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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Kepler Planet Detection Metrics: Per-Target Flux-Level Transit Injection Tests of TPS for Data Release 25

Quantifying the ability of a transiting planet survey to recover transit signals has commonly been accomplished through Monte-Carlo injection of transit signals into the observed data and subsequent running of the signal search algorithm (Gilliland et al., 2000; Weldrake et al., 2005; Burke et al., 2006). In order to characterize the performance of the Kepler pipeline (Twicken et al., 2016; Jenkins et al., 2017) on a sample of over 200,000 stars, two complementary injection and recovery tests are utilized:1. Injection of a single transit signal per target into the image or pixel-level data, hereafter referred to as pixel-level transit injection (PLTI), with subsequent processing through the Photometric Analysis (PA), Presearch Data Conditioning (PDC), Transiting Planet Search (TPS), and Data Validation (DV) modules of the Kepler pipeline. The PLTI quantification of the Kepler pipeline's completeness has been described previously by Christiansen et al. (2015, 2016); the completeness of the final SOC 9.3 Kepler pipeline acting on the Data Release 25 (DR25) light curves is described by Christiansen (2017).2. Injection of multiple transit signals per target into the normalized flux time series data with a subsequent transit search using a stream-lined version of the Transiting Planet Search (TPS) module. This test, hereafter referred to as flux-level transit injection (FLTI), is the subject of this document. By running a heavily modified version of TPS, FLTI is able to perform many injections on selected targets and determine in some detail which injected signals are recoverable. Significant numerical efficiency gains are enabled by precomputing the data conditioning steps at the onset of TPS and limiting the search parameter space (i.e., orbital period, transit duration, and ephemeris zero-point) to a small region around each injected transit signal.The PLTI test has the advantage that it follows transit signals through all processing steps of the Kepler pipeline, and the recovered signals can be further classified as planet candidates or false positives in the exact same manner as detections from the nominal (i.e., observed) pipeline run (Twicken et al., 2016, Thompson et al., in preparation). To date, the PLTI test has been the standard means of measuring pipeline completeness averaged over large samples of targets (Christiansen et al., 2015, 2016; Christiansen, 2017). However, since the PLTI test uses only one injection per target, it does not elucidate individual-target variations in pipeline completeness due to differences in stellar properties or astrophysical variability. Thus, we developed the FLTI test to provide a numerically efficient way to fully map individual targets and explore the performance of the pipeline in greater detail. The FLTI tests thereby allow a thorough validation of the pipeline completeness models (such as window function (Burke and Catanzarite, 2017a), detection efficiency (Burke Catanzarite, 2017b), etc.) across the spectrum of Kepler targets (i.e., various astrophysical phenomena and differences in instrumental noise). Tests during development of the FLTI capability revealed that there are significant target-to-target variations in the detection efficiency.

DR25↗
NASA NTRS2019

New Features in the SPOC Pipeline Release 4.0

The Science Processing Operations Center is in the process of testing and deploying Release 4.0 of the codebase in the March 2019 timeframe. This paper describes the new features of the software and their likely impact on the quality of the TESS science data products. The major goals of Release 4.0 are to improve the extraction of photometry from the pixels in light of the non-uniform pointing performance and the identification of instrumental signatures from the light curves. We also describe modifications to the FFI pipeline to allow the generation of FFI light curves, correction of the instrumental systematics therein, and planet searches, primarily for the purpose of validating the 2-min pipeline against the FFI pipeline, but also to be able to provide cotrending basis vectors (CBVs) derived directly from the FFIs to the public to aid them in their extraction and correction of photometry. We also discuss the improvements in photometric performance of the pipeline and its various components.The lapse in funding experienced between 22 December 2018 and 27 January 2019 significantly delayed our ability to conduct integration testing as planned for late December/early January, delaying the start of V&V by one month to the end of February 2019.The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.The Science Processing Operations Center is in the process of testing and deplo!"ing Release 4.0 of thecodebase In the March 2019 tlmeframe. This paper describes the new features or the software and theirlikely impact on the quality of the TESS science data products. The major goals or Release 4.0 are to Imtheidentification of instrumental signatures from the light cuNes. We also describe modifications tothe FFI pipeline to allow the generation of FFI light curves, correction of the instrumental systematicstherein, and planet searches, primarily for the purpose of validating the 2-min pipelineagainst the FFI pipeline, but also to be able to provide cotrending basis vectors (C3Vs) ,,.~,.;.derived directly from the FFls to the public to aid them in their extractbn and correction , :-; ~'-'\'.'.of photometry. We also discuss the Improvements In photometric performance• of ~~\":;:•the pipeline and its various components. :,;.-.;The lapse In funding experienced between 22 December 2018 and 27January 2019 significantly delayed our ability to conduct Integrationtesting as planned for late December/early January, delaying thestart of V&V by one month to the end of February 2019.The TESS Mission is funded by NASA's Science Mission Directorateas an Astrophysics Explorer Mission.o.iu.c...,.....~~New Features in SPOC 4.01. Use of quatemions In photometry and centroiding.2. Use of quaternions to Identify high-motion cadences and exclude same.3. Use of the TPS detections to deemphasize pathological cadences ("skyline flattenlng"I.4. Improved CAL calculations for black and smear correction.5. PA brightness metric calculation improvements (induo'e crowding in calrulation)./ • 6. Improved POC spike goodness metric.•~• 7. Improved handling of gaps and momentum duni:>S in POC.8. Improved tuning of POC., 9. Improved attitude tweak correction in PDC.10. Improvements in PDC introduced noise and correlation goodness metrics11. Using the improved spike goodness metric to minimize overlitting in the spikeremover ' • :,''l./ 12. Enable FFI processing through planet search.,,. ,• • "« ,;,,,•.~'A , 13.1 D4.V S mtreinaim-relipnoinrgts d aartcah irveetrdie tvoa Ml aAnSdT p ersistence to database 15. Improved management of jobs on the NAS Pleiadss supercomputer

Jenkins, Jon M.↗
NASA NTRS2019

Risk Estimation of Threatening Asteroids

When faced with the question of designing an asteroid deflection mission or with the decision of launching it, significant uncertainties are present in the asteroid’s physical properties, and its orbit solution. The success of the deflection mission relies heavily on these aspects. For example, a heavier than expected asteroid will reduce the imparted deflection DV. So will a larger porosity value by reducing the beta factor [1]. Here, we present a new capability that estimates asteroid impact risk under consideration of these uncertainties. The new method samples the uncertainty space along multiple dimensions, performs a predetermined deflection, propagates the deflected samples to the Earth, models the impact damage, and estimates the overall risk outcome. The work builds on the Probabilistic Asteroid Impact Risk (PAIR) assessment tool [2] by including orbital uncertainty and deflection capabilities. We demonstrate this risk estimation approach for threatening asteroids using the example of the fictitious impactor 2019 PDC. Such analysis provides a quantitative basis for the work of decision makers and disaster managers. It may further find application in areas such as mitigation mission planning where projected post-mitigation risk can be compared to premitigation levels as a means of cost-benefit analysis formitigation options.

Rumpf, Clemens↗
NASA NTRS2019

PDC19 Impact Exercise: Probabilistic Asteroid Impact Risk Assessment

Probabilistic Asteroid Impact Risk (PAIR) - PDC (Planetary Defense Conference) 2019 Hypothetical Exercise, NASA Ames, Asteroid Threat Assessment Project (ATAP) - Characterization Summary and Updates: Assessment date: 19 April 2027; Impact date: 29 April 2027 (10 days); Earth impact probability: 100 percent, New York Area; Diameter (meters): 60 plus or minus 10 (1 minus sigma), range 26–93; Energy: mean 11 megatons, range 650 kilotons to 46 megatons; Type: S class, remaining chunk of disrupted contact binary. Risk Summary: Affected population: mean 2.4 million, range zero to 10.2 million; Likely airburst at approximately16 kilometers altitude (8 to 29 kilometers); Blast overpressure is primary hazard; Damage out to approximately 70 kilometers if larger, lower burst; Little-to-no damage if burst is small and high.

Wheeler, Lorien↗
NASA NTRS2018

Fuzzy Modeling and Parallel Distributed Compensation for Aircraft Flight Control from Simulated Flight Data

A method is described that combines fuzzy system identification techniques with Parallel Distributed Compensation (PDC) to develop nonlinear control methods for aircraft using minimal a priori knowledge, as part of NASA’s Learn-to-Fly initiative. A fuzzy model was generated with simulated flight data, and consisted of a weighted average of multiple linear time invariant state-space cells having parameters estimated using the equation-error approach and a least-squares estimator. A compensator was designed for each subsystem using Linear Matrix Inequalities (LMI) to guarantee closed-loop stability and performance requirements. This approach is demonstrated using simulated flight data to automatically develop a fuzzy model and design control laws for a simplified longitudinal approximation of the F-16 nonlinear flight dynamics simulation. Results include a comparison of flight data with the estimated fuzzy models and simulations that illustrate the feasibility and utility of the combined fuzzy modeling and control approach.

Weinstein, Rose↗
NASA NTRS2015

Advanced Solar Electric Propulsion for Planetary Defense

Once the current survey to identify all near-Earth objects larger than 140-m diameter is complete, the major hazard from asteroid impacts may be from asteroids in the 50- to 100-m diameter size range. High-power solar electric propulsion systems employed in “slow-push” techniques may be the best way to deflect asteroids in this size range if deflection is warranted. The relative performance of three slow-push techniques—gravity tractor (GT), enhanced gravity tractor (EGT), and ion beam deflection (IBD)—are compared, assuming solar electric propulsion vehicles derived from NASA’s Asteroid Redirect Robotic Mission concept vehicle. Both the enhanced gravity tractor and ion beam deflection concepts are shown to be significantly better than the standard gravity tractor concept. The Hall-thruster based enhanced gravity tractor systems and ion beam deflection systems (based on the use of high-power gridded ion thrusters) are shown to provide comparable performance, i.e., similar deflection times and propellant required. Enhanced gravity tractor systems require the acquisition of material from the surface of the hazardous object in order to achieve the required “enhancement” of the gravitational coupling force. This makes EGT systems sensitive to the rotational state and surface properties of the unknown object, and potentially severely limits its applicability. Ion beam deflection is completely independent of the characteristics of the threat object. In fact, it is the only asteroid deflection technique, slow-push or otherwise, that can make this claim, thus potentially greatly increasing its applicability relative to other deflection techniques. Finally, high-power IBD systems are shown to be capable of deflecting the fictitious asteroid 2015 PDC used in the hypothetical asteroid impact exercise conducted at the 2015 Planetary Defense Conference.

Brophy, John↗
NASA NTRS2020

An Integrated Model of Models for Global Flood Alerting

A dramatic increase in frequency of minor to major flooding since 2000 has caused significant damage to infrastructure and economic losses across the world. To mitigate and recover from these losses, actions have been taken to build resilient communities and infrastructures. Situational awareness in near real-time is essential to ensure community resilience and enhance response and recovery efforts. Several hydrologic and hydraulic flood models are available at various spatial and temporal resolutions at regional to global scale. Given the global coverage of two operational flood models - GloFAS (Global Flood Awareness System) and GFMS (Global Flood Monitoring System), the first component of this project first focuses on integrating the outputs from these two models to classify flood severity and send alerts based on potential for impacts similar to the USGS PAGER (used for severity alerting and impact analysis for earthquakes). The second component of the project focuses on using flood outputs derived from earth observation data to validate, update and add additional exposure and impact products to flood alerts. The flood impacts and severity information will be disseminated as alerts and maps through the DisasterAWARE platform, operated by the Pacific Disaster Center (PDC), that provides global multi-hazard alerting and Situational Awareness information to the emergency management community and public. In this presentation, the following objectives will be covered: (i) the effective integration of the flood models, (ii) accuracy of the flood model outputs (flood extent and depth) for specific flood events both in the United States and globally in comparison with each other and earth observation data.

Glasscoe, Margaret↗
NASA NTRSDate not supplied

Consequences of Asteroid Characterization on the State of Knowledge about Inferred Physical Properties and Impact Risk

Physical characteristics of Near-Earth Objects (NEOs) are essential inputs to planetary defense assessments. The size, density, and strength of an NEO are critical inputs to modeling behavior during atmospheric entry as well as assessing the risk of impact. Similarly, knowledge of the physical characteristics of an object are necessary to evaluate the probable result of a mitigation mission. Usually, these attributes cannot be directly measured, but increasingly sophisticated methods have been developed to infer physical properties from related measurements of asteroids, meteors, and/or meteorites. Fortuitously, some of these measurements have been obtained for enough NEOs to elucidate the distribution of values across the sampled population. However, the situation becomes more challenging when considering a specific asteroid, since it is unlikely that all the relevant measurements have been made for any given object. We have developed a Bayesian network that can combine available information about a particular NEO with knowledge of the larger population to infer probabilistic values and uncertainties for physical characteristics of interest. Distributions of asteroid population albedos, taxonomic classes, and macroporosities, along with meteorite density distributions and associations between taxonomic classes and meteorite classes, provide the default distributions for the network’s parameter nodes. The inference network links parameters for each virtual asteroid either deterministically or probabilistically as appropriate, and eliminates any unphysical combinations of parameters. Within the context of planetary defense, our Bayesian network can be used to constrain the ranges of likely impactor properties, which can subsequently reduce the uncertainty in modelling of atmospheric entry, mitigation efficacy, and impact risk assessment. When additional measurements become available for a specific object, the network incorporates those measurements to generate virtual asteroids with property distributions that are consistent with the measurements. We will use the 2023 PDC scenario to demonstrate how the inference network can be combined with plausible characterization measurements to refine the state of knowledge about likely combinations of physical parameters and the resulting impact risk.

risk assessment↗
NASA NTRSDate not supplied

Sensitivity Study of Impact Risk Model Results to Thermal Radiation Damage Model for Large Objects

NASA’s Probabilistic Asteroid Impact Risk (PAIR) assessment model assesses the likelihood of potential damage for asteroid impact scenarios. Fast-running models are used to capture the effects of different hazards. This paper looks specifically at local ground damage hazards, including blast overpressure and thermal radiation damage, for large object impact scenarios. A sensitivity study is conducted to determine which parameters, and over what ranges, cause impact risks to become sensitive to thermal damage. Two additional thermal models with different approaches are used for comparison. The study determined the current thermal model is most sensitive to the luminous efficiency parameter that reflects the model’s uncertainty in the amount of energy contributing to the thermal radiation damage. This sensitivity was most apparent for the highest severity damage levels. Comparisons of the three models showed that in addition to sensitivities within the models, the impact risks are also sensitive to the choice of thermal model. The study results were applied to the 2023 PDC hypothetical asteroid impact scenario and parameter ranges of interest determined. At the serious damage level, luminous efficiencies above 0.006 showed a small chance of thermal playing an important role, while luminous efficiencies above 0.0008 led to thermal playing a significant role at the unsurvivable damage severity level. Study results are used to identify key areas where additional model refinement and better knowledge of asteroid properties may be important for improving damage estimates.

SMD↗
NASA NTRSDate not supplied

Consequences of Asteroid Characterization on the State of Knowledge about Inferred Physical Properties and Impact Risk

Physical characteristics of Near-Earth Objects (NEOs) are essential inputs to planetary defense assessments. The size, density, and strength of an NEO are critical inputs to modeling behavior during atmospheric entry as well as assessing the risk of impact. Similarly, knowledge of the physical characteristics of an object are necessary to evaluate the probable result of a mitigation mission. Usually, these attributes cannot be directly measured, but increasingly sophisticated methods have been developed to infer physical properties from related measurements of asteroids, meteors, and/or meteorites. Fortuitously, some of these measurements have been obtained for enough NEOs to elucidate the distribution of values across the sampled population. However, the situation becomes more challenging when considering a specific asteroid, since it is unlikely that all the relevant measurements have been made for any given object. We have developed a Bayesian network that can combine available information about a particular NEO with knowledge of the larger population to infer probabilistic values and uncertainties for physical characteristics of interest. Distributions of asteroid population albedos, taxonomic classes, and macroporosities, along with meteorite density distributions and associations between taxonomic classes and meteorite classes, provide the default distributions for the network’s parameter nodes. The inference network links parameters for each virtual asteroid either deterministically or probabilistically as appropriate, and eliminates any unphysical combinations of parameters. Within the context of planetary defense, our Bayesian network can be used to constrain the ranges of likely impactor properties, which can subsequently reduce the uncertainty in modelling of atmospheric entry, mitigation efficacy, and impact risk assessment. When additional measurements become available for a specific object, the network incorporates those measurements to generate virtual asteroids with property distributions that are consistent with the measurements. We will use the 2023 PDC scenario to demonstrate how the inference network can be combined with plausible characterization measurements to refine the state of knowledge about likely combinations of physical parameters and the resulting impact risk.

risk assessment↗
NASA NTRSDate not supplied

Mars Sample Return Mars Ascent Vehicle Separation Analysis Utilizing the CLVTOPS Toolchain

A key element of the joint NASA and European Space Agency (ESA) Mars Sample Return (MSR) Campaign is the Mars Ascent Vehicle (MAV), which is being developed primarily by NASA Marshall Space Flight Center (MSFC), in association with NASA’s Jet Propulsion Laboratory (JPL) and Langley Research Center (LaRC). The MAV is a Mars-launched rocket that is responsible for transporting soil samples collected by the Perseverance rover from the Martian surface into orbit, where they will be captured by ESA's Earth Return Orbiter (ERO) for the return journey to Earth. The MAV design concept developed during the MAV Systems Requirement Cycle (SRC) and Preliminary Design Cycle (PDC) consisted of a two-solid-stage configuration, where the second stage is completely unguided in order to reduce vehicle and overall mission mass. The unguided second stage design presents technical challenges for the stage separation event, as the second stage trajectory and the payload’s ability to rendezvous with the ERO is extremely sensitive to disturbances during vehicle staging. The MSFC-developed CLVTOPS multibody dynamics toolchain was utilized to quickly assess multiple stage separation hardware options and to optimize the separation Concept of Operations (ConOps) in order to ensure successful near-field stage separation performance and maximize the orbital accuracy of the payload. This paper will describe how the CLVTOPS toolchain was used to assess the MAV stage separation event and help inform and optimize the MAV design and ConOps.

MSR↗
NASA NTRS1998

New Approach to Concept Feasibility and Design Studies for Astrophysics Missions

JPL has assembled a team of multidisciplinary experts with corporate knowledge of space mission and instrument development. The advanced Concept Design Team, known as Team X, provides interactive design trades including cost as a design parameter, and advanced visualization for pre-Phase A Studies.

Concept Feasibility Design Studies Team X Astrophy↗
NASA NTRS2014

Organic Entrainment and Preservation in Volcanic Glasses

Unaltered pyroclastic deposits have previously been deemed to have "low" potential for the formation, concentration and preservation of organic material on the Martian surface. Yet volcanic glasses that have solidified very quickly after an eruption may be good candidates for containment and preservation of refractory organic material that existed in a biologic system pre-eruption due to their impermeability and ability to attenuate UV radiation. Analysis using NanoSIMS of volcanic glass could then be performed to both deduce carbon isotope ratios that indicate biologic origin and confirm entrainment during eruption. Terrestrial contamination is one of the biggest barriers to definitive Martian organic identification in soil and rock samples. While there is a greater potential to concentrate organics in sedimentary strata, volcanic glasses may better encapsulate and preserve organics over long time scales, and are widespread on Mars. If volcanic glass from many sites on Earth could be shown to contain biologically derived organics from the original environment, there could be significant implications for the search for biomarkers in ancient Martian environments.

glass from lava domes↗