↗

NASA NTRS2012

Towards Reliable Evaluation of Anomaly-Based Intrusion Detection Performance

This report describes the results of research into the effects of environment-induced noise on the evaluation process for anomaly detectors in the cyber security domain. This research was conducted during a 10-week summer internship program from the 19th of August, 2012 to the 23rd of August, 2012 at the Jet Propulsion Laboratory in Pasadena, California. The research performed lies within the larger context of the Los Angeles Department of Water and Power (LADWP) Smart Grid cyber security project, a Department of Energy (DoE) funded effort involving the Jet Propulsion Laboratory, California Institute of Technology and the University of Southern California/ Information Sciences Institute. The results of the present effort constitute an important contribution towards building more rigorous evaluation paradigms for anomaly-based intrusion detectors in complex cyber physical systems such as the Smart Grid. Anomaly detection is a key strategy for cyber intrusion detection and operates by identifying deviations from profiles of nominal behavior and are thus conceptually appealing for detecting "novel" attacks. Evaluating the performance of such a detector requires assessing: (a) how well it captures the model of nominal behavior, and (b) how well it detects attacks (deviations from normality). Current evaluation methods produce results that give insufficient insight into the operation of a detector, inevitably resulting in a significantly poor characterization of a detectors performance. In this work, we first describe a preliminary taxonomy of key evaluation constructs that are necessary for establishing rigor in the evaluation regime of an anomaly detector. We then focus on clarifying the impact of the operational environment on the manifestation of attacks in monitored data. We show how dynamic and evolving environments can introduce high variability into the data stream perturbing detector performance. Prior research has focused on understanding the impact of this variability in training data for anomaly detectors, but has ignored variability in the attack signal that will necessarily affect the evaluation results for such detectors. We posit that current evaluation strategies implicitly assume that attacks always manifest in a stable manner; we show that this assumption is wrong. We describe a simple experiment to demonstrate the effects of environmental noise on the manifestation of attacks in data and introduce the notion of attack manifestation stability. Finally, we argue that conclusions about detector performance will be unreliable and incomplete if the stability of attack manifestation is not accounted for in the evaluation strategy.

cyber defense↗

NASA NTRS1999

An Integrated Architecture for Onboard Spacecraft

As increasingly complex scientific and environmental observation spacecraft are deployed, the burden on the downlink assets, and ground-based systems complexity and cost is becoming a major problem. Already, the limitations of communications bandwidth and processing throughput limit the science data gathering, both in volume and in rate. This poses a dilemma to the scientist experimenter forcing choices between data collection and bandwidth/processing/archiving. Advances in ground based processing and space-to-Earth links have fallen behind the requirements for observation data, at increasing rates, over the last few decades. As NASA achieves its 40th anniversary, the ability to observe and capture phenomena of theoretical and practical interest to life on Earth far outstrips the ability to transfer, process, or store these data. NASA recognizes the need to invest on technological advancements that will enable both the space and ground systems to address the limitations. Spacecraft onboard computing power is a clear one. The capability of creating data products onboard the spacecraft adds a new level of flexibility to address the more demanding observation needs. Current spacecraft computing power is limited and incapable of addressing the needs of the new generation of observation satellites because extensive onboard data processing is required. Traditional spacecraft architectures only collect, package, and transmit to Earth the data acquired by multiple instruments. Conversely, the experience on developing ground data systems shows the need for high performance computing systems to process and create information from the instrumentation data. The expectation is that supercomputing technology is required to enable spacecraft to create information onboard. Moving supercomputing capability onboard spacecraft requires an approach that considers an integrated data architecture. Otherwise, it may simply convert a compute-bound problem into a communications bound problem, as has been shown numerous times in the context of massively parallel architectures. What is left to determine are the technologies that will enable spacecraft high performance computing.

Figueiredo, Marco A.↗

NASA NTRSDate not supplied

Simulating Ordinary Chondrite (Tamdakht) Ablation at the Hypersonic Materials Environmental Test System (HyMETS) Facility.

NASA’s Science Mission Directorate (SMD) created the Asteroid Threat Assessment Project (ATAP) to inform decision-makers of risks associated with Potentially Hazardous Objects (PHOs), which may pose an existential threat to human civilization. ATAP assesses risk, in part, by developing analytical physics-based damage models which draw upon data collected during material property characterization efforts, entry simulations, hazard simulations, and ground-based arc-jet testing. Therefore, a pathfinder test campaign was con-ducted at the Hypersonic Materials Environmental Test System (HyMETS) at the NASA Langley Re-search Center to investigate the ablation mechanisms of an ordinary chondrite (Tamdakht H5) and a terrestrial analog (basalt). The HyMETS facility is a 400 kW constricted arc heater used to screen material performance under simulated aerothermal conditions of hypersonic flow.1 Facility conditions were chosen to simulate Earth entry conditions be-tween the upper-mesosphere and the lower thermo-sphere. The ablation mechanisms of Tamdakht and bas-alt are illustrated with still images collected from high-speed video cameras (fig. 1, Tamdakht). Tamdakht produces a relatively stable melt flow, as evidenced by the perpetual growth of a flange at the sidewall and the exiguous detachment of molten material into the flow. Furthermore, an inspection of high-speed video and chemical analysis of the post-test melt layer suggests that the dominant mode of mass loss for Tamdakht, at these test conditions, is expressed through the vaporization of volatiles (e.g., iron, potassium, sodium, phosphorus, and sulfur). The vaporization rates of Tamdakht are greater than basalt under the most extreme test conditions, which leads to an enhanced blowing layer, in-creased thermal shielding, and reduced recession. The ablation mechanisms of basalt are markedly different from Tamdakht and are attributed to the presence of hydrated minerals dispersed at irregular intervals throughout the silicate matrix. Rapid de-composition of secondary minerals and the subsequent formation of water lead to the ejection of the subsurface and overlying melt layer. Furthermore, the presence of water is suspected of lowering the viscosity of the melt layer resulting in increased mass loss near the edge of the test article where drag forces overcome rheological properties (fig. 1, bas-alt). Finally, the results will be discussed in the broader context of meteorite-based material response model development and the potential impact on the Asteroid Threat Assessment Project (ATAP).

Brody K. Bessire↗