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NASA NTRS2022

A History of the NASA Planetary Astronomy Program: 1958-2022

For decades, the public has been enraptured by popular high-resolution images and data taken of our multicolored planets by space-based telescopes. However, at the time NASA was established in October 1958, there was limited astronomical interest in planetary science with ground-based telescopes. Instead, stellar astronomy dominated most of the observing time at facilities, as astrophysics was considered the forefront of astronomical research. Once NASA determined that it wanted launch planetary missions to explore the solar system in detail, it became obvious that there were not enough high-quality solar system observations to lay the foundation for these missions. Therefore, the NASA Planetary Astronomy program (PAST) was established to fund ground-based research on solar system objects. This research covers the history of this important but little-known NASA program, which not only provided necessary support for planetary missions but also was responsible for rejuvenating astronomer interest in solar system research.

NASA PAST Program↗

NASA NTRS2022

Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters

High-resolution space-based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal-to-noise ratio. Different applications drive divergent instrument designs, so optimization for wide-reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications-agnostic, data-driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high-dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal-to-noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher-level algorithms, products, applications, or disciplines.

Intrinsic dimensionality↗

NASA NTRS1981

Payload carrier systems for conducting sortie mode science

The capabilities and characteristics of the payload carriers developed to provide structural and operational interfaces between the Space Shuttle and the various types of experiments designed to operate in the sortie mode are discussed. The Spacelab is a flexible laboratory system composed of interchangeable elements that can be put together in eight different combinations of pallets and pressurized modules, and provides considerable standard services to users in such areas as equipment installation, power distribution, thermal control, command and data management, software, pointing systems and crew participation. A modular three-axis pointing control system designated the Annular Suspension and Pointing System, is being developed to provide additional pointing capabilities to those payloads that require capabilities not provided by the Spacelab instrument pointing system. Two engineering models of the Spacelab pallet have been designated Orbital Flight Test Pallets which, together with a special experiment support structure, are intended for initial and operational payloads that do not constitute a complete Spacelab mission. The simplest and smallest payload carriers are the Getaway Special cans, intended for small, self-contained, self-sufficient payloads, and the orbiter middeck lockers. In this way, most of the user requirements for Shuttle sortie missions identified to date can be fulfilled.

Jean, O. C.↗

NASA NTRS2009

Ocean, Land and Meteorology Studies Using Space-Based Lidar Measurements

CALIPSO's main mission objective is studying the climate impact of clouds and aerosols in the atmosphere. CALIPSO also collects information about other components of the Earth's ecosystem, such as oceans and land. This paper introduces the physics concepts and presents preliminary results for the valueadded CALIPSO Earth system science products. These include ocean surface wind speeds, column atmospheric optical depths, ocean subsurface backscatter, land surface elevations, atmospheric temperature profiles, and A-train data fusion products.

Hu,Yongxiang↗

DOE OSTI2016

Invited Review Article: Pump-probe microscopy

Multiphoton microscopy has rapidly gained popularity in biomedical imaging and materials science because of its ability to provide three-dimensional images at high spatial and temporal resolution even in optically scattering environments. Currently the majority of commercial and home-built devices are based on two-photon fluorescence and harmonic generation contrast. These two contrast mechanisms are relatively easy to measure but can access only a limited range of endogenous targets. Recent developments in fast laser pulse generation, pulse shaping, and detection technology have made accessible a wide range of optical contrasts that utilize multiple pulses of different colors. Molecular excitation with multiple pulses offers a large number of adjustable parameters. For example, in two-pulse pump-probe microscopy, one can vary the wavelength of each excitation pulse, the detection wavelength, the timing between the excitation pulses, and the detection gating window after excitation. Such a large parameter space can provide much greater molecular specificity than existing single-color techniques and allow for structural and functional imaging without the need for exogenous dyes and labels, which might interfere with the system under study. In this review, we provide a tutorial overview, covering principles of pump-probe microscopy and experimental setup, challenges associated with signal detection and data processing, and an overview of applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1999

622-Mbps Orthogonal Frequency Division Multiplexing Modulator Developed

The Communications Technology Division at the NASA Lewis Research Center is developing advanced electronic technologies for the space communications and remote sensing systems of tomorrow. As part of the continuing effort to advance the state-of-the art in satellite communications and remote sensing systems, Lewis is developing a programmable Orthogonal Frequency Division Multiplexing (OFDM) modulator card for high-data-rate communication links. The OFDM modulator is particularly suited to high data-rate downlinks to ground terminals or direct data downlinks from near-Earth science platforms. It can support data rates up to 622 megabits per second (Mbps) and high-order modulation schemes such as 16-ary quadrature amplitude modulation (16-ary QAM) or 8- phase shift keying (8PSK). High order modulations can obtain the bandwidth efficiency over the traditional binary phase shift keying (BPSK) or quadrature phase shift keying (QPSK) modulator schemes. The OFDM modulator architecture can also be precompensated for channel disturbances and alleviate amplitude degradations caused by nonlinear transponder characteristics.

Nguyen, Na T.↗

NASA NTRS2019

Providing a Service that Doubles the ISS Science Data Return

NASA’s missions rely on the Space Network to relay critical mission data to control centers and scientists here on Earth. The international Space Station is NASA’s most critical missions that relies on this network. The International Space Station plays a key role in the international science community, enabling human spaceflight, space and Earth science experiments, as well as technology demonstrations, in the space environment. The unique environment of the station’s approximately 250-mile-high orbit allows astronauts to conduct experiments which provide valuable insight in the fields of physics, biology, astronomy, meteorology and more. The station also transmits time-sensitive, mission-critical data like information about the crew’s health and the status of the station’s systems.

Barclay, Catherine B.↗

NASA NTRS1993

Lunar Scout Two spacecraft gravity experiment

Measurement of the gravity field of the Moon has a high science priority because of its implications for the internal structure and thermal history of the Moon, and it has a high priority for future exploration activities because of the influence of lunar gravity on spacecraft navigation and orbit maintenance. The current state of knowledge in the lunar gravity field (and the uncertainty in the knowledge) is based primarily on data accumulated from the Lunar Orbiter and Apollo programs. Data are sparse and emphasize the equatorial band (+/- 30 deg) on the near side of the Moon. There are no tracking data on the far side and only the Lunar Orbiter 5 provides a small amount of high inclination data. A host of gravity models developed from different combinations of tracking data have large discrepancies in their predictions of spacecraft motion and orbit lifetimes. There are also large disagreements in the Mercator projections of the gravity acceleration from each model, especially on the far side, where the contours tend to have no obvious relationship with the local topography. The science and engineering requirements for global gravity field mapping will be satisfied with continuous radio metric tracking of Lunar Scout 1 in a low polar orbit using the Deep Space Network and Lunar Scout 2 in a high elliptical orbit. The gravity field of the Moon will be mapped during the Scout Program using a two spacecraft concept. In the two spacecraft concept, one spacecraft is placed in a high altitude eccentric orbit while the second spacecraft is in a low altitude polar orbit. The gravity experiment requires a radio frequency that will permit two-way Doppler tracking between the spacecraft and the Deep Space Network (DSN). Both spacecraft carry NASA standard transponder systems for data transmission to Earth as well as for tracking and orbit determination. Data sufficient to produce a gravity field map could be acquired within one month with this system.

Cheng, Andrew F.↗

NASA NTRS2015

NASA Near Earth Network (NEN), Deep Space Network (DSN) and Space Network (SN) Support of CubeSat Communications

There has been a historical trend to increase capability and drive down the Size, Weight and Power (SWAP) of satellites and that trend continues today. Small satellites, including systems conforming to the CubeSat specification, because of their low launch and development costs, are enabling new concepts and capabilities for science investigations across multiple fields of interest to NASA. NASA scientists and engineers across many of NASAs Mission Directorates and Centers are developing exciting CubeSat concepts and welcome potential partnerships for CubeSat endeavors. From a communications and tracking point of view, small satellites including CubeSats are a challenge to coordinate because of existing small spacecraft constraints, such as limited SWAP and attitude control, low power, and the potential for high numbers of operational spacecraft. The NASA Space Communications and Navigation (SCaN) Programs Near Earth Network (NEN), Deep Space Network (DSN) and the Space Network (SN) are customer driven organizations that provide comprehensive communications services for space assets including data transport between a missions orbiting satellite and its Mission Operations Center (MOC). The NASA NEN consists of multiple ground antennas. The SN consists of a constellation of geosynchronous (Earth orbiting) relay satellites, named the Tracking and Data Relay Satellite System (TDRSS). The DSN currently makes available 13 antennas at its three tracking stations located around the world for interplanetary communication. The presentation will analyze how well these space communication networks are positioned to support the emerging small satellite and CubeSat market. Recognizing the potential support, the presentation will review the basic capabilities of the NEN, DSN and SN in the context of small satellites and will present information about NEN, DSN and SN-compatible flight radios and antenna development activities at the Goddard Space Flight Center (GSFC) and across industry. The presentation will review concepts on how the SN multiple access capability could help locate CubeSats and provide a low-latency early warning system. The presentation will also present how the DSN is evolving to maximize use of its assets for interplanetary CubeSats. The critical spectrum-related topics of available and appropriate frequency bands, licensing, and coordination will be reviewed. Other key considerations, such as standardization of radio frequency interfaces and flight and ground communications hardware systems, will be addressed as such standardization may reduce the amount of time and cost required to obtain frequency authorization and perform compatibility and end-to-end testing. Examples of standardization that exist today are the NASA NEN, DSN and SN systems which have published users guides and defined frequency bands for high data rate communication, as well as conformance to CCSDS standards. The workshop session will also seek input from the workshop participants to better understand the needs of small satellite systems and to identify key development activities and operational approaches necessary to enhance communication and navigation support using NASA's NEN, DSN and SN.

Telecommunication↗

DOE OSTI2013

Methods for improved forewarning of condition changes in monitoring physical processes

This invention teaches further improvements in methods for forewarning of critical events via phase-space dissimilarity analysis of data from biomedical equipment, mechanical devices, and other physical processes. One improvement involves objective determination of a forewarning threshold (U.sub.FW), together with a failure-onset threshold (U.sub.FAIL) corresponding to a normalized value of a composite measure (C) of dissimilarity; and providing a visual or audible indication to a human observer of failure forewarning and/or failure onset. Another improvement relates to symbolization of the data according the binary numbers representing the slope between adjacent data points. Another improvement relates to adding measures of dissimilarity based on state-to-state dynamical changes of the system. And still another improvement relates to using a Shannon entropy as the measure of condition change in lieu of a connected or unconnected phase space.

47 OTHER INSTRUMENTATION↗

NASA NTRS2021

Scheduling and Operations of the ECOSTRESS Mission

This paper describes the development and use of an automated scheduling system for the National Aeronautics and Space Administration’s (NASA) ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission. Key to the success of the ECOSTRESS mission has been the use of automated scheduling in mission analysis pre-launch, and in successful operations where automated scheduling was deployed to address several operational challenges. ECOSTRESS uses an adaptation of the Compressed Large-scale Activity Scheduling and Planning (CLASP) system to automatically select science observations respecting area and point target priorities as well as visibility, illumination, onboard storage, and radiation constraints to satisfy high-level prioritized science campaigns. The ECOSTRESS scheduler was used pre-launch to predict the effectiveness of alternative formulations of science campaign definitions accounting for the impact of data volume, keepout, and orbit/illumination/visibility constraints to derive the initial operational science campaign definitions and priorities. The scheduler was then used after instrument checkout for operations. ECOSTRESS has faced multiple operational challenges relating to instrument firmware and hardware, and the scheduler has been updated several times to address these challenges. The instrument Mass Storage Units (MSUs) had operational issues, requiring the scheduler to plan for and schedule commands to handle intricacies of data management. After many months of operations, both MSUs on the instrument became non-functioning and the firmware of the instrument was updated to bypass the MSUs. A further update to the ECOSTRESS scheduler enabled the scheduler to operate in this new operations mode. The ECOSTRESS scheduler has also been updated to improve handling of along-track uncertainty inherent in International Space Station operations. The flexibility and ease of updating of the automated scheduler has been a significant contributor to successful operations of the ECOSTRESS mission.

Padams, Jordan↗

NASA NTRS1999

In-Situ Production of Solar Power Systems for Exploration

Current proposals for developing an extended human presence, beyond space stations, on the Moon and Mars increasingly consider the processing of non-terrestrial materials essential for keeping the Earth launch burden reasonable. Utilization of in-situ resources for construction of lunar and Mars bases will initially require assessment of resource availability followed by the development of economically acceptable and technically feasible extractive processes. In regard to materials processing and fabrication the lower gravity level on the Moon (0.125 g) and Mars (0.367 g) will dramatically change the presently accepted hierarchy of materials in terms of specific properties, a factor which must be understood and exploited. Furthermore, significant changes are expected in the behavior of liquid materials during processing. In casting, for example, mold filling and associated solidification processes have to be reevaluated. Finally microstructural development and therefore material properties, presently being documented through on-going research in microgravity science and applications, needs to be understood and scaled to the reduced gravity environments. One of the most important elements of a human planetary base is power production. Lunar samples and geophysical measurements returned by the Apollo missions provide detailed data on the composition and physical characteristics of the lunar materials and environment. Based on this knowledge and extrapolations of terrestrial industrial experience it is clear that several types of solar-to-electric converters can be manufactured on the Moon. It is conceivable that well over 90% of a solar-to- electric power system could be made from lunar materials. Production and utilization of photovoltaic devices for solar energy production on Earth is primarily driven by the market economy. On Earth a production plant for photovoltaic devices is intimately linked to the planets massive industrial base. A selection of off the shelf refined materials are available as well as cheap fast transportation on demand. The processes takes place (except for the few seconds reprieve in shot towers etc.) under one gravity, with solar radiation significantly modulated by weather, and under conditions where one atmosphere is free and high vacuum is cumbersome and expensive. Off Earth, on lunar or Mars bases, the cost of photovoltaic power is driven by transport costs - Earth launch, deep space transport, landing on the planetary surface. Thus there is a premium for processes that are materials self-sufficient or for closed loop in-situ processes. The lack of differentiated ores on the Moon, and lack of explored minerals on Mars and interplanetary space give a premium to universal/non-ore-specific mineral extractive processes. Initially a semiconductor/photovoltaic production facility will build on no conveniently located industrial base, further increasing the premium on closed loop self sufficient processes.

Curreri, Peter A.↗

NASA NTRS2016

Reanalyzing Environmental Lidar Data for Archaeology: Mesoamerican Applications and Implications

This paper presents a preliminary archaeological assessment of extensive transects of lidar recently collected by environmental scientists over southern Mexico using the G-LiHT system of NASA's Goddard Space Flight Center. In particular, this article offers the results of a first phase of research, consisting of: 1) characterization and classification of the cultural and ecological context of the samples, and 2) bare earth processing and visual inspection of a sample of the flight paths for identification of probable anthropogenic Precolumbian features. These initial results demonstrate that significant contributions to understanding variations in Precolumbian land-use and settlement patterns and change is possible with truly multi-regional lidar surveys not originally captured for archaeological prospection. We point to future directions for the development of archaeological applications of this robust data set. Finally, we offer the potential for enriching archaeological research through tightly coupled collaborations with environmental science and monitoring. Archaeologists in the neotropics can acquire more data, better realize the full potential of lidar surveys, and better contribute to interdisciplinary studies of human-environmental dynamic systems through regionally focused and collaborative scientific research.

Golden, Charles↗

DOE OSTI2024

Matilda v1.0: An R package for probabilistic climate projections using a reduced complexity climate model

A primary advantage to using reduced complexity climate models (RCMs) has been their ability to quickly conduct probabilistic climate projections, a key component of uncertainty quantification in many impact studies and multisector systems. Providing frameworks for such analyses has been a target of several RCMs used in studies of the future co-evolution of the human and Earth systems. In this paper, we present Matilda, an open-science R software package that facilitates probabilistic climate projection analysis, implemented here using the Hector simple climate model in a seamless and easily applied framework. The primary goal of Matilda is to provide the user with a turn-key method to build parameter sets from literature-based prior distributions, run Hector iteratively to produce perturbed parameter ensembles (PPEs), weight ensembles for realism against observed historical climate data, and compute probabilistic projections for different climate variables. This workflow gives the user the ability to explore viable parameter space and propagate uncertainty to model ensembles with just a few lines of code. The package provides significant freedom to select different scoring criteria and algorithms to weight ensemble members, as well as the flexibility to implement custom criteria. Additionally, the architecture of the package simplifies the process of building and analyzing PPEs without requiring significant programming expertise, to accommodate diverse use cases. We present a case study that provides illustrative results of a probabilistic analysis of mean global surface temperature as an example of the software application.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2022

Supporting Responsible Machine Learning in Heliophysics

Over the last decade, Heliophysics researchers have increasingly adopted a variety of machine learning methods such as artificial neural networks, decision trees, and clustering algorithms into their workflow. Adoption of these advanced data science methods had quickly outpaced institutional response, but many professional organizations such as the European Commission, the National Aeronautics and Space Administration (NASA), and the American Geophysical Union have now issued (or will soon issue) standards for artificial intelligence and machine learning that will impact scientific research. These standards add further (necessary) burdens on the individual researcher who must now prepare the public release of data and code in addition to traditional paper writing. Support for these is not reflected in the current state of institutional support, community practices, or governance systems. We examine here some of these principles and how our institutions and community can promote their successful adoption within the Heliophysics discipline.

Machine learning↗

NASA NTRS1988

Oceanographic wide field sensor

The Oceanographic Wide Field Sensor (SeaWiFS) science project will provide measurements of ocean color from space to which will support research into: (1) the character of ocean physical and biological processes; (2) to assess the global oceanic biomass; and (3) to better understand the role of oceanic processes in modulating the Earth's biogeochemical cycles, including the CO2 cycle as it is affected by fossil fuel combustion. The present work extends previous work to study the feasibility of an ocean color mission using the proposed compact Wide-Field Sensor (SeaWiFS) and the EOSAT Corporation's LANDSAT-6 satellite. A Phase A study was conducted which defines a NASA Facility Data System and accompanying Science Program for the EOSAT Company's commercial ocean color instrument called SeaWiFS to be launched on board LANDSAT-6 in 1991.

Kirk, R. G.↗

NASA NTRS2009

An Overview of the Microgravity Science Glovebox (MSG) Facility and the Research Performed in the MSG on the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS) designed for investigation handling. The MSG has been operating on the ISS since July 2002 and is currently located in the Columbus Laboratory Module. The unique design of the facility allows it to accommodate science and technology investigations in a workbench type environment. The facility has an enclosed working volume that is held at a negative pressure with respect to the crew living area. This allows the facility to provide two levels of containment for small parts, particulates, fluids, and gases. This containment approach protects the crew from possible hazardous operations that take place inside the MSG work volume. Research investigations operating inside the MSG are provided a large 255 liter enclosed work space, 1000 watts of dc power via a versatile supply interface (120, 28, +/- 12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. These capabilities make the MSG one of the most utilized facilities on ISS. In fact, the MSG has been used for over 5000 hours of scientific payload operations. MSG investigations involve research in cryogenic fluid management, fluid physics, spacecraft fire safety, materials science, combustion, plant growth, and life support technologies. MSG is an ideal platform for science investigations and research required to advance the technology readiness levels (TRLs) applicable to the Constellation Program. This paper will provide an overview of the MSG facility, a synopsis of the research that has already been accomplished in the MSG, an overview of future investigations currently planned for operation in the MSG, and potential applications of MSG investigations that can provide useful data to the Constellation Program. In addition, this paper will address the role of the MSG facility in the ISS National Lab.

Spivey, Reggie↗

NASA NTRSDate not supplied

Nearest-Neighbor Machine Learning Feature Selection for Interpretation of Microbial Molecular Signatures from Isotope Ratio Mass Spectrometry Data

Mass spectrometry (MS) promises to be a powerful tool for potential biosignature detection during astrobiological missions on ocean worlds in our solar system. Accurate and generalizable machine learning methods could enhance science return on investment by predicting seawater chemistry and classifying isotopic biosignatures, either as a signature consistent with microbial life (biotic) or as a novelty (unclassified/unique). However, machine learning models are likely to be complex and involve interactions between MS features, making biosignatures difficult to interpret. Feature selection methods provide biological and chemical context that help interpret the mechanisms of machine learning models, but these methods also need the ability to detect complex interactions. Previously, we developed a machine learning feature selection algorithm called nearest-neighbor projected distance regression (NPDR) that has the ability to identify important model features that involve complex interactions and automatically reduce correlation and the dimensionality in a high-dimensional variable space. The standard distance metrics used in NPDR – Manhattan and Euclidean – assume the multivariate data are isotropic, which is often violated in real data due to differences in the covariance between variables. Thus, we extend NPDR to include a random forest distance, and other anisotropic distance metrics, for computing nearest neighbors. We also augment the isotope-ratio MS data with time-series features from the raw MS signal to improve biotic classification. We test NPDR on our novel experimental ocean world seawater analog MS data. We measure isotope fractionations of volatile CO 2 that could be measured in exospheres or plumes. Samples include baseline abiotic conditions using a range of possible seawater chemistry consistent with Europa and Enceladus, and biotic samples that include microbes in these seawaters. We use penalized NPDR with random forest proximity to identify interpretable microbial molecular signatures. We compare features with random forest importance, and we train a classifier that discriminates between biotic and abiotic samples with high accuracy. These ML-trained ocean-world analog MS data could be used to assist in identifying biosignatures during future missions.

geochemistry↗