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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 NTRS1986

Application of the cepstrum to remove echoes from rotor acoustic spectra

The application of the power cepstrum technique to the analysis of model scale helicopter rotor noise spectra is investigated. The power cepstrum technique emerges as a useful tool for the removal of undesired acoustic reflections from measured rotor spectra. It is most effective when the reflections are exact duplicates of the signal, i.e., when the echo transfer function is linear. Moreover, the technique is best applied to a measured spectrum which is due entirely to the signal and its echoes, when no nonsource related signals are present. It is noted that this technique can be applied without prior knowledge of the echo characteristics.

Martin, R. M.↗
NASA NTRS1990

Superconducting applications in propulsion systems. Magnetic insulation for plasma propulsion devices

The purpose of this paper is to review the status of knowledge of the basic concepts needed to establish design parameters for effective magnetic insulation. The objective is to estimate the effectiveness of the magnetic field in insulating the plasma, to calculate the magnitude of the magnetic field necessary to reduce the heat transfer to the walls sufficiently enough to demonstrate the potential of magnetically driven plasma rockets.

Gonzalez, Dora E.↗
NASA NTRS2004

Astrobiology of Comets

We review the current state of knowledge concerning microbial extremophiles and comets and the potential significance of comets to Astrobiology. We model the thermal history of a cometary body, regarded as an assemblage of boulders, dust, ices and organics, as it approaches a perihelion distance of - IAU. The transfer of incident energy from sunlight into the interior leads to the melting of near surface ices, some under stable porous crust, providing possible habitats for a wide range of microorganisms. We provide data concerning new evidence for indigenous microfossils in CI meteorites, which may be the remains of extinct cometary cores. We discuss the dominant microbial communities of polar sea-ice, Antarctic ice sheet, and cryoconite environments as possible analogs for microbial ecosystems that may grow in sub-crustal pools or in ice/water films in comets.

Hoover, Richard B.↗
DOE OSTI2022

PemNet: A Transfer Learning-Based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems

Widespread adoption of high-temperature electrochemical systems such as polymer electrolyte membrane fuel cells (HT-PEMFCs) requires models and computational tools for accurate optimization and guiding new materials for enhancing fuel cell performance and durability. Furthermore, while robust and better suited for extrapolation, knowledge-based modeling has limitations as it is time-consuming and requires information about the system that is not always available (e.g., material properties and interfacial behavior between different materials). Data-driven modeling, on the other hand, is easier to implement but often necessitates large datasets that could be difficult to obtain. In this contribution, knowledge-based modeling and data-driven modeling are combined by implementing a few-shot learning (FSL) approach. A knowledge-based model originally developed for a HT-PEMFCs was used to generate simulated data (887,735 points) and used to pretrain a neural network source model tuned via a genetic algorithm-based AutoML. Then, experimental datasets from HT-PEMFCs with different materials and operating conditions (~50 points each) were used to train six target models via FSL. Models for the unseen data reached high accuracies in all cases (rRMSE < 10%).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Enabling Graph Mining in RDF Triplestores using SPARQL for Holistic In-situ Graph Analysis

The graph analysis is now considered as a promising technique to discover useful knowledge in data with a new perspective. We envi- sion that there are two dimensions of graph analysis: OnLine Graph Analytic Processing (OLGAP) and Graph Mining (GM) where each respectively focuses on subgraph pattern matching and automatic knowledge discovery in graph. Moreover, as these two dimensions aim to complementarily solve complex problems, holistic in-situ graph analysis which covers both OLGAP and GM in a single system is critical for minimizing the burdens of operating multiple graph systems and transferring intermediate result-sets between those systems. Nevertheless, most existing graph analysis systems are only capable of one dimension of graph analysis. In this work, we take an approach to enabling GM capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.) in RDF triplestores, which are originally developed to store RDF datasets and provide OLGAP capability. More specifically, to achieve our goal, we implemented six representative graph mining algorithms using SPARQL. The approach allows a wide range of available RDF data sets directly applicable for holistic graph analysis within a system. For validation of our approach, we evaluate performance of our implementations with nine real-world datasets and three different computing environments - a laptop computer, an Amazon EC2 instance, and a shared-memory Cray XMT2 URIKA-GD graph-processing appliance. The experimen- tal results show that our implementation can provide promising and scalable performance for real world graph analysis in all tested environments. The developed software is publicly available in an open-source project that we initiated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Improved Stability and Performance of Visible Photoelectrochemical Water Splitting on Solution-Processed Organic Semiconductor Thin Films by Ultrathin Metal Oxide Passivation

Solution-processable organic semiconductors have potentials as visible photoelectrochemical (PEC) water splitting photoelectrodes due to their tunable small band gap and electronic energy levels, but they are typically limited by poor stability and photocatalytic activity. In this study, we demonstrate the direct visible PEC water oxidation on solution-processed organic semiconductor thin films with improved stability and performance by ultrathin metal oxide passivation layers. N-type fullerene-derivative thin films passivated by sub-2 nm ZnO via atomic layer deposition enabled the visible PEC water oxidation at wavelengths longer than 600 nm in harsh alkaline electrolyte environments with up to 30 μA/cm 2 photocurrents at the thermodynamic water-oxidation equilibrium potential and the photoanode half-lifetime extended to ~1000 s. The systematic investigation reveals the enhanced water oxidation catalytic activity afforded by ZnO passivation and the charge tunneling governing the hole transfer through passivation layers. Further enhanced PEC performances were realized by improving the bottom ohmic contact to the organic semiconductor, achieving ~60 μA/cm 2 water oxidation photocurrent at the equilibrium potential, the highest values reported for organic semiconductor thin films to our knowledge. The improved stability and performance of passivated organic photoelectrodes and discovered design rationales provide useful guidelines for realizing the stable visible solar PEC water splitting based on organic semiconductor thin films.

14 SOLAR ENERGY↗
DOE OSTI2019

Is there such a thing as a molecular organic alloy?

In inorganic materials, an alloy is a mixture of two or more substances that generally exhibits electronic and/or physical properties that differ from those of its constituents. In organic systems, the formation of a “molecular alloy” comprising mixtures of molecular organic materials has also been proposed. We test the validity of this concept via the study of the optoelectronic properties of a ternary system that has previously been identified to form a molecular acceptor alloy, namely a blend of a poly(3-hexylthiophene) (P3HT) donor, with two acceptors indene-C 60 bisadduct (ICBA) and phenyl-C 61 -butyric acid methyl ester (PC 61 BM) [R. A. Street, et al., J. Am. Chem. Soc., 2013, 135, 986–989]. Using photoelectron spectroscopy, we find that the ICBA:PC 61 BM blend shows the same highest occupied molecular orbital and exciton energies as that of ICBA, indicating the absence of a new exciton state in the blend. Furthermore, charge transfer state spectra of ternary blends are found to comprise a simple linear superposition of the corresponding binaries. From these results, no evidence of new, emergent electronic states is found to support the existence of a molecular alloy in this system. To our knowledge there is as yet no clear evidence of the existence of an alloy in any organic semiconductor system. Finally, we discuss the criteria that should be met by a molecular organic alloy and procedures needed for their unambiguous identification.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Detection of radiation induced lung injury in rats using dynamic hyperpolarized {sup 129}Xe magnetic resonance spectroscopy

Purpose: Radiation induced lung injury (RILI) is a common side effect for patients undergoing thoracic radiation therapy (RT). RILI can lead to temporary or permanent loss of lung function and in extreme cases, death. Combining functional lung imaging information with conventional radiation treatment plans may lead to more desirable treatment plans that reduce lung toxicity and improve the quality of life for lung cancer survivors. Magnetic Resonance Imaging of the lung following inhalation of hyperpolarized{sup 129}Xe may provide a useful nonionizing approach for probing changes in lung function and structure associated with RILI before, during, or after RT (early and late time-points). Methods: In this study, dynamic{sup 129}Xe MR spectroscopy was used to measure whole-lung gas transfer time constants for lung tissue and red blood cells (RBC), respectively (T{sub Tr-tissue} and T{sub Tr-RBC}) in groups of rats at two weeks and six weeks following 14 Gy whole-lung exposure to radiation from a {sup 60}Co source. A separate group of six healthy age-matched rats served as a control group. Results: T{sub Tr-tissue} values at two weeks post-irradiation (51.6 ± 6.8 ms) were found to be significantly elevated (p < 0.05) with respect to the healthy control group (37.2 ± 4.8 ms). T{sub Tr-RBC} did not show any significant changes between groups. T{sub Tr-tissue} was strongly correlated with T{sub Tr-RBC} in the control group (r = 0.9601 p < 0.05) and uncorrelated in the irradiated groups. Measurements of arterial partial pressure of oxygen obtained by arterial blood sampling were found to be significantly decreased (p < 0.05) in the two-week group (54.2 ± 12.3 mm Hg) compared to those from a representative control group (85.0 ± 10.0 mm Hg). Histology of a separate group of similarly irradiated animals confirmed the presence of inflammation due to radiation exposure with alveolar wall thicknesses that were significantly different (p < 0.05). At six weeks post-irradiation, T{sub Tr-tissue} returned to values (35.6 ± 9.6 ms) that were not significantly different from baseline. Conclusions: Whole-lung tissue transfer time constants for{sup 129}Xe (T{sub Tr-tissue}) can be used to detect the early phase of RILI in a rat model involving 14 Gy thoracic {sup 60}Co exposure as early as two weeks post-irradiation. This knowledge combined with more sophisticated models of gas exchange and imaging techniques, may allow functional lung avoidance radiation therapy planning to be achievable, providing more beneficial treatment plans and improved quality of life for recovering lung cancer patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Soil Aggregate Microbial Communities: Towards Understanding Microbiome Interactions at Biologically Relevant Scales

Soils contain a tangle of minerals, water, nutrients, gases, plant roots, decaying organic matter, and microorganisms which work together to cycle nutrients and support terrestrial plant growth. Most soil microorganisms live in periodically interconnected communities closely associated with soil aggregates, i.e., small (<2 mm), strongly bound clusters of minerals and organic carbon that persist through mechanical disruptions and wetting events. Their spatial structure is important for biogeochemical cycling, and we cannot reliably predict soil biological activities and variability by studying bulk soils alone. To fully understand the biogeochemical processes at work in soils, it is necessary to understand the micrometer-scale interactions that occur between soil particles and their microbial inhabitants. Here, we review the current state of knowledge regarding soil aggregate microbial communities and identify areas of opportunity to study soil ecosystems at a scale relevant to individual cells. We present a framework for understanding aggregate communities as “microbial villages” that are periodically connected through wetting events, allowing for the transfer of genetic material, metabolites, and viruses. Here, we describe both top-down (whole community) and bottom-up (reductionist) strategies for studying these communities. Understanding this requires combining “model system” approaches (e.g., developing mock community artificial aggregates), field observations of natural communities, and broader study of community interactions to include understudied community members, like viruses. Initial studies suggest that aggregate-based approaches are a critical next step for developing a predictive understanding of how geochemical and community interactions govern microbial community structure and nutrient cycling in soil.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Shuttle Continuous Open Wind Tunnel (SCOWT)

The aerodynamic and heat transfer coefficients are studied within the range of thermo-fluid-dynamic conditions experienced by a satellite during Tethered Satellite System (TSS) atmospheric flights. The gasdynamic processes occuring downstream of the bow wave standing in front of the satellite are also studied. The knowledge of the chemistry and physics of the upper atmosphere related to satellite aerothermodynamics is furthered. The existence of an overshooting of the air drag coefficient of the sphere in the transition regime is validated. A complete set of measurements is performed in order to provide the data base to develop and validate theoretical models of free molecule transition flow fields.

Carlomagno, G. M.↗
DOE OSTI2026

Learning to Trigger: Reinforcement Learning at the Large Hadron Collider

High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (\textit{triggering}) under tight constraints on bandwidth, latency, and storage. In practice, trigger menus are largely static and hand-tuned and can become suboptimal as detector conditions, pileup, and background composition drift over time. We cast online threshold tuning as a sequential decision-making problem: a reinforcement learning agent ingests streaming summaries of recent rates and signal-sensitive features and updates trigger thresholds to maximize signal efficiency while tracking a target background rate within a tolerance band. We adapt Group-Filtered Policy Optimization (GFPO) to streaming control and introduce two variants (GFPO-F, GFPO-FR) that enforce background rate feasibility during training. On a benchmark that emulates realistic collider operation, we study two representative triggers: a total transverse energy ($H_{T}$) trigger sensitive to pileup variation, and an anomaly-detection (AD) trigger based on reconstruction loss for rare or non-standard signatures. On Monte Carlo streams, our agent increases the fraction of in-tolerance time intervals by 48% ($H_T$) and 28% (AD), with a cumulative gain of up to 2% in signal efficiency on those in-tolerance intervals. Transferring from simulation to \emph{real} collision data (CMS Run 283408), the same agent, without fine-tuning, achieves a 56% ($H_T$) and 28% (AD) in-tolerance improvement over baselines, with further signal-efficiency gain on both triggers. To our knowledge, this is the \emph{first} demonstration of RL-based trigger control on real Large Hadron Collider collision data. Code is available at https://github.com/Zixind/GFPO_LHC (see repo for details).

Ding, Zixin [Chicago U.]↗
NASA NTRS1999

SeaWiFS Postlaunch Technical Report Series: The SeaWiFS Solar Radiation-Based Calibration and the Transfer-to-Orbit Experiment - Volume 5

The solar radiation-based calibration (SRBC) of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) was performed on 1 November 1993. Measurements were made outdoors in the courtyard of the instrument manufacturer. SeaWiFS viewed the solar irradiance reflected from the sensor's diffuser in the same manner as viewed on orbit. The calibration included measurements using a solar radiometer designed to determine the transmittances of principal atmospheric constituents. The primary uncertainties in the outdoor measurements are the transmission of the atmosphere and the reflectance of the diffuser. Their combined uncertainty is about 5 or 6%. The SRBC also requires knowledge of the extraterrestrial solar spectrum. Four solar models are used. When averaged over the responses of the SeaWiFS bands, the irradiance models agree at the 3.6% level, with the greatest difference for SeaWiFS band 8. The calibration coefficients from the SRBC are lower than those from the laboratory calibration of the instrument in 1997. For a representative solar model, the ratios of the SRBC coefficients to laboratory values average 0.962 with a standard deviation of 0.012. The greatest relative difference is 0.946 for band 8. These values are within the estimated uncertainties of the calibration measurements. For the transfer-to-orbit experiment, the measurements in the manufacturer's courtyard are used to predict the digital counts from the instrument on its first day on orbit (August 1, 1997). This experiment requires an estimate of the relative change in the diffuser response for the period between the launch of the instrument and its first solar measurements on orbit (September 9, 1997). In relative terms, the counts from the instrument on its first day on orbit averaged 1.3% higher than predicted, with a standard deviation of 1.2% and a greatest difference of 2.4% or band 7. The estimated uncertainty for the transfer-to-orbit experiment is about 3 or 4%.

Hooker, Stanford B.↗
DOE OSTI2023

Extracellular electron uptake from a cathode by the lactic acid bacterium Lactiplantibacillus plantarum

A subset of microorganisms that perform respiration can endogenously utilize insoluble electron donors, such as Fe(II) or a cathode, in a process called extracellular electron transfer (EET). However, it is unknown whether similar endogenous EET can be performed by primarily fermentative species like lactic acid bacteria. We report for the first time electron uptake from a cathode by Lactiplantibacillus plantarum, a primarily fermentative bacteria found in the gut of mammals and in fermented foods. L. plantarum consumed electrons from a cathode and coupled this oxidation to the reduction of both an endogenous organic (pyruvate) and an exogenous inorganic electron acceptor (nitrate). This electron uptake from a cathode reroutes glucose fermentation toward lactate degradation and provides cells with a higher viability upon sugar exhaustion. Moreover, the associated genes and cofactors indicate that this activity is mechanistically different from that one employed by lactic acid bacteria to reduce an anode and to perform respiration. Our results expand our knowledge of the diversity of electroactive species and of the metabolic and bioenergetic strategies used by lactic acid bacteria.

biocathode↗
DOE OSTI2016

Cellular Assays for Ferredoxins: A Strategy for Understanding Electron Flow through Protein Carriers That Link Metabolic Pathways

The ferredoxin (Fd) protein family is a structurally diverse group of iron–sulfur proteins that function as electron carriers, linking biochemical pathways important for energy transduction, nutrient assimilation, and primary metabolism. While considerable biochemical information about individual Fd protein electron carriers and their reactions has been acquired, we cannot yet anticipate the proportion of electrons shuttled between different Fd-partner proteins within cells using biochemical parameters that govern electron flow, such as holo-Fd concentration, midpoint potential (driving force), molecular interactions (affinity and kinetics), conformational changes (allostery), and off-pathway electron leakage (chemical oxidation). In this paper, we describe functional and structural gaps in our Fd knowledge within the context of a sequence similarity network and phylogenetic tree, and we propose a strategy for improving our understanding of Fd sequence–function relationships. We suggest comparing the functions of divergent Fds within cells whose growth, or other measurable output, requires electron transfer between defined electron donor and acceptor proteins. By comparing Fd-mediated electron transfer with biochemical parameters that govern electron flow, we posit that models that anticipate energy flow across Fd interactomes can be built. This approach is expected to transform our ability to anticipate Fd control over electron flow in cellular settings, an obstacle to the construction of synthetic electron transfer pathways and rational optimization of existing energy-conserving pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Aqueous Interfaces in Chemical Separations

Chemical separations play a vital role in refinery and reprocessing of critical materials, such as platinum group metals, rare earths, and actinides. The choice of separation system─whether it is liquid–liquid extraction (LLE), sorbents, or membranes─depends on specific needs and applications. In almost all separation processes, the desired metal ions adsorb or transfer across an aqueous interface, such as the solid/liquid interface in sorbents or oil/water interfaces in LLE. Despite these separation technologies being extensively used for decades, our understanding of the molecular-scale mechanisms governing ion adsorption and transport at interfaces remains limited. This knowledge gap presents a significant challenge in meeting the increasing demands for these critical materials due to their growing use in advanced technologies. Fortunately, recent advancements in surface-specific experimental and computational techniques offer promising avenues to bridge this gap and facilitate the development of next-generation separation systems. Interestingly, unanswered questions regarding interfacial phenomena in chemical separations hold great relevance to various fields, including energy storage, geochemistry, and atmospheric chemistry. Therefore, the model interfacial systems developed for studying chemical separations, such as amphiphilic molecules assembled at a solid/water, air/water, or oil/water interface, may have far-reaching implications, extending beyond separations and opening doors to addressing a wide range of scientific inquiries. This perspective discusses recent interfacial studies elucidating amphiphile–ion interactions in chemical separations of metal ions. Finally, these studies provide direct, molecular-scale information about solute and solvent behavior at aqueous interfaces, including multivalent and complex ions in highly concentrated solutions, which play key roles in LLE of critical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

High-Speed and High-Quality Field Welding Repair Based on Advanced Non-Destructive Evaluation and Numerical Modeling

Creep strength-enhanced ferritic (CSEF) steels such as Grade 91 (9Cr-1Mo-V) and Grade 92 (Fe-9Cr-2W-0.5Mo) steels are widely used in the fossil-fuel-fired and nuclear power plants. The weld integrity of these steels is crucial for power plants' safe and reliable operations. Due to harsh service conditions, the steel weld can become susceptible to environmental degradation. Field welding repair is used to restore the degraded weld’s performance where a controlled temper-bead welding technique is commonly used to temper the freshly formed martensite during welding. However, knowledge of weld repairability is limited and experimental trial and error optimization to achieve desired microstructure and joint properties is expensive and time-consuming. Many existing computational models, e.g., finite element models, are limited to solving heat conduction equation and ignoring convective heat transfer due to molten metal flow. These models can result in over-prediction of peak temperatures of weld pool and heat-affected zone (HAZ), which in turn can affect the accuracy of tempering prediction. Moreover, these finite element models require an input of the deposit profiles in advance and thus limits the usability of these models. Here, a molten pool-based, multi-pass multi-layer model has been developed based on computational fluid dynamics (CFD) approach with the Volume of Fluid (VOF) method. The model calculates the bead formation, thereby eliminating the need for pre-determined bead profiles required by finite element models. For computational efficiency, a coordinate system attached to the moving heat source is utilized. A subroutine is developed to convert the temperature profiles in the reference frame stationary to the heat source to that stationary to the workpiece. The converted thermal cycles are then imported into a microstructure model to compute the tempering kinetics and resultant hardness using a Johnson-Mehl-Avrami-Kolmogorov (JMAK), and modified Grange-Baughman parameter. The modeling approach is first developed and validated on single- and multi-pass deposition of stainless steel filler metal onto a SA-533 high strength steel substrate. The models are then applied to a multi-pass V-groove repair weld of Grade 91 steel plate as well as directed energy deposition of Grade 92 steel. Non-destructive characterization of microstructures was performed on Grade 91 and 92 steel welds. Two welding processes, cold metal transfer (CMT) and flux-cored arc welding (FCAW), were investigated for the Grade 91 steel weld samples. For the Grade 92 weld samples, three different heat inputs (low, medium, and high) of gas tungsten arc welding (GTAW) were utilized to replicate traditional field welding processes. The non-destructive evaluation (NDE) method used for this research was immersion ultrasonic testing (UT) using a micro-resolution ultrasonic imaging methodology specifically designed to operate in the through-transmission configuration operating at 20 MHz of frequency. The system used a focused ultrasonic beam spot size diameter between 250-300 μm, and a 6 μm laser vibrometer spot size for detection, to produce highly defined images with longitudinal and mode-converted shear waves. From the micro-resolution ultrasonic C-scan images, three microstructural regions, i.e., weld metal (WM), HAZ, and base metal (BM), were clearly identifiable. Various levels of ultrasonic amplitudes distributed over the three regions were correlated with electron beam backscattered diffraction (EBSD) images using grain size, grain boundaries, and dislocation densities. The results showed that areas with relatively higher ultrasonic amplitude levels were associated with smaller grains and higher dislocation densities, while areas with lower amplitude levels were associated with larger grains and lower dislocation densities. In addition, ultrasonic velocity data obtained across the three different weld microstructural regions of Grade 91 test samples were correlated with optical metallographic images and hardness measurements. The results showed distinctive decreases in ultrasonic velocity and hardness over the HAZ region, where weld failures often occur during service.

36 MATERIALS SCIENCE↗
NASA NTRS2011

NASA Soil Moisture Active Passive (SMAP) Mission Formulation

The Soil Moisture Active Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Earth Science Decadal Survey [1]. SMAP s measurement objectives are high-resolution global measurements of near-surface soil moisture and its freeze-thaw state. These measurements would allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. The soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP s planned observations can help mitigate these natural hazards, resulting in potentially great economic and societal benefits. SMAP measurements would also yield high resolution spatial and temporal mapping of the frozen or thawed condition of the surface soil and vegetation. Observations of soil moisture and freeze/thaw timing over the boreal latitudes will contribute to reducing a major uncertainty in quantifying the global carbon balance and help resolve an apparent missing carbon sink over land. The SMAP mission would utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna (see Figure 1) [2]. The radar and radiometer instruments would be carried onboard a 3-axis stabilized spacecraft in a 680 km polar orbit with an 8-day repeating ground track. The instruments are planned to provide high-resolution and high-accuracy global maps of soil moisture at 10 km resolution and freeze/thaw at 3 km resolution, every two to three days (see Table 1 for a list of science data products). The mission is adopting a number of approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). These approaches are being incorporated into the radiometer and radar flight hardware and ground processing designs.

Entekhabi, Dara↗