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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 NTRS2015

Exploration Architecture with Quantum Inertial Gravimetry and In-Situ ChipSat Sensors

The Dual Exploration Architecture is a mission concept that combines remote sensing and in-situ observations into a single mission to answer planetary science questions that can only be answered with both types of data. Adoption of dual exploration architectures may short circuit the long, slow cycle of missions to inaccessible bodies by eliminating the need for separate precursor and follow-up missions. Additionally, the dual architecture possesses inherent flexibility that enables the design of adaptive, event-driven missions that are very different from traditional, largely pre-planned missions. Five key observations about the state and trends of planetary science exploration lead us to the dual architecture: increasing complexity of observations; scarcity of future mission opportunities; desire to capture transitory events; continued miniaturization of spacecraft components; and the Mars exploration cycle. Our goal in this study is to explore missions that can only happen using the dual architecture concept and find technology development needs that must be filled for those missions to compete. A survey of historical and current missions finds that opportunities for exploration are becoming less frequent, causing the flexibility and dual-nature elements of each mission to become more common. The dual exploration architecture takes these trends to their far conclusion, attempting to eliminate precursor and follow-up missions while still returning more scientific payoff. A study of the future of planetary science goals through the decadal survey reveals broad applicability of dual missions to solve mysteries that cannot be answered with a traditional mission architecture. These missions fall into three broad classes: choosing a local target from a global survey; dynamic/reactive science; and global in-situ networks. Two example missions of each class are notionally described. A deeper look at these dual architecture classes reveals four technology development needs that must be addressed for wide adoption of dual missions: passive landers; guided atmospheric probes; robust sensing packages; and small, precise orbital instruments. This study pursues a specific focus on two examples of such enabling technologies: the ChipSat and cold atom gravimetry. The ChipSat is a fully functional spacecraft-on-a-chip system that has broad versatility in the dual architecture mission space. Initial studies show that ChipSats could survive as passive impactor landers on bodies up to the size of Europa. Furthermore, COTS (Commercial Off-The-Shelf) components could provide an in-situ sensor suite that readily answers a number of pressing planetary science questions. Cold atom gravimetry uses inertial sensors based on light-pulse atom interferometry in a small form factor to map the gravity field of a body to precision equaling what would normally require two full spacecraft to achieve. The cold atom gravimeter provides an example of how advanced remote sensing capability can enable dual missions by providing greater returns in a significantly smaller package. Using the above two technologies, we study an example dual-architecture mission to both characterize and sample the subsurface oceans at Europa. The greatest scientific return in terms of detecting extraterrestrial life is in those regions where Europa’s ice crust is thin. The identification of regions with thin ice should therefore precede the selection of surface targets and dispatch of probes to those targets. This two-step process, if accomplished by separate flagship-scale missions, might take decades. As a result, a combined mission to both identify thin areas of Europa’s ice and follow up with surface observations at those regions is a good candidate for the dual-exploration architecture. This example mission consists of an orbiter spacecraft carrying a cold atom gravimeter capable of sensing or inferring the ice thickness on regional to local scales, along with a number of ChipSat probes capable of landing on the moon. The small size and weight of the ChipSats allows large numbers of them to be carried, ensuring that enough can be dropped to ensure survival of a minimum number of probes and potentially allowing for the in-situ sampling of multiple locations on the moon. The example missions and Europa case study show that amazing scientific return can obtained from dual-exploration architecture missions with a single launch by breaking the long timescales of planetary exploration and providing the flexibility to capturing transitory events and collect data across the local, regional, and global scales.

Exploration↗
DOE OSTI2025

National Energy Water Treatment & Speciation (NEWTS): A Water & Critical Mineral Database and Dashboard

The scarcity of water resources, the need for beneficial water reuse, and the challenges of wastewater treatment are becoming increasingly pressing in economic, social, and environmental domains. Addressing these concerns requires effective treatment strategies to manage wastewater streams and tackle environmental and economic issues. Furthermore, the recovery of critical minerals from the waste streams associated with energy production holds the promise of offsetting treatment costs and securing local sources of valuable minerals. However, relevant data on these waste streams are dispersed and challenging to locate. The process of ingesting such data into modeling software often involves multiple steps, requiring data restructuring to meet software-input requirements. The non-standardized reporting of water data makes data aggregation and reformatting a time-consuming process. Additionally, essential attributes necessary for modeling water treatment and mineral scale formation are frequently missing. Moreover, data gaps vary depending on the region of interest. Consequently, there is a pressing need for high-quality energy-water composition data that can be easily imported into water chemistry modeling software. To address this need, the National Energy Technology Laboratory has created the National Energy Water Treatment and Speciation (NEWTS) Database and Dashboard—a free online tool catering to community leaders and water researchers. NEWTS facilitates a comprehensive understanding of the composition of energy-related wastewater streams in the United States. The datasets provide detailed concentrations and speciation of major and minor aqueous compounds in energy-related wastewater streams, including power plant leachate, acid mine drainage, brackish water, and oil and gas produced water across the United States. Many of the aqueous species are critical minerals (Li, REEs) in high demand to modernize the world’s energy infrastructure. Many of the datasets also contain volumetric flow-rates needed to model the treatment and reuse scenarios in advanced aqueous chemistry software programs. The NEWTS Database and Dashboard offer public access to hitherto challenging-to-access datasets, presented in a standardized format that is tailored for easy input into aqueous chemistry modeling software. By performing the work needed to transform dispersed, disparate data sources into unified, model-ready datasets, NEWTS serves as an essential resource in advancing water treatment research and sustainable water resource management.

produced water management↗
NASA NTRS2010

Walking the Walk/Talking the Talk: Mission Planning with Speech-Interactive Agents

The application of simulation technology to mission planning and rehearsal has enabled realistic overhead 2-D and immersive 3-D "fly-through" capabilities that can help better prepare tactical teams for conducting missions in unfamiliar locales. For aircrews, detailed terrain data can offer a preview of the relevant landmarks and hazards, and threat models can provide a comprehensive glimpse of potential hot zones and safety corridors. A further extension of the utility of such planning and rehearsal techniques would allow users to perform the radio communications planned for a mission; that is, the air-ground coordination that is critical to the success of missions such as close air support (CAS). Such practice opportunities, while valuable, are limited by the inescapable scarcity of complete mission teams to gather in space and time during planning and rehearsal cycles. Moreoever, using simulated comms with synthetic entities, despite the substantial training and cost benefits, remains an elusive objective. In this paper we report on a solution to this gap that incorporates "synthetic teammates" - intelligent software agents that can role-play entities in a mission scenario and that can communicate in spoken language with users. We employ a fielded mission planning and rehearsal tool so that our focus remains on the experimental objectives of the research rather than on developing a testbed from scratch. Use of this planning tool also helps to validate the approach in an operational system. The result is a demonstration of a mission rehearsal tool that allows aircrew users to not only fly the mission but also practice the verbal communications with air control agencies and tactical controllers on the ground. This work will be presented in a CAS mission planning example but has broad applicability across weapons systems, missions and tactical force compositions.

Bell, Benjamin↗
DOE OSTI2025

A systematic review of machine learning in groundwater monitoring

With increasing concerns about water scarcity, groundwater has become crucial since this resource provides most of the freshwater needs. However, various human and natural activities often contaminate the groundwater, making it unsuitable for use. Over the years, scientists and engineers have used many methods to predict and track groundwater contamination as part of environmental monitoring. Consequently, there is an urgent need for improved methods, particularly in the face of increasing contamination. Machine learning has sometimes been used to monitor groundwater, air quality, and climate. Traditional methods must be improved due to the complexity and large amount of environmental data. This includes using hybrid models that combine traditional and new techniques. Despite the use of machine learning in many scientific areas, there is a lack of comprehensive reviews focusing on its use in environmental monitoring, especially groundwater monitoring. We aim to fill this gap by exploring machine-learning applications in groundwater monitoring. We discuss relevant methods, their limitations, and future potential. We summarize research on automating data processing and model training using groundwater sensor data. Our research underscores the transformative potential of machine learning to revolutionize long-term groundwater monitoring and contamination detection, providing valuable insights for future research and practical applications.

AI/ML↗
NASA NTRS2004

An experimental study of the Richtmyer-Meshkov instability in microgravity

Richtmyer-Meshkov (RM) instability occurs when a planar interface separating two fluids of different density is impulsively accelerated in the direction of its normal. It is one of the most fundamental fluid instabilities and is of importance to the fields of astrophysics and inertial confinement fusion. Because RM instability experiments are normally carried out in shock tubes, where the generation of a sharp, well-controlled interface between gases is difficult, there is a scarcity of good experimental results. The experiments presented here use a novel technique that circumvents many of the experimental difficulties that have previously limited the study of RM instability in shock tubes. In these experiments, the instability is generated incompressibly, by bouncing a rectangular tank containing two liquids off of a fixed spring. These experiments, which utilize PLIF flow visualization, yield time-motion image sequences of the nonlinear development and transition to turbulence of the instability that are of a quality unattainable in shock tube experiments. Measurements obtained from these images, therefore, provide benchmark data for the evaluation of nonlinear models for the late-time growth of the instability. Because the run time in these experiments is limited, new experiments in the NASA Glenn 2.2 second drop tower, capable of achieving longer run times, are currently under way.

Rheology/methods↗
DOE OSTI2025

Discovering the Multisectoral Impacts of Global Energy Sector Outcomes Through Multiple Ensemble Aggregation Measures

Understanding complex human-Earth system interactions often involves analyzing large scenario ensembles that encompass a wide range of plausible futures. These ensembles often require aggregation to summarize information based on specific criteria or conditions. However, previous research using global change scenario ensembles has largely overlooked how the choice of aggregation method influences the interpretation of results. To address this gap, we leverage a large ensemble data set designed to capture broad energy system dynamics generated using the Global Change Analysis Model. We first explore how energy-related uncertainties are propagated to both global and regional water-energy-food sectors. We then conduct a rank correlation analysis across seven ensemble aggregation measures and demonstrate the need to consider multiple measures in global change scenarios. Our results suggest that global water and food sector outcomes in the 21st century vary widely depending on different scenario assumptions. The global energy productivity is projected to improve by the end of the century across all scenarios. Moreover, regions facing water scarcity challenges in 2100 do not always overlap with those facing extreme energy and food sector outcomes. Although rank correlations across seven aggregation measures are relatively stable across sectors, we identify cases where relying on a single measure leads to losing critical information in the full ensemble. Reliance on a single aggregation measure can distort the interpretation of global change scenario outcomes. Instead, adopting multiple ensemble aggregation measures provides a more holistic understanding of global change scenario ensembles.

Kim, Gijoo↗
NASA NTRS1999

Doppler RAdar Observations of Convection from the NASA/TOGA C-band Radar During TRMM-LBA in Rondonia, Brazil

The Tropcial RAinfall Measuring Mission-Large Scale Biosphere-Atmosphere experiment in Amazonia (TRMM-LBA) was conducted near Ji Parana, Rondonia, Brazil during the 1999 Amazonian wet season (Jan-Feb). TRMM-LBA provided detailed observations of precipitating systems from surface and aircraft instrumentation which may be compared to measurements from the TRMM satellite. The surface-based platforms included two scanning Doppler radars (the NASA TOGA C-band radar and the NCAR SPOL S-band dual polarization radar) which collected continuous dual-Doppler measurements of precipitating convection.This paper focuses on data from the TOGA radar to provide a preliminary overview of general properties of convective organization observed during TRMM-LBA. These include squall line evolution and morphology, diurnal variation of precipitation, and the vertical intensity of convection. Mesoscale squall lines were most commonly observed in the afternoon, with associated regions of stratiform precipitation persisting into the evening. Nocturnal widespread stratiform rain often formed before sunrise, with no apparent source region of deep convection and very weak radar bright band. Reflectivity values in deep convective cells typically decreased rapidly above the melting level, reminiscent of tropical oceanic convection, and consistent with the relative scarcity of lightning (with respect to other tropical continental regions). Vertically developed electrified convection, though infrequent, did occur regularly.

Rickenbach, T. M.↗
NASA NTRS2006

Identifying Basic Factors for Communal Prosperity - Space Technologies are Bridging this Gap

There are many aspects, which are important for maintaining environmentally clean and safe conditions for a healthy and economically self-sufficient community. This problem was somewhat of a lesser concern in earlier days because many communities were small, isolated and solely dependent upon their owners or landlords. Due to an astronomical growth in human population within the last century, extensive use of combustion technologies, and changing environmental conditions has resulted in scarcity of natural resources. In reality, the societal sustainability issues are becoming much more acute and complex. Therefore, the researchers and social scientists are joining forces to address these topics and find solutions to many contentious areas such as public health and diseases, water resources, agriculture production, survivability during and after the natural disasters, energy needs and many others. Forthrightly speaking, there is no canned solution or a methodology to go about solving these issues since the magnitude and complexity of these issues are multi-dimensional and are further inter-locked with other areas. A common sense tells us that we need data, resources and technologies to begin addressing these problems. This is where space observations have provided us with tremendous information and opportunities, which are of great assets to the science, economist, and social scientists. This paper specifically addresses what are critical areas for a successful societal sustainability and growth; and how can we take advantage of multiple sensors and models already in existence. Increasing our knowledge of the home planet, via amplified set of observations, is certainly a right step in a right direction. Furthermore, this is a pre-requisite in understanding multiple hazard phenomena's. This paper further examines various space sensors and observing architectures that can be useful specifically in addressing some of these complex issues. The ultimate goal is to serve the society by providing such valuable information so the decision makers can take full advantage in making timely societal decisions.

Habib, Shahid↗
NASA NTRS2015

Assessing the Evolving Fragility of the Global Food System

The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992-2009 to analyse the changing properties of the global food system. Over the 18-year study period, we show that the global food system is relatively homogeneous (85 of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9 (3.8) for 1992-1996, increasing to 11 (5.7) for 20052009. Over the same intervals, rice losses increase from 8.2 (2.2) to 14 (5.2). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity.

complex networks↗
NASA NTRS2022

Global Gridded Crop Models Underestimate Yield Responses to Droughts and Heatwaves

Extreme events can lead to crop yield declines, resulting in financial losses and threats to food security, and the frequency and intensity of such events is projected to increase. As global gridded crop models (GGCMs) are commonly used to assess climate change impacts on agricultural yields, there is a need to understand whether these models are able to reproduce the observed yield declines. We evaluated 13 GGCMs from the Inter-Sectoral Impact Model Intercomparison Project and compared observed and simulated impact of past droughts and heatwaves on yields for four crops (maize, rice, soy, wheat). We found that most models detect but underestimate the impact of droughts and heatwaves on yield. Specifically, the drought signal was detected by 12 of 13 models for maize and all models for wheat, while the heat signal was detected by eleven models for maize and six models for wheat. To investigate whether the difference between simulated and observed yield declines is due to a misrepresentation of simulated exposure to heat or water scarcity (i.e. misrepresentation of growing season), we analysed the relationship between average discrepancies between observed and simulated yield losses, and average simulated exposure to extreme weather conditions across all crop models. We found a positive correlation between simulated exposure to heat and model performance for heatwaves, but found no correlation for droughts. This suggests that there is a systematic underestimation of yield responses to heat and drought and not only a misrepresentation of exposure. Assuming that performance for the past indicates models' capacity to project future yield impacts, models likely underestimate future yield decline from climate change. High-quality temporally and spatially resolved observational data on growing seasons will be highly valuable to further improve crop models' capacity to adequately respond to extreme weather events.

extreme events↗
DOE OSTI2025

PROTOCALC, a W -band Polarized Calibrator for Cosmic Microwave Background Telescopes: Application to Simons Observatory and CLASS

Current- and next-generation cosmic microwave background (CMB) experiments will measure polarization anisotropies with unprecedented sensitivities. The need for high precision in these measurements underscores the importance of gaining a comprehensive understanding of instrument properties, with a particular emphasis on the study of the beam properties, and especially their polarization characteristics and the measurement of the polarization angle. In this context, a major challenge lies in the scarcity of millimeter polarized astrophysical sources with sufficient brightness and calibration knowledge to meet the stringent accuracy requirements of future CMB missions. This led to the development of a drone-borne calibration source designed for the frequency band centered on approximately 90 GHz, matching a commonly used channel in ground-based CMB measurements. The Prototype Calibrator for Cosmology, PROTOCALC, has undergone thorough in-lab testing, and its properties have been subsequently modeled through simulation software integrated into the standard Simons Observatory analysis pipeline. Moreover, the PROTOCALC system has been tested in the field, having been deployed twice on calibration campaigns with CMB telescopes in the Atacama Desert. The data collected constrain the roll angle of the source with a statistical accuracy of 0$^°_•$045.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

PolarMERRA: A Polar-Focused Global Reanalysis Project for Scientific and Stakeholder Needs

The adequate modeling of physical processes in the Arctic and Antarctic is vital for developing prediction capabilities and for obtaining an understanding of rapidly evolving polar conditions, including their potential global impacts. These processes are often poorly represented in global models and reanalyses, owing to a legacy modeling focus on midlatitude processes, as well as a scarcity of observations needed for model development in polar regions. The polarMERRA initiative, a joint effort between NASA’s Cryospheric Sciences and Modeling and Prediction programs, seeks to improve the representation of cryospheric and polar atmospheric processes and to develop an open-source framework for a quantitively evaluation of polar-relevant variables against current and future satellite and in-situ observations, models, and reanalyses. Here, we evaluate the impacts of spatial resolution and modifications to sea ice, ice sheet, and atmospheric parameterizations on the representation of high latitude conditions by using a quantitative scorecard approach that leverages NASA’s extensive satellite record. Investigations are conducted using the NASA Goddard Earth Observing System model (GEOS) and its data assimilation system (GEOS DAS). Through a quantitative identification of process deficiencies, bias reductions in key surface variables, including temperature and precipitation over cryospheric surfaces, may be achieved. The polarMERRA project additionally seeks to identify additional data sources for use in the GEOS DAS, and to incorporate data and parameterization improvements into future model and reanalysis products for scientific and stakeholder use.

Lauren C Andrews↗
NASA NTRS1997

Structure and Kinematics of a Complex Crater: Upheaval Dome, Southeast, Utah

Two vastly different phenomena, extraterrestrial impact and salt diapirism, have been proposed for the origin of Upheaval Dome. Upheaval Dome is a about 2.5-km-diameter structural dome surrounded by a 5-km-diameter ring structural depression, which is in turn flanked by extensive, nearly flat-lying Colorado Plateau strata. Seismic refraction data and geologic mapping indicate that the dome originated by the collapse of a transient cavity formed by impact; data also show that rising salt has had a negligible influence on dome development. Evidence for this includes several factors: (1) a rare lag deposit of impactite is present; (2) fan-tailed fracture surfaces (shatter surfaces) and a few shattercones are present; (3) the top of the underlying salt horizon is at least 500 m below the center of the dome, with no exposures of salt in the dome to support the possibility that a salt diapir has ascended through it; (4) sedimentary strata in the center are significantly imbricated by top-to-the-center thrust faulting and are complexly folded; (5) top-to-the-center low-angle normal faults are found at the perimeter of the structure; and (6) clastic dikes are widespread. The scarcity of melt rocks and shock fabrics is attributed to approximately 0.5 km of erosion; the structures of the dome reflect processes of complex crater development at a depth of about 0.5 km below the crater floor. Based on mapping and kinematic analysis, we infer that the dome formed mainly by centerward motion of rock units along listric faults. Outcrop-scale folding and upturning of beds, especially common in the center, largely resulted from this motion. In addition, we have detected some centerward motion of fault-bounded wedges resulting from displacements on subhorizontal faults that conjoin and die out within horizontal bedding in the perimeter of the structure. Collectively, the observed deformation accounts for the creation of both the central uplift and the encircling ring syncline.

Kriens, B. J.↗
DOE OSTI2024

Transforming Agricultural Productivity with AI-Driven Forecasting: Innovations in Food Security and Supply Chain Optimization

Global food security is under significant threat from climate change, population growth, and resource scarcity. This review examines how advanced AI-driven forecasting models, including machine learning (ML), deep learning (DL), and time-series forecasting models like SARIMA/ARIMA, are transforming regional agricultural practices and food supply chains. Through the integration of Internet of Things (IoT), remote sensing, and blockchain technologies, these models facilitate the real-time monitoring of crop growth, resource allocation, and market dynamics, enhancing decision making and sustainability. The study adopts a mixed-methods approach, including systematic literature analysis and regional case studies. Highlights include AI-driven yield forecasting in European hydroponic systems and resource optimization in southeast Asian aquaponics, showcasing localized efficiency gains. Furthermore, AI applications in food processing, such as plasma, ozone and Pulsed Electric Field (PEF) treatments, are shown to improve food preservation and reduce spoilage. Key challenges—such as data quality, model scalability, and prediction accuracy—are discussed, particularly in the context of data-poor environments, limiting broader model applicability. The paper concludes by outlining future directions, emphasizing context-specific AI implementations, the need for public–private collaboration, and policy interventions to enhance scalability and adoption in food security contexts.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Solvent Transport in Disordered and Dynamic Membrane Pores: Implications for Reverse Osmosis and Nanofiltration Membranes

Pressure-driven separations with nanoporous membranes, such as reverse osmosis and nanofiltration, play a vital role in addressing water scarcity and enabling resource recovery. Understanding water or solvent transport in membrane pores is essential for advancing membrane separation technologies. A key question in transport modeling is to establish a relationship between solvent permeability and membrane porous structure properties, such as porosity or pore size. The nano- and subnanometer pores in polymeric membranes such as reverse osmosis and nanofiltration membranes are highly tortuous and dynamically connected, which challenges the conventional methods of transport modeling. This study addresses this challenge by developing a theoretical framework to describe solvent transport through membranes with dynamic and disordered porous structure. Specifically, we propose a lattice model to describe the pore network, while preserving the viscous nature of solvent permeation. We further establish a relationship between solvent permeability and membrane porosity or pore size, which is validated by molecular dynamics simulations and experimental data. By integrating this relationship into the solution-friction model, we define pore connectivity and local friction coefficient to quantify the impact of pore structure on solvent permeability. Our analysis highlights the dominant influence of pore connectivity on the permeability of reverse osmosis and nanofiltration membranes, particularly when the pore size approaches the dimensions of solvent molecules. Overall, this study provides critical insights into water and solvent transport mechanisms in nanoporous membranes, opening the door for strategies to substantially enhance membrane performance.

membranes↗
NASA NTRS1998

Stratospheric Sulfuric Acid and Black Carbon Aerosol Measured During POLARIS and its Role in Ozone Chemistry

Stratospheric aerosol can affect the environment in three ways. Sulfuric acid aerosol have been shown to act as sites for the reduction of reactive nitrogen and chlorine and as condensation sites to form Polar Stratospheric Clouds, under very cold conditions, which facilitate ozone depletion. Recently, modeling studies have suggested a link between BCA (Black Carbon Aerosol) and ozone chemistry. These studies suggest that HNO3, NO2, and O3 may be reduced heterogeneously on BCA particles. The ozone reaction converts ozone to oxygen molecules, while HNO3 and NO2 react to form NOx. Finally, a buildup of BCA could reduce the single-scatter albedo of aerosol below a value of 0.98, a critical value that has been postulated to change the effect of stratospheric aerosol from cooling to warming. Correlations between measured BCA amounts and aircraft usage have been reported. Attempts to link BCA to ozone chemistry and other stratospheric processes have been hindered by questions concerning the amount of BCA that exists in the stratosphere, the magnitude of reaction probabilities, and the scarcity of BCA measurements. The Ames Wire Impactors (AWI) participated in POLARIS as part of the complement of experiments on the NASA ER-2. One of our main objectives was to determine the amount of aerosol surface area, particularly BCA, available for reaction with stratospheric constituents and assess if possible, the importance of these reactions. The AWI collects aerosol and BCA particles on thin Palladium wires that are exposed to the ambient air in a controlled manner. The samples are returned to the laboratory for subsequent analysis. The product of the AWI analysis is the size, surface area, and volume distributions, morphology and elemental composition of aerosol and BCA. This paper presents results from our experiments during POLARIS and puts these measurements in the context of POLARIS and other missions in which we have participated. It describes modifications to the AWI data analysis procedures in which the collection of BCA is modeled as a fractal aggregate. The new analysis results in an increase in BCA surface area of approximately 24 and an increase in mass of 7-10 from the previous method. For the current study, BCA surface area is used in computer models that attempt to predict measured NOx/NOy ratios and O3 depletion rates. Inclusion of the HNO3 reaction with BCA in one model tends to improve the agreement of calculated to measured NOx/NOy ratio. However, it was found that these trends are viable only if the reactions are catalytic.

Strawa, Anthony W.↗
NASA NTRS2022

Highly Supercooled Riming and Unusual Triple-Frequency Radar Signatures Over McMurdo Station, Antarctica

Riming of ice crystals by supercooled water droplets is an efficient ice growth process, but its basic properties are still poorly known. While it has been shown to contribute significantly to surface precipitation at mid-latitudes, little is known about its occurrence at high latitudes. In Antarctica, two competing effects can influence the occurrence of riming: (i) the scarcity of supercooled liquid water clouds due to the extremely low tropospheric temperatures and (ii) the low aerosol concentration, which may lead to the formation of fewer and larger supercooled drops potentially resulting in an enhanced riming efficiency. In this work, by exploiting the deployment of an unprecedented number of multiwavelength remote sensing systems (including triple-frequency radar measurements) in West Antarctica, during the Atmospheric Radiation Measurements West Antarctic Radiation Experiment (AWARE) field campaign, we evaluate the riming incidence at McMurdo Station and find that riming occurs at much lower temperatures when compared to previous results in the mid-latitudes. This suggests the possible occurrence of a common atmospheric state over Antarctica that includes a rather stable atmosphere inhibiting turbulent mixing, and a high riming efficiency driven by large cloud droplets. We then focus on a peculiar case study featuring a persistent layer with a particularly pronounced riming signature in triple-frequency radar data but only a relatively modest amount of supercooled liquid water. In-depth analysis of the radar observations suggests that such signatures can only be explained by the combined effects of moderately rimed aggregates or similarly shaped florid polycrystals and a narrow particle size distribution (PSD). Simulations of this case study performed with a one-dimensional bin model indicate that similar triple-frequency radar observations can be reproduced when narrow PSDs are simulated. Such narrow PSDs can in turn be explained by two key factors: (i) the presence of a shallow homogeneous droplet or humidified aerosol freezing layer aloft seeding an underlying supercooled liquid layer, and (ii) the absence of turbulent mixing throughout a stable polar atmosphere that sustains narrow PSDs, as hydrometeors grow from the nucleation region aloft to ice particles of several millimeters in size, by vapor deposition and then riming.

Riming↗
NASA NTRS2016

Risk of Performance Decrement and Crew Illness Due to an Inadequate Food System

NASA is preparing for long duration manned missions beyond low-Earth orbit that will be challenged in several ways, including long-term exposure to the space environment, impacts to crew physiological and psychological health, limited resources, and no resupply. The food system is one of the most significant daily factors that can be altered to improve human health, and performance during space exploration. Therefore, the paramount importance of determining the methods, technologies, and requirements to provide a safe, nutritious, and acceptable food system that promotes crew health and performance cannot be underestimated. The processed and prepackaged food system is the main source of nutrition to the crew, therefore significant losses in nutrition, either through degradation of nutrients during processing and storage or inadequate food intake due to low acceptability, variety, or usability, may significantly compromise the crew's health and performance. Shelf life studies indicate that key nutrients and quality factors in many space foods degrade to concerning levels within three years, suggesting that food system will not meet the nutrition and acceptability requirements of a long duration mission beyond low-Earth orbit. Likewise, mass and volume evaluations indicate that the current food system is a significant resource burden. Alternative provisioning strategies, such as inclusion of bioregenerative foods, are challenged with resource requirements, and food safety and scarcity concerns. Ensuring provisioning of an adequate food system relies not only upon determining technologies, and requirements for nutrition, quality, and safety, but upon establishing a food system that will support nutritional adequacy, even with individual crew preference and self-selection. In short, the space food system is challenged to maintain safety, nutrition, and acceptability for all phases of an exploration mission within resource constraints. This document presents the evidence for the Risk of Performance Decrement and Crew Illness Due to an Inadequate Food System and the gaps in relation to exploration, as identified by the NASA Human Research Program (HRP). The research reviewed here indicates strategies to establish methods, technologies, and requirements that increase food stability, support adequate nutrition, quality, and variety, enable supplementation with grow-pick-and-eat salad crops, ensure safety, and reduce resource use. Obtaining the evidence to establish an adequate food system is essential, as the resources allocated to the food system may be defined based on the data relating nutritional stability and food quality requirements to crew performance and health.

Douglas, Grace L.↗