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The retrieval lesson learned is important to many current and future hyperspectral remote sensors. Validated retrieval algorithms demonstrate the advancement of hyperspectral remote sensing capabilities to be achieved with current and future satellite instruments.
Terrestrial water storage (TWS) consists of groundwater, soil moisture and permafrost, surface water, snow and ice, and wet biomass. TWS variability tends to be dominated by snow and ice in polar and alpine regions, by soil moisture in mid-latitudes, and by surface water in wet, tropical regions such as the Amazon (Rodell and Famiglietti, 2001; Bates et al., 2007). Drought may be defined as a period of abnormally dry weather long enough to cause significant deficits in one or more of the TWS components. Thus, along with observations of the agricultural and socioeconomic impacts, measurements of TWS and its components enable quantification of drought severity. Each of the TWS components exhibits significant spatial variability, while installation and maintenance of sufficiently dense monitoring networks is costly and labor-intensive. Thus satellite remote sensing is an appealing alternative to traditional measurement techniques. Several current remote sensing instruments are able to detect variations in one or more TWS variables, including the Advanced Microwave Scanning Radiometer (AMSR) on NASA's Aqua satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua. Future satellite missions have been proposed to improve this capability, including the European Space Agency's Soil Moisture Ocean Salinity mission (SMOS) and the Soil Moisture Active Passive (SMAP), Surface Water Ocean Topography (SWOT), and Snow and Cold Land Processes (SCLP) missions recommended by the US National Academy of Science's Decadal Survey for Earth Science (NRC, 2007). However, only one remote sensing technology is able to monitor changes in TWS from the land surface to the base of the deepest aquifer: satellite gravimetry. This paper focuses on NASA's Gravity Recovery and Climate Experiment mission (GRACE; http://www.csr.utexas.edu/grace/) and its potential as a tool for drought monitoring.
The LTP (LISA Technology Package) is the core part of the Laser Interferometer Space Antenna (LISA) Pathfinder mission. The main goal of the mission is to study the sources of any disturbances that perturb the motion of the freely-falling test masses from their geodesic trajectories as well as 10 test various technologies needed for LISA. The LTP experiment is designed as a sequence of experimental runs in which the performance of the instrument is studied and characterized under different operating conditions. In order to best optimize subsequent experimental runs, each run must be promptly analysed to ensure that the following ones make best use of the available knowledge of the instrument ' In order to do this, all analyses must be designed and tested in advance of the mission and have sufficient built-in flexibility to account for unexpected results or behaviour. To support this activity, a robust and flexible data analysis software package is also required. This poster presents two of the main components that make up the data analysis effort: the data analysis software and the mock-data challenges used to validate analysis procedures and experiment designs.
Within the rocket engine industry, SSME turbomachines are the de facto standards of success with regard to meeting aggressive performance requirements under challenging operational environments. Over the Shuttle era, SSME has invested heavily in our national inducer impeller design infrastructure. While both low and high pressure turbopump failures/anomaly resolution efforts spurred some of these investments, the SSME program was a major benefactor of key areas of turbomachinery inducer-impeller research outside of flight manifest pressures. Over the past several decades, key turbopump internal environments have been interrogated via highly instrumented hot-fire and cold-flow testing. Likewise, SSME has sponsored the advancement of time accurate and cavitating inducer impeller computation fluid dynamics (CFD) tools. These investments together have led to a better understanding of the complex internal flow fields within aggressive high performing inducers and impellers. New design tools and methodologies have evolved which intend to provide confident blade designs which strike an appropriate balance between performance and self induced load management.
The Picosat and Uninhabited Aerial Vehicle Systems Engineering (PAUSE) project is developing balloon-borne instrumentation systems as aerobots for scientific exploration of remote planets and for diverse terrestrial purposes that can include scientific exploration, mapping, and military surveillance. The underlying concept of balloon-borne gondolas housing outer-space-qualified scientific instruments and associated data-processing and radio-communication equipment is not new. Instead, the novelty lies in numerous design details that, taken together, make a PAUSE aerobot smaller, less expensive, and less massive, relative to prior aerobots developed for similar purposes: Whereas the gondola (including the instrumentation system housed in it) of a typical prior aerobot has a mass of hundreds of kilograms, the mass of the gondola (with instrumentation system) of a PAUSE aerobot is a few kilograms.
NASA/Wallops Flight Facility has focused on the development of new technologies for the advancement of 6 Unit (6U) small satellites. From the design of the structure and instrument support hardware to improvements in the deployer, NASA is concentrating on maximizing the potential of small satellites for the benefit of science. The telemetry system provides much higher data rates than typical I U UHF system. 6U provides up to several hundred kilobits per second and utilizes the existing NASA Ground Network for data reception. The guidance, navigation and control system keeps the satellite pointed within plus or minus 10 degrees of the sun and has knowledge of the sun vector within 1 degree. The 6U power design increased the options for different voltages and power switching capabilities and is capable of supporting instruments with higher power requirements. The Command & Data Handling (C&DH) system includes a low-power 520 MHz flight processor which provides more processing capability than existing I U processor technologies. These optimized technologies will offer the science community a greater opportunity for flying more sophisticated and complex instruments.
The growing interest in comparative climatology among the terrestrial planets, the explosion of planets being discovered around other stars and the exciting results of recent orbital and remote observations of Venus provide evidence for a growing case to better understand Earths sister planet. The surface of Venus is quite unlike Earths surface conditions, and in fact is rather extreme. Science, technology, and planetary mission communities have a growing interest in the unique physiochemical properties and processes that occur under extreme temperature and pressure conditions in exotic and even hostile chemical environments such as Venus. The steadily growing catalog of exoplanets likely contains many examples of bodies with environments dramatically different than the surface of the Earth. Understanding these properties and processes will help us under-stand the history and present day state of inhospitable and even inaccessible regions of the Earth as well as other solar or extrasolar planets. Additionally, Venus and Saturn targets are prioritized in the current Planetary Decadal Survey, with reference missions that include in-situ investigations of these challenging environments. The fact that two of the five recent Discovery mission proposals selected by NASA for further development are Venus-focused adds additional priority and even urgency to laboratory-based extreme environment investigations. In addition to the importance of science-focused investigations, there is a current and future need for understanding the behavior of advanced technologies and materials in these extreme environments. The materials of course make up instruments and systems in missions and ultimately the success of planetary missions is dependent upon performance testing of instruments and systems in conditions that closely approximate those of the target. Until very recently, there was limited ability to accurately simulate Venus surface-like conditions, especially in vessels large enough to accommodate full-size instruments and components. This gap in capability is being addressed by NASA Glenn's Extreme Environment Rig, called GEER, located in Cleveland, Ohio. This large chamber allows for engineering tests of newly-developed as well as heritage instruments, while simultaneously affording opportunities for geochemical and materials-based science investigations.
Disclosed are watercrafts with rotatable air propulsion steering units and retractable measurement instruments. The watercraft can include a substantially flat bottom, a top deck, a rotatable air propulsion steering unit configured to propel the watercraft and to rotate in order to steer the watercraft when the watercraft is submerged in a liquid body without requiring a submerged rudder steering system under the substantially flat bottom. The watercraft can also include a retractable measurement deck configured to alternatively raise measurement instruments above the liquid body and lower into the liquid body.
This paper describes the development of the Detector Array Assembly (DAA) structure for the Advanced Topographic Laser Altimeter System (ATLAS) on the ICESat2 Mission built at NASA Goddard Space Flight Center (GSFC). It describes the challenges faced in designing a structure to protect sensitive detectors with limited data available for the detectors and the environment, including shock. The paper shows the successful re-design and testing that was performed to allow for a design to handle launch, shock and thermal environments with flexibility to incorporate design changes.
In response to the 2018 White House Space Policy Directive- sustainable lunar exploration, and to the Vice President’s March 2019 direction to do so by 2024, NASA is working to establish humanity's presence on and around the Moon by: 1) sending payloads to its surface, 2) assembling the Gateway outpost in orbit and 3) demonstrating the first human lunar landings since 1972. NASA’s Artemis program is implementing a multi-faceted and coordinated agency-wide approach with a focus on the lunar South Pole. The Artemis missions will demonstrate new technologies, capabilities and business approaches needed for future exploration, including Mars. Assessing options to accelerate development of required systems, NASA is utilizing public-private engagements through the Human Exploration and Operations (HEO) Mission Directorate’s NextSTEP Broad Agency Announcements. The design, development and demonstration of the Human Landing System (HLS) is expected to be led by commercial partners. Utilizing efforts across mission directorates, the Artemis effort will benefit from programs from the Science Mission Directorate (SMD) and Space Technology Mission Directorate (STMD). SMD’s Commercial Lunar Payload Services (CLPS) initiative will procure commercial robotic lunar delivery services and the development of science instruments and technology demonstration payloads. The Space Technology Mission Directorate (STMD) portfolio of technology advancements relative to HLS include lunar lander components and technologies for pointing, navigation and tracking, fuel storage and transfer, autonomy and mobility, communications, propulsion and power. In addition to describing the objectives and requirements of the 2024 Artemis mission, this paper will present NASA’s approach to accessing the lunar surface with an affordable human-rated landing system, current status and the role o a sustainable lunar presence.
The objective of this project is to demonstrate a new imaging technology with unprecedented capabilities for scientific exploration. This technology innovation will enable extremely high-resolution imaging capability, otherwise unattainable with conventional approaches. It is based on a unique combination of novel diffractive optical sensing (photon sieve), advanced image processing, and small satellite formation flying. The spatial resolution of current solar instruments are more than 100 times coarser than the size of energy dissipation features in coronal heating (<100 km) since conventional optics cannot be figured to near diffraction-limited accuracy at extreme ultraviolet (EUV) wavelengths. This project will demonstrate the feasibility of imaging of a few milli-arcseconds (MAS) to study the structure and development of these dissipation regions.
Techniques for making atmospheric measurements are as wide-ranging as the atmosphere is complex. From in situ measurements made by land, sea, or air, to remote sensing data collected by satellites orbiting the Earth, atmospheric measurements have been paramount in advancing the combined understanding of our planet. To date, many of these advancements have been enabled by NASA Airborne Science platforms, which provide unique opportunities to make these measurements in remote regions, and to compare them with an ever-increasing archive of remote satellite data. Here, we discuss recent advances and current capabilities of the National Suborbital Research Center (NSRC) which provides comprehensive instrumentation and data system support on a variety of NASA airborne research platforms. Application of these methods to a number of diverse science missions, as well as upcoming project opportunities, will also be discussed.
Nanoflares are thought to be prime candidates to heat the solar non-flaring active regions. However, their direct individual detection with current instrumentation remains challenging. Understanding the frequency and magnitude of nanoflares is crucial for understanding their role in coronal heating. In this study, we employ a field-aligned hydrodynamic model to simulate the evolution of an active region (AR) under nanoflare heating scenarios. By comparing the simulated emission with EUV and X-ray observations, we determine the frequency of heating events and investigate how it evolves with the AR evolution. Additionally, we analyze the impact of observational parameters, such as instrument spatial resolution and energy band, on estimating nanoflare properties. Our findings contribute to advancing our understanding of the role of nanoflares in coronal heating and refining observational parameters for detecting these events.
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This study describes the application development of multiple-input multiple-output radios to provide persistent mobile ad hoc network (MANET) for the Department of Homeland Security. By using Man Portable Unit (MPU5) fifth generation radios (manufactured by Persistent Systems) with the Android Team Awareness Kit (ATAK), an Android smartphone geospatial infrastructure and military situational awareness application, the Remote Sensing Laboratory has developed a MANET connectivity to monitor deployed nuclear/radiological search operation assets.
Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components: (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine.
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With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.