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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 811 records · Page 45

Toward a Global Planetary Boundary Layer Observing System: The NASA PBL Incubation Study Team Report

A global Planetary Boundary Layer (PBL) observing system is urgently needed to address fundamental PBL science questions and societal applications related to weather, climate and air quality. This PBL observing system should optimally combine new space-based observations of the PBL thermodynamic structure with complementary surface-based and suborbital assets, while taking advantage of, and helping improve, modeling and data assimilation systems.

Planetary boundary layer↗

A NASA-Air Force Precipitation Analysis for Near-Real-Time Operations

This article describes a new precipitation analysis algorithm developed by NASA for time-sensitive operations at the United States Air Force. Implemented as part of the Land Information System—a land modeling and data assimilation software framework—this NASA–Air Force Precipitation Analysis (NAFPA) combines numerical weather prediction model outputs with rain gauge measurements and satellite estimates to produce global, gridded 3-h accumulated precipitation fields at approximately 10-km resolution. Input observations are subjected to quality control checks before being used by the Bratseth analysis algorithm that converges to optimal interpolation. NAFPA assimilates up to 3.5 million observations without artificial data thinning or selection. To evaluate this new approach, a multiyear reanalysis is generated and intercompared with eight alternative precipitation products across the contiguous United States, Africa, and the monsoon region of eastern Asia. NAFPA yields superior accuracy and correlation over low-latency (up to 14 h) alternatives (numerical weather prediction and satellite retrievals), and often outperforms high-latency (up to 3.5 months) products, although the details for the latter vary by region and product. The development of NAFPA offers a high-quality, near-real-time product for use in meteorological, land surface, and hydrological research and applications.

Africa↗

A Look at the Truths and Misconceptions of the Variational Quantum Eigensolver and the Implications of Overparameterization

In this work, we investigate loss landscapes of the variational quantum eigensolver (VQE) by quantifying the number of local minima through empirical analyses. We focus on minimal models in chemistry and physics so that we can do a complete analysis using more computationally expensive tools. We employ Hessian eigenvalue calculations and the nudged elastic band algorithm to characterize these landscapes. Our results expand upon the existing literature by highlighting the optimization challenges faced by VQE. We find that, as the number of parameters in our ansatz increases, the number of basins increases while the corresponding loss function values converge toward the global minimum value. This observation implies that overparameterization may lead to an ``effective convexity'' in VQE loss landscapes, a phenomenon supported by theoretical and numerical work in classical machine learning.

quantum computing↗

Analysis and Design of Rotors at Ultra-Low Reynolds Numbers

Design tools have been developed for ultra-low Reynolds number rotors, combining enhanced actuator-ring / blade-element theory with airfoil section data based on two-dimensional Navier-Stokes calculations. This performance prediction method is coupled with an optimizer for both design and analysis applications. Performance predictions from these tools have been compared with three-dimensional Navier Stokes analyses and experimental data for a 2.5 cm diameter rotor with chord Reynolds numbers below 10,000. Comparisons among the analyses and experimental data show reasonable agreement both in the global thrust and power required, but the spanwise distributions of these quantities exhibit significant deviations. The study also reveals that three-dimensional and rotational effects significantly change local airfoil section performance. The magnitude of this issue, unique to this operating regime, may limit the applicability of blade-element type methods for detailed rotor design at ultra-low Reynolds numbers, but these methods are still useful for evaluating concept feasibility and rapidly generating initial designs for further analysis and optimization using more advanced tools.

Kunz, Peter J.↗

Thermal acclimation of stem respiration implies a weaker carbon-climate feedback

The efflux of carbon dioxide (CO2) from woody stems, a proxy for stem respiration, is a critical carbon flux from ecosystems to the atmosphere, which increases with temperature on short timescales. However, plants acclimate their respiratory response to temperature on longer timescales, potentially weakening the carbon-climate feedback. The magnitude of this acclimation is uncertain despite its importance for predicting future climate change. We develop an optimality-based theory dynamically linking stem respiration with leaf water supply to predict its thermal acclimation. We show that the theory accurately reproduces observations of spatial and seasonal change. We estimate the global value for current annual stem CO2 efflux as 27.4 ± 5.9 PgC. By 2100, incorporating thermal acclimation reduces projected stem respiration without considering acclimation by 24 to 46%, thus reducing land ecosystem carbon emissions.

Zhang, Han↗

Studies of thermal wave phenomena on the Jovian planets

Ground-based and Voyager observations of Jupiter provided evidence that the tropospheric temperature shows global-scale longitudinal variations which are often wavelike in character. The investigation is presented which is directed toward obtaining additional ground-based data in IR spectral bands whose contribution functions are optimized for specific atmospheric regions, in order to confirm the previous results, and to identify the nature and physical significance of wavelike longitudinal temperature fluctuations on the Jovian planets.

Deming, Drake↗

Domain Knowledge Guided Bayesian Optimization For Autonomous Alignment Of Complex Scientific Instruments

Bayesian Optimization (BO) is a powerful tool for optimizing complex non-linear systems. However, its performance degrades in high-dimensional problems with tightly coupled parameters and highly asymmetric objective landscapes, where rewards are sparse. In such needle-in-a-haystack scenarios, even advanced methods like trust-region BO (TurBO) often lead to unsatisfactory results. We propose a domain knowledge guided Bayesian Optimization approach, which leverages physical insight to fundamentally simplify the search problem by transforming coordinates to decouple input features and align the active subspaces with the primary search axes. We demonstrate this approach's efficacy on a challenging 12-dimensional, 6-crystal Split-and-Delay optical system, where conventional approaches, including standard BO, TuRBO and multi-objective BO, consistently led to unsatisfactory results. When combined with an reverse annealing exploration strategy, this approach reliably converges to the global optimum. The coordinate transformation itself is the key to this success, significantly accelerating the search by aligning input co-ordinate axes with the problem's active subspaces. As increasingly complex scientific instruments, from large telescopes to new spectrometers at X-ray Free Electron Lasers are deployed, the demand for robust high-dimensional optimization grows. Our results demonstrate a generalizable paradigm: leveraging physical insight to transform high-dimensional, coupled optimization problems into simpler representations can enable rapid and robust automated tuning for consistent high performance while still retaining current optimization algorithms.

FOS: Computer and information sciences↗

Extremized nonlinear and linearized responses in soft metamaterials enabled by gradient-based design and grayscale digital light processing

In this study, we develop a gradient-based design approach that exploits grayscale digital light processing (DLP) 3D printing for extremizing the nonlinear and linearized response of soft metamaterials — materials that harness engineered geometric instabilities to undergo large and programmable changes in configuration. Grayscale DLP approaches modulate local mechanical properties at the pixel scale by tuning the light intensity within a single grayscale image, unlocking an exceptionally large design space. To effectively navigate this space, we develop smooth mappings between local light intensity values and global quantities of interest that characterize the behavior of soft metamaterials. Enabling these smooth mappings are robust and differentiable nonlinear finite element simulations powered by a trust region solver. A PDE-constrained optimization problem is then solved to invert these mappings and produce light intensity distributions that endow the printed part with varying stiffness and flexibility in distinctive regions. It is shown that optimizing the distribution of soft and stiff phases throughout a metamaterial structure results in markedly different buckling and self-contact configurations to drive extremized nonlinear compression and linearized vibration responses. Optimized light intensity distributions are translated to grayscale images and directly used to print soft metamaterial samples, showing remarkable agreement between the buckling and self-contact response in simulated and measured deformed configurations.

Additive manufacturing↗

Ambient Synthesis for Fe(II) Polypyridyl Complexes with an Order of Magnitude Increase in Charge-Transfer Excited-State Lifetimes over [Fe(bpy) 3 ] 2+

Replacing precious metals with abundant metals is an important research focus in photochemical energy conversion and storage to meet global energy demands. However, transition metal complexes (TMCs) based on abundant 3d metals typically possess photochemical disadvantages─such as short charge-transfer excited-state lifetimes─and molecular modifications have focused on optimizing the interplay of structure, dynamics, and energetics to overcome their limitations. One strategy to do so is the use of bespoke ligands that can extend the lifetimes of chemically useful excited states. Here, in this study, we report the synthesis and characterization of novel Fe(II) complexes featuring lengthy polypyridyl ligands that can be readily synthesized. Steady-state and transient absorption spectroscopies indicate that these complexes have desirable properties and their excited metal-to-ligand charge-transfer states live an order of magnitude longer than in the benchmark [Fe(bpy) 3 ] 2+ . This lifetime is largely preserved in the heteroleptic complexes, thereby enabling the preparation of asymmetric complexes. Additionally, we apply nonradiative transition theory to explain the long-time decay kinetics. In light of their ease of preparation and reasonable excited-state lifetimes, we suggest the use of these complexes in Fe(II) dye-sensitized solar cells, where the rate of charge injection would be competitive with increased lifetime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Translocation mechanism of xeroderma pigmentosum group D protein on single-stranded DNA and genetic disease etiology

Abstract XPD is a key nucleotide excision repair (NER) protein whose function is vital for genome integrity. During NER, XPD serves as a 5′−3′ single-strand DNA translocase that enables lesion scanning and verification in genomic DNA. Yet, its translocation mechanism is incompletely understood. Here we use molecular simulations and chain-of-replicas path optimization methods to model the ATP-driven translocation mechanisms of XPD and its bacterial homolog DinG, revealing all on-path metastable intermediates and corresponding kinetic rates. We identify the XPD(DinG) global domain motions that modulate the strength of DNA association at the opposing ends of the DNA-binding groove. During the ATP hydrolysis cycle, alternating weak and strong interactions at two defined groove constrictions enable DNA reptation and forward displacement of the ATPase. Moreover, we show that DNA- or ATP-binding residues directly involved in translocation are hotspots for genetic disease mutations. Thus, our findings shed light on the etiology of XPD-associated genetic syndromes.

Paul, Tanmoy↗

Neurocomputing strategies in decomposition based structural design

The present paper explores the applicability of neurocomputing strategies in decomposition based structural optimization problems. It is shown that the modeling capability of a backpropagation neural network can be used to detect weak couplings in a system, and to effectively decompose it into smaller, more tractable, subsystems. When such partitioning of a design space is possible, parallel optimization can be performed in each subsystem, with a penalty term added to its objective function to account for constraint violations in all other subsystems. Dependencies among subsystems are represented in terms of global design variables, and a neural network is used to map the relations between these variables and all subsystem constraints. A vector quantization technique, referred to as a z-Network, can effectively be used for this purpose. The approach is illustrated with applications to minimum weight sizing of truss structures with multiple design constraints.

Szewczyk, Z.↗

Evolution of Galaxies and the Star Formation Rate in the Infrared

A central goal of extragalactic observational astronomy is to understand how normal galaxies evolve with redshift, and particularly when galaxies formed their stars. While optical and rest-frame UV observations have begun to address these issues, the interpretation of such data is particularly challenging because of the sensitivity to dust obscuration (at optical and UV wavelengths). The absorbed light is reradiated at IR wavelengths, hence the optimal indicators of the star-formation rate (SFR) is at a rest-frame wavelength of approx. 60 microns. The Spitzer Space Telescope mission is beginning to revolutionize the study of the global properties and evolution of galaxies. Spitzer reaches nearly two orders of magnitude more sensitivity than previous IR space missions. This research program is to study the SFR using statistical samples of galaxies in the local universe, at intermediate redshifts, and set the stage for continuing studies up to z=5. The overall research program is divided into three main investigations: A Mid-IR Hubble Atlas and SFR estimators in the local universe, Evolution of the SFR at 0 < z < 1 using pencil beam redshift surveys, and Galaxy formation and evolution at 1 < z < 5. The Spitzer Space Telescope launched during the past year and the first papers from it are currently being submitted to The Astrophysical Journal. This is clearly an exciting time for IR astronomy!

Pahre, Michael A.↗

NASA’s WB-57F High Altitude Research Aircraft is Looking Up: A Flexible and Capable Heliophysics Platform for Coronal Observations During Total Solar Eclipses

NASA's WB-57F "Canberra" high altitude research aircraft is a unique airborne platform that serves a critical need in airborne science. Although the aircraft has been conventionally used for earth observation/remote sensing and in situ atmospheric sampling, research teams have begun to recognize the aircraft’s emerging role in heliophysics research. With the ability to operate at altitudes in excess of 60,000 feet and with a range of over 2,500 miles, the particular capabilities of the WB-57 are unparalleled by other aircraft in the government or commercial spaces. The Canberra has capacity to carry nearly 9,000 pounds of instrumentation across the aircraft, including modular payload areas in the belly, the nose, wing pods, and wing hatches. The WB-57 features a dedicated "person in the loop" sensor equipment operator, real-time high bandwidth data link between air and ground, and an on-board data network allowing interoperability between multiple systems and operator interfaces. The aircraft has a truly global reach, and has operated out of airfields all over the world with a minimal personnel footprint. The Program maintains a highly qualified engineering team that will work closely with customer requirements to optimize efficiency of payload installation and operation on the aircraft. NASA maintains its own airworthiness authority, allowing a bespoke "in house" approach to aircraft modifications and instrument integration. This often saves months of coordination and cost when compared with commercial options. On 8 April 2024, the WB-57 program executed a one-of-a-kind observation the corona over North America and provided a first-flight opportunity for several instruments that were historically strictly terrestrial. By integrating imagers, spectrometers, and ionosondes on the aircraft, research team partnerships with Southwest Research Institute, University of Hawai’i Institute for Astronomy, and Virginia Tech have demonstrated new and exciting applications for this venerable platform, were able to effectively eliminate the risk of adverse weather spoiling the data collection during totality, and reduce the amount of atmospheric interference in the collected spectral data.

Airborne Science↗

Opportunity Assessment for Sustainable Aviation Fuel Production from Woody Biomass via Ex Situ Catalytic Fast Pyrolysis and Refinery Hydroprocessing

Biofuels have become a promising solution to reduce emissions in hard-to-electrify transportation sectors, such as aviation. However, several biofuel conversion pathways will likely be needed to scale sustainable aviation fuel (SAF) production to meet lower carbon intensity goals when biomass feedstock availability constraints are considered. This study evaluates the future potential of the catalytic fast pyrolysis (CFP) pathway to contribute to U.S. SAF production goals as outlined in the U.S. Department of Energy’s (DOE) SAF Grand Challenge, understanding that the CFP pathway is still under development toward maturity and scaleup. National forestland resource data from the DOE’s 2023 Billion Ton Study are integrated with recent experimental results demonstrating end-to-end woody biomass conversion to SAF via CFP and hydroprocessing in a novel bioeconomy optimization framework. U.S. refinery hydroprocessing capacity is also considered with repurposing and coprocessing strategies. Results indicate that the CFP process can contribute up to 4.6 billion gallons of SAF annually by 2040, meeting 13% of the 2050 SAF Grand Challenge target while reducing the carbon intensity (CI) of the U.S. jet fuel pool by 16%. The study further explores optimal processing strategies, suggesting that colocating CFP operations with existing petroleum refineries and repurposing some U.S. hydrocracking capacity may offer significant cost advantages and enhance the commercial viability of the CFP pathway. These results underscore the CFP pathway’s potential to support the global aviation industry’s lower carbon intensity objectives while producing other renewable fuels and products.

09 BIOMASS FUELS↗

Automated Resonance Fitting for Nuclear Data Evaluation

Global and national efforts to deliver high-quality nuclear data to users have a wide-ranging impact, affecting applications in national security, reactor operations, basic science, medicine, and more. Cross section evaluation is a major part of this effort, combining theory and experimentation to produce recommended values and uncertainties for reaction probabilities. Resonance region evaluation is a specialized type of nuclear data evaluation that can require significant manual effort and months of time from expert scientists. In this article, non-convex non-linear optimization methods are combined with concepts of inferential statistics to infer a resonance model from experimental data in an automated manner that is not dependent on prior evaluation(s). This methodology aims to enhance the workflow of a resonance evaluator by minimizing time, effort, and the potential for bias from prior assumptions, while enhancing reproducibility and documentation, thereby addressing well-known challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Assimilating All-Sky Microwave Radiance Data to Improve NASA GEOS Forecasts and Analysis

The NASA Global Modeling and Assimilation Office (GMAO) has been pursuing efforts to utilize all-sky (clear+cloudy+precipitating) MW radiance data and has developed a system to assimilate all-sky GPM Microwave Imager (GMI) radiance data in the Goddard Earth Observing System (GEOS) during the last PMM funding period. The system provides additional constraints on the analysis process near the storm regions and adjusts the geophysical parameters such as precipitation, cloud, moisture, surface pressure, and wind by combining information from GMI radiance measurements and model forecasts in an optimal manner. The system proved that assimilating the GMI all-sky radiance data improve the GEOS atmospheric analyses and forecasts. This all-sky data framework has been included in the GEOS Forward Processing (FP) system since July 11, 2018 and assimilates all-sky GMI data in real-time for GEOS global analysis and forecast production at the GMAO. We are currently extending this all-sky GMI radiance data assimilation system to assimilate more all-sky MW radiance data from other sensors such as the Microwave Humidity Sounder (MHS), the Advanced Technology Microwave Sounder (ATMS), the Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Microwave Scanning Radiometer 2 (AMSR2), and the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometery (SAPHIR) onboard the GPM constellation spacecrafts. Preliminary results from this extended all-sky system show increased benefit from cloud- and precipitation-affected MW radiances with much larger spatial and temporal coverages compared to the all-sky system assimilating GMI alone and improved GEOS forecast skills especially for lower tropospheric humidity fields.

Kim, Min-Jeong↗

An Evaluation of the Effect of Network Cost Optimization for Leadership Class Supercomputers

Dragonfly-based networks are an extensively deployed network topology in large-scale high-performance computing due to their cost-effectiveness and efficiency. The US will soon have three Exascale supercomputers for leadership class workloads deployed using dragonfly networks. Compared to indirect networks of similar scale, the dragonfly network has considerably reduced cable lengths, cable counts, and switch counts, resulting in significant network cost savings for a given system size, however, these cost reductions result in reduced global minimal paths and more challenging routing. Additionally, large scale dragonfly networks often require a taper at the global link level, resulting in less bisection bandwidth than is achievable in other traditional non-blocking topologies of equivalent scale. While dragonfly networks have been extensively studied, they have yet to be fully evaluated in an extreme scale (i.e., exascale) system that targets capability workloads. In this paper, we present the results of the first large scale evaluation of a dragonfly network on an exascale system (Frontier) and compare its behavior to a similar scale fat-tree network on a previous generation TOP500 system (Summit). This evaluation aims to determine the effect of network cost optimizations by measuring a tapered topology’s impact on capability workloads. Our evaluation is based on a collection of synthetic microbenchmarks, mini-apps, and full scale applications. It compares the scaling efficiencies of each benchmark between the dragonfly-based Frontier and the fat-tree-based Summit systems. Our results show that a dragonfly network is $\sim \mathbf{3 0 \%}$ more cost efficient than a fat-tree topology, which amortizes to $\sim 3 \%$ of an exascale system cost. Furthermore, while tapered dragonfly networks impose significant tradeoffs, the impacts are not as broad as initially thought and are mostly seen in applications with global communication patterns, particularly all-to-all (e.g., FFT-based algorithms), but also local communication patterns (e.g., nearest-neighbor algorithms) that are sensitive to network performance variability.

Khan, Awais↗

Integrative SP3 Workflow for Multi-PTM Proteomics Profiling (TZ-DP0)

The goal of the experiment was to demonstrate that the optimized multiplexed multi-PTM profiling workflow can comprehensively and quantitatively capture dynamic changes in protein abundance, cysteine oxidation, phosphorylation, and acetylation in cytokine-induced inflammatory stress in mouse pancreatic ß-cells. Global proteomic, redox proteomic, phosphoproteomic, and acetylomic were data collected from mouse Beta-TC-6 pancreatic Beta-cells, untreated (mock) and cytokine-treated Beta-cells at 4, 8, and 24 hours with 4 biological replicates. Samples were digested with trypsin and Lys-C, then analyzed by LC-MS/MS. Data were searched with MS-GF+, MASIC, and MaxQuant using PNNL's DMS processing pipeline.

59 BASIC BIOLOGICAL SCIENCES↗