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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 1,207 records · Page 67

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NASA NTRS2019

Diagnosing Bias in Modeled Soil Moisture/runoff Coefficient Correlation Using the SMAP Level 4 Soil Moisture Product

The physical parameterization of key processes in land surface models (LSMs) remains uncertain, and new techniques are required to evaluate LSM accuracy over coarse spatial scales. Given the role of soil moisture in the partitioning of surface water fluxes (between infiltration, runoff and evapotranspiration), surface soil moisture (SSM) estimates represent an important observational benchmark for such evaluations. Here, we apply SSM estimates from the NASA Soil Moisture Active Passive Level 4 product (SMAP_L4) to diagnose bias in the coupling between SSM and surface runoff for multiple Noah-Multiple Physics (Noah-MP) LSM parameterization cases. Results demonstrate that Noah-MP surface runoff parameterizations often underestimate the coupling strength between pre-storm SSM and the event-scale runoff coefficient (RC; defined as the ratio between event-scale streamflow and precipitation volumes). This bias squanders RC information contained in pre-storm SSM and reduces RC estimation skill. Such bias can be quantified against an observational benchmark calculated using streamflow observations and SMAP_L4 SSM and applied to explain a substantial fraction of the observed basin-to-basin (and case-to-case) variability in the skill of event-scale Noah-MP RC estimates. Based on this concept, a novel case selection strategy for ungauged basins is introduced and demonstrated to successfully identify poorly performing Noah-MP parameterization cases.

SSM↗

NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. It affects the efficiency of the National Airspace System (NAS) and both surface and airspace operations can benefit from better understanding future runway configurations. In this paper, we present a comprehensive implementation of predictive models for runway configuration estimation from large volumes of historical data. Specifically, operational data from two full years (2018 and 2019) is collected, analyzed, and fused together to build the data product used in this work. The data set differs from prior work in the field in terms of its scope, resolution, and variety of factors collected and considered. Meteorological data is collected from two different sources – current weather conditions from METAR (Meteorological Terminal Aviation Routine Weather Report) and forecast weather conditions from Localized Aviation MOS Program (LAMP). Operational data from the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) related to scheduled and actual number of arrivals and departures, average taxi times, etc. are collected. NASA’s Sherlock Data Warehouse is used to identify critical information such as go-arounds, and other events that might impact RCM decision-making. All data is collected and aggregated over 15-minute intervals throughout the two years. This provides a resolution like the timescales that might be necessary for runway configuration management decision-making. A variety of supervised learning algorithms are tested including Support Vector Machine, Random Forest, Gradient Boosting, etc. including tuning of the model hyperparameters. The modeling process is applied and presented on two representative U.S. airports – Charlotte Douglas International Airport (KCLT) and Denver International Airport (KDEN). The two airports present different levels of complexity in terms of the total number of configurations used and provide a balanced perspective on the generalizability of the developed approach to other airports in the NAS. Initial results are promising (F1 score of 0.91 at KCLT and 0.83 at KDEN) for data in the test set. The final paper will contain a comprehensive comparison between different models and model building strategies as well as further refined results. Most important predictors for each airport will be identified along with a discussion and recommendations on adapting the framework to other scenarios.

Tejas G Puranik↗

DOE OSTI2021

Variable-focus magnetostatic lens

Variable-focus solenoidal lenses for charged particle beams with integrated emittance filtering are disclosed. The emittance may be controlled via selection of collimating irises. The focal length may be changed by altering the spacing between two permanent ring magnets.

Lewellen, John↗

NASA NTRS2012

Radio-to-Gamma-Ray Monitoring of the Narrow-line Seyfert 1 Galaxy PMN J0948+0022 from 2008 to 2011

We present more than three years of observations at different frequencies, from radio to high-energy γ-rays, of the Narrow-Line Seyfert 1 (NLS1) Galaxy PMN J0948+0022 (z = 0.585). This source is the first NLS1 detected at energies above 100 MeV and therefore can be considered the prototype of this emerging new class of γ-ray emitting active galactic nuclei (AGN). The observations performed from 2008 August 1 to 2011 December 31 confirmed that PMN J0948+0022 generates a powerful relativistic jet, which is able to develop an isotropic luminosity at gamma-rays of the order of 1048 erg per second, at the level of powerful quasars. The evolution of the radiation emission of this source in 2009 and 2010 followed the canonical expectations of relativistic jets with correlated multiwavelength variability (gamma-rays followed by radio emission after a few months), but it was difficult to retrieve a similar pattern in the light curves of 2011. The comparison of gamma-ray spectra before and including 2011 data suggested that there was a softening of the highenergy spectral slope. We selected five specific epochs to be studied by modelling the broad-band spectrum, which are characterised by an outburst at gamma-rays or very low/high flux at other wavelengths. The observed variability can largely be explained by changes in the injected power, the bulk Lorentz factor of the jet, or the electron spectrum. The characteristic time scale of doubling/halving flux ranges from a few days to a few months, depending on the frequency and the sampling rate. The shortest doubling time scale at gamma-rays is 2.3 +/- 0.5 days. These small values underline the need of highly sampled multiwavelength campaigns to better understand the physics of these sources.

monitoring↗

DOE OSTI2018

Novel brain-expressed noncoding RNA, HSTR1, identified at a human-specific variable number tandem repeat locus with a human accelerated region

Highlights: • A novel noncoding RNA gene HSTR1 is expressed in human brain and testis. • The evolutionary accelerated region showed enhanced promoter activity in human. • The variable number tandem repeat in HSTR1 is associated with its RNA stability. The evolutionary conserved genomic sequences that have acquired significantly increased number of nucleotide substitutions specifically in the human lineage, called human accelerated regions (HARs), have been identified as candidate genomic regions that have contributed to the evolution of human-specific traits. A number of HARs were indeed shown to have novel enhancer activity and be associated with human-specific brain development and with cognition and social behavior. It is therefore of great importance to investigate the details of genomic function of each HAR to understand the roles of HARs as critical contributors to the genetic basis of human evolution. In this study, we identified a previously unannotated brain-expressed noncoding RNA gene, HSTR1, at a human-specific tandem repeat locus. Notably, the 5′ flanking sequence of HSTR1 showed the signature of HARs and the dramatic human-specific enhancement of promoter activity, providing the evidence of positive selection to increase the expression level of HSTR1 during human evolution. We also revealed that the tandem repeat number in HSTR1 was highly variable among individual alleles and affected the stability of HSTR1 RNA, suggesting variation in the activity of HSTR1 between human individuals. Our work thus provides a novel candidate gene that potentially contributed to the evolution of the human brain. It may also underpin some of the variation between human brains.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Assessing the sensitivity of land-atmosphere coupling strength to boundary and surface layer parameters in the WRF model over Amazon

Modeling tools can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations, but subject to uncertainties associated with parameters in model physical parameterizations. Different sensitivity analysis (SA) approaches may lead to different conclusions about the underlying sensitivities. In this study, we quantify simulation uncertainties related to parameter perturbations, and use different approaches to conduct parameter SA on the WRF model pertaining to L-A coupling strength for simulations over the Amazon region. A total of twenty parameters from the Yonsei University (YSU) planetary boundary layer (PBL) and the revised MM5 surface layer (SL) schemes were selected in this analysis. Three different SA methods, the Morris One-at-A-Time (MOAT) method, the Multivariate Adaptive Regression Splines (MARS) method, and the Sobol’ method, were employed to analyze seven WRF-simulated variables and five L-A coupling metrics. Results show that 1) parameter perturbations cause large simulation uncertainties which are comparable to those in the observations; 2) three different SA methods give consistent L-A coupling strength outcomes; 3) six out of the twenty parameters contribute 80%–95% of the total variance in the metrics analyzed, and first-order effects dominate over interaction effects; 4) the twelve variables/metrics of interest show similar sensitivity patterns to the selected parameters, which is consistent across all the methods used. Physical mechanisms for how the sensitive parameters act in determining the L-A coupling strength and associated variables also are illustrated. Our results will help quantifying L-A coupling strength and establishing a basis for parameter calibration over the Amazon region.

Wang, Chen↗

DOE OSTI2021

Melting rate correlation with batch properties and melter operating conditions during conversion of nuclear waste melter feeds to glasses

The rate of conversion of nuclear waste melter feed to glass is affected by the selection of melter feed materials and by melter design and operation. The melting rate correlation (MRC) is an equation that relates the glass production rate with two types of variables: (1) feed and melt properties: conversion heat, cold-cap bottom temperature, and glass melt viscosity; and (2) melter design and operation parameters: melter geometry, melter operating temperature, and gas bubbling rate. The MRC shows good agreement for an extended melting-rate data set of high-level waste (HLW) melter feeds and a data set generated for low-activity waste (LAW) melter feeds. Laboratory observation of heated melter feed samples is often used to assess the cold-cap bottom temperature of HLW melter feeds (moderately foaming feeds), but this technique appears inadequate for LAW melter feeds (vigorously foaming feeds). For LAW feeds, an adequate assessment of the cold-cap bottom temperature was achieved using evolved gas analysis, which allows identification of the collapse of primary foam for oxidized feeds. This assessment shows that the cold-cap bottom temperature for vigorously foaming LAW feeds is higher than that for moderately foaming HLW feeds. When the results of MRC are compared, LAW feeds are generally less sensitive to the bubbling rate and melt viscosity, and more sensitive to the cold-cap bottom temperature than HLW feeds. The MRC qualifies as a promising tool to support the selection of melter feed materials and melter operating conditions, which is determined from expensive independent scaled melter experiments, and sophisticated mathematical models.

Lee, Seung Min↗

DOE OSTI2024

Grain structure and texture selection regimes in metal powder bed fusion

Additive manufacturing (AM) offers opportunities to produce complex part geometries not possible with conventional processing and in some cases even improve part performance. However, adoption has been slowed by difficulties assessing microstructure variability and there is no straightforward approach to relate processing to grain structure characteristics. In this study, datasets from AdditiveFOAM heat transport simulations of laser powder bed fusion (LPBF) are used to drive ExaCA simulations of grain structure. The GPU utilization of ExaCA and an algorithmic update for modeling melt pool overlap region solidification enabled rapid and parallel simulation across a wider range of process conditions than previously explored with cellular automata-based solidification models. A texture selection angle $θ_s$ is defined based on melt pool overlap geometry, and the range of $θ_s$ over which a commonly observed texture transition occurs in characterized AM builds was well-reproduced by ExaCA simulations over a wide range of melt pool shape, hatch spacing, and layer height. ExaCA simulations with 90 degree rotation of the scan direction on every other layer reproduced a number of trends from the AM literature including grain refinement, the dominance of layers with larger melt pools on the final grain structure, and the weakening or strengthening of texture depending on odd and even layer melt pool overlap geometry. EBSD data from a benchmark AM part is used to validate the simulated mechanism of a layer rotation-induced texture strengthening effect. Importantly, these results expand the understanding of the mechanisms for texture selection in alloys with cubic crystal symmetry and offer an approach to easily evaluate processing conditions. With this new understanding, these modeling tools will enable anticipation of previously unexpected variations in grain structure and target specific microstructures and properties.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Evaluation of a Class of Simple and Effective Uncertainty Methods for Sparse Samples of Random Variables and Functions

When very few samples of a random quantity are available from a source distribution of unknown shape, it is usually not possible to accurately infer the exact distribution from which the data samples come. Under-estimation of important quantities such as response variance and failure probabilities can result. For many engineering purposes, including design and risk analysis, we attempt to avoid under-estimation with a strategy to conservatively estimate (bound) these types of quantities -- without being overly conservative -- when only a few samples of a random quantity are available from model predictions or replicate experiments. This report examines a class of related sparse-data uncertainty representation and inference approaches that are relatively simple, inexpensive, and effective. Tradeoffs between the methods' conservatism, reliability, and risk versus number of data samples (cost) are quantified with multi-attribute metrics use d to assess method performance for conservative estimation of two representative quantities: central 95% of response; and 10 -4 probability of exceeding a response threshold in a tail of the distribution. Each method's performance is characterized with 10,000 random trials on a large number of diverse and challenging distributions. The best method and number of samples to use in a given circumstance depends on the uncertainty quantity to be estimated, the PDF character, and the desired reliability of bounding the true value. On the basis of this large data base and study, a strategy is proposed for selecting the method and number of samples for attaining reasonable credibility levels in bounding these types of quantities when sparse samples of random variables or functions are available from experiments or simulations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

High temperature air oxidation behavior of Hastelloy X processed by Electron Beam Melting (EBM) and Selective Laser Melting (SLM)

The microstructure and oxidation behavior of Laser Beam Melted, Electron Beam Melted and wrought Hastelloy X were studied at 950 °C in dry air, 50 h cycles, up to 1000 h. The variability of processing parameters and powder compositions strongly impacted the oxidation and spallation behavior. Finally, the alloys with high Mn and Si were associated with higher oxidation rates, finer Cr 2 O 3 grain microstructure and increased spallation was observed for the alloys with large elongated grain microstructures (aspect ratio of 10 ± 3).

36 MATERIALS SCIENCE↗

DOE OSTI2022

Optimization of the moderators in the STS preliminary design

This report details the results for an optimization of the dimensions of the moderators in the preliminary design of the Spallation Neutron Source Second Target Station (STS). This study uses the optimization algorithms of Dakota and an unstructured mesh model for the moderators in MCNP. More details on the unstructured mesh model and the automated mesh generation can be found in [3]. Parallel to this effort, the same moderator geometries have been optimized using a constructive solid geometry (CSG) MCNP model. More details on this model and its results can be found in [4]. Three optimal designs are selected for each moderator: one that is optimized for maximum peak brightness, one for maximum time-integrated brightness, and one for a combination of peak and time-integrated brightness. The backbone of the optimization work flow is provided by Dakota. For each set of design parameters requested by Dakota, a new solid geometry is automatically built in Creo and SpaceClaim, and subsequently exported to Attila4MC to generate an unstructured mesh geometry for MCNP. After the MCNP calculation is finished, the objective function (e.g., brightness metric) is returned to Dakota. After the new design has been evaluated, a result-file is written, and Dakota proposes the next set of design parameters to be evaluated. The loop continues until a specified convergence criterion has been met. The design parameters of the cylindrical (upper) moderator include the hydrogen radius, the premoderator thickness (top, bottom, radial), the beryllium radius and the horizontal position of the moderator. The crucial design choice is the hydrogen radius. A radius of 62 mm is shown to provide the maximum time-integrated brightness. The maximum peak brightness occurs with a radius of 40 mm. A combined (middle) design, which balances peak and time-integrated brightnesses, is obtained with a hydrogen radius of 50 mm. The premoderator thicknesses and the beryllium radius are slightly larger in the design optimized for time-integrated brightness than in the design optimized for peak brightness. The sensitivity to these two parameters is relatively small close to the optimal configurations. The hydrogen vessel and vacuum vessel wall thicknesses are dependent on the radius of the liquid hydrogen due to structural integrity requirements. The increased wall thicknesses for larger vessels significantly penalize the time-integrated brightness, with the maximum obtainable value reduced by more than 10% relative to earlier studies which used fixed vessel wall thicknesses. The impact of the variable wall thicknesses is much less for the peak brightness and combined brightness designs. The design parameters of the tube (lower) moderator selected for the optimization are the tube length, the annular premoderator thickness, the beryllium radius and the horizontal position of the moderator. The tube length is the crucial parameter and is chosen large (210 mm) and small (125 mm) in the designs optimized for time-integrated and peak brightness respectively. A combined optimal design has a tube length of 170 mm. The premoderator thickness and the beryllium radius are chosen larger in the design optimized for time-integrated brightness.

42 ENGINEERING↗

NASA NTRS1986

Composite interlaminar fracture toughness: Three-dimensional finite element modeling for mixed mode 1, 2 and 3 fracture

A computational method/procedure is described which can be used to simulate individual and mixed mode interlaminar fracture progression in fiber composite laminates. Different combinations of Modes 1, 2, and 3 fracture are simulated by varying the crack location through the specimen thickness and by selecting appropriate unsymmetric laminate configurations. The contribution of each fracture mode to strain energy release rate is determined by the local crack closure methods while the mixed mode is determined by global variables. The strain energy release rates are plotted versus extending crack length, where slow crack growth, stable crack growth, and rapid crack growth regions are easily identified. Graphical results are presented to illustrate the effectiveness and versatility of the computational simulation for: (1) evaluating mixed-mode interlaminar fracture, (2) for identifying respective dominant parameters, and (3) for selecting possible simple test methods.

Murthy, P. L. N.↗

NASA NTRS1988

Composite interlaminar fracture toughness - Three-dimensional finite-element modeling for mixed mode I, II, and fracture

Murthy, Pappu L. N.↗

DOE OSTI2025

Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots

The cultivation of sterile giant miscanthus (Miscanthus × giganteus, M × g) for bioenergy and bioproducts has expanded into grain-cropped land in the United States (US) as local markets developed for this high-yielding perennial grass (10–30 Mg DM ha −1 ). However, the magnitude of spatial and temporal variability in yield within US Corn Belt fields, along with impacts on economic return and sustainable land management, is poorly understood. This study established a diagnostic model relating remote sensing-derived vegetation indices to ground truth data from 105 hand-harvested stem biomass samples, which were strategically selected to represent the full range of vegetation index observations. The high-resolution satellite-sensed vegetation indices captured > 90% of the yield variation measured within fields. This model was then used to predict yield variability and assess economic performance across four of the first commercial M × g fields in the Corn Belt state of Iowa, US. Significant spatial variability in biomass dry matter (DM) yields (9.3–18.1 Mg DM ha −1 ) and net profits ($\$$83 to $\$$1211.5 ha −1 ) was observed. All fields were profitable in all site-years. When low profit occurred, it was explained by limited management experience of the crop in Iowa. The breakeven yield at a selling price of $\$$130 Mg −1 varied from 9.0–12.1 Mg ha −1 at 15% moisture content (7.6–10.3 Mg DM ha −1 ). Breakeven prices ranged from $\$$73 to $\$$122.4 Mg −1 , matching ranges used in the Department of Energy Billion Ton Report (US Department of Energy, 2023). Notably, M × g yield and profits were commensurate with grain crops particularly with favorable precipitation. This study provides insight on the M × g management “learning curve”, performance on marginal land and in drought conditions, and demonstrates that addressing yield gaps, reducing costs, and implementing precision agriculture strategies can enhance profitability. These findings emphasize the value of remote sensing technologies in guiding sustainable and competitive commercial-scale M × g production.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Application of the Aquifer Impact Model to support decisions at a CO 2 sequestration site

The National Risk Assessment Partnership (NRAP) has developed a suite of tools to assess and manage risk at CO 2 sequestration sites. The NRAP tool suite includes the Aquifer Impact Model (AIM), which evaluates the potential for groundwater impacts from leaks of CO 2 and brine through abandoned wellbores. There are two aquifer reduced-order models (ROMs) included with the AIM tool, a confined alluvium aquifer, and an unconfined carbonate aquifer. The models accept aquifer parameters as a range of variable inputs so they may have broad applicability. The generic aquifer models may be used at the early stages of site selection, when site-specific data is not available. Guidelines have been developed for determining when the generic ROMs might be applicable to a new site. This work considers the application of the AIM to predicting the impact of CO 2 or brine leakage were it to occur at the Illinois Basin Decatur Project (IBDP). Results of the model sensitivity analysis can help guide characterization efforts; the hydraulic parameters and leakage source term magnitude are more sensitive than clay fraction or cation exchange capacity. Sand permeability was the only hydraulic parameter measured at the IBDP site. More information on the other hydraulic parameters could reduce uncertainty in risk estimates. Some non-adjustable parameters are significantly different for the ROM than for the observations at the IBDP site. The generic ROMs could be made more useful to a wider range of sites if the initial conditions and no-impact threshold values were adjustable parameters.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

Specific stereochemistry of OP-1074 disrupts estrogen receptor alpha helix 12 and confers pure antiestrogenic activity

Complex tissue-specific and cell-specific signaling by the estrogen receptor (ER) frequently leads to the development of resistance to endocrine therapy for breast cancer. Pure ER antagonists, which completely lack tissue-specific agonist activity, hold promise for preventing and treating endocrine resistance, however an absence of structural information hinders the development of novel candidates. Here we synthesize a small panel of benzopyrans with variable side chains to identify pure antiestrogens in a uterotrophic assay. We identify OP-1074 as a pure antiestrogen and a selective ER degrader (PA-SERD) that is efficacious in shrinking tumors in a tamoxifen-resistant xenograft model. Biochemical and crystal structure analyses reveal a structure activity relationship implicating the importance of a stereospecific methyl on the pyrrolidine side chain of OP-1074, particularly on helix 12.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Colloidal fibers and rings by cooperative assembly

Abstract Janus colloids with one attractive patch on an otherwise repulsive particle surface serve as model systems to explore structure formation of particles with chemically heterogeneous surfaces such as proteins. While there are numerous computer studies, there are few experimental realizations due to a lack of means to produce such colloids with a well-controlled variable Janus balance. Here, we report a simple scalable method to precisely vary the Janus balance over a wide range and selectively functionalize one patch with DNA. We observe, via experiment and simulation, the dynamic formation of diverse superstructures: colloidal micelles, chains, or bilayers, depending on the Janus balance. Flexible dimer chains form through cooperative polymerization while trimer chains form by a two-stage process, first by cooperative polymerization into disordered aggregates followed by condensation into more ordered stiff trimer chains. Introducing substrate binding through depletion catalyzes dimer chains to form nonequilibrium rings that otherwise do not form.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

The role of radio loudness in Eigenvector 1 and the Baldwin Effect of [O iii ] λ5007

ABSTRACT The radio emission is an important observable of quasars, but its relationship to Eigenvector 1 and the [O iii] λ5007 Baldwin Effect is not fully understood. We explore these issues based on a sample of 1800 quasars taken from the Sloan Digital Sky Survey Data Release 7. We employ a new approach of selecting subsamples in the plane of fundamental physical parameters of the black hole mass and Eddington ratio, so as to reduce variables and complexity in analyses. Based on these subsamples, we investigate the relationship between radio loudness R and Eigenvector 1 and find that radio loudness is correlated with [O iii] λ5007 emission, but has no clear relationship with optical Fe ii emission, which indicates that the radio power is probably not a driver of Eigenvector 1 but merely a secondary process. In addition, we also investigate the impact of radio loudness on the Baldwin Effect of [O iii] λ5007. We find that when the radio loudness is not strong (log R < 2), the Baldwin Effect of [O iii] λ5007 is clear, while in the samples of extreme radio loudness (log R ≥ 2), the Baldwin Effect of [O iii] λ5007 becomes weaker or even disappears. We suggest that both radio loudness and luminosity influence the relative strength of [O iii].

79 ASTRONOMY AND ASTROPHYSICS↗