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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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At least 379 records · Page 21

Identifying Sources of Sulfate Preserved in High Elevation Lava Tubes From Mauna Loa, Hawaii

Volcanic sulfates record a history of their formation pathways in their triple oxygen isotope compositions, making them a powerful target for understanding atmospheric chemistry. To understand how these isotopic signals may be preserved in sulfate minerals, we investigate multiple O and S isotopes of thenardite, mirabilite, and gypsum from in a Mars analog environment: a pair of lava tubes near the summit of Mauna Loa, Hawaii. Based on 16 O-, 17 O- 18 O compositions, the primary oxygen sources for sulfates in the lava tube are atmospheric oxygen (O 2 ), peroxide (H 2 O 2 ), and ozone (O 3 ). We suggest the isotopic signature of O 2 originates from combustion of reduced sulfur gases and/or elemental sulfur at the eruptive source or within the lava tube soon after skylight collapse. Sulfate with isotopic signatures of peroxide and ozone are typically expected from aqueous reactions in cloud droplets. Chemical modeling indicates the observed proportion of ozone sourced sulfate requires pH greater than ~5.4, higher than measured cloud water pH, instead suggesting the observed O 3 signature could not have formed in cloud water droplets. We interpret that sulfate possessing an ozone signature in the lava tube sulfates formed on wetted surfaces of the lava tubes with alkalinity from alteration of basaltic glass. Furthermore, the oxygen and sulfur isotopes of the sulfate are uncorrelated. Multiple sulfur isotopes ( 32 S- 33 S- 34 S- 36 S) from the Mauna Loa sulfates are consistent with ocean island basalt from Pitcairn, suggesting the sulfate-sulfur has not been modified compared to its volcanic source. The findings of this study indicate that oxidation by ozone plays a key role in the formation of sulfate within lava tubes. We also find that combustion is a significant pathway toward sulfuric acid formation in volcanic environments. Similar signatures should be expected on other planets if volcanism is a significant sulfate source, as has been suggested for Mars. If true, sulfates in returned samples from Mars may hold key information on pO 2 , pCO 2 and planetary scale oxygen fluxes at the time of sulfate formation.

Justin Hayles↗

Responsible Exploration Preserving the Cosmos for Tomorrow

This submittal encompasses NASA presentations to be shared at the forthcoming Trilateral S&MA Summit at ESRIN in Frascati, Italy. This event is an annual meeting comprised of SMA leadership and supporting staff from NASA, ESA, and JAXA. The Trilateral Parties discuss current and future areas of cooperation in areas of Safety & Mission Assurance.

trilateral↗

Terrestrial Analogue Studies from ISRO’s Venus Mission Perspective: Polarimetric Radar Properties of Hawaiian Lava Flows

Detection of present and past volcanism on Venus is one of the major goals of the proposed ISRO’s Venus orbiter mission. The S-band, high-resolution (40 m/pixel) fully Polarimetric Synthetic Aperture Radar (PolSAR) instrument on this mission [1] may have the capabilities to detect volcanism within the mission lifetime using repeated PolSAR imagery, and possibly SAR Interferometry (InSAR, experimental mode). The global mapping efforts of Venus by Magellan mission has enabled comprehensive mapping of lava flows and indicated that Venus has an extensive history of volcanism, the ages of which are largely unknown (e.g. [2]). While Magellan radar emissivity data (e.g. [3, 4]) and Near Infrared emissivity data from VIRTIS [5] suggested the occurrence of recent episodes of volcanic activity (e.g. Maat Mons and Ganis Chasma), as well as the presence of stratigraphically young lava flows (e.g. Idunn Mons), measuring changes in radar backscatter amplitude alone to identify lava flows has many challenges. Although very large changes in the shape of the terrain can be observed in radar backscatter amplitude changes (e.g. [6]), smaller, or relatively flat lava flows are difficult to detect. Previous terrestrial studies suggest that PolSAR and InSAR techniques are very effective for mapping lava flows (e.g. [7-9]), and can be used when changes cannot be distinguished in radar backscatter images. We use the unvegetated lava flows on Hawaiʻi island as a terrestrial analogue to study Venus lava flows for the following reasons: (a) It is extensively studied at several wavelengths commonly used in remote sensing studies (including PolSAR and InSAR methods); and (b) it is a volcanically active area with new lava flows frequently covering older emplaced flows. To investigate the surface roughness, texture, and fine-grained mantling associated with Mauna Loa and Kilauea lava flows, we utilize C- and L-band PolSAR datasets obtained from RISAT-1A (EOS-4) and ALOS PALSAR missions respectively. In particular, we will use the quad-polarized backscatter and polarimetric parameters to characterize the texture of the terrestrial lava flows to understand whether the Venus crust is continuously disrupted during flow emplacement. While some previous studies (e.g. [10, 11]) suggested that surface roughness of most of the Venus flows is comparable to that of terrestrial pāhoehoe flows, other studies indicated that fractal dimensions of some large lava flows on Venus imply high eruption rates which favour the formation of a’a flows (e.g. [12]). We will also analyse the terrestrial flows for the presence/absence of pyroclastic mantling as radar-bright diffuse deposits near the summit regions of some coronae on Venus have been proposed to be young pyroclastics, and possible evidence of a renewed epoch of mantle volcanism that taps into deeper volatiles [13]. A recent study using EOS-4 RISAT-1 data of a part of fresh Mauna Loa lava flows (2022 eruption) emphasizes the ability of fully polarimetric SAR data to understand the diversity of physical properties (e.g. texture and morphology) associated with them (Sreejith et al. 2024); and we will apply similar methods to the PolSAR data obtained from ISRO’s Venus mission for our proposed objectives.

Sriram S Bhiravarasu↗

POWER's Journey and Roadmap: Where Have We Been and Where Are We Going?

This is a keynote presentation for the NASA LaRC's POWER (Prediction of Worldwide Energy Resources) Project's Global Summit to be held from November 6-7 as a on-line interactive webinar. This presentation presents a quick overview of the POWER project, the most recent accomplishments and the an overview of POWER's initiatives in 2025 and beyond.

remote sensing↗

Harmonizing Food Systems Emissions Accounting for More Effective Climate Action

Food systems—encompassing activities in food production, land-use change, supply chains and waste management—contribute significantly to climate change. Recent estimates indicate that food systems produce over 30% of annual anthropogenic greenhouse gas (GHG) emissions (about 20% of CO 2 , 50% of CH 4 , and 75% of N 2 O), with the Intergovernmental Panel on Climate Change (IPCC) estimating a notably broad range of 23%–42% of global GHG emissions. This paper synthesizes current research on the contributions of food systems to climate change, highlights challenges in quantifying their impact and proposes a harmonized accounting framework for more effective climate action. We recommend that an expert committee aligned with the IPCC develop guidance for food systems emissions accounting in four key areas, including: (1) defining system boundaries and nomenclature; (2) developing protocols to allocate broader sectoral emissions to food systems; (3) prioritizing critical areas for research into activity data and emissions factors; and (4) developing a balanced framework for evaluating the impact of mitigation interventions in light of other food systems imperatives. The committee should be integrated into two key international policy processes—the United Nations Framework Convention on Climate Change and the United Nations Food Systems Summit—to support coordinated action towards global net-zero goals. Guidance from the committee could significantly improve the ability of governments, companies, and researchers to estimate, report, monitor and ultimately reduce the climate impacts of food systems.

GHG accounting↗

Getting to 100%: Six Strategies for the Challenging Last 10%

This presentation summarizes the challenge of decarbonizing the last 10%" of the power system and discusses six strategies for addressing that challenge. This presentation was given at the IRA, BIL, and the Future of Energy: A Summit to Support State Implementation" workshop in Washington, D.C., in April 2024.

carbon capture↗

Distributed Multi-GPU Community Detection on Exascale Computing Platforms

Community detection is a fundamental operation in graph mining, and by uncovering hidden structures and patterns within complex systems it helps solve fundamental problems pertaining to social networks, such as information diffusion, epidemics, and recommender systems. Scaling graph algorithms for massive networks becomes challenging on modern distributed-memory multi-GPU (Graphics Processing Unit) systems due to limitations such as irregular memory access patterns, load imbalances, higher communication-computation ratios, and cross-platform support. We present a novel algorithm HiPDPL-GPU (Distributed Parallel Louvain) to address these challenges. We conduct experiments involving different partitioning techniques to achieve an optimized performance of HiPDPL-GPU on the two largest supercomputers: Frontier and Summit. Remarkably, HiPDPL-GPU processes a graph with 4.2 billion edges in less than 3 minutes using 1024 GPUs. Qualitatively, the performance of HiPDPL-GPU is similar or better compared to other state-of-the-art CPU- and GPU-based implementations. While prior GPU implementations have predominantly employed CUDA, our first-of-its-kind implementation for community detection is cross-platform, accommodating both AMD and NVIDIA GPUs.

Sattar, Naw Safrin↗

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups

Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids (Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling and Optimization of a Rotating Packed Bed Contactor with a Tetraamine-Appended Metal−Organic Framework for CO 2 Capture

A potential contactor technology for sorbent-based CO 2 capture is the rotating packed bed that contains separate sections for continuous adsorption and desorption. A heat exchanger can be embedded to remove heat in the adsorption section and add heat in the desorption section. In this work, we develop a two-dimensional (2D) model of a rotating packed bed for use in CO 2 capture applications. Mass and energy balances for the model are developed based on a Ljungström-type air preheater, which accounts for the counter-current axial flow of gas phases in separate sections of the bed and the rotation of a solid sorbent, which cycles between adsorption and desorption sections. The sorbent used for this analysis is the tetraamine-appended metal−organic framework Mg 2 (dobpdc)(3−4− 3), chosen for its stability and affinity for CO 2 at low partial pressures, such as those from a natural gas power plant source. An optimization problem is solved that considers the trade-off between maximizing the productivity of the bed and minimizing energy consumption. Maximum productivity and minimum energy are found to be 8.53 kg/h/m 3 and 3.84 MJ/kg, respectively, when these objectives are optimized independently. It is observed that the flue gas pressure and bed rotational speed are the desired operating variables to vary for model-based design of experiments to reduce uncertainty in parameter estimation, as these two variables yielded the most information content based on the Fisher information matrix.

20 FOSSIL-FUELED POWER PLANTS↗

Optimal Design and Techno-Economic Analysis of 3D-Printed, Intensified Packings for Absorbers and Strippers in Solvent-Based CO 2 Capture

A potential technology for the CO 2 absorption process is utilizing intensified structured packing with embedded cooling/heating channels for continuous heat exchange, which can overcome limitations of discrete methods, such as discrete intercooling and centralized reboilers, to aid in reducing energy consumption and decreasing costs. This work investigates the modeling of intensified packing (IP) for the stripper tower, extending on previous work for the absorber, which distributes heat internally within the column, improving the thermodynamics for the solvent regeneration process. The model includes submodels for steam turbine extraction to produce steam at various qualities as well as a surrogate model for calculating steam enthalpy. A cost model for a plant-scale absorption capture process was developed, allowing for the design of the plant to be optimized, subject to minimizing capture cost using two different power plant flue gas sources. In this optimization, the placement of IP in both towers is optimized to balance the trade-off between enhanced heat transfer and reduced mass transfer volume. For natural gas combined cycle flue gas, the standard process configuration had a minimum cost of $\$$65.40/tonne CO 2 , and considering IP, the minimum capture cost is reduced to $\$$62.73/tonne, with utilization in the stripper column, which reduces yearly costs by up to $\$$2.67 MM/yr. Cooling the absorber through IP, or intercoolers, was only found to be beneficial at higher capture rates, with IP in both towers having a cost of capture of $\$$68.08/tonne at 99.9% capture, a reduction of $\$$12.64/tonne when using only intercoolers at the same capture rate. When capturing from pulverized-coal power plants, the minimum cost of capture when using IP in both towers is $\$$44.18/tonne (at 97% capture), while the standard configuration with and without intercoolers was $\$$45.69 and $\$$47.22 per tonne, respectively. This results in a reduction in yearly costs of $\$$16.98 MM/yr from the base-case configuration. At this higher CO 2 concentration, cooling in the absorber from the IP becomes extremely beneficial, reducing energy consumption by up to 6%.

20 FOSSIL-FUELED POWER PLANTS↗

Optimal Design and Operation of Intensified Absorbers with 3D-Printed Packing for Solvent-Based CO 2 Capture

Many potential solvent-based carbon capture processes suffer from a high heat of absorption of CO 2 that adversely affects the thermodynamic driving force. While interstage coolers are often used for removing a portion of the generated heat by removing the solvent or a portion of the solvent from a stage and cooling and returning it back to the absorber, they can be placed only at discrete locations in the tower. This work investigates intensified absorbers with 3D-printed packing that includes an internal cooler and therefore can be potentially used for maximizing the operational efficiency of the absorbers for CO 2 capture. The intensified absorber is modeled by using a generic, first-principles, equation-oriented absorber column model. Since the placement of these intensified packings would cause a loss of area/volume used for mass transfer, optimization of the proposed intensified absorber is performed by optimally selecting the locations at which to place these devices and designing them such that the trade-off due to the addition of the heat removal area and the resulting loss in the mass transfer area is accounted for. Results show that optimally placed and designed intensified packings can lead to a significant increase in the capture efficiency of the process in comparison to a similar column with no internal cooling. It is also observed that by optimally placing and designing intensified packings, the lean solvent flow rate to the absorber can be decreased, and the CO 2 lean loading can be increased while still maintaining the same capture efficiency. These process changes can lead to a substantial reduction in the cost of capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Net Present Value Optimization of a Natural Gas Combined Cycle Plant with CO 2 Capture using a Water-Lean Solvent Considering Transient Electricity Price for Multiple Regions

Global CO 2 emissions are increasing at about a 1.5% rate per year. Fossil fuel-based plants are one of the main contributors to this rise. In the power generation industry, fossil fuel plants are dominant, and many plants are under development. In this study, a natural gas combined cycle (NGCC) power plant with postcombustion capture using a leading water-lean solvent is considered. For optimal design and operating schedule, large-scale dynamic optimization is undertaken for net present value (NPV) optimization. The first principle dynamic model of NGCC is developed, including a model of the highly efficient H-class gas turbines. For computational tractability of the dynamic optimization problem, a reduced-order model is developed by using the Hankel singular value decomposition. A waterlean solvent, N-(2-ethoxyethyl)-3-morpholinopropan-1-amine, is used for carbon capture. A model of the capture system is developed in Aspen Plus, which is used to develop a reduced-order model by using ALAMO, a machine learning software. In addition, a reduced model of the CO 2 compression system with a dehydration unit is also considered. The integrated system is used for NPV optimization by using the Python-based PYOMO platform. The PCC process is analyzed for three configurations-conventional packed bed, rotating packed bed (RPB), and a combination of RPB and direct contact cooler. The NPV optimization is performed for 14 regional markets by considering year-long clustered and continuous locational marginal price data with a 1 h interval. Optimization results show that the PCC can achieve 90% CO 2 capture with a positive NPV for six regions. Sensitivity studies conducted by using the PCC configurations indicate that the process is economically feasible for 9 regions out of 14 regional electricity markets with NPV values in the range of 33−540 $MM.

cabon capture↗

Scalable Hybrid Learning Techniques for Scientific Data Compression

Data compression is becoming critical for storing scientific data because many scientific applications need to store large amounts of data and post process this data for scientific discovery. Unlike image and video compression algorithms that limit errors to primary data (PD), scientists require compression techniques that accurately preserve derived quantities of interest (QoIs). Here, this article presents a physics-informed compression technique implemented as an end-to-end, scalable, GPU-based pipeline for data compression that addresses this requirement. Our hybrid compression technique combines machine learning techniques and standard compression methods. Specifically, we combine an autoencoder, an error-bounded lossy compressor to provide guarantees on raw data error, and a constraint satisfaction post-processing step to preserve the QoIs within a minimal error (generally less than floating point error). The effectiveness of the data compression pipeline is demonstrated by compressing nuclear fusion simulation data generated by a large-scale fusion code, XGC, which produces hundreds of terabytes of data in a single day. Our approach works within the ADIOS framework and results in compression by a factor of more than 150 while requiring only a few percent of the computational resources necessary for generating the data, making the overall approach highly effective for practical scenarios.

ITER↗

Optimal Design and Operation of a Solvent-Sorbent Hybrid Capture Process for Minimizing the Cost of High Capture

High capture can cause a significant increase in energy penalty if the appropriate technology/technologies are not utilized. The optimal technology for bulk capture is not necessarily the optimal technology for polishing capture (i.e., high extent of capture from the flue gas with very low partial pressure of CO2). This work investigates the use of MEA for bulk capture with the polishing capture being accomplished by a functionalized metal organic framework (MOF).

Kasturi, Pooja↗

Development of Algebraic and Topological-Based Structured Packing Model

Poster being presented at the 2024 annual AICHE meeting held from October 27-31, 2024. The poster focuses on developing an algebraic and topological model for designing structured packing for a CO2 absorption tower. The model can be optimized to determine an optimal packing structure.

Summits, Stephen↗