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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Global maximum carboxylation rate trait scaling in the Sheffield Dynamic Global Vegetation Model 1901-2012

This data package contains model output data and climate input data associated with the New Phytologist publication: Walker, A.P., Quaife, T., van Bodegom, P.M., De Kauwe, M.G., Keenan, T.F., Joiner, J., Lomas, M.R., MacBean, N., Xu, C., Yang, X., Woodward, F.I., 2017. The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax) on global gross primary production. New Phytologist 215, 1370–1386. https://doi.org/10.1111/nph.14623. This dataset contains maximum carboxylation rate at 25 ºC (Vcmax,25), Gross Primary Production (GPP), Net Biome Production (NBP), vegetation carbon, and soil carbon data from Sheffield Dynamic Global Vegetation Model (SDGVM) for multiple trait-scaling methods for scaling Vcmax,25 across Earth, and alternative instantaneous temperature scaling functions. Vcmax,25 values are mean top-leaf values taken during the growing seasons, which were defined as periods during which leaf area index (LAI) was greater than one. Vcmax,25 values were reported prior to scaling of Vcmax by water-stress or leaf-age. The attached metadata file (SDGVM_vcmax_dataset.docx) describes the methods used and explains the organization of data within the included .zip file. This metadata file is also included in PDF format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

MENT-Flow: maximum-entropy phase space tomography using normalizing flows

Generative models can be trained to reproduce low-dimensional projections of high-dimensional phase space distributions. Normalizing flows are generative models that parameterize invertible transformations, allowing exact probability density evaluation and sampling. Consequently, flows are unbiased entropy estimators and could be used to solve the high-dimensional maximum-entropy tomography (MENT) problem. In this work, we evaluate a flow-based MENT solver (MENT-Flow) against exact maximum-entropy solutions and Minerbo's iterative MENT algorithm in two dimensions.

Hoover, Austin↗
DOE OSTI2022

Methodology for assessing the maximum potential impact of separations opportunities in industrial processes

Separation technologies currently used in U.S. manufacturing industries are estimated to account for more than 20% of plant energy consumption. However, accurately determining the impact of new separation technology solutions can sometimes be difficult, especially when evaluating a slate of new candidate separation technologies, each of which has its own separation performance, energy demand, and capital cost. In these cases, a typical approach is to assess each new separation technology by collecting performance and cost information and then using that information to develop a techno-economic analysis to identify overall benefits. While this approach is thorough, it can be time consuming and can hinder reaching a critical understanding of the potential of a given separation challenge, especially when there is no known solution. To address these issues, we developed an assessment methodology, using industrial screening processes, that can be used to better understand the potential impacts of addressing a given separation challenge. This paper presents an overview of our separation challenge stream assessment methodology. The methodology involves defining an “ideal” separator and deriving the associated minimum separation energy. The “ideal” separator represents the most optimistic outlook of a given opportunity so the maximum impact from existing and not-yet-developed solutions can be assessed. Using established biorefinery models, we applied the methodology to 10 different separation challenge streams from two different biomass conversion platforms to identify the type of information that can be obtained. Three of the ten challenge streams assessed had maximum possible cost savings predictions >20%, and associated reductions in process energy carbon intensity ranging from 0 to 54%. Two streams had cost and energy savings potential that were < 5%. Some of the opportunity drivers from the various assessments include higher product yields, reduction or elimination of downstream equipment, new co-products, and cost savings associated with raw materials and energy consumption. The information from these assessments can help guide the selection or development of new separation technology solutions based on the various potential factors that drive the projected benefits.

09 BIOMASS FUELS↗
DOE OSTI2024

Efficient First-Order Algorithms for Large-Scale, Non-Smooth Maximum Entropy Models with Application to Wildfire Science

Maximum entropy (MaxEnt) models are a class of statistical models that use the maximum entropy principle to estimate probability distributions from data. Due to the size of modern data sets, MaxEnt models need efficient optimization algorithms to scale well for big data applications. State-of-the-art algorithms for MaxEnt models, however, were not originally designed to handle big data sets; these algorithms either rely on technical devices that may yield unreliable numerical results, scale poorly, or require smoothness assumptions that many practical MaxEnt models lack. In this paper, we present novel optimization algorithms that overcome the shortcomings of state-of-the-art algorithms for training large-scale, non-smooth MaxEnt models. Our proposed first-order algorithms leverage the Kullback–Leibler divergence to train large-scale and non-smooth MaxEnt models efficiently. For MaxEnt models with discrete probability distribution of n elements built from samples, each containing m features, the stepsize parameter estimation and iterations in our algorithms scale on the order of O(mn) operations and can be trivially parallelized. Moreover, the strong ℓ1 convexity of the Kullback–Leibler divergence allows for larger stepsize parameters, thereby speeding up the convergence rate of our algorithms. To illustrate the efficiency of our novel algorithms, we consider the problem of estimating probabilities of fire occurrences as a function of ecological features in the Western US MTBS-Interagency wildfire data set. Our numerical results show that our algorithms outperform the state of the art by one order of magnitude and yield results that agree with physical models of wildfire occurrence and previous statistical analyses of wildfire drivers.

Physics↗
DOE OSTI2021

The Twins Embedding of Type Ia Supernovae. I. The Diversity of Spectra at Maximum Light

In this work, we study the spectral diversity of Type Ia supernovae (SNe Ia) at maximum light using high signal-to-noise spectrophotometry of 173 SNe Ia from the Nearby Supernova Factory. We decompose the diversity of these spectra into different extrinsic and intrinsic components, and we construct a nonlinear parameterization of the intrinsic diversity of SNe Ia that preserves pairings of "twin"SNe Ia. We call this parameterization the "Twins Embedding."Our methodology naturally handles highly nonlinear variability in spectra, such as changes in the photosphere expansion velocity, and uses the full spectrum rather than being limited to specific spectral line strengths, ratios, or velocities. We find that the time evolution of SNe Ia near maximum light is remarkably similar, with 84.6% of the variance in common to all SNe Ia. After correcting for brightness and color, the intrinsic variability of SNe Ia is mostly restricted to specific spectral lines, and we find intrinsic dispersions as low as ~0.02 mag between 6600 and 7200 Å. With a nonlinear three-dimensional model plus one dimension for color, we can explain 89.2% of the intrinsic diversity in our sample of SNe Ia, which includes several different kinds of "peculiar"SNe Ia. A linear model requires seven dimensions to explain a comparable fraction of the intrinsic diversity. We show how a wide range of previously established indicators of diversity in SNe Ia can be recovered from the Twins Embedding. In a companion article, we discuss how these results can be applied to the standardization of SNe Ia for cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Maximum respiration rates in hyporheic zone sediments are primarily constrained by organic carbon concentration and secondarily by organic matter chemistry

Abstract. River corridors are fundamental components of the Earth system, and their biogeochemistry can be heavily influenced by processes in subsurface zones immediately below the riverbed, referred to as the hyporheic zone. Within the hyporheic zone, organic matter (OM) fuels microbial respiration, and OM chemistry heavily influences aerobic and anaerobic biogeochemical processes. The link between OM chemistry and respiration has been hypothesized to be mediated by OM molecular diversity, whereby respiration is predicted to decrease with increasing diversity. Here we test the specific prediction that aerobic respiration rates will decrease with increases in the number of unique organic molecules (i.e., OM molecular richness, as a measure of diversity). We use publicly available data across the United States from crowdsourced samples taken by the Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS) consortium. Our continental-scale analyses rejected the hypothesis of a direct limitation of respiration by OM molecular richness. In turn, we found that organic carbon (OC) concentration imposes a primary constraint over hyporheic zone respiration, with additional potential influences of OM richness. We specifically observed respiration rates to decrease nonlinearly with the ratio of OM richness to OC concentration. This relationship took the form of a constraint space with respiration rates in most systems falling below the constraint boundary. A similar, but slightly weaker, constraint boundary was observed when relating respiration rate to the inverse of OC concentration. These results indicate that maximum respiration rates may be governed primarily by OC concentration, with secondary influences from OM richness. Our results also show that other variables often suppress respiration rates below the maximum associated with the richness-to-concentration ratio. An important focus of future research will identify physical (e.g., sediment grain size), chemical (e.g., nutrient concentrations), and/or biological (e.g., microbial biomass) factors that suppress hyporheic zone respiration below the constraint boundaries observed here.

58 GEOSCIENCES↗
NASA NTRS1971

The Determination of the Geometries of Multiple-Element Airfoils Optimized for Maximum Lift Coefficient

Optimum airfoils in the sense of maximum lift coefficient are obtained by a newly developed method. The maximum lift coefficient is achieved by requiring that the turbulent skin friction be zero in the pressure rise region on the upper surface. Under this constraint, the pressure distribution is optimized. The optimum pressure distribution consists of a uniform stagnation pressure on the lower surface, a uniform minimum pressure on the upper surface immediately downstream of the front stagnation point followed by a Stratford zero skin friction pressure rise. When multiple-element airfoils are under consideration, this optimum pressure distribution appears on every element. The parameters used to specify the pressure distribution on each element are the Reynolds number and the normalized trailing edge velocity. The newly developed method of design computes the velocity distribution on a given airfoil and modifies the airfoil contour in a systematic manner until the desired velocity distribution is achieved. There are no limitations on how many elements the airfoil to be designed can have.

Chen, A. W.↗
NASA NTRS1972

Longitudinal stability and control derivatives of a jet fighter airplane extracted from flight test data by utilizing maximum likelihood estimation

A method of parameter extraction for stability and control derivatives of aircraft from flight test data, implementing maximum likelihood estimation, was developed and successfully applied to actual longitudinal flight test data from a modern sophisticated jet fighter. The results of this application establish the merits of the estimation technique and its computer implementation(allowing full analyst interaction with the program) as well as provide data for the validation of a portion of the differential maneuvering simulator (DMS). The results are presented for all flight test runs in tabular form and as time history comparisons between the estimated states and the actual flight test data. Comparisons between extracted and manufacturer's values for five major derivatives are presented and reveal good agreement for these principal derivatives with one exception. This particular derivative is extensively investigated by utilizing the interactive capabilities of the computer program. The results of this investigation verify the numbers extracted by maximum likelihood estimation.

Steinmetz, G. G.↗
NASA NTRS1972

Maximum power transfer from a solar-cell array by sensing array temperature

A technique is described in which a spacecraft solar-cell array is caused to operate at or near maximum power output over a wide range of environmental conditions. The output of an array temperature sensor is used to vary the duty cycle of a pulse-width-modulated impedance regulator so that the array operates at the voltage of maximum power. A resistance-type temperature sensor was found to be applicable for most spacecraft missions. However, a solar cell used as a temperature sensor has the advantage of negligible transient errors on lightweight arrays for orbiting spacecraft.

Sussman, M.↗
NASA NTRS1973

The auroral green line in Perseid spectra near sunspot maximum

Thirty-one spectra photographed during the Perseid showers of 1969 and 1970 are found to exhibit greater ionization and stronger, more frequent appearance of the forbidden oxygen line at 5577 A than Perseid spectra obtained with the same instrument in 1961. Data from 13 Perseid showers indicate a relationship between the frequency of occurrence of the oxygen line and solar activity. In 1969-70, near sunspot maximum, the strength of this auroral green line is greatest near shower maximum, as though the nature of the meteoroids were a function of their distance from the core of the stream, or, alternatively, the strength of the green line were a function of the altitude of the radiant.

Russell, J. A.↗
NASA NTRS1973

Maximum likelihood classification by thresholding

The standard maximum-likelihood classifier is reformulated so that, in most cases, only a small number of density functions need be computed each time a data point is to be classified. The technique relies upon class thresholds which are obtained at the beginning of the classification process and which remain fixed thereafter. The result of the reformulation is that a significant reduction in classification processing time is obtained while retaining complete consistency with the standard maximum-likelihood classifier.

Minter, T. C.↗
NASA NTRS1974

Maximum power transfer in n ports with passive loads

The problem of drawing maximum power from an n port by suitably terminating it with another passive n port is studied. Methods are derived for determining sets of passive impedance matrices which are 'optimal' in the sense that they draw maximum power from a given n port. It is shown that, in all nontrivial cases, if there exists any (passive or otherwise) optimum-load impedance matrix, then there exist, in fact, infinitely many passive optimum-load impedance matrices.

Vidyasagar, M.↗
NASA NTRS1975

Maximum two-phase flow rates of subcooled nitrogen through a sharp-edged orifice

Data are presented of an experiment in which subcooled liquid nitrogen was discharged through a sharp-edged orifice at flow rates near the maximum. The data covered a range of inlet stagnation pressures from slightly above saturation to twice the thermodynamic critical pressure. The data were taken along five separate inlet stagnation isotherms ranging from 0.75 to 1.035 times the thermodynamic critical temperature. The results indicate that subcooled liquids do not choke or approach maximum flow in an asymptotic manner even though the back pressure is well below saturation; and orifice flow coefficients are not constant as is frequently assumed. A metastable jet appears to exist which breaks down if the difference between back pressure and saturation pressure is large enough.

Simoneau, R. J.↗
NASA NTRS1975

Maximum likelihood signature estimation

Maximum-likelihood estimates are discussed which are based on an unlabeled sample of observations, of unknown parameters in a mixture of normal distributions. Several successive approximation procedures for obtaining such maximum-likelihood estimates are described. These procedures, which are theoretically justified by the local contractibility of certain maps, are designed to take advantage of good initial estimates of the unknown parameters. They can be applied to the signature extension problem, in which good initial estimates of the unknown parameters are obtained from segments which are geographically near the segments from which the unlabeled samples are taken. Additional problems to which these methods are applicable include: estimation of proportions and adaptive classification (estimation of mean signatures and covariances).

Walker, H. F.↗
NASA NTRS1974

Monte Carlo analysis of the solar-wind modulation of galactic C-N-O at solar maximum

A previous (Moss and Giuli, 1971) Monte Carlo analysis of the solar-wind modulation of galactic cosmic-ray rigidity spectra is extended to include particles in the C-N-O group. A solar cavity 'radius' of 7 AU is found to be consistent with observations of the C-N-O component at solar maximum. The variation in modulation between solar maximum and solar minimum may be explained solely by variation of the solar cavity size, with no change in the scattering mean free path.

Moss, T. A.↗
NASA NTRS1974

Computational aspects of maximum likelihood estimation and reduction in sensitivity function calculations

This paper discusses numerical aspects of computing maximum likelihood estimates for linear dynamical systems in state-vector form. Different gradient-based nonlinear programming methods are discussed in a unified framework and their applicability to maximum likelihood estimation is examined. The problems due to singular Hessian or singular information matrix that are common in practice are discussed in detail and methods for their solution are proposed. New results on the calculation of state sensitivity functions via reduced order models are given. Several methods for speeding convergence and reducing computation time are also discussed.

Gupta, N. K.↗
NASA NTRS1974

Optimization of self-acting herringbone journal bearings for maximum stability

The stability of herringbone grooved journal bearings was increased by optimizing the groove depth, width, length, and angle. Optimization was performed on the basis of a small-eccentricity infinite-groove analysis in combination with a previously developed Newton-Raphson procedure for bearings with the smooth member rotating or with the grooved member rotating at low compressibility numbers. A newly-developed vector technique for bearings with the grooved member rotating at high compressibility numbers also was used in the analysis. The design curves obtained are suitable for choosing the optimum bearing for a wide range of operating conditions (compressibility numbers from 0 to 80, length to diameter ratios from 1/4 to 2, and smooth or grooved member rotating). Compared to bearings optimized for maximum load, bearings optimized for maximum stability are shown to provide a drastic increase in bearing-supported mass. Bearings with grooved member rotating are substantially more stable than bearing with smooth member rotating, particularly at high compressibility numbers.

Fleming, D. P.↗