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NASA NTRS2024

Deducing Land-Atmosphere Coupling Regimes from SMAP Soil Moisture

In recent years, there has been a growing recognition of the significance of Land-Atmosphere (L-A) interactions and feedback mechanisms in understanding and predicting Earth’s water and energy cycles. Soil moisture plays a critical role in mediating the strength of L-A interactions and is important for understanding the complex and governing processes across this interface. This study aims to identify the significance of soil moisture in identifying L-A coupling strength within the Convective Triggering Potential (CTP) and Humidity Index (HI) framework. To address this, a consistent and reliable dataset of atmospheric profiles is created by merging CTP and HI using Triple Collocation (TC) with three reanalysis datasets. The merged CTP and HI product demonstrates enhanced performance globally as compared to the individual datasets when validated with radiosonde and satellite observations. This merged product of CTP and HI is then used to compare the L-A coupling strength based on Soil Moisture Active Passive Level 3 (SMAPL3) and SMAP Level 4 (SMAPL4) over two decades (2003-2022) where L-A coupling strength is defined as the persistence probability within the dry and wet coupling regimes. Results indicate that the persistency-based coupling strength is related to the ability of soil moisture to predict future atmospheric humidity and dry vs. wet coupling state. The coupling strength in SMAPL4 is consistently stronger than in SMAPL3 and is likely due to its reliance on a land surface model and reduced susceptibility to random noise. The difference in coupling strength based on the same CTP-HI underscores the importance of soil moisture data in estimating coupling strength within the CTP-HI framework. These findings lay the groundwork for understanding the role of L-A interactions and drought evolution due to soil moisture variations, by providing insight into the quantification of coupling strength and its role in drought monitoring and forecast efforts.

Land-atmosphere coupling↗

NASA NTRS1987

NESSUS/expert and NESSUS/FPI in the Probabilistic Structural Analysis Methods (PSAM) program

The Numerical Evaluation of Stochastic Structures under Stress (NESSUS) is the primary computer code being developed in the NASA Probabilistic Structural Analysis Methods (PSAM) project. It consists of four modules NESSUS/EXPERT, NESSUS/FPI, NESSUS/PRE and NESSUS/FEM. This presentation concentrates on EXPERT and FPI. To provide an effective interface between NESSUS and the user, an expert system module called NESSUS/EXPERT is being developed. That system uses the CLIPS artificial intelligence code developed to NASA-JSC. The code is compatible with FORTRAN, the standard language for codes in PSAM. The user interacts with the CLIPS inference engine, which is linked to the knowledge database. The perturbation database generated by NESSUS/FEM and managed in EXPERT is used to develop the so-called response or performance model in the random variables. Two independent probabilistic methods are available in PSAM for the computation of the probabilistic structural response. These are the Fast Probability Integration (FPI) method and Monte Carlo simulation. FPI is classified as an advanced reliability method and has been developed over the past ten years by researchers addressing the reliability of civil engineering structures. Monte Carlo is a well-established technique for computing probabilities by conducting a number of deterministic analyses with specified input distributional information.

Burnside, O. H.↗

DOE OSTI2025

Limited effects of tannin supplementation on the dairy cattle fecal microbiome with modulation of metabolites

Tannins are plant secondary metabolites that bind organic carbon (C) and nitrogen (N), potentially altering substrate bioavailability for enteric fermentation in ruminants. This interaction may reduce greenhouse gas (GHG) emissions and influence nitrogen partitioning. Given tannins' resistance to ruminal degradation and persistence through the gastrointestinal tract, this study investigated the effects of a tannin-based feed additive on fecal microbial diversity, fecal chemical composition, and GHG emissions. Twenty-four early- to mid-lactation dairy cows were randomized to receive either a tannin-based feed additive (TRT; containing condensed and hydrolyzable tannins from Schinopsis quebracho-colorado [Schltdl.]) or a control diet (CON) for 64 days. Cows were blocked by parity, dry matter intake, milk yield, body weight, and days in milk. Fecal samples were collected on days 0, 16, 32, and 64 and analyzed using 16S rRNA gene amplicon sequencing. Fecal C, N, and indole-3-lactate were measured, and GHG emissions (N2O, CH4, CO2) were assessed via 14-day laboratory incubation. A total of 1,538 amplicon sequence variants were identified, with Firmicutes as the dominant phylum. Fecal phylogenetic diversity showed a significant treatment × day interaction (p < 0.01), with TRT cows exhibiting reduced microbial diversity from day 16 to 64. Fecal C and N concentrations were significantly lower (p < 0.01) in TRT cows on day 16, while indole-3-lactate levels were higher on day 64 (p = 0.02). GHG emissions did not differ significantly between treatments. The tannin-based feed additive influenced fecal microbial community structure and select chemical parameters but did not significantly affect GHG emissions from feces. These findings suggest that dietary tannins may modulate gut microbial ecology with minimal impact on downstream manure-related emissions.

Klein, Matthew L↗

NASA NTRS2026

Machine Learning for Predicting Team Functioning in HERA Missions

Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.

Shrivatsa Mishra↗

DOE OSTI2023

Deterministic Current–Induced Perpendicular Switching in Epitaxial Co/Pt Layers without an External Field

Current–induced spin–orbit torques (SOTs) have emerged as a powerful tool to control magnetic elements and non–uniform magnetic textures such as domain walls and skyrmions. SOT–induced switching of perpendicular magnetization generally requires an external field to break the rotational symmetry of the spin–orbit effective fields responsible for the deterministic reversal. The proposed mechanisms to eliminate this requirement often rely on complex multilayer structures that necessitate laborious optimization in the material and spin transport properties, making them less attractive for applications. Herein, current–induced, external field–free switching of an epitaxial MgO/Pt/Co trilayer with an extremely large perpendicular anisotropy in excess of 3 Tesla is reported. It is found that switching occurs due to the interplay of strong SOTs, local anisotropy fluctuations, and the Dzyaloshinkii–Moriya interaction inherent to this epitaxial system. Finally, given that these layers constitute the base stack of a magnetic tunnel junction, this switching mechanism offers the most technologically viable path toward devices such as field–free SOT–based magnetic random–access memories.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Spin disorder control of topological spin texture

Abstract Stabilization of topological spin textures in layered magnets has the potential to drive the development of advanced low-dimensional spintronics devices. However, achieving reliable and flexible manipulation of the topological spin textures beyond skyrmion in a two-dimensional magnet system remains challenging. Here, we demonstrate the introduction of magnetic iron atoms between the van der Waals gap of a layered magnet, Fe 3 GaTe 2 , to modify local anisotropic magnetic interactions. Consequently, we present direct observations of the order-disorder skyrmion lattices transition. In addition, non-trivial topological solitons, such as skyrmioniums and skyrmion bags, are realized at room temperature. Our work highlights the influence of random spin control of non-trivial topological spin textures.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Discovery of Geographically Robust Hybrid Poplar Clones

Hybrid poplar clonal growth in the states (regions) of Minnesota (MN), Indiana (IN), Michigan (MI), and New York (NY) USA was analyzed to discover 10 geographically robust (geo-robust) clones, all P. deltoides x P. nigra (D x N) hybrids previously tested and screened in MN, that were broadly adapted across latitudinal and longitudinal ranges of 9 and 20 degrees, respectively. The clonal effect for growth explained 25 to 36 % of the total variance, 2.5–4.1 times the clone x site interaction. Clone explained 24 to 46 % of total variation in canker occurrence on two sites. Genetic gain in growth was calculated relative to commercial check clones. Genetic gain in growth of geo-robust clones exceeded that of random clones by 24 to 44 %. Geo-robust clones and the best clones on each site were not significantly different on the MN sites, but best clones outperformed geo-robust clones on the other sites by 10 to 39 % genetic gain. Geo-robust clones grew faster than commercial check clones on all but the MI site. The reduction in genetic gain for growth due to using broadly adapted clones relative to the best clones has to be compared to the additional costs and benefits of multiple breeding zones.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1976

Characteristics of corona impulses from insulated wires subjected to high ac voltages

Corona discharges arise due to ionization of air or gas subject to high electric fields. The free electrons and ions contained in these discharges interact with molecules of insulating materials, resulting in chemical changes and destroying the electrical insulating properties. The paper describes some results of measurements aimed at determining corona pulse waveforms, their repetition rate, and amplitude distribution during various randomly-sampled identical time periods of a 60-Hz high-voltage wave. Described are properties of positive and negative corona impulses generated from typical conductors at various test high voltages. A possible method for calculating the energies, densities, and electromagnetic interferences by making use of these results is suggested.

Doreswamy, C. V.↗

NASA NTRS1985

Scattering Models and Basic Experiments in the Microwave Regime

The objectives of research over the next three years are: (1) to develop a randomly rough surface scattering model which is applicable over the entire frequency band; (2) to develop a computer simulation method and algorithm to simulate scattering from known randomly rough surfaces, Z(x,y); (3) to design and perform laboratory experiments to study geometric and physical target parameters of an inhomogeneous layer; (4) to develop scattering models for an inhomogeneous layer which accounts for near field interaction and multiple scattering in both the coherent and the incoherent scattering components; and (5) a comparison between theoretical models and measurements or numerical simulation.

Fung, A. K.↗

NASA NTRS1991

Effect of patch borders on coercivity in amorphous rare earth-transition metal thin films

The coercivity at the micron scale is a very important property of magneto-optical media. It is a key factor that determines the magnetic domain wall movement and domain reversal. How the coercivity is influenced by a special type of patch borders is discussed. Patch formation is a general phenomenon in growth processes of amorphous rare earth transition metal thin films. Different patches may stem from different seeds and the patch borders are formed when they merge. Though little is known about the exact properties of the borders, we may expect that the exchange interaction at the patch border is weaker than that within a patch, since there is usually a spatial gap between two patches. Computer simulations were performed on a 2-D hexagonal lattice consisting of 37 complete patches with random shape and size. From the series of simulations we may conclude that the domain in the patch with borders of 30 percent exchange strength can expand most easily to the whole lattice, because the exchange strength can expand most easily to the whole lattice, because the exchange strength of the border is not too high to prevent the domain from growing within the patch and it is not too low to prevent the domain from expanding beyond the patch.

Patterson, G.↗

NASA NTRS2003

Simple Math is Enough: Two Examples of Inferring Functional Associations from Genomic Data

Non-random features in the genomic data are usually biologically meaningful. The key is to choose the feature well. Having a p-value based score prioritizes the findings. If two proteins share a unusually large number of common interaction partners, they tend to be involved in the same biological process. We used this finding to predict the functions of 81 un-annotated proteins in yeast.

Liang, Shoudan↗

NASA NTRS2014

An Evaluation of a Passively Cooled Cylindrical Spectrometer Array in Lunar Orbit

This thesis will evaluate a passively cooled cylindrical spectrometer array in lunar orbit characterizing the thermal response in order to provide context for decision-making to scientists and engineers. To provide perspective on thermal issues and controls of space science instruments, a background search of historical lunar missions is provided. Next, a trial science mission is designed and analyzed which brings together the elements of the background search, lunar orbit environment and passive cooling. Finally, the trial science mission analysis results are provided along with the conclusions drawn. Scintillators are materials that when struck by particle radiation, absorb the particle energy which is then reemitted as light in or near the visible range. Nuclear astrophysics utilizes scintillating materials for observation of high-energy photons which are generated by sources such as solar flares, supernovae and neutron stars. SPMs are paired with inorganic scintillators to detect the light emitted which is converted into electronic signals. The signals are captured and analyzed in order to map the number and location of the high-energy sources. The SPM is utilized as it has single photon sensitivity, low voltage requirements and a fast response. SPMs are also compact, relatively inexpensive and allow the usage of lower-cost scintillating materials within the spectrometer. These characteristics permit large-area arrays while lowering cost and power requirements. The ability of a spectrometer to record and identify the interaction of high-energy photons for scientific return is not a trivial matter. Background noise is generated when particles that have not originated from the desired distant source impact the spectrometer. Additionally, thermally induced electrical signals are randomly generated within the SPM even in the absence of light which is referred to as dark current. Overcoming these obstacles requires greater light emittance and energy resolution with reduced dark current. Strong scintillation photon emittance ensures that low energy impacts will produce enough visible photons to be detected by the SPM. Higher energy resolution will ensure that single photon impacts can be distinguished from others of similar wavelength and energy; reduced dark current decreases the generation of random signals not associated with a photon impact. Increasing efficiency in each of these properties in a spectrometer comprised of inorganic scintillators and SPMs requires low temperatures. Low temperature maintenance in a lunar environment presents many unique challenges of its own. Even with the accumulated successes of past missions, the lunar environment remains a thermal challenge for engineers. The lunar orbit thermal environment is driven by radiation from three sources, direct solar radiation, reflected solar radiation from the lunar surface (albedo) and lunar radiation (Clawson 2002). Direct solar radiation values are consistent with those seen in Earth orbit (1325 W/m2) (Clawson 2002). The percentage of solar radiation reflected from the moon is consistently very low with the moon's dark regolith covered surface absorbing nearly 90% of the incident light (Clawson 2002). Yet, it is this absorption that gives the lunar orbit environment one of its most difficult thermal attributes as the absorbed solar radiation is released from the lunar surface as infrared radiation (IR). IR is of a wavelength that is readily absorbed by surfaces designed to function as radiation emitters. It is practical to therefore "choose radiator locations and spacecraft attitude to minimize radiator views to the lunar surface, when possible...pointing the radiator towards the sun to some extent, to minimize its view to the lunar surface, is frequently preferable. (Clawson 2002)" Additionally, the amount of direct solar radiation, lunar IR and albedo an orbiting satellite receives varies from one side of the moon to the other as the moon blocks the sun from view. This environment produces large temperature variations in a satellite's instrumentation, control electronics and propulsion systems which must be understood to characterize operating temperature envelopes.

Waggoner, Jason↗

DOE OSTI2022

Modeling Chemo-Mechanics with Electrolyte Infiltration to Quantify Degradation of Cathode Particles

One of the main goals in modeling lithium-ion batteries is to improve/predict longevity and resilience of new chemistries. To that end, this talk investigates the formation of stress-induced fracture within polycrystalline cathode particles and the impact on capacity loss. Physically based cathode aging dynamics is simulated in a 3D, continuum-level chemo-mechanical model. The model captures anisotropic Li diffusion within a single polycrystalline particle comprised of hundreds to thousands of randomly oriented grains. A recent addition to this model includes electrolyte infiltration, which occurs when the electrolyte seeps into surface cracks within the particle. The model predicts that particle fracture is primarily due to non-ideal grain interactions with slight dependence on high-rate charge demands. Essentially, when neighboring grains are misaligned, they expand a different rates relative to one another leading to high stresses and ultimately the formation of intraparticle cracks. The model predicts that small particles with large grains develop significantly less damage than larger particles with small grains. Finally, the model predicts most of the chemo-mechanical damage accumulates in the first charge after formation. This chemo-mechanical "damage saturation" effect indicates that initial particle fracture occurs within the first few cycles, while long-term cathode degradation is not solely chemo-mechanically induced. The principle contribution of this research is the use of an anisotropic chemo-mechanical model to test how particle geometry affect capacity fade, which predicts that particle size has a stronger effect on capacity fade than grain size and ultimately that small particles with large grains have the least capacity fade.

cathode↗

DOE OSTI2023

Community response of soil microorganisms to combined contamination of polycyclic aromatic hydrocarbons and potentially toxic elements in a typical coking plant

Both polycyclic aromatic hydrocarbons (PAHs) and potentially toxic elements (PTEs) of coking industries impose negative effects on the stability of soil ecosystem. Soil microbes are regarded as an essential moderator of biochemical processes and soil remediation, while their responses to PAHs-PTEs combined contamination are largely unknown. In the present study, soil microbial diversity and community composition in the typical coking plant under the chronic co-exposure of PAHs and PTEs were investigated and microbial interaction networks were built to reveal microbial co-occurrence patterns. The results indicated that the concentrations of PAHs in the soil inside the coking plant were significantly higher than those outside the plant. The mean concentration of ∑16PAHs was 2894.4 ng·g −1 , which is 5.58 times higher than that outside the plant. The average Hg concentration inside the coking plant was 22 times higher than the background value of Hebei province. The soil fungal community inside the coking plant showed lower richness compared with that of outside community, and there are significant difference in the bacterial and fungal community composition between inside and outside of coking plant ( p < 0.01). Predicted contribution of different environmental factors to each dominant species based on random forest identified 20 and 25 biomarkers in bacteria and fungi, respectively, that were highly sensitive to coking plant soil in operation, such as Betaproteobacteria，Sordariomycetes and Dothideomycetes . Bacterial and fungal communities were shaped by the soil chemical properties (pH), PTEs (Hg), and PAHs together in the coking plant soils. Furthermore, the bacterial and fungal interaction patterns were investigated separately or jointly by intradomain and interdomain networks. Competition is the main strategy based on the co-exclusion pattern in fungal community, and the competitive relationship inside the coking plant is more complex than that outside the plant. In contrast, cooperation is the dominant strategy in bacterial networks based on the co-occurrence pattern. The present study provided insights into microbial response strategies and the interactions between bacteria and fungi under long-term combined contamination.

Shen, Qihui↗

NASA NTRS2024

Overview of Integrated Random Vibration Testing of the NASA Orion Crew Survival Suit

The launch ascent and abort random vibration environments from NASA’s Orion spacecraft drove the need to test the NASA Orion Crew Survival Suit as an integrated system with exposure to the design levels. In order to properly characterize component responses, a series of integrated tests were designed to incorporate the interaction between a crew member, suit, seat, and the attenuation system. The first Development Test (2017) included human subjects, and was performed with early development seat and suit components, and low level inputs. It provided a baseline for frequency response and behavior of the integrated system. The next two tests, Development Test (2019) and Qualification Test (2020), used manikin surrogates to represent the crew member and increasing levels of component hardware fidelity in order to test to higher input levels. Testing was performed at NASA Johnson Space Center (JSC) and Kennedy Space Center (KSC) Vibration Labs and provided the input levels required to represent the ascent and abort vehicle profiles as well as recorded component response behavior from accelerometer instrumentation and high speed cameras. Inspection of the suit and related components showed that for all seat orientations, and input environments, no damage occurred. Additional pre and post-test checks confirmed the functionality of all suited hardware. Response data of the suited components generally showed heavy attenuation across most of the tested frequency range. Transmissibility plots showed some amplification of components at lower frequency ranges. Overall this series of integrated tests showed that 1) the use of surrogate manikins in the tests were adequate for representing crew in a vibration environment, 2) full vibration levels for ascent and abort were heavily attenuated in the suit components and were non-damaging, and 3) the suit and related components are qualified for the Orion random vibration environments.

Jeffrey D Suhey↗

NASA NTRSDate not supplied

Overview of Integrated Random Vibration Testing of the NASA Orion Crew Survival Suit

Jeffrey Suhey↗

DOE OSTI2021

Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. Our present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Direct Fabrication of Atomically Defined Pores in MXenes Using Feedback-Driven STEM

Controlled fabrication of nanopores in 2D materials offer the means to create robust membranes needed for ion transport and nanofiltration. Techniques for creating nanopores have relied upon either plasma etching or direct irradiation; however, aberration-corrected scanning transmission electron microscopy (STEM) offers the advantage of combining a sub-Å sized electron beam for atomic manipulation along with atomic resolution imaging. Here, for this work, a method for automated nanopore fabrication is utilized with real-time atomic visualization to enhance the mechanistic understanding of beam-induced transformations. Additionally, an electron beam simulation technique, Electron-Beam Simulator (E-BeamSim) is developed to observe the atomic movements and interactions resulting from electron beam irradiation. Using the MXene Ti 3 C 2 T x , the influence of temperature on nanopore fabrication is explored by tracking atomic transformations and find that at room temperature the electron beam irradiation induces random displacement and results in titanium pileups at the nanopore edge, which is confirmed by E-BeamSim. At elevated temperatures, after removal of the surface functional groups and with the increased mobility of atoms results in atomic transformations that lead to the selective removal of atoms layer by layer. This work can lead to the development of defect engineering techniques within functionalized MXene layers and other 2D materials.

36 MATERIALS SCIENCE↗