Interpreting Archival Cross-Section vs. LET Fit Parameters Based On Data Quality
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Ray Ladbury↗
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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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Aqua vs. GCOM-W1 Orbit Passing Event Executive Summary
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Earth Observing ystem (EOS)↗
Unraveling Solar Wind Space Weathering of Carbon-Rich Asterods: Low-Flux VS. High-Flux Ion Irradiation of Murchison
Introduction: Space weathering processesalter the microstructural, compositional, and optical properties of airless planetary surfaces.Solar wind space weatheringforms ion-damaged rims within the outermost ~100 nm of regolith grains through atomic-displacements and implantation of energetic H+and He+ions[1]. Transmission electron microscope(TEM)studies of space weathered Itokawa and lunar olivine particles reveal predominantly nanocrystalline solar wind-damaged rims with only minor regions of amorphization[2-5]. This finding differs from laboratoryion irradiation experiments in which samples become amorphous at fluences 2-3 orders of magnitude lower than the independentlyconstrained fluences for still-crystalline natural samples [6-7].Ion flux is generally considered to have a secondaryeffectcompared to fluence in these irradiation experiments. However, solar wind irradiation of natural samples occurs at a flux that is ~4-5 orders of magnitude lower than whatisused inlaboratory simulations (e.g., [6,8-9]). Constraining how the very low ion flux of solar wind influences the microstructural, chemical, and spectral alteration of silicate minerals will improve our understanding of solar wind space weathering and aid in the analysis of returned samples from the Hayabusa2 and OSIRIS-REx missions. Here we report results from low-and high-flux ion irradiation experiments on the Murchison (CM2)meteoritewithcomparable total fluences. Methods: We performed low-flux and high-flux He+(4 keV) and H+(1 keV) irradiation experiments on separate, dry-cut Murchison slabs. Low-flux He+irradiation reached a total fluence of 2.1 x 1016ions/cm2(~400 years of exposure at Bennu) using a flux of 3.6 x 1011ions/cm2/s; low-flux H+irradiation reached a total fluence of 3.9 x 1016ions/cm2(~30 years) using a flux of 6.6 x 1011ions/cm2/s. High-flux He+irradiation reached a total fluence of 2.0 x 1016ions/cm2(~400 years)using a flux of 9.1 x 1012ions/cm2/s; high-flux H+irradiation reached a total fluence of 5.8 x 1016ions/cm2(~50 years)using flux of 8.4 x 1012ions/cm2/s. By irradiating to similar total fluences in both the low-flux and high-flux experiments, we can better isolate and evaluatethe effects of ion flux. Differences between unirradiatedand irradiated surfaces are determined using threeanalytical techniques:(1) in situX-ray photoelectron spectroscopy(XPS) reveals changes in surface chemistry,(2) visible to near-infrared spectroscopy (VNIR; 0.35-2.5 μm) highlights changes in spectraltrends, such as albedo and slope, and (3) TEM and energy-dispersive X-ray spectroscopy (EDS) identifieschanges in nanoscale structure and elemental composition within olivine and matrix electron-transparent thin sections prepared using focused ion beam scanning electron microscopy (FIB-SEM). Results and Discussion: XPS analyses of the low-fluxand high-fluxHe+-and H+-irradiated samples showa minorreduction in surface carbon contentand chemicalreduction ofFe3+to Fe2+. The latter result is consistent with the higher Fe2+/Fe3+ratios observed in phyllosilicate-rich space weathered rims of Ryugu grains [10].VNIR analyses suggest that the low-flux H+-irradiated spectrum has a slightly bluer slope (over 0.65-2.5 μm) compared to the unirradiated VNIR spectrum from [9] while the low-flux He+-irradiated spectral slope is comparable to the unirradiated surface. Both the high-flux He+-and H+-irradiated VNIR spectra exhibitslightlyhigheralbedos at shorter wavelengths relativeto their unirradiated counterparts, with He+irradiation yielding a greater change. Thus far, the low-flux He+-irradiated matrix and olivine FIBsections as well as the low-flux H+-irradiated olivine FIBsection have been examined with TEM. The surfaces of all three samplesshowless vesiculation than high-flux/high-fluenceirradiated matrix and olivine samples from [9]. The depth of phyllosilicate amorphization in thelow-fluxHe+-irradiated matrix FIBsection varieslaterally, with crystalline domains occurring as shallow as ~25 nm in some regions. Thelow-flux He+-irradiated olivine FIBsection has acontinuous,~40-90 nm thick ion-affected layer with polycrystalline and amorphous microstructures. The low-flux H+-irradiated olivine sampleexhibits a distinct, ~10-40 nm ion-affected layer whose uppermost ~20 nmin thicker regions is predominantly amorphous.Continuing to compare results from this work to those from [9] will provide a comprehensive understanding of how ion flux impacts the microstructural, chemical, and optical modification of various mineral phases and, in turn,help identify space weathering features from parent body alteration in Hayabusa2 and OSIRIS-REx returned samples.
D L Laczniak↗
Metallic Vs Inflatable Primary Structure: A Comprehensive Trade for a Mars Transit Habitat
Large diameter inflatable habitat solutions are hypothesized to have an advantage over traditional metallic habitats of equal volume and functional requirements in terms of minimizing mass. A fair and comprehensive trade of metallic primary structure versus inflatable softgoods primary structure for a Mars Transit Habitat was conducted by The Boeing Company under the NASA Next Space Technologies for Exploration Partnerships-2 (NextSTEP-2)Appendix A contract in order to determine the minimum mass option from a system level. A Mars Transit Habitat is a major system mass driver because small increases in the mass can create large mass changes in the propulsive stage, adding complexity and cost to the mission. Three different vehicle configurations were traded using a fixed volume constraint and the same Ground Rules and Assumptions(GR&A)provided by NASA. The configurations were 1) 5.5 m diameter metallic habitat, 2) 7.0 m diameter metallic habitat, and 3) 7.63 m diameter inflatable habitat. In order to complete the trade, each configuration was analyzed and sized, but a system level approach had to be taken to ensure other aspects and subsystems besides the structure were captured. The primary functions (i.e. restraint layer, bladder, multilayer insulation [MLI], micro-meteoroid orbital debris [MMOD]) and strength advantages of softgoods are well understood, but there were other system level impacts that were discovered or addressed that are unique to softgoods. For the metallic structure, a modern and mass optimal material and manufacturing process was adopted to ensure the lightest weight options were evaluated. Two different aluminium lithium structures were evaluated, a longer length 5.5 m diameter and a shorter length 7 m diameter structure. The trade demonstrates that each configuration is feasible and close to the target dry mass for the Mars Transit Habitat Trans-Martian Injection burn. System level mass was the primary consideration, but since the three concepts were close in total mass, a clear winner did not arise. Secondary factors were evaluated such as architecture habitability (human factors), development considerations, on-orbit activation and outfitting, extensibility to other applications, and configuration flexibility. The aggregation of the lowest mass, most benefits, and fewest challenges resulted in the 5.5m diameter metallic configuration being the most favorable.
Matthew Ziglar↗
Expectation vs. Reality: The Sunrise Problem Applied to Probabilistic Risk Assessment
The Sunrise Problem is succinctly stated as a question: “what is the probability that the sun will rise tomorrow?” Attempts to answer this seemingly simple question reveal unexpected incongruities between statistical/probabilistic estimates and “real-world” expectations. Rather than being a purely philosophical problem, similar incongruities can be found in reliability and probabilistic risk assessment (PRA) analyses. These differences between statistical predictions and demonstrated reliability can result in analysis shortcomings that should be addressed and resolved. This presentation will begin by discussing the nature of the Sunrise Problem and how it applies to PRA and reliability. Examples of the Sunrise Problem in a PRA estimate will also be included, along with tips to identify and resolve the shortcomings that result from these anomalous situations.
Sunrise Problem↗
Assessment of M2020 Terrain Relative Landing Accuracy: Flight Performance vs Predicts
No abstract provided
Chen, Allen↗
A Brief Review of Chaotropic vs. Kosmotropic Salts on the Degree of Saturation of Membrane Fatty Acids: Implications for Preservation of Environmental Biomarkers
Water activity is well known to have a significant impact on habitability, due to the presence of salts. However, salt composition is also important for habitability, as it can impact microbial activity and biomolecular interactions since certain salts are known to disrupt hydrogen bonding. Chaotropic agents disrupt hydrogen bonding in aqueous solutions leading to increased entropy (chaos) whereas kosmotropic agents are compounds that promote hydrogen bonding (order). The Hofmeister series (Fig. 1) shows the ordering of ions in terms of their ability to stabilize and induce precipitation or aggregation of proteins.
M B Wilhelm↗
Assessment of M2020 Terrain Relative Landing Accuracy: Flight Performance vs Predicts
Terrain Relative Navigation (TRN) was a critical enabling Entry, Descent, and Landing (EDL) technology that enabled Mars 2020 mission Perseverance rover to land at Jezero crater. TRN pro-vides real-time, autonomous, map-relative position determination and generates a landing target based on a priori knowledge of hazards. The required performance for TRN was to land within 60m of the selected target. The required 60m was sub-allocated to various error sources in three major categories: targeting error, knowledge error, and control error. The targeting error is the error in selecting an appropriate landing target and the knowledge of the target on the surface. It includes the Lander Vision System (LVS) position localization with respect the ground, the synchronization between the Lander Vision System measurement and the main Navigation filter, and errors associated with the LVS Reference Map and Safe Target Selec-tion (STS). The knowledge error is the contribution of knowledge growth from the synchronization with LVS to touchdown. The control error encompasses how accurately the system could stay on the desired reference trajectory. The TRN error budget uses a combination of analysis, simulation, and hardware test-ing results to bound the various error contributions obtained during the verification and validation process. This paper first presents a description the TRN system, focusing on the architecture of LVS and STS. The paper then gives detailed overview of the TRN error budget, with a description of the major error contribu-tions in each of the three categories. Next, the paper gives the results for three versions of the error budget, pre-launch, in-flight pre-landing, and post-landing. The paper compares the pre-flight analysis, the pre-landing analysis using in-flight data during cruise, to the post-landing analysis of the TRN performance. Pre-landing analysis best estimate of the landing performance was 33m, compared to the 60m require-ment. Post-landing analysis estimated a landing accuracy of 8.53m or better, much better than the 33m pre-landing estimate. The actual post-landing imagery calculated the distance of the rover to the targeted location to be 5m. The post-landing analysis closely bounds the image-based assessment of landing accu-racy, indicating the success of the error budget architecture in bounding the landing accuracy, as well as the fidelity of the simulations used to model and predict performance.
Chen, Allen↗
Predictability of the Minimum Sea Ice Extent from Late Winter Fram Strait Ice Export: Model vs Observations
Late winter coastal divergence along the Eurasian coastline (referred to as the ice factory) – or the Fram Strait ice export, a proxy for coastal divergence in the ice factory – is a skillful predictor of the minimum sea ice extent (Williams et al., 2016; Brunette et al., 2018; Sesternikov and, 1979). Coastal divergence leads to the formation of coastal polynya where new ice grows but to a thickness that is not large enough to survive the following summer melt. This signal is then amplified by the ice albedo feedback and leads to more open water at the end of the summer melt season. In this thesis project, we will identify if this source of predictive skill in the seasonal forecast of the minimum sea ice extent is present in General Circulation Models, more precisely in the CESM2-LE, GISS-E2.1-G, GFDL FLOR-LE, CNRM-CM6-1 and the CanESM5. Since even small biases in the large-scale atmospheric circulation simulated by a model can short circuit this coupling between dominant modes of atmospheric variability (NAO and AO), coastal divergence along the Eurasian coastline, Fram Strait ice export and therefore seasonal forecasting skill of the model, failure to reproduce this coupling observed in the real Arctic will be used to identify biases in GCM. Preliminary results show that subtle changes in the large-scale atmospheric circulation leads to opposite statistical relationship between Fram Strait ice area export, coastal divergence along the Eurasian coastline, and seasonal predictability of the minimum sea ice extent both in the CESM2-LE and the GISS-E2.1-G models. Differences are linked with the partitioning between recirculation within the Beaufort Gyre, ice exported through Fram Strait and ridging north of the Canadian Arctic Archipelago.
Sea ice↗
Autonomous Operations: Expectations vs. Reality (at NASA)
- Future deep-space exploration drives need for autonomy - Communication time delay between Earth and deep-space system precludes Earth-based remote-control - Autonomy is: - Acting separately from others (Webster’s Dictionary) - Able to independently choose how to act to achieve goals - Autonomy is a relative term: Autonomous from whom? for what purpose? and when? - Autonomous Operations is: - Automatically controlled operation of a system that replaces human effort - Able to perform a pre-specified set of instructions on its own - Automation is a tool that enables and supports autonomy
Autonomous Operation↗
Predictability of the Minimum Sea Ice Extent from Winter Fram Strait Ice Area Export: Model vs Observations
Observations show predictive skill of the minimum sea ice extent (Min SIE) from late winter anomalous off-shore ice drift along the Eurasian coastline – leading to local ice thickness anomalies at the onset of the melt season – a signal then amplified by the ice-albedo feedback. We assess whether the observed seasonal predictability of September sea ice extent (Sept SIE) from Fram Strait Ice Area Export (FSIAE, a proxy for Eurasian coastal divergence) is present in Global Climate Model (GCM) large ensembles, namely the CESM2-LE, GISS-E2.1-G, FLOR-LE, CNRM-CM6-1, and CanESM5. All models show distinct periods where winter FSIAE anomalies are negatively correlated with the May sea ice thickness (May SIT) anomalies along the Eurasian coastline, and the following Sept Arctic SIE, as in observations. Counter-intuitively, several models show occasional periods where winter FSIAE anomalies are positively correlated with the following Sept SIE anomalies when the mean ice thickness is large or late in the simulation when the sea ice is thin, and/or when internal variability increases. More importantly, periods with weak correlation between FSIAE and the Sept SIE dominate, suggesting that summer melt processes dominate over late winter preconditioning and May SIT anomalies. In general, we find that the coupling between the FSIAE and ice thickness anomalies along the Eurasian coastline is an ubiquitous feature of GCMs and that the relationship with the following Sept SIE is dependent on the mean Arctic sea ice thickness.
off-shore ice drift↗
Future CH4 Budgets as Modelled By A Fully Coupled Earth System Model Using Prescribed GHG Concentrations vs. Interactive CH4 Sources and Sinks
We have used the NASA Goddard Institute for Space Studies (GISS) Earth system model GISS-E2.1 to study the future budgets and trends of global and regional CH4 under different emission scenarios. GISS-E2.1 is one of the few ESMs that can be driven by anthropogenic CH4 emissions, as well as interactive natural sources such as wetlands, and can simulate the tropospheric CH4 chemistry. In frame of the recent short-lived climate forcers (SLCFs) assessment by the Arctic Monitoring and Assessment Programme (AMAP), we used the GISS-E2.1 model with prescribed long-lived greenhouse gas (GHG) concentrations. In the present study, we have supplemented these simulations using the interactive CH4 sources and sinks in order to quantify the model performance and the sensitivity to CH4 sources and sinks. We have used the Current Legislation (CLE) and the Maximum Feasible Reduction (MFR) emission scenarios from the Eclipse V6b emission database to simulate the future chemical composition and climate impacts from 2015 to 2050. We have also simulated 1995-2014 in order to evaluate the model performance following the AMAP-SLCF protocol. The prescribed GHG version underestimates the Global Atmospheric Watch (GAW) surface CH4 observations during the period between 1995 and 2023 by 1% [-8.4%-2.0%], with a correlation (r) of 0.71 [-0.41 0.99]. The largest underestimations are over the continental emission regions such as North America, Europe, and Asia, while biases are smallest over oceans. On the other hand, the simulation with interactive sources and sinks underestimates the GAW observations more than the prescribed simulation, by 18.5% [-25% -10.4%], with a lower r of 0.36 [-0.82 0.93]. Opposite to the prescribed simulation, the biases are largest over oceans and smaller over the continents, however they are still larger over land than the prescribed simulation. The interactive simulation, with large sources virtually over land and strong sink over oceans, has a land/ocean ratio larger than 1 while the prescribed simulation has this ratio equal to 1 as it distributes the global prescribed CH4 concentration equally in longitude over a given latitude. This clearly shows that the interactive sources and sinks should be represented in models in order to realistically simulate the chemical composition and the oxidative capacity of the atmosphere. As expected, the MFR scenario simulates lower global surface CH4 concentrations and burdens compared to the CLE scenario, however in both cases, global surface CH4 and burden continue to increase through 2050 compared to present day. In the CLE scenario, increases are largest over the equatorial belt, in particular over India and East China, while the MFR scenario shows increases over the whole Southern Hemisphere, however much smaller compared to CLE. Finally, the interactive simulation shows that the chemical CH4 sink increases in the CLE scenario, while it slightly decreases in the MFR, leading to a larger CH4 lifetime in the MFR scenario compared to in the CLE scenario.
CH4↗
Analysis and Prediction of VFR Vs IFR Traffic Behavior to Support Uncrewed Aircraft Flight Operations at Regional Airports
Uncrewed Aircraft flight operations at a regional airport will be affected by the uncertainty in the Visual Flight Rules traffic around. This paper analyzes Visual Flight Rules traffic behavior, compares it with Instrument Flight Rules traffic and develops traffic prediction methods to support uncrewed aircraft flight operations. The spatio-temporal distribution of traffic operating under Visual Flight Rules and Instrument Flight Rules was analyzed from one month of historical track data around Fort Worth Alliance airport as a representative regional airport. The traffic behavior was visualized as occupancy maps generated at different altitudes. The Instrument Flight Rules traffic was concentrated in fewer regions of the airspace along structured routes where the risk of interacting with one or more flights reached close to fifty percent in some areas. Visual Flight Rules traffic was spread over more regions, mostly segregated from the Instrument Flight Rules regions, and the risk of interaction was lower reaching up to twenty-five percent on average over the month in some regions. The interaction risk was predicted using predictive occupancy maps over multiple time horizons and conditioned on time and partial observation of traffic in the vicinity. The month-to-month predictability of Visual Flight Rules risk was lower than that of the Instrument Flight Rules traffic, consistently over all the conditions analyzed. However, the prediction and its accuracy were demonstrated to be sensitive to the conditions used. The predictive models generated can be used to support both strategic planning and in-flight decision-making by uncrewed aircraft during flight operations while maintaining an acceptable risk of interacting with other traffic.
VFR↗
Analysis and Prediction of VFR Vs IFR Traffic Behavior to Support Uncrewed Aircraft Flight Operations at Regional Airports
Uncrewed Aircraft flight operations at a regional airport will be affected by the uncertainty in the Visual Flight Rules traffic around. This paper analyzes Visual Flight Rules traffic behavior, compares it with Instrument Flight Rules traffic and develops traffic prediction methods to support uncrewed aircraft flight operations. The spatio-temporal distribution of traffic operating under Visual Flight Rules and Instrument Flight Rules was analyzed from one month of historical track data around Fort Worth Alliance airport as a representative regional airport. The traffic behavior was visualized as occupancy maps generated at different altitudes. The Instrument Flight Rules traffic was concentrated in fewer regions of the airspace along structured routes where the risk of interacting with one or more flights reached close to fifty percent in some areas. Visual Flight Rules traffic was spread over more regions, mostly segregated from the Instrument Flight Rules regions, and the risk of interaction was lower reaching up to twenty-five percent on average over the month in some regions. The interaction risk was predicted using predictive occupancy maps over multiple time horizons and conditioned on time and partial observation of traffic in the vicinity. The month-to-month predictability of Visual Flight Rules risk was lower than that of the Instrument Flight Rules traffic, consistently over all the conditions analyzed. However, the prediction and its accuracy were demonstrated to be sensitive to the conditions used. The predictive models generated can be used to support both strategic planning and in-flight decision-making by uncrewed aircraft during flight operations while maintaining an acceptable risk of interacting with other traffic.
VFR↗
Factors in AC vs DC Trade Study for Lunar Surface Electrical Power Transmission
Introduction: This lightning talk gives an overview of the factors relevant to the trade between AC and DC high voltage long distance transmission on the Lunar surface, particularly those factors unique to the Lunar surface.
Electrical power↗
Early Comparison of Ocean Analyses Using JEDI/SOCA 3 DVar vs. GEOS-S2S- 3 ODAS LETKF
At NASA’s Global Modeling and Assimilation Office (GMAO), data assimilation (DA) for the next-generation Goddard Earth Observing System Subseasonal-to-Seasonal (GEOS-S 2 S) coupled-model forecast system will transition to the Joint Effort for DA Integration (JEDI) system, which includes the marine DA component SOCA (Sea ice, Ocean, and Coupled Assimilation). It is envisioned that incorporating SOCA into GMAO Earth System Modeling will allow a more systematic approach to assimilating new data types (e.g., SWOT KaRIn), increasing resolution (e.g., 1/12°), and facilitating weakly (and eventually strongly) coupled DA (air-sea-ice, etc.). To prepare for this transition, testing is underway to compare SOCA results at high ocean resolution against the current GEOS-S 2 S Version 3 Ocean DA System (ODAS) 1 using similar initial conditions and observations.
David Russell↗