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NASA NTRS2011

Overview of Pre-Flight Physical Training, In-Flight Exercise Countermeasures and the Post-Flight Reconditioning Program for International Space Station Astronauts

International Space Station (ISS) astronauts receive supervised physical training pre-flight, utilize exercise countermeasures in-flight, and participate in a structured reconditioning program post-flight. Despite recent advances in exercise hardware and prescribed exercise countermeasures, ISS crewmembers are still found to have variable levels of deconditioning post-flight. This presentation provides an overview of the astronaut medical certification requirements, pre-flight physical training, in-flight exercise countermeasures, and the post-flight reconditioning program. Astronauts must meet medical certification requirements on selection, annually, and prior to ISS missions. In addition, extensive physical fitness testing and standardized medical assessments are performed on long duration crewmembers pre-flight. Limited physical fitness assessments and medical examinations are performed in-flight to develop exercise countermeasure prescriptions, ensure that the crewmembers are physically capable of performing mission tasks, and monitor astronaut health. Upon mission completion, long duration astronauts must re-adapt to the 1 G environment, and be certified as fit to return to space flight training and active duty. A structured, supervised postflight reconditioning program has been developed to prevent injuries, facilitate re-adaptation to the 1 G environment, and subsequently return astronauts to training and space flight. The NASA reconditioning program is implemented by the Astronaut Strength, Conditioning, and Rehabilitation (ASCR) team and supervised by NASA flight surgeons. This program has evolved over the past 10 years of the International Space Station (ISS) program and has been successful in ensuring that long duration astronauts safely re-adapt to the 1 g environment and return to active duty. Lessons learned from this approach to managing deconditioning can be applied to terrestrial medicine and future exploration space flight missions.

Kerstman, Eric↗

NASA NTRS2012

Carbon Dioxide Reduction Post-Processing Sub-System Development

The state-of-the-art Carbon Dioxide (CO2) Reduction Assembly (CRA) on the International Space Station (ISS) facilitates the recovery of oxygen from metabolic CO2. The CRA utilizes the Sabatier process to produce water with methane as a byproduct. The methane is currently vented overboard as a waste product. Because the CRA relies on hydrogen for oxygen recovery, the loss of methane ultimately results in a loss of oxygen. For missions beyond low earth orbit, it will prove essential to maximize oxygen recovery. For this purpose, NASA is exploring an integrated post-processor system to recover hydrogen from CRA methane. The post-processor, called a Plasma Pyrolysis Assembly (PPA) partially pyrolyzes methane to recover hydrogen with acetylene as a byproduct. In-flight operation of post-processor will require a Methane Purification Assembly (MePA) and an Acetylene Separation Assembly (ASepA). Recent efforts have focused on the design, fabrication, and testing of these components. The results and conclusions of these efforts will be discussed as well as future plans.

Abney, Morgan B.↗

NASA NTRS2016

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post - Bed Rest and Spaceflight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. These alterations may disrupt crewmembers' ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual spaceflight, which crewmembers are likely to experience the greatest challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures. Our approach includes: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features, using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; and 3) assessment of genotypic markers of genetic polymorphisms in the catechol-O-methyl transferase, dopamine receptor D2, and brain-derived neurotrophic factor genes and genetic polymorphisms of alpha2-adrenergic receptors that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate that these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration spaceflight and exposure to an analog bed rest environment. We will be conducting a retrospective study, leveraging data already collected from relevant ongoing or completed bed rest and spaceflight studies. These data will be combined with predictor metrics that will be collected prospectively (as described for behavioral, brain imaging and genomic measures) from these returning subjects to build models for predicting post-mission (bed rest - non-astronauts or space flight - astronauts) adaptive capability as manifested in their outcome measures. To date we have completed a study on 15 normal subjects with all of the above measures. In this presentation we will discuss the optimized set of tests for predictive metrics to be used for evaluating post mission adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive capacity, brain structure and functional capacities, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.↗

NASA NTRS2017

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post-Bed Rest and Space Flight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. These alterations may disrupt crewmembers' ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts are affected will improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual spaceflight, which crewmembers are likely to experience greater challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures. Our approach includes: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features, using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; and 3) assessment of genetic polymorphisms in the catechol-O-methyl transferase, dopamine receptor D2, and brain-derived neurotrophic factor genes and genetic polymorphisms of alpha2-adrenergic receptors that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate that these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration spaceflight and exposure to an analog bed rest environment. We will be conducting a retrospective study, leveraging data already collected from relevant ongoing or completed bed rest and spaceflight studies. This data will be combined with predictor metrics that will be collected prospectively (as described for behavioral, brain imaging and genomic measures) from these returning subjects to build models for predicting post spaceflight and bed rest adaptive capability. In this presentation we will discuss the optimized set of tests for predictive metrics to be used for evaluating post mission adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive ability, brain structure, brain function, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to mitigate the deleterious effects of spaceflight.

Mulavara, A. P.↗

NASA NTRS2016

Post-Test Inspection of NASA's Evolutionary Xenon Thruster Long-Duration Test Hardware: Discharge and Neutralizer Cathodes

The NEXT Long-Duration Test is part of a comprehensive thruster service life assessment intended to demonstrate overall throughput capability, validate service life models, quantify wear rates as a function of time and operating condition, and identify any unknown life-limiting mechanisms. The test was voluntarily terminated in February 2014 after demonstrating 51,184 hours of high-voltage operation, 918 kg of propellant throughput, and 35.5 MN-s of total impulse. The post-test inspection of the thruster hardware began shortly afterwards with a combination of non-destructive and destructive analysis techniques, and is presently nearing completion. This paper presents relevant results of the post-test inspection for both discharge and neutralizer cathodes. Discharge keeper erosion was found to be significantly reduced from what was observed in the NEXT 2 kh wear test and NSTAR Extended Life Test, providing adequate protection of vital cathode components throughout the test with ample lifetime remaining. The area of the discharge cathode orifice plate that was exposed by the keeper orifice exhibited net erosion, leading to cathode plate material building up in the cathode-keeper gap and causing a thermally-induced electrical short observed during the test. Significant erosion of the neutralizer cathode orifice was also found and is believed to be the root cause of an observed loss in flow margin. Deposition within the neutralizer keeper orifice as well as on the downstream surface was thicker than expected, potentially resulting in a facility-induced impact on the measured flow margin from plume mode. Neutralizer keeper wall erosion on the beam side was found to be significantly lower compared to the NEXT 2 kh wear test, likely due to the reduction in beam extraction diameter of the ion optics that resulted in decreased ion impingement. Results from the post-test inspection have led to some minor thruster design improvements.

Electric Propulsion↗

NASA NTRS2016

Post-Test Inspection of NASA's Evolutionary Xenon Thruster Long-Duration Test Hardware: Discharge Chamber

The NEXT Long-Duration Test is part of a comprehensive thruster service life assessment intended to demonstrate overall throughput capability, validate service life models, quantify wear rates as a function of time and operating condition, and identify any unknown life-limiting mechanisms. The test was voluntarily terminated in February 2014 after demonstrating 51,184 hours of high-voltage operation, 918 kg of propellant throughput, and 35.5 MN-s of total impulse. The post-test inspection of the thruster hardware began shortly afterwards with a combination of non-destructive and destructive analysis techniques, and is presently nearing completion. This paper presents relevant results of the post-test inspection for the discharge chamber as well as other miscellaneous components such as the high-voltage propellant isolators and electrical cabling. Comparison of magnetic field measurements taken during pretest and post-test inspections indicate that the field strength did not degrade, consistent with performance data obtained during the test. Inspection of discharge chamber mesh samples show a deposition coating primarily composed of grid material that is approximately 15 micrometers in thickness. This thickness is well within the retention capability of the mesh and is therefore not expected to present any issues. Approximately 3.1 grams of deposition flakes were found at the bottom of the discharge chamber, composed primarily of grid material and carbon. Calculated size histograms of these flakes indicate that 99% have a maximum dimension of 200 micrometers or smaller, which is significantly less than the ion optics grid gap. Larger flakes that are capable of causing a grid-to-grid short will be analyzed to determine if their formation will occur in flight or is a facility effect. The high-voltage propellant isolators as well as numerous other electrical insulators were inspected and no evidence of arcing or any other issues were found.

Electric Propulsion↗

NASA NTRS2017

Orion Exploration Flight Test Post-Flight Inspection and Analysis

The principal mechanism for developing orbital debris environment models, is to make observations of larger pieces of debris in the range of several centimeters and greater using radar and optical techniques. For particles that are smaller than this threshold, breakup and migration models of particles to returned surfaces in lower orbit are relied upon to quantify the flux. This reliance on models to derive spatial densities of particles that are of critical importance to spacecraft make the unique nature of the EFT-1's return surface a valuable metric. To this end detailed post-flight inspections have been performed of the returned EFT-1 backshell, and the inspections identified six candidate impact sites that were not present during the pre-flight inspections. This paper describes the post-flight analysis efforts to characterize the EFT-1 mission craters. This effort included ground based testing to understand small particle impact craters in the thermal protection material, the pre- and post-flight inspection, the crater analysis using optical, X-ray computed tomography (CT) and scanning electron microscope (SEM) techniques, and numerical simulations.

Miller, J. E.↗

NASA NTRS2017

Improvement of Automated POST Case Success Rate Using Support Vector Machines

During early conceptual design of complex systems, concept down selection can have a large impact upon program life-cycle cost. Therefore, any concepts selected during early design will inherently commit program costs and affect the overall probability of program success. For this reason it is important to consider as large a design space as possible in order to better inform the down selection process. For conceptual design of launch vehicles, trajectory analysis and optimization often presents the largest obstacle to evaluating large trade spaces. This is due to the sensitivity of the trajectory discipline to changes in all other aspects of the vehicle design. Small deltas in the performance of other subsystems can result in relatively large fluctuations in the ascent trajectory because the solution space is non-linear and multi-modal [1]. In order to help capture large design spaces for new launch vehicles, the authors have performed previous work seeking to automate the execution of the industry standard tool, Program to Optimize Simulated Trajectories (POST). This work initially focused on implementation of analyst heuristics to enable closure of cases in an automated fashion, with the goal of applying the concepts of design of experiments (DOE) and surrogate modeling to enable near instantaneous throughput of vehicle cases [2]. Additional work was then completed to improve the DOE process by utilizing a graph theory based approach to connect similar design points [3]. The conclusion of the previous work illustrated the utility of the graph theory approach for completing a DOE through POST. However, this approach was still dependent upon the use of random repetitions to generate seed points for the graph. As noted in [3], only 8% of these random repetitions resulted in converged trajectories. This ultimately affects the ability of the random reps method to confidently approach the global optima for a given vehicle case in a reasonable amount of time. With only an 8% pass rate, tens or hundreds of thousands of reps may be needed to be confident that the best repetition is at least close to the global optima. However, typical design study time constraints require that fewer repetitions be attempted, sometimes resulting in seed points that have only a handful of successful completions. If a small number of successful repetitions are used to generate a seed point, the graph method may inherit some inaccuracies as it chains DOE cases from the non-global-optimal seed points. This creates inherent noise in the graph data, which can limit the accuracy of the resulting surrogate models. For this reason, the goal of this work is to improve the seed point generation method and ultimately the accuracy of the resulting POST surrogate model. The work focuses on increasing the case pass rate for seed point generation.

Zwack, Matthew R.↗

NASA NTRS2017

Automation of POST Cases via External Optimizer and "Artificial p2" Calculation

During early conceptual design of complex systems, speed and accuracy are often at odds with one another. While many characteristics of the design are fluctuating rapidly during this phase there is nonetheless a need to acquire accurate data from which to down-select designs as these decisions will have a large impact upon program life-cycle cost. Therefore enabling the conceptual designer to produce accurate data in a timely manner is tantamount to program viability. For conceptual design of launch vehicles, trajectory analysis and optimization is a large hurdle. Tools such as the industry standard Program to Optimize Simulated Trajectories (POST) have traditionally required an expert in the loop for setting up inputs, running the program, and analyzing the output. The solution space for trajectory analysis is in general non-linear and multi-modal requiring an experienced analyst to weed out sub-optimal designs in pursuit of the global optimum. While an experienced analyst presented with a vehicle similar to one which they have already worked on can likely produce optimal performance figures in a timely manner, as soon as the "experienced" or "similar" adjectives are invalid the process can become lengthy. In addition, an experienced analyst working on a similar vehicle may go into the analysis with preconceived ideas about what the vehicle's trajectory should look like which can result in sub-optimal performance being recorded. Thus, in any case but the ideal either time or accuracy can be sacrificed. In the authors' previous work a tool called multiPOST was created which captures the heuristics of a human analyst over the process of executing trajectory analysis with POST. However without the instincts of a human in the loop, this method relied upon Monte Carlo simulation to find successful trajectories. Overall the method has mixed results, and in the context of optimizing multiple vehicles it is inefficient in comparison to the method presented POST's internal optimizer functions like any other gradient-based optimizer. It has a specified variable to optimize whose value is represented as optval, a set of dependent constraints to meet with associated forms and tolerances whose value is represented as p2, and a set of independent variables known as the u-vector to modify in pursuit of optimality. Each of these quantities are calculated or manipulated at a certain phase within the trajectory. The optimizer is further constrained by the requirement that the input u-vector must result in a trajectory which proceeds through each of the prescribed events in the input file. For example, if the input u-vector causes the vehicle to crash before it can achieve the orbital parameters required for a parking orbit, then the run will fail without engaging the optimizer, and a p2 value of exactly zero is returned. This poses a problem, as this "non-connecting" region of the u-vector space is far larger than the "connecting" region which returns a non-zero value of p2 and can be worked on by the internal optimizer. Finding this connecting region and more specifically the global optimum within this region has traditionally required the use of an expert analyst.

Dees, Patrick D.↗

NASA NTRS2021

Post-test Inspection of NASA’s Evolutionary Xenon Thruster Long-Duration Test Hardware: Discharge Chamber

The NEXT Long-Duration Test is part of a comprehensive thruster service life assessment intended to demonstrate overall throughput capability, validate service life models, quantify wear rates as a function of time and operating condition, and identify any unknown life-limiting mechanisms. The test was voluntarily terminated in February 2014after demonstrating 51,184 hours of high-voltage operation, 918 kg of propellant throughput, and 35.5 MN-s of total impulse. The post-test inspection of the thruster hardware began shortly afterwards with a combination of non-destructive and destructive analysis techniques, and is presently nearing completion. This paper presents relevant results of the post-test inspection for the discharge chamber as well as other miscellaneous components such as the high-voltage propellant isolators and electrical cabling. Comparison of magnetic field measurements taken during pretest and post-test inspections indicate that the field strength did not degrade, consistent with performance data obtained during the test. Inspection of discharge chamber mesh samples show a deposition coating primarily composed of grid material that is approximately 15 μm in thickness. This thickness is well within the retention capability of the mesh and is therefore not expected to present any issues. Approximately 3.1 grams of deposition flakes were found at the bottom of the discharge chamber, composed primarily of grid material and carbon. Calculated size histograms of these flakes indicate that 99% have a maximum dimension of 200 μm or smaller, which is significantly less than the ion optics grid gap. Larger flakes that are capable of causing a grid-to-grid short will be analyzed to determine if their formation will occur in flight or is a facility effect. The high-voltage propellant isolators as well as numerous other electrical insulators were inspected and no evidence of arcing or any other issues were found.

Rohit Shastry↗

NASA NTRS2021

Post-test Inspection of NASA’s Evolutionary Xenon Thruster Long-Duration Test Hardware: Discharge and Neutralizer Cathodes

The NEXT Long-Duration Test is part of a comprehensive thruster service life assessment intended to demonstrate overall throughput capability, validate service life models, quantify wear rates as a function of time and operating condition, and identify any unknown life-limiting mechanisms. The test was voluntarily terminated in February 2014 after demonstrating 51,184 h of high-voltage operation, 918 kg of propellant throughput, and 35.5 MN-s of total impulse. The post-test inspection of the thruster hardware began shortly afterwards with a combination of non-destructive and destructive analysis techniques, and is presently nearing completion. This paper presents relevant results of the post-test inspection for both discharge and neutralizer cathodes. Discharge keeper erosion was found to be significantly reduced from what was observed in the NEXT 2 kh wear test and NSTAR Extended Life Test, providing adequate protection of vital cathode components throughout the test with ample lifetime remaining. The area of the discharge cathode orifice plate that was exposed by the keeper orifice exhibited net erosion, leading to cathode plate material building up in the cathode-keeper gap and causing a thermally-induced electrical short observed during the test. Significant erosion of the neutralizer cathode orifice was also found and is believed to be the root cause of an observed loss in flow margin. Deposition within the neutralizer keeper orifice as well as on the downstream surface was thicker than expected, potentially resulting in a facility-induced impact on the measured flow margin from plume mode. Neutralizer keeper wall erosion on the beam side was found to be significantly lower compared to the NEXT 2 kh wear test, likely due to the reduction in beam extraction diameter of the ion optics that resulted in decreased ion impingement. Results from the post-test inspection have led to some minor thruster design improvements.

Ion engine↗

NASA NTRSDate not supplied

Extreme Environment Hot Fire Durability of Post-Processed Additively Manufactured GRCop-Alloy Combustion Chambers in LOX/Hydrogen and LOX/Methane

Extreme environment survivability of metal additive manufactured (AM) GRCop-alloy thrust chambers has been demonstrated in different bi-propellants at near stoichiometric and even oxygen rich combustion. GRCop-alloy chambers tested at NASA Marshall Space Flight Center (MSFC) have accumulated over 26,000 seconds of hot fire duration and over 500 starts. These chambers are produced using an AM process called laser powder bed fusion (L-PBF). A major feature of this process is high wall surface roughness which can be customized in post processing to leverage various performance advantages. Post-processing can include heat treatment, final machining, polishing, and welding and is key to hardware survivability in extreme environments. Surface finish enhancement techniques were applied to the hot wall and coolant channels to reduce the overall total heat load to the chamber walls. Performance optimization of various thrust class TCA’s is a strategic technology goal of NASA MSFC. Three different chamber geometries using cryogenic methane and de-ionized water as coolants were hot fire tested to obtain their life cycle, pressure drop, and heat load performances. Several 1.2K lbf LOX/H2 chambers, 1K lbf LOX/CH4 chambers, and 7K lbf LOX/CH4 chambers were tested. All post-processed configurations performed remarkably well when subjected to extreme hot fire test conditions. Streaking and blanching due to localized oxygen rich conditions were observed on some test articles in their as-built surface finish state. However, this is actually a function of the injector mixing and only serves to further establish the durability of L-PBF GRCop-alloy thrust chambers. Several different polishing techniques were applied to the hot wall and integrated coolant channels prior to hot fire testing and their performances assessed. Overall, AM produced GRCop chambers are extremely reliable, durable, and customizable to the desired performance metrics.

grcop↗

NASA NTRS2022

Climate Conditions During a Rift Valley Fever Post-epizootic Period in Free State, South Africa, 2014–2019

Rift Valley fever virus (RVFV) activity in Southern Africa tends to occur during periods of sustained elevated rainfall, cooler than normal conditions, and abundant vegetation cover creating ideal conditions for the increase and propagation of populations of RVFV mosquito vectors. These climatic and ecological conditions are modulated by large-scale tropical-wide El Niño–Southern Oscillation (ENSO) phenomena. The aim of this 5-year study was to investigate climatic conditions during Rift Valley fever “post-epizootic” period in Free State province of the Republic of South Africa, which historically experienced the largest RVF outbreaks in this country. We collected satellite-derived rainfall, land surface temperature (LST), and normalized difference vegetation index (NDVI) data since 2014 to understand broad environmental conditions in the years following a period of sustained and widespread large RVF outbreaks (2008–2011) in the region. We found this post-epizootic/interepizootic period to be characterized by below-normal rainfall (~-500 mm), above LSTs (~+12°C), depressed NDVI (60% below normal), and severe drought as manifested particularly during the 2015–2016 growing season. Such conditions reduce the patchwork of appropriate habitats available for emergence of RVFV vectors and diminish chances of RVFV activity. However, the 2016–2017 growing season saw a marked return to somewhat wetter conditions without any reported RVFV transmission. In general, the aggregate vector collections during this 5-year period follow patterns observed in climate measurements. During the 2017–2018 growing season, late and seasonally above average rainfall resulted in a focal RVF outbreak in one location in the study region. This unanticipated event is an indicator of cryptic RVF activity during post-epizootic period and may be a harbinger of RVFV activity in the coming years.

climate variability↗

NASA NTRSDate not supplied

Mapping Post-fire Conifer Regeneration using Snow-on Imagery

The 2000 Jasper Fire in the Black Hills of South Dakota was the largest wildfire to date in the region, burning over 83,000 acres of ponderosa pine forest. In collaboration with partners from the United States Forest Service (USFS) Black Hills Experimental Forest, USFS Rocky Mountain Research Station, and United States Geological Survey Geosciences and Environmental Change Science Center, we characterized post-fire forest regeneration within high severity burn patches. We accomplished this by implementing novel conifer detection techniques using a snow index mask to create a winter, snow-on image composite from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data. We utilized 2015 USFS stem maps of field-observed regeneration plots and ocularly sampled reforestation sites planted from 2001–2013. The field data and imagery were used to train a Random Forest (RF) model in Google Earth Engine. The RF model classified conifer regeneration density as low, medium, or high across the high-severity burn area with an overall accuracy of 81.3% for 2021. Approximately 45.9% of the high-severity burn area had low or no regeneration (0-40 trees per acre) 20 years post-fire. Given our partners' desire to find easily accessible low conifer regeneration zones, we identified 4,079 acres of priority planting sites that were within 1,500 feet of roads, had not been planted previously, and were larger than 50 acres. This method supports the use of snow-on imagery as a successful technique to identify conifer regeneration in a post-wildfire landscape.

Yeshey Seldon↗

NASA NTRS2017

The Detection of 6.9 µm Emission Features in the Infrared Spectra of IRAS 04296+3429, IRAS 05341+0852, IRAS 22272+5435: Evidence for the Presence of Hn-PAHs in Post AGB Stars

Polycyclic aromatic hydrocarbons (PAHs) are generally believed to be ubiquitous in space and responsible for numerous telltale interstellar infrared emission bands. In Sandford et al., (2013), we suggested that polycyclic aromatic hydrocarbons with excess hydrogenation at their periphery (Hn-PAHs) may be an important subclass of these molecules in some astrophysical environments. These molecules are candidates to explain objects with anomalously large 3.4 μm features, which are presumed to be associated with the aliphatic C—H stretching vibrations of the excess hydrogen. In that work, we suggest that for Hn-PAHs to be a viable candidate as the source for this 3.4 μm feature, we must also expect to observe methylene scissoring modes at 6.9 μm. In this work, we continue to develop the Hn-PAH hypothesis with a focus on the 6.9 μm feature. We also present some new observations of three post-asymptotic giant branch (post- AGB) objects with abnormally large 3.4 μm features, IRAS 04296+3429, IRAS 05341+0852, IRAS 22272+5435, in addition to one post-AGB object with normal PAH emissions, IRAS 20000+3239. These observations were made using the FORCAST instrument in grism mode on the Stratospheric Observatory for Infrared Astronomy (SOFIA) aircraft (Adams et al. 2010) and demonstrate the presence of a 6.9 μm feature for the three objects with abnormally large 3.4 μm features and no detectable 6.9 μm feature for the normal PAH emitter. These results are consistent with the hypothesis that Hn-PAHs are a possible source of these infrared emission bands.

ISM↗

NASA NTRS2022

Post-flight Analysis of Atmospheric Properties from Mars 2020 Entry, Descent, and Landing

The Mars 2020 spacecraft landed the Perseverance rover and Ingenuity helicopter successfully in Jezero crater on Feb. 18, 2021. The entry, descent, and landing (EDL) sequence of the spacecraft largely leveraged the previous 2012 Mars Science Laboratory (MSL) mission. The atmospheric modeling approach for Mars 2020 was also borrowed from MSL. It consisted of two mesoscale atmospheric models of the target site during the Martian season of landing, and a statistical model of the pressure, density, temperature, and winds based on the mesoscale model data. This paper briefly describes the pre-flight atmospheric models used for Mars 2020, but focuses on the post-flight assessment of these models and comparison to near-landing day orbiter sounder and other onboard atmospheric measurements. Observations from post-flight analysis showed that density was under-predicted in the upper atmosphere, but within the altitudes covered by the mesoscale models, the pre-flight modeling matched post-flight results, including for quantities like wind velocities. Potential improvements to address the upper atmosphere and other deficiencies of the Mars 2020 pre-flight model are also discussed.

Villar, Gregorio↗

NASA NTRSDate not supplied

Comparison of Pre- and Post-Flight Estimations of Pitch Damping Coefficients for Unguided Entry Vehicles

Pre-flight predictions of pitch damping coefficient (C M q + C m ȧ ) curves are used in entry simulations to determine flight readiness and if any dynamic remediation strategies are required. Accurate characterization of these pitch damping coefficient curves is crucial for mission success. Historically, pre-flight estimations of these curves are derived experimentally either via ballistic range testing or with 1-degree-of-freedom (DOF) free-or forced-oscillation wind tunnel testing. With post-flight best-estimated trajectories, a fitting procedure as described in Karlgaard, et. al. is used to compare pre-and post-flight pitch damping coefficients. This technique relies on an assumed analytical form of the trajectory, a limited 3-DOF representation described in Schoenenberger and Queen, which results in an Euler-Cauchy solution form. This solution assumes constant density, thus limited amplitude multi-peak windows of the trajectory are considered to populate the pitch damping-amplitudes pace. The estimated post-flight pitch damping approximations and the pre-flight predictions shown are effective representations of pitch damping, or the integrated effect of the pitch damping coefficient over one pitch cycle at the corresponding cycle’s peak amplitude. Effective pitch damping coefficient curves provide more intuitive insights about where the vehicle is stable and permits readily processed comparisons between data-sets. It is important to note that most pitch damping curves, such as those reported in aero databases and utilized in flight mechanics trajectory simulations, are represented in instantaneous angle-of-attack space distinct from what is presented in the paper.

pitch damping coefficient↗

NASA NTRS2025

An Observation-Driven Framework for Modeling Post-Fire Hydrologic Response: Evaluation for Two Central California Case Studies

In a warming climate, wildfires are becoming increasingly common, especially in semi-arid environments. Wildfires can disrupt forest ecosystems and induce changes to the land surface. Collectively, these impacts can alter the hydrologic response of a catchment following a fire, resulting in increased potential for surface runoff, reduced evapotranspiration, and, ultimately, a higher risk for flash flooding and mass wasting. The timescale of post-fire recovery of hydrological processes to return to pre-fire conditions is not well established due to the lack of ground measurements. Accurate characterization of the impacts of fire on hydrologic response is also challenging to simulate, given the complex interplay of various processes. Here, we present a generalized framework to quantify the impacts of wildfire on runoff generation. We consider the disturbances in the vegetation and soil as the two main factors contributing to post-fire floods. Using an ensemble modeling structure to account for parameter uncertainty, remotely sensed leaf area index (LAI) is assimilated into a land surface model (LSM) to simulate vegetation disturbance, and the maximum land surface saturation LSM parameter is decreased to parameterize the soil disturbance following observed fires. We consider the impacts of fire-induced changes to LAI and soil saturation on hydrologic states like runoff and evapotranspiration for two case studies. These case studies demonstrate the general applicability of hydrophobicity formulation to serve as a guideline for exploring the range of hydrologic responses post-fire.

Fire Hydrology↗