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NASA NTRS2020

Application of Remote Sensing for Ex-Ante Decision Support and Evaluating Impact

Deforestation is an environmental stressor that dramatically threatens biodiversity while having adverse, deep-rooted socioeconomic impacts. Interventions to address deforestation require considerable long-term investments; therefore, assessing their impact is crucial. The UN Convention on Biological Diversity encourages establishing Protected Areas (PAs) as a strategy to conserve biodiversity, secure ecosystem services, support local livelihoods, and reduce climate change impacts. The Global Environment Facility (GEF) has supported the conservation and management of PAs, yet site accessibility and data availability present challenges in assessing PAs using traditional evaluation methods. We present a novel application of satellite Earth observations for evaluating the effectiveness and impact of PAs as a deforestation mitigation strategy. Geospatial analysis and ecological forecasting methodologies provide an efficient way to quantify land cover change, estimate above-ground carbon stock, and evaluate ecosystem services provided by the PAs ex-ante. We demonstrate the value of a geospatial approach through evaluation of GEF-supported PAs in Kenya.

Remote sensing↗

NASA NTRS2013

Advanced Multifunctional MMOD Shield: Radiation Shielding Assessment

As NASA is looking to explore further into deep space, multifunctional materials are a necessity for decreasing complexity and mass. One area where multifunctional materials could be extremely beneficial is in the micrometeoroid orbital debris (MMOD) shield. A typical MMOD shield on the International Space Station (ISS) is a stuffed whipple shield consisting of multiple layers. One of those layers is the thermal blanket, or multi-layer insulation (MLI). Increasing the MMOD effectiveness of MLI blankets, while still preserving their thermal capabilities, could allow for a less massive MMOD shield. Thus, a study was conducted to evaluate a concept MLI blanket for an MMOD shield. In conjunction, this MLI blanket and the subsequent MMOD shield was also evaluated for its radiation shielding effectiveness towards protecting crew. The overall MMOD shielding system using the concept MLI blanket proved to only have a marginal increase in the radiation mitigating properties. Therefore, subsequent analysis was performed on various conceptual MMOD shields to determine the combination of materials that may prove superior for radiation mitigating purposes. The following paper outlines the evaluations performed and discusses the results and conclusions of this evaluation for radiation shielding effectiveness.

Rojdev, Kristina↗

NASA NTRS2016

Analysis of RFI Statistics for Aquarius RFI Detection and Mitigation Improvements

Aquarius is an L-band active/passive sensor designed to globally map sea surface salinity from space. Two instruments, a radar scatterometer and a radiometer, observe the same surface footprint almost simultaneously. The radiometer is the primary instrument for sensing sea surface salinity (SSS), while the scatterometer is included to provide a correction for sea surface roughness, which is a primary source of error in the salinity retrieval. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. An important feature of the data processing includes detection and mitigation of Radio Frequency Interference (RFI) which is done separately for both active and passive instruments. Correcting for RFI is particularly critical over ocean because of the high accuracy required in the brightness temperature measurements for SSS retrieval. It is also necessary for applications of the Aquarius data over land, where man-made interference is widespread, even though less accuracy is required in this case. This paper will provide an overview of the current status of the Aquarius RFI processing and an update on the ongoing work on the improvement of the RFI detection and mitigation performance.

Microwave remote sensing↗

NASA NTRSDate not supplied

Quantitative analysis of short-radius artificial gravity parameters to mitigate spaceflight-relevant physiological deconditioning

Explore the source record for details and available documents.

Kathrine N. Bretl↗

NASA NTRSDate not supplied

Decision Aid for Conjunction Risk Mitigation by Differential Drag

The NASA Conjunction Assessment Risk Analysis (CARA) team has conducted are view of the historical record of high-risk conjunctions involving CARA-protected missions and evaluated whether (and how much) differential drag can provide effective mitigation. From this analysis, CARA has identified a rule of thumb: missions with perigees below 560 km capable of tripling their drag area for 72 hours(or a larger scale factor for a lesser amount of time) can reliably use differential drag to remediate high-risk events.

mission design↗

NASA NTRS2011

Investigating On-Orbit Attitude Determination Anomalies for the Solar Dynamics Observatory Mission

The Solar Dynamics Observatory (SDO) was launched on February 11, 2010 from Kennedy Space Center on an Atlas V launch vehicle into a geosynchronous transfer orbit. SDO carries a suite of three scientific instruments, whose observations are intended to promote a more complete understanding of the Sun and its effects on the Earth's environment. After a successful launch, separation, and initial Sun acquisition, the launch and flight operations teams dove into a commissioning campaign that included, among other things, checkout and calibration of the fine attitude sensors and checkout of the Kalman filter (KF) and the spacecraft s inertial pointing and science control modes. In addition, initial calibration of the science instruments was also accomplished. During that process of KF and controller checkout, several interesting observations were noticed and investigated. The SDO fine attitude sensors consist of one Adcole Digital Sun Sensor (DSS), two Galileo Avionica (GA) quaternion-output Star Trackers (STs), and three Kearfott Two-Axis Rate Assemblies (hereafter called inertial reference units, or IRUs). Initial checkout of the fine attitude sensors indicated that all sensors appeared to be functioning properly. Initial calibration maneuvers were planned and executed to update scale factors, drift rate biases, and alignments of the IRUs. After updating the IRU parameters, the KF was initialized and quickly reached convergence. Over the next few hours, it became apparent that there was an oscillation in the sensor residuals and the KF estimation of the IRU bias. A concentrated investigation ensued to determine the cause of the oscillations, their effect on mission requirements, and how to mitigate them. The ensuing analysis determined that the oscillations seen were, in fact, due to an oscillation in the IRU biases. The low frequencies of the oscillations passed through the KF, were well within the controller bandwidth, and therefore the spacecraft was actually following the oscillating biases, resulting in movement of the spacecraft on the order of plus or minus 20 arcsec. Though this level of error met the ACS attitude knowledge requirement of [35, 70, 70] arcsec, 3 sigma, the desire of the ACS and instrument teams was to remove as much of the oscillation as possible. The Kearfott IRUs have an internal temperature controller, designed to maintain the IRU temperature at a constant temperature of approximately 70 C, thus minimizing the change in the bias drift and scale factors of the mechanical gyros. During ground testing of the observatory, it was discovered that the 83-Hz control cycle of the IRU heaters put a tremendous amount of stress on the spacecraft battery. Analysis by the power systems team indicated that the constant charge/discharge on the battery due to the IRU thermal control cycle could potentially limit the life of the battery. After much analysis, the decision was made not to run the internal IRU heaters. Analysis of on orbit data revealed that the oscillations in the IRU bias had a connection to the temperature of the IRU; changes in IRU temperature resulted in changes in the amplitude and period of the IRU biases. Several mitigating solutions were investigated, the result of which was to tune the KF with larger IRU noise assumptions which allows the KF to follow and correct for the time-varying IRU biases.

Vess, Melissa F.↗

NASA NTRS2019

Statistical Analysis of Aquarius Radiometer Radio Frequency Interference (RFI) and Implications on RFI Detection and Mitigation

The Aquarius/SAC-D mission operated between August 2011 and June 2015 with the main goal of providing global estimates of sea surface salinity (SSS). It comprised both active and passive microwave sensors operating at L-band to observe the same surface area almost simultaneously. Measurements from both instruments underwent subsequent filtering to mitigate the effect of Radio Frequency Interference (RFI). This report describes the analysis of statistics of RFI in samples acquired by the Aquarius radiometers, and its results could be used to improve the performance of the interference detection algorithm.

De Matthaeis, Paolo↗

NASA NTRS2007

NASA GRC and MSFC Space-Plasma Arc Testing Procedures

Tests of arcing and current collection in simulated space plasma conditions have been performed at the NASA Glenn Research Center (GRC) in Cleveland, Ohio, for over 30 years and at the Marshall Space Flight Center (MSFC) in Huntsville, Alabama, for almost as long. During this period, proper test conditions for accurate and meaningful space simulation have been worked out, comparisons with actual space performance in spaceflight tests and with real operational satellites have been made, and NASA has achieved our own internal standards for test protocols. It is the purpose of this paper to communicate the test conditions, test procedures, and types of analysis used at NASA GRC and MSFC to the space environmental testing community at large, to help with international space-plasma arcing-testing standardization. Discussed herein are neutral gas conditions, plasma densities and uniformity, vacuum chamber sizes, sample sizes and Debye lengths, biasing samples versus self-generated voltages, floating samples versus grounded samples, test electrical conditions, arc detection, preventing sustained discharges during testing, real samples versus idealized samples, validity of LEO tests for GEO samples, extracting arc threshold information from arc rate versus voltage tests, snapover, current collection, and glows at positive sample bias, Kapton pyrolysis, thresholds for trigger arcs, sustained arcs, dielectric breakdown and Paschen discharge, tether arcing and testing in very dense plasmas (i.e. thruster plumes), arc mitigation strategies, charging mitigation strategies, models, and analysis of test results. Finally, the necessity of testing will be emphasized, not to the exclusion of modeling, but as part of a complete strategy for determining when and if arcs will occur, and preventing them from occurring in space.

Ferguson, Dale C.↗

NASA NTRS2005

NASA GRC and MSFC Space-Plasma Arc Testing Procedures

Tests of arcing and current collection in simulated space plasma conditions have been performed at the NASA Glenn Research Center (GRC) in Cleveland, Ohio, for over 30 years and at the Marshall Space flight Center (MSFC) for almost as long. During this period, proper test conditions for accurate and meaningful space simulation have been worked out, comparisons with actual space performance in spaceflight tests and with real operational satellites have been made, and NASA has achieved our own internal standards for test protocols. It is the purpose of this paper to communicate the test conditions, test procedures, and types of analysis used at NASA GRC and MSFC to the space environmental testing community at large, to help with international space-plasma arcing testing standardization. To be discussed are: 1. Neutral pressures, neutral gases, and vacuum chamber sizes. 2. Electron and ion densities, plasma uniformity, sample sizes, and Debye lengths. 3. Biasing samples versus self-generated voltages. Floating samples versus grounded. 4. Power supplies and current limits. Isolation of samples from power supplies during arcs. Arc circuits. Capacitance during biased arc-threshold tests. Capacitance during sustained arcing and damage tests. Arc detection. Preventing sustained discharges during testing. 5. Real array or structure samples versus idealized samples. 6. Validity of LEO tests for GEO samples. 7. Extracting arc threshold information from arc rate versus voltage tests. 8 . Snapover and current collection at positive sample bias. Glows at positive bias. Kapton pyrolization. 9. Trigger arc thresholds. Sustained arc thresholds. Paschen discharge during sustained arcing. 10. Testing for Paschen discharge thresholds. Testing for dielectric breakdown thresholds. Testing for tether arcing. 11. Testing in very dense plasmas (ie thruster plumes). 12. Arc mitigation strategies. Charging mitigation strategies. Models. 13. Analysis of test results. Finally, the necessity of testing will be emphasized, not to the exclusion of modeling, but as part of a complete strategy for determining when and if arcs will occur, and preventing them from occurring in space.

Ferguson, Dale C.a↗

NASA NTRS2005

NASA GRC and MSFC Space-Plasma Arc Testing Procedures

Tests of arcing and current collection in simulated space plasma conditions have been performed at the NASA Glenn Research Center (GRC) in Cleveland, Ohio, for over 30 years and at the Marshall Space Flight Center (MSFC) in Huntsville, Alabama, for almost as long. During this period, proper test conditions for accurate and meaningful space simulation have been worked out, comparisons with actual space performance in spaceflight tests and with real operational satellites have been made, and NASA has achieved our own internal standards for test protocols. It is the purpose of this paper to communicate the test conditions, test procedures, and types of analysis used at NASA GRC and MSFC to the space environmental testing community at large, to help with international space-plasma arcing-testing standardization. To be discussed are: 1.Neutral pressures, neutral gases, and vacuum chamber sizes. 2. Electron and ion densities, plasma uniformity, sample sizes, and Debuy lengths. 3. Biasing samples versus self-generated voltages. Floating samples versus grounded. 4. Power supplies and current limits. Isolation of samples from power supplies during arcs. 5. Arc circuits. Capacitance during biased arc-threshold tests. Capacitance during sustained arcing and damage tests. Arc detection. Prevention sustained discharges during testing. 6. Real array or structure samples versus idealized samples. 7. Validity of LEO tests for GEO samples. 8. Extracting arc threshold information from arc rate versus voltage tests. 9. Snapover and current collection at positive sample bias. Glows at positive bias. Kapon (R) pyrolisis. 10. Trigger arc thresholds. Sustained arc thresholds. Paschen discharge during sustained arcing. 11. Testing for Paschen discharge threshold. Testing for dielectric breakdown thresholds. Testing for tether arcing. 12. Testing in very dense plasmas (ie thruster plumes). 13. Arc mitigation strategies. Charging mitigation strategies. Models. 14. Analysis of test results. Finally, the necessity of testing will be emphasized, not to the exclusion of modeling, but as part of a complete strategy for determining when and if arcs will occur, and preventing them from occurring in space.

Ferguson, Dale C.↗

NASA NTRSDate not supplied

Passive Dust Mitigation Technologies Being Developed for Demonstration Under Patch Plate Materials Compatibility Analysis Task

With the Artemis program, we are planning longer stays on the surface, with more activities that have the potential to put the astronauts and equipment in contact with greater quantities of lunar dust. The success of these missions will depend on our understanding of material interactions with lunar dust and the development of ways to mitigate dust effects in cases where exposure to dust will lead to failure of components, unacceptable loss of power or thermal control, unacceptable loss of visibility, or health issues. Passive dust mitigation by coating or surface alteration is one method that is being developed and demonstrated under the Space Technology Mission Directorate’s Game Changing Technology, Dust Mitigation Program as part of the Patch Plate Materials Compatibility Assessment Task. The goal of the task is to alter the surfaces of materials in order to passively reduce the adhesion of dust, demonstrate their performance in relevant ground-based tests using lunar simulants, and prepare them for demonstration through experiment on the lunar surface. Optically transparent, sputter deposited, work function matching coatings are being developed to reduce adhesion of dust to windows, lenses and display panels by matching the minimum energy to remove an electron from the surface to that of lunar dust in order to reduce adhesion due to charge transfer. Low surface energy coatings and surfaces for thermal control are also being developed to reduce the bonding of dust with the surface enabling it to be removed more easily. Conductive coatings with the ability to shed dust more easily are being developed for use with the active Electrodynamic Dust Shield technology to help reduce the power needed to remove dust from the surface. Passive dust mitigation surfaces for metals such as aluminum, stainless steel, and titanium are being developed that reduce the area of dust contact with the surfaces through topographical modification using laser ablation patterning to impart hierarchical topographies with nanometer to micrometer length scales in a single step. Topographically modified polymeric materials, both those with extensive space heritage and those with lower technology readiness levels, are also being evaluated. Space suit fabric surfaces that can reduce dust penetration into and through the fabric are also being investigated as well as pristine and topographically modified ceramic materials that exhibit high wear resilience. An overview of the passive dust mitigation surfaces and coatings being developed under this task, ground testing being conducted using lunar simulants, characterization techniques, and materials preparation for flight sample delivery for integration into the Alpha Space Regolith Adherence Characterization experiment going to the lunar surface on a Commercial Lunar Payload Services (CLPS) lander in 2023 will be discussed.

Lunar dust, passive mitigation, lunar simulant, co↗

NASA NTRS2014

Temporal Variability of Upper-level Winds at the Eastern Range, Western Range and Wallops Flight Facility

Space launch vehicles incorporate upper-level wind profiles to determine wind effects on the vehicle and for a commit to launch decision. These assessments incorporate wind profiles measured hours prior to launch and may not represent the actual wind the vehicle will fly through. Uncertainty in the upper-level winds over the time period between the assessment and launch can be mitigated by a statistical analysis of wind change over time periods of interest using historical data from the launch range. Five sets of temporal wind pairs at various times (.75, 1.5, 2, 3 and 4-hrs) at the Eastern Range, Western Range and Wallops Flight Facility were developed for use in upper-level wind assessments. Database development procedures as well as statistical analysis of temporal wind variability at each launch range will be presented.

Decker, Ryan K.↗

NASA NTRS2014

Temporal Variability of Upper-level Winds at the Eastern Range, Western Range and Wallops Flight Facility

Decker, Ryan↗

NASA NTRS2014

Temporal Variability of Upper-level Winds at the Eastern Range, Western Range and Wallops Flight Facility

Space launch vehicle commit-to-launch decisions include an assessment of the upper-level (UL) atmospheric wind environment to assess the vehicle's controllability and structural integrity during ascent. These assessments occur at predetermined times during the launch countdown based on measured wind data obtained prior to the assessment. However, the pre-launch measured winds may not represent the wind environment during the vehicle ascent. Uncertainty in the UL winds over the time period between the assessment and launch can be mitigated by a statistical analysis of wind change over time periods of interest using historical data from the launch range. Without historical data, theoretical wind models must be used, which can result in inaccurate wind placards that misrepresent launch availability. Using an overconservative model could result in overly restrictive vehicle wind placards, thus potentially reducing launch availability. Conversely, using an under-conservative model could result in launching into winds that might damage or destroy the vehicle. A large sample of measured wind profiles best characterizes the wind change environment. These historical databases consist of a certain number of wind pairs, where two wind profile measurements spaced by the time period of interest define a pair.

Decker, Ryan K.↗

NASA NTRS2014

NASA Space Rocket Logistics Challenges

The Space Launch System (SLS) is the new NASA heavy lift launch vehicle in development and is scheduled for its first mission in 2017. SLS has many of the same logistics challenges as any other large scale program. However, SLS also faces unique challenges. This presentation will address the SLS challenges, along with the analysis and decisions to mitigate the threats posed by each.

Bramon, Chris↗

NASA NTRS2015

Implementation of an Open-Scenario, Long-Term Space Debris Simulation Approach

This paper provides a status update on the implementation of a flexible, long-term space debris simulation approach. The motivation is to build a tool that can assess the long-term impact of various options for debris-remediation, including the LightForce space debris collision avoidance concept that diverts objects using photon pressure [9]. State-of-the-art simulation approaches that assess the long-term development of the debris environment use either completely statistical approaches, or they rely on large time steps on the order of several days if they simulate the positions of single objects over time. They cannot be easily adapted to investigate the impact of specific collision avoidance schemes or de-orbit schemes, because the efficiency of a collision avoidance maneuver can depend on various input parameters, including ground station positions and orbital and physical parameters of the objects involved in close encounters (conjunctions). Furthermore, maneuvers take place on timescales much smaller than days. For example, LightForce only changes the orbit of a certain object (aiming to reduce the probability of collision), but it does not remove entire objects or groups of objects. In the same sense, it is also not straightforward to compare specific de-orbit methods in regard to potential collision risks during a de-orbit maneuver. To gain flexibility in assessing interactions with objects, we implement a simulation that includes every tracked space object in Low Earth Orbit (LEO) and propagates all objects with high precision and variable time-steps as small as one second. It allows the assessment of the (potential) impact of physical or orbital changes to any object. The final goal is to employ a Monte Carlo approach to assess the debris evolution during the simulation time-frame of 100 years and to compare a baseline scenario to debris remediation scenarios or other scenarios of interest. To populate the initial simulation, we use the entire space-track object catalog in LEO. We then use a high precision propagator to propagate all objects over the entire simulation duration. If collisions are detected, the appropriate number of debris objects are created and inserted into the simulation framework. Depending on the scenario, further objects, e.g. due to new launches, can be added. At the end of the simulation, the total number of objects above a cut-off size and the number of detected collisions provide benchmark parameters for the comparison between scenarios. The simulation approach is computationally intensive as it involves tens of thousands of objects; hence we use a highly parallel approach employing up to a thousand cores on the NASA Pleiades supercomputer for a single run. This paper describes our simulation approach, the status of its implementation, the approach to developing scenarios and examples of first test runs.

laser↗

NASA NTRS2017

Assessment of Intralaminar Progressive Damage and Failure Analysis Using an Efficient Evaluation Framework

Reducing the timeline for development and certification for composite structures has been a long standing objective of the aerospace industry. This timeline can be further exacerbated when attempting to integrate new fiber-reinforced composite materials due to the large number of testing required at every level of design. computational progressive damage and failure analysis (PDFA) attempts to mitigate this effect; however, new PDFA methods have been slow to be adopted in industry since material model evaluation techniques have not been fully defined. This study presents an efficient evaluation framework which uses a piecewise verification and validation (V&V) approach for PDFA methods. Specifically, the framework is applied to evaluate PDFA research codes within the context of intralaminar damage. Methods are incrementally taken through various V&V exercises specifically tailored to study PDFA intralaminar damage modeling capability. Finally, methods are evaluated against a defined set of success criteria to highlight successes and limitations.

Hyder, Imran↗

NASA NTRSDate not supplied

Inferred Sea Level Prediction in the NASA GMAO Seasonal Forecasting System

Reliable predictions of sea level anomalies on seasonal timescales with lead times of 1 to 9 months may have relevance to stakeholders – for example, in the advance deployment of resources for coastal flood mitigation. Routine prediction and analysis may also highlight physical processes associated with sea level change and modeling capabilities on seasonal and other timescales. These forecasts may represent interannual changes in the seasonal slope of the ocean surface, teleconnection effects such as the El Niño/Southern Oscillation phenomenon, and variations in seasonal hydrology including precipitation and coastal runoff. Coupled atmosphere/ocean models are routinely used in the seasonal prediction of temperature anomalies, precipitation anomalies, sea ice cover, and climate indices such as the Niño3.4 predictions under the North American Multi-Model Ensemble (NMME) protocol. Within the limits of their configuration, these complex Earth-system models have a potential for depicting regional changes in oceanic column properties, including the sea surface height. Seasonal prediction models generally have no representation of long-term mass contributions from melting land ice, or changes in vertical land motion; their output may be more specifically characterized as predictions of the ocean dynamic sea level. In practice however, the sea surface height prognostic variable is substantially compromised by the forecast model response to initial conditions. Imbalances between the initial, observed hydrologic cycle and the forecast model state produce abrupt adjustments in the model sea surface height. As a result, most seasonal prediction systems employ a constraint on the globally-averaged sea surface height that is applied at each time step. This essentially renders the prognostic sea surface height variable as unserviceable. Several approaches have previously been used to retrieve sea level information from seasonal forecasts beyond the use of the sea surface height variable. Here, we extend a method of relating other prognostic values, including ocean circulation and climate indices, to observed sea level variations. We use the merged altimetry record of the NASA MEaSUREs Gridded Sea Surface Height Anomalies data set and monthly revised local reference gauge observations from the National Oceanography Centre Permanent Service for Mean Sea Level (PSMSL) to evaluate derived prognostic variables from the NASA Global Modeling and Assimilation Office subseasonal-to-seasonal system version 2.1 (GMAO S2S v2.1). We focus on results for the midlatitudes with particular emphasis on US gauge locations. As shown in previous studies, prognostic ENSO-related indices in boreal winter are well correlated with gauge observations for the US west coast, but also for other locations in the southeastern US. Other forecast climate indices such as the North Atlantic Oscillation have relations to sea level that are limited both seasonally and spatially. As expected, surface atmospheric pressure (e.g., inverse barometer effect) is found to be particularly well correlated with observed sea level. We provide a characterization of forecast skill for seasonal sea level with this method.

Richard I Cullather↗