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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Calcium Balance in Mature Rats Exposed to a Space Flight Model

Negative calcium balances are seen in humans during spaceflight and bed rest, an analog of space flight. Due to the infrequency and costliness of space flight and the difficulties, cost, and restraints in using invasive procedures in bed rest studies, several ground based animal models of space flight have been employed. The most useful and well developed of these models is hind limb unloading in the rat. In this model the hind limbs are non-weight bearing (unloaded) but still mobile; there is a cephalad fluid shift similar to that seen in astronauts in flight; the animals are able to feed, groom and locomote using their front limbs; the procedure is reversible; and, importantly, the model has been validated by comparison to space flight. Several laboratories have studied calcium balance using rats in hind limb unweighting. Roer and Dillaman used young male rats to study calcium balance in this model for 25 days. They found no differences in dietary calcium intake, percent calcium absorption, urinary and fecal excretion, hence indicating no differences in calcium balance between control and unloaded rats. In another study, employing 120 day old females, rats' hind limbs were unloaded for 28 days. While negative calcium balances were observed during a 25 day recovery period no balance measurements were possible during unweighting since the researchers did not employ appropriate metabolic cages. In a recent study from this laboratory, using 200 g rats in the space flight model for two weeks, we found depressed intestinal calcium absorption and increased fecal calcium excretion (indicating less positive calcium balances) and lower circulating 1,25-dihydroxyvitamin D. The above studies indicate that there remains a dearth of information on calcium balance during the hind limb unloading rat space flight model, especially in mature rats, whose use is a better model for planned manned space flight than juvenile or growing animals. With the aid of a newly designed metabolic cage developed in our laboratory it is now possible to accurately measure urinary and fecal calcium excretions in this space flight model. The purpose of this study, then, was to extend and enlarge our previous findings viz: to measure calcium balances in mature rats exposed to a space flight model.

Wolinsky, Ira↗
DOE OSTI2019

Robust Time-Varying Parameter Identification for Composite Load Modeling

With the increasing integration of uncertain resources, e.g., renewables, electric vehicles, and demand responses, it is imperative to understand the characteristics of loads for power system analysis and control. Challenges of load modeling come from a variety of load components and time-varying compositions. In addition, the existence of outliers in measurements further complicates the problem. This paper proposes a robust time-varying parameter identification technique for composite ZIP and induction motor load models. A batch-model regression form, including time-varying parameters, is established based on state transition models and observation models with current observations and previous predictions to guarantee data redundancy. To deal with outliers, down-weighting coefficients of measurements are calculated with a projection statistics approach. Based on the batch-model regression and the down-weighting coefficients, parameter identification at each sample time is formulated as a weighted least squares optimization, which is solved by the Newton-Raphson approach with the previous estimated parameters as the initial iteration values. In addition, parameters' sensitivities to different outliers in measurements are analyzed. Results on the IEEE 57-bus system and IEEE 118-bus system show that the proposed algorithm can robustly identify time-varying parameters for the composite load models.

Composite load model↗
DOE OSTI2023

HopBox: An image analysis pipeline to characterize hop cone morphology

Abstract Hop cone morphology can influence picking and drying ability, and color can impact consumer preference and may be indicative of quality. However, these characteristics are not generally evaluated in hop breeding programs due to the tedious nature of trait quantification and the extensive variation among cones within a genotype. We developed the HopBox, which is a simply constructed light box with a camera mount, and a publicly available image processing pipeline that identifies hop cones within color‐corrected images, reads a QR code within the image, and outputs data on hop cone length, width, area, perimeter, openness, weight, color, and density. The trained model was applied to images of 500 cones each from 15 replicated advanced hop genotypes from the USDA‐ARS breeding program in Prosser, Washington. Analysis of variance revealed significant ( p < 0.001) differences between genotypes for all traits measured, enabling breeders to discriminate between genotypes for selection purposes. Broad sense heritability for all traits ranged from 0.23 to 0.59. A random sampling of hop cones from the complete dataset revealed that imaging only 5–10 cones adequately captured genotypic variation and provided acceptable rank correlations ( r s > 0.75); however, increasing the sample size to 30 provided optimal precision. Instructions for constructing a HopBox and the code for the analysis pipeline are publicly available online and have wide applicability for hop breeding and research.

Altendorf, Kayla R.↗
DOE OSTI2021

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

Here we present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.

protein complexes↗
DOE OSTI2019

Effective Adsorption of Cr(VI) by High Strength Chitosan/Montmorillonite Composite Hydrogels Involving Spirulina Biomass/Microalgae

The “3-in-1 type” biopolymer composite (chitosan/montmorillonite clay/biosorbent) hydrogels were produced and used as adsorbents for Cr(VI) ion. Na-Montmorillonite (NaMMT) clay was modified with Spirulina (Sp) biosorbent by using lyophilization based “cryoscopic expansion” (C-XP) method. The Sp immobilized MMT (SpMMT) clay containing hydrogels were found to have an open/extended form of Sp structure on their pores’ walls, presenting all possible receptor groups for adsorption of Cr(VI) ions. SpMMT loaded hydrogels showed higher adsorption capacities than NaMMT loaded ones. The physically crosslinked hydrogel including only 1% SpMMT (1SpM-H) clay exhibited 150% higher adsorption capacity as compared to neat chitosan hydrogel even in 50 ppm Cr(VI) solution. The same composite hydrogel was found to adsorp about 780% Cr(VI) with respect to the clay’s weight while individual uses of Sp and MMT can remove only about 4.80 and 0.36% Cr(VI) with respect to their weights. The pseudo-first order model was found to be the most suitable for the kinetic data of NaMMT loaded hydrogels while that of SpMMT containing hydrogels followed the pseudo-second order kinetics. The isotherm data of all the hydrogels exhibited a better fit to the Freundlich and Sips model. The maximum adsorption capacity (3333 mg g{sup −1}) calculated by Sips model was achieved via the hydrogel having 1% SpMMT which is in good agreement with the experimental kinetic data. The highest adsorption with the lowest amount of SpMMT clay could be attributed to its looser Sp network structure whose functional groups are in long-distance, releasing more adsorption sites for the Cr(VI). The highest compression modulus and toughness were also obtained with the 1SpM-H hydrogel which is probably due to increased physical and reversible interactions between chitosan molecules and SpMMT clay layers at optimum clay loading (1%).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Metal hydride composition-derived parameters as machine learning features for material design and H 2 storage

Though hydrogen is a promising energy carrier for a green future, many challenges persist. One is the difficulty in engineering storage solutions, with metal hydrides being a leading contender among solid-state strategies. To facilitate efficient searching of candidate materials, ridge regression, simple decision trees, random forest ensembles, and gradient boosting ensembles were employed to predict the energy of formation, with the random forest ensemble resulting in the lowest test set error. First, two public databases, Materials Project and HydPark, were searched for metal hydrides. Feature engineering was performed before the models were developed, resulting in electronegativity, density, atomic density, d-character, f-character, band gap, hydrogen weight fraction, magnetization, temperature, and pressure being retained. The models were then benchmarked by the lowest test error before a random forest ensemble was used to populate entries missing energy of formation. Furthermore, all were then scored by hydrogen storage capacity and energy of formation suitability. Readily available features including several derived from only the chemical formula which were found to be highly predictive. and so are promising for high-throughput screening of arbitrary novel hydride formulations and blends for thermodynamic feasibility.

25 ENERGY STORAGE↗
DOE OSTI2016

Pulse shape discrimination in helium-4 scintillation detectors

We investigated three algorithms for discriminating between neutrons and gamma rays in a pres-surized 4 He gas fast neutron detector: charge comparison, weighted integration, and neutron-gamma model analysis (NGMA). And for each algorithm, a comprehensive pulse shape discrimination study was conducted using time-of-flight measurements, receiver operator characteristic curves, figure of merit performance measures, and a comparison of performance between 252 Cf and PuBe mixed neutron/gamma sources. The NGMA method was found to have the best overall performance by both the figure of merit and the receiver operator characteristic curve. Our results also illustrated the high gamma rejection efficiency of these detectors, which is desirable in a variety of neutron monitoring applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Evolution of (001) and (111) facets for selective epitaxial growth inside submicron trenches

The evolution of (001) and (111) facets for the epitaxial growth inside submicron trenches is systematically studied in this report. The analysis with the method of “Lagrange multiplier” indicates the equilibrium crystal shape. In the case of non-equilibrium without external fluxes, we employed the “weighted mean curvature” method to mathematically model the inter-facet migration rate for two extreme kinetic cases: “surface diffusion limited” and “surface attachment/detachment limited.” Coupled with external supply of atoms, the self-limited behavior of facet size is theoretically predicted. Moreover, we find that the self-limited stable facet size in trenches of different widths has a specific relationship determined by the surface energy ratio, kinetic rate ratio, and isolated growth rate difference. The two limited cases could be discriminated according to the mathematical fitting of one exponent in this relationship based on the stable facet size in trenches of different widths.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Evidence for the role of hydrogen in the stabilization of minority carrier lifetime in boron-doped Czochralski silicon

This study demonstrates that the presence of a hydrogen source during fast-firing is critical to the regeneration of B-O defects and that is it not a pure thermally based mechanism or due to plasma exposure. Boron-doped p-type wafers were fired with and without hydrogen-rich silicon nitride (SiN{sub x}:H) films present during the fast-firing process. After an initial light-induced degradation step, only wafers fired with the SiN{sub x}:H films present were found to undergo permanent and complete recovery of lifetime during subsequent illuminated annealing. In comparison, wafers fired bare, i.e., without SiN{sub x}:H films present during firing, were found to demonstrate no permanent recovery in lifetime. Further, prior exposure to hydrogen-rich plasma processing was found to have no impact on permanent lifetime recovery in bare-fired wafers. This lends weight to a hydrogen-based model for B-O defect passivation and casts doubt on the role of non-hydrogen species in the permanent passivation of B-O defects in commercial-grade p-type Czochralski silicon wafers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Why many polymers are so fragile: A new perspective

Many polymers exhibit much steeper temperature dependence of their structural relaxation time (higher fragility) than liquids of small molecules, and the mechanism of this unusually high fragility in polymers remains a puzzle. To reveal additional hints for understanding the underlying mechanism, we analyzed correlation of many properties of polymers to their fragility on example of model polymer polystyrene with various molecular weights (MWs). Here, we demonstrate that these correlations work for short chains (oligomers), but fail progressively with increase in MW. Our surprising discovery is that the steepness of the temperature dependence (fragility) of the viscosity that is determined by chain relaxation follows the correlations at all molecular weights. These results suggest that the molecular level relaxation still follows the behavior usual for small molecules even in polymers, and its fragility (chain fragility) falls in the range usual for molecular liquids. It is the segmental relaxation that has this unusually high fragility. We also speculate that many polymers cannot reach an ergodic state on the time scale of segmental dynamics due to chain connectivity and rigidity. This leads to sharper decrease in accessible configurational entropy upon cooling and results in steeper temperature dependence of segmental relaxation. Our proposed scenario provides a new important insight into the specifics of polymer dynamics: the role of ergodicity time and length scale. At the end, we suggest that a similar scenario can be applicable also to other molecular systems with slow intra-molecular degrees of freedom and to chemically complex systems where the time scale of chemical fluctuations can be longer than the time scale of structural relaxation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantitative analysis of cost savings and occupants’ preferences in grid-interactive smart home operation

Many utility companies in the United States have introduced time-of-use (TOU) rates for homeowners with the goal of regulating electricity consumption during peak hours. The electrical appliances in homes include various thermostatically controlled devices, such as air conditioners (AC) for thermal comfort, and nonthermostatically controlled devices such as clothes washers. As a result, homeowners face the complicated challenge of economically operating multiple electrical appliances in their homes while maintaining comfort and convenience. This is usually due to the lack of an explicit understanding of the correlation between cost saving and the users’ comfort. To understand the correlation, this article is designed to construct a framework by integrating three major components: a multi-objective optimization method accommodating multiple competing goals with different weights, a learning-based system modeling approach describing the dynamics and thermal coupling effects of appliances, and a novel comfort index method differentiating preferred and acceptable thermal comfort. Our proposed framework can allow the indoor air temperature to fall into the "preferred" range with a marginal cost increase. Furthermore, the simulation result shows that an additional 8 h for the preferred thermal comfort can be achieved with a cost increase of only 1.77%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Bi-Level Linear Programming Model for Automatic Load Shedding: A Distributed Wide-Area Measurement System-based Solution

Load shedding is currently implemented as a two-step based approach. In the first step, manual load shedding is taken place, were system operators, using estimates, inform distribution utilities of predicted stressful conditions. Information provided include the potential use of energy reserves, as well as load shedding amount. In a second step, automatic load shedding is done. The latter is realized using protection relays. While considering frequency variation, pre-defined values of load to be shed and correspondent number of stages for such to be realized are transformed into relay settings. Under-frequency protection relays use only local measurements towards decision making, thus operate in a decentralized architecture. Decision making is done in milliseconds plus breaker time. While this approach has provided much system reliability, considering the new smart grid paradigm, where system dynamics are much faster due to increasing renewable resources penetration, in some operating conditions it will generate sub-optimal solutions, such as islanding. Phasor measurement units provide a source of information which can be useful for this problem. Centralized architecture-based solutions for automatic load shedding, as present in the state-of-the-art, require though total processing times which are not acceptable for real-life implementation. In this work, considering the above, a bi-level linear programming model is presented. The model is implemented considering a distributed architecture while leveraging phasor measurement units data. The upper-level model estimates the current system state. Results of this model are embedded in a lower-level model, which decision variables are the location and load value to be shed. Easy-to-implement model, built-on the classic weighted least squares solution, highlight potential aspects towards real-life applications.

Bretas, Arturo Suman↗
DOE OSTI2017

Machine-learning data and model for autoconversion and accretion rates

This PI product includes two key components of a recently developed machine-learning model for predicting autoconversion and accretion rates. The training data set and the testing data set used to build our machine-learning model, containing sets of four input variables (cloud water content, cloud droplet number concentration, drizzle water content, and drizzle drop number concentration) and two output variables (autoconversion rate and accretion rate). The machine-learning model, containing information on the trained weights and biases, and the coefficients for scaling the inputs and outputs variables. The uncertainty in the new estimates of autoconversion and accretion rates is about 15% and 5%, respectively.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Static performance of a 13.97 cm (5.5 inch) diameter model VTOL lift fan

A tip-turbine-driven fan of the type currently being used in wind tunnel tests of VTOL lift fan models was tested. Values of thrust, weight flow, exit total and static pressure, exit swirl angle, and turbine temperature drop were measured as a function of fan speed for several inlet and exit configurations. A standard fan performance map was also obtained.

Lowe, W. H.↗
NASA NTRS1974

A general solution for the registration of optical multispectral scanners

The paper documents a general theory for registration (mapping) of data sets gathered by optical scanners such as the ERTS satellite MSS and the Skylab S-192 MSS. This solution is generally applicable to scanners which have rotating optics. Navigation data and ground control points are used in a statistically weighted adjustment based on a mathematical model of the dynamics of the spacecraft and the scanner system. This adjustment is very similar to the well known photogrammetric adjustments used in aerial mapping. Actual tests have been completed on NASA aircraft 24 channel MSS data, and the results are very encouraging.

Rader, M. L.↗