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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Digital image processing of nanometer-size metal particles on amorphous substrates

The task of differentiating very small metal aggregates supported on amorphous films from the phase contrast image features inherently stemming from the support is extremely difficult in the nanometer particle size range. Digital image processing was employed to overcome some of the ambiguities in evaluating such micrographs. It was demonstrated that such processing allowed positive particle detection and a limited degree of statistical size analysis even for micrographs where by bare eye examination the distribution between particles and erroneous substrate features would seem highly ambiguous. The smallest size class detected for Pd/C samples peaks at 0.8 nm. This size class was found in various samples prepared under different evaporation conditions and it is concluded that these particles consist of 'a magic number' of 13 atoms and have cubooctahedral or icosahedral crystal structure.

Soria, F.↗
NASA NTRS1996

NASA Rat Acoustic Tolerance Test 1994-1995: 8 kHz, 16 kHz, 32 kHz Experiments

Adult male Sprague-Dawley rats were exposed to chronic applied sound (74 to 79 dB, SPL) with octave band center frequencies of either 8, 16 or 32 kHz for up to 60 days. Control cages had ambient sound levels of about 62 dB (SPL). Groups of rats (test vs. control; N=9 per group) were euthanized after 0. 5. 14, 30, and 60 days. On each euthanasia day, objective evaluation of their physiology and behavior was performed using a Stress Assessment Battery (SAB) of measures. In addition, rat hearing was assessed using the brain stem auditory evoked potential (BAER) method after 60 days of exposure. No statistically significant differences in mean daily food use could be attributed to the presence of the applied test sound. Test rats used 5% more water than control rats. In the 8 kHz and 32 kHz tests this amount was statistically significant(P less than .05). This is a minor difference of questionable physiological significance. However, it may be an indication of a small reaction to the constant applied sound. Across all test frequencies, day 5 test rats had 6% larger spleens than control rats. No other body or organ weight differences were found to be statistically significant with respect to the application of sound. This spleen effect may be a transient adaptive process related to adaptation to the constant applied noise. No significant test effect on differential white blood cell counts could be demonstrated. One group demonstrated a low eosinophil count (16 kHz experiment, day 14 test group). However this was highly suspect. Across all test frequencies studied, day 5 test rats had 17% fewer total leukocytes than day 5 control rats. Sound exposed test rats exhibited 44% lower plasma corticosterone concentrations than did control rats. Note that the plasma corticosterone concentration was lower in the sound exposed test animals than the control animals in every instance (frequency exposure and number of days exposed).

Mele, Gary D.↗
NASA NTRS2018

NASA's Black Marble Nighttime Lights Product Suite

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500 meters resolution since January 2012 with data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-, terrain-, vegetation-, snow-, lunar-, and stray light-corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Key algorithm enhancements include: (1) lunar irradiance modeling to resolve non-linear changes in phase and libration; (2) vector radiative transfer and lunar bidirectional surface anisotropic reflectance modeling to correct for atmospheric and BRDF (Bidirectional Reflectance Distribution Function) effects; (3) geometric-optical and canopy radiative transfer modeling to account for seasonal variations in NTL; and (4) temporal gap-filling to reduce persistent data gaps. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Initial validation results are presented together with example case studies illustrating the scientific utility of the products. This includes an evaluation of temporal patterns of NTL dynamics associated with urbanization, socioeconomic variability, cultural characteristics, and displaced populations affected by conflict. Current and planned activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at different geographic locations and time periods representing the full range of retrieval conditions.

Suomi-NPP↗
DOE OSTI2025

A Role for the Plastidial GPT2 Translocator in the Modulation of Lignin Biosynthesis

ABSTRACT Engineering plants with reduced lignin content can result in pleiotropic growth defects. In stems of Arabidopsis plants with reduced expression of hydroxycinnamoyl CoA: shikimate hydroxycinnamoyl transferase (HCT), the plastidial glucose 6‐phosphate: phosphate co‐transporter GPT2 is highly overexpressed, and this coincides with reduced lignin levels and extensive transcriptional and metabolic reprogramming. To explore the potential relationship between GPT2 expression and lignin accumulation, GPT2 transcript levels were evaluated in a suite ofArabidopsis thalianaandMedicago truncatulalignin‐defective lines. We also examined lignin levels and composition, and transcriptomic and metabolic profiles in GPT2 loss‐of‐function, GPT2 overexpression, and wild‐type Arabidopsis plants. Loss of GPT2 had no effect on lignin, but its overexpression caused a decrease in stem lignin levels due to reduced accumulation of both guaiacyl and syringyl lignins and their associated monolignol pools.HCTtranscript levels were diminished in 35S‐GPT2 lines, indicating a potential transcriptional regulatory connection between lignin biosynthesis and GPT2. Based on our transcriptomic and metabolomic analyses, we suggest that GPT2 operates to balance the flux between the biosynthesis of lignin and light‐protective phenylpropanoid derivatives.

Plant Sciences↗
DOE OSTI2022

Enantioselectivity of Pentedrone and Methylone on Metabolic Profiling in 2D and 3D Human Hepatocyte-like Cells

Pentedrone and methylone can express stereoselectivity in toxicokinetic and toxicodynamic processes. Similarly, their chiral discrimination in metabolism, which was not yet evaluated, can result in different metabolic profiles and subsequent hepatotoxic effects. Therefore, the aim of this work was to assess, for the first time, both the hepatic cytotoxic and metabolic profile of pentedrone and methylone enantiomers using physiologically relevant in vitro models. The hepatotoxicity of these compounds was observed in a concentration-dependent manner in human stem-cell-derived hepatocyte-like cells (HLCs) cultured under 3D (3D-HLCs) and 2D (2D-HLCs) conditions. Enantioselectivity, on the other hand, was only shown for pentedrone (1 mM) in 3D-HLCs, being R-(−)-pentedrone the most cytotoxic. Furthermore, the metabolic profile was initially evaluated in human liver microsomes (HLM) and further demonstrated in 3D-HLCs and 2D-HLCs applying a gas chromatography coupled to a mass spectrometer (GC–MS) technique. Methylone and pentedrone showed distinct and preferential metabolic routes for their enantiomers, resulting in the production of differentiated metabolites; R-(+)-methylone and R-(−)-pentedrone are the most metabolized enantiomers. In conclusion, the results demonstrated enantioselectivity for pentedrone and methylone in the metabolic processes, with enantioselectivity in cytotoxicity for pentedrone.

Silva, Bárbara (ORCID:0000000173990197)↗
DOE OSTI2021

New insights into the role of constitutive bacterial rhizobiome and phenolic compounds in two Pinus spp. with contrasting susceptibility to pine pitch canker

Abstract The rhizobiome is being increasingly acknowledged as a key player in plant health and breeding strategies. The pine pitch canker (PPC), caused by the fungus Fusarium circinatum, affects pine species with varying susceptibility degrees. Our aims were to explore the bacterial rhizobiome of a susceptible (Pinus radiata) and a resistant (Pinus pinea) species together with other physiological traits, and to analyze shifts upon F. circinatum inoculation. Pinus seedlings were stem inoculated with F. circinatum spores and needle gas exchange and antioxidant-related parameters were analyzed in non-inoculated and inoculated plants. Rhizobiome structure was evaluated through 16S rRNA gene massive parallel sequencing. Species (non-inoculated plants) harbored distinct rhizobiomes (<40% similarity), where P. pinea displayed a rhizobiome with increased abundance of taxa described in suppressive soils, displaying plant growth promoting (PGP) traits and/or anti-fungal activity. Plants of this species also displayed higher levels of phenolic compounds. F. circinatum induced slight changes in the rhizobiome of both species and a negative impact in photosynthetic-related parameters in P. radiata. We concluded that the rhizobiome of each pine species is distinct and higher abundance of bacterial taxa associated to disease protection was registered for the PPC-resistant species. Furthermore, differences in the rhizobiome are paralleled by a distinct content in phenolic compounds, which are also linked to plants’ resistance against PPC. This study unveils a species-specific rhizobiome and provides insights to exploit the rhizobiome for plant selection in nurseries and for rhizobiome-based plant-growth-promoting strategies, boosting environmentally friendly disease control strategies.

Leitão, Frederico↗
DOE OSTI2022

Effect of Low Frequency Repetitive Transcranial Magnetic Stimulation (rTMS) Combined with Hyperbaric Oxygen (HBO) on Awakening of Coma Patients with Traumatic Brain Injury

Coma caused by craniocerebral injury is a common condition of neurosurgical acute injury. There is no specific method to promote awakening in a clinic. Early comprehensive treatment may be helpful to patients. The common methods are hyperbaric oxygen (HBO) and low-frequency repetitive transcranial magnetic stimulation (rTMS). However, the application effect and mechanism of rTMS combined with HBO on coma patients with traumatic brain injury need to be further studied. The brain stem auditory evoked potential (BAEP) is examined by the Kennedy coma recovery scale (CRS-R), the recovery of brain function and the state of consciousness are evaluated, and the therapeutic effect is evaluated by the Glasgow Coma Scale (GCS). Cerebrospinal fluid NE level, MCA blood flow velocity, and left brainstem and right brainstem auditory evoked potential are used to evaluate brain rehabilitation. RTMS combined with HBO could shorten the wake-up time, improve the wake-up rate, improve the GCS score and CRS-R score, shorten the brain wave latency time of the left and right brainstem, increase the NE level of cerebrospinal fluid, and decrease the blood flow velocity of MCA. RTMS combines with HBO can improve the nerve excitability of brain cells, reduce the disturbance of consciousness, promote the functional recovery of brain injury, and has a certain role in promoting the awakening of patients with traumatic brain injury coma.

Liu, Mei↗
NASA NTRS1993

On the estimation algorithm for adaptive performance optimization of turbofan engines

The performance seeking control (PSC) algorithm is designed to continuously optimize the performance of propulsion systems. The PSC algorithm uses a nominal propulsion system model and estimates, in flight, the engine deviation parameters (EDPs) characterizing the engine deviations with respect to nominal conditions. In practice, because of measurement biases and/or model uncertainties, the estimated EDPs may not reflect the engine's actual off-nominal condition. This factor has a direct impact on the PSC scheme exacerbated by the open-loop character of the algorithm. In this paper, the effects produced by unknown measurement biases over the estimation algorithm are evaluated. This evaluation allows for identification of the most critical measurements for application of the PSC algorithm to an F100 engine. An equivalence relation between the biases and EDPs stems from the analysis; therefore, it is undecided whether the estimated EDPs represent the actual engine deviation or whether they simply reflect the measurement biases. A new algorithm, based on the engine's (steady-state) optimization model, is proposed and tested with flight data. When compared with previous Kalman filter schemes, based on local engine dynamic models, the new algorithm is easier to design and tune and it reduces the computational burden of the onboard computer.

Espana, Martin D.↗
NASA NTRS2021

Multi-Pass Sequential Mini-Batch Stochastic Gradient Descent Algorithms for Noise Covariance Estimation in Adaptive Kalman Filtering

Estimation of unknown noise covariances in a Kalman filter is a problem of significant practical interest in a wide array of applications. Although this problem has a long history, reliable algorithms for their estimation were scant, and necessary and sufficient conditions for identifiability of the covariances were in dispute until recently. Necessary and sufficient conditions for covariance estimation and a batch estimation algorithm were presented in our previous study. This paper presents stochastic gradient descent algorithms for noise covariance estimation in adaptive Kalman filters that are an order of magnitude faster than the batch method for similar or better root mean square error. More significantly, these algorithms are applicable to non-stationary systems where the noise covariances can occasionally jump up or down by an unknown magnitude. The computational efficiency of the new algorithms stems from adaptive thresholds for convergence, recursive fading memory estimation of the sample cross-correlations of the innovations, and accelerated stochastic gradient descent algorithms. The comparative evaluation of the proposed methods on a number of test cases demonstrates their computational efficiency and accuracy.

Adaptive Kalman filtering↗
DOE OSTI2020

Low-pressure methanol synthesis from CO 2 over metal-promoted Ni-Ga intermetallic catalysts

Ni-Ga and M-Ni-Ga (M = Au, Co, Cu) catalysts were evaluated for methanol synthesis from CO 2 at 10 bar and 200-270°C. The following trend in turnover frequency (TOF) for CO 2 hydrogenation was observed: AuNiGa > CuNiGa > NiGa > CoNiGa, where TOF increased with decreasing catalyst affinity for CO. The presence of a third metal was found to influence both the formation of the Ni-Ga intermetallic phase as well as the number of available sites for CO chemisorption. Phase formation, catalyst composition and stability were evaluated using therm ogravimetric analysis (TGA), X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning transmission electron microscopy and energy dispersive X-ray spectroscopy (STEM-EDX). Au-Ni-Ga, which showed a nearly 4-fold improvement in TOF at 263°C and 10 bar compared to Ni-Ga, consisted of Ni 3 Ga particles decorated with Au, as evidenced by post catalysis characterization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Assessing Prior Emergent Constraints on Surface Albedo Feedback in CMIP6

An emergent constraint (EC) is a popular model evaluation technique, which offers the potential to reduce intermodel variability in projections of climate change. Two examples have previously been laid out for future surface albedo feedbacks (SAF) stemming from loss of Northern Hemisphere (NH) snow cover (SAF snow ) and sea ice (SAF ice ). These processes also have a modern-day analog that occurs each year as snow and sea ice retreat from their seasonal maxima, which is strongly correlated with future SAF across an ensemble of climate models. The newly released CMIP6 ensemble offers the chance to test prior constraints through out-of-sample verification, an important examination of EC robustness. Here, we show that the SAF snow EC is equally strong in CMIP6 as it was in past generations, while the SAF ice EC is also shown to exist in CMIP6, but with different, slightly weaker characteristics. We find that the CMIP6 mean NH SAF exhibits a global feedback of 0.25 ± 0.05 W m -2 K -1 , or ~61% of the total global albedo feedback, largely in line with prior generations despite its increased climate sensitivity. Additionally, the NH SAF can be broken down into similar contributions from snow and sea ice over the twenty-first century in CMIP6. Crucially, intermodel variability in seasonal SAF snow and SAF ice is largely unchanged from CMIP5 because of poor outlier simulations of snow cover, surface albedo, and sea ice thickness. These outliers act to mask the noted improvement from many models when it comes to SAF ice , and to a lesser extent SAF snow .

58 GEOSCIENCES↗
DOE OSTI2025

Overview of leakage scenarios in supervised machine learning

Machine learning (ML) provides powerful tools for predictive modeling. ML’s popularity stems from the promise of sample-level prediction with applications across a variety of fields from physics and marketing to healthcare. However, if not properly implemented and evaluated, ML pipelines may contain leakage typically resulting in overoptimistic performance estimates and failure to generalize to new data. This can have severe negative financial and societal implications. Our aim is to expand understanding associated with causes leading to leakage when designing, implementing, and evaluating ML pipelines. Illustrated by concrete examples, we provide a comprehensive overview and discussion of various types of leakage that may arise in ML pipelines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Resilience Metrics and Framework for Distributed Wind Presentation

This presentation communicates information about the MIRACL project Resilience Metrics report and Resilience Framework report. It was created for the 2021 MIRACL advisory board meeting. We propose a three-tiered approach for the resilience framework. At the top level, we consider the time horizons on which resilience will be evaluated and executed. At the middle level, we consider the core functions of resilience, which span across the time horizons. At the lower level, we consider the process steps that correspond to implementing practices for resilience in each of the core functions. The framework considers three time horizons in order to enable organizations to assess and improve their system’s resilience throughout its lifecycle. We call these time horizons the planning, operational, and future stages. The planning stage uses organizational needs and current system evaluation to prepare for potential hazards. The operational stage seeks to execute responses to hazards as prudently and efficiently as possible to maintain system resilience. The future stage seeks to improve on current system resilience and feeds back into the planning stage to promote continuous improvement. While all three time horizons are important when considering a specific topic, the planning and evaluation phase (i.e., what is done in advance of the event) is critical in defining a system’s resilience characteristics and in outlining how a system responds to an event. This framework intentionally emphasizes the planning stage to highlight the overarching emphasis of this effort, not to imply that the other two time-related horizons (i.e., operational and change the future) are less important. The core functions in the framework are identify, prepare, detect, adapt, and recover. These five functions stem from a rigorous analysis of definitions used across the industry, and they represent the core capabilities that an organization must have to enable lifecycle resilience. Within each core function, process steps are described that help walk an organization through the information gathering, evaluation, decision-making, and implementation processes they will need to ensure their resilience goals are maintained throughout the system and the system lifecycle. Also highlighted in the figure is the concept that a resilience framework should be cyclical in nature. Because a system’s resilience is based on finite resources and time, it must continually evolve through this framework’s risk management and capital investment steps at an appropriate level of scope and pace.

17 WIND ENERGY↗
DOE OSTI2024

Compliant Intramedullary Stems for Joint Reconstruction

The longevity of current joint replacements is limited by aseptic loosening, which is the primary cause of non-infectious failure for hip, knee, and ankle arthroplasty. Aseptic loosening is typically caused either by osteolysis from particulate wear, or by high shear stresses at the bone-implant interface from over-constraint. Our objective was to demonstrate feasibility of a compliant intramedullary stem that eliminates over-constraint without generating particulate wear. The compliant stem is built around a compliant mechanism that permits rotation about a single axis. We first established several models to understand the relationship between mechanism geometry and implant performance under a given angular displacement and compressive load. We then used a neural network to identify a design space of geometries that would support an expected 100-year fatigue life inside the body. We additively manufactured one representative mechanism for each of three anatomic locations, and evaluated these prototypes on a KR-210 robot. The neural network predicts maximum stress and torsional stiffness with 2.69% and 4.08% error respectively, relative to finite element analysis data. We identified feasible design spaces for all three of the anatomic locations. Simulated peak stresses for the three stem prototypes were below the fatigue limit. Benchtop performance of all three prototypes was within design specifications. Our results demonstrate the feasibility of designing patient- and joint-specific compliant stems that address the root causes of aseptic loosening. Guided by these results, we expect the use of compliant intramedullary stems in joint reconstruction technology to increase implant lifetime.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Tree hydrodynamic modelling of the soil–plant–atmosphere continuum using FETCH3

Modelling the water transport along the soil–plant–atmosphere continuum is fundamental to estimating and predicting transpiration fluxes. A Finite-difference Ecosystem-scale Tree Crown Hydrodynamics model (FETCH3) for the water fluxes across the soil–plant–atmosphere continuum is presented here. The model combines the water transport pathways into one vertical dimension, and assumes that the water flow through the soil, roots, and above-ground xylem can be approximated as flow in porous media. This results in a system of three partial differential equations, resembling the Richardson–Richards equation, describing the transport of water through the plant system and with additional terms representing sinks and sources for the transfer of water from the soil to the roots and from the leaves to the atmosphere. The numerical scheme, developed in Python 3, was tested against exact analytical solutions for steady state and transient conditions using simplified but realistic model parameterizations. The model was also used to simulate a previously published case study, where observed transpiration rates were available, to evaluate model performance. With the same model setup as the published case study, FETCH3 results were in agreement with observations. Through a rigorous coupling of soil, root xylem, and stem xylem, FETCH3 can account for variable water capacitance, while conserving mass and the continuity of the water potential between these three layers. FETCH3 provides a ready-to-use open access numerical model for the simulation of water fluxes across the soil–plant–atmosphere continuum.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Observational Data for Next-Generation Climate Model Evaluation: Requirements, Considerations, and Best Practices

Climate model simulations are an important source of information about our planet’s climate system and also enable informed decision-making under different future scenarios. As a new archive of results from the next generation of climate models is anticipated to become available with the Coupled Model Intercomparison Project phase 7 (CMIP7), the need to develop efficient and robust methods to evaluate models is paramount. Observations are an integral part of model evaluation, providing a means to quantify and understand the degree to which climate models can faithfully reproduce Earth system processes. Such analysis is critical for constraining climate projections, identifying areas of focus for model development, and assisting analysts in deciphering the utility of models for specific applications. Observations of Earth system come from a diversity of sources, span different space–time domains, and are produced by different communities, and each dataset features different data structures and formats, metadata standards, and its own unique uncertainties. Uncertainties in an observational dataset may stem from gaps in temporal and spatial coverage, instrumentation errors, or assumptions in retrieval and processing methods. How then does one ensure that observational data are ready for use and utilized in the most appropriate way for robust, rapid, and routine climate model evaluation? The CMIP7 Model Benchmarking Task Team with input from the broader climate modeling, model evaluation, and observational data communities present a vision and considerations for best practices toward the optimal and appropriate use of observational data to support next-generation climate model evaluation.

Climate models↗
NASA NTRS1994

Evaluation of a GCM cirrus parameterization using satellite observations

This study applies a simple yet effective methodology to validate a general circulation model parameterization of cirrus ice water path. The methodology combines large-scale dynamic and thermodynamic fields from operational analyses with prescribed occurrence of cirrus clouds from satellite observations to simulate a global distribution of ice water path. The predicted cloud properties are then compared with the corresponding satellite measurements of visible optical depth and infrared cloud emissivity to evaluate the reliability of the parameterization. This methodology enables the validation to focus strictly on the water loading side of the parameterization by eliminating uncertainties involved in predicting the occurrence of cirrus internally within the parameterization. Overall the parameterization performs remarkably well in capturing the observed spatial patterns of cirrus optical properties. Spatial correlations between the observed and the predicted optical depths are typically greater than 0.7 for the tropics and northern hemisphere midlatitudes. The good spatial agreement largely stems from the strong dependence of the ice water path upon the temperature of the environment in which the clouds form. Poorer correlations (r approximately 0.3) are noted over the southern hemisphere midlatitudes, suggesting that additional processes not accounted for by the parameterization may be important there. Quantitative evaluation of the parameterization is hindered by the present uncertainty in the size distribution of cirrus ice particles. Consequently, it is difficult to determine if discrepancies between the observed and the predicted optical properties are attributable to errors in the parameterized ice water path or to geographic variations in effective radii.

Soden, B. J.↗
DOE OSTI2021

Correction and verification of x-ray imaging crystal spectrometer analysis on Wendelstein 7-X through x-ray ray tracing

X-ray ray tracing is used to develop ion-temperature corrections for the analysis of the X-ray Imaging Crystal Spectrometer (XICS) used at Wendelstein 7-X (W7-X) and perform verification on the analysis methods. The XICS is a powerful diagnostic able to measure ion-temperature, electron-temperature, plasma flow, and impurity charge state densities. While these systems are relatively simple in design, accurate characterization of the instrumental response and validation of analysis techniques are difficult to perform experimentally due to the requirement of extended x-ray sources. For this reason, a ray tracing model has been developed that allows characterization of the spectrometer and verification of the analysis methods while fully considering the real geometry of the XICS system and W7-X plasma. Through the use of ray tracing, several important corrections have been found that must be accounted for in order to accurately reconstruct the ion-temperature profiles. The sources of these corrections are described along with their effect on the analyzed profiles. The implemented corrections stem from three effects: (1) effect of sub-pixel intensity distribution during de-curving and spatial binning, (2) effect of sub-pixel intensity distribution during forward model evaluation and generation of residuals, and (3) effect of defocus and spherical aberrations on the instrumental response. Possible improvements to the forward model and analysis procedures are explored, along with a discussion of trade-offs in terms of computational complexity. Finally, the accuracy of the tomographic inversion technique in stellarator geometry is investigated, providing for the first time a verification exercise for inversion accuracy in stellarator geometry and a complete XICS analysis tool-chain.

47 OTHER INSTRUMENTATION↗