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Results for “variational method”

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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Parametric study of variation in cargo-airplane performance related to progression from current to spanloader designs

A parametric analysis was made to investigate the relationship between current cargo airplanes and possible future designs that may differ greatly in both size and configuration. The method makes use of empirical scaling laws developed from statistical studies of data from current and advanced airplanes and, in addition, accounts for payload density, effects of span distributed load, and variations in tail area ratio. The method is believed to be particularly useful for exploratory studies of design and technology options for large airplanes. The analysis predicts somewhat more favorable variations of the ratios of payload to gross weight and block fuel to payload as the airplane size is increased than has been generally understood from interpretations of the cube-square law. In terms of these same ratios, large all wing (spanloader) designs show an advantage over wing-fuselage designs.

Toll, T. A.↗
NASA NTRS1978

The gravity method and interpretive techniques for detecting vertical crustal movements

Observations of temporal variations of gravity can be used as an inexpensive and rapid means of detecting, monitoring, and studying crustal deformation associated with many active geological processes. Such observations can yield qualitative or semiquantitative information on elevation changes and, when combined with independent elevation data, can yield information about changes of the subsurface density field arising from both subsurface displacements and temporal variations of the density of materials in the subsurface. The effectiveness of gravity techniques in specific cases of crustal deformation depends on the configuration of the local gravity field, the physical processes involved in the deformation, and the accuracy with which temporal gravity variations can be measured.

Jachens, R. C.↗
NASA NTRS1918

An Investigation of the Elements which Contribute to Statical and Dynamical Stability, and of the Effects of Variation in Those Elements

Part 1 gives details of models tested and methods of testing of the Eiffel 36 wing alone and the JN2 aircraft. Characteristics and performance curves for standard JN are included. Part 2 presents a statistical analysis of the following: lift and drag contributed by body and chassis tested without wings; lift and drag contributed by tail, tested without wings; the effect on lift and drift of interference between the wings of a biplane combination; lift and drag contributed by the addition of body, chassis, and tail to a biplane combination; total parasite resistance; effect of varying size of tail, keeping angle of setting constant; effect of varying length of body and size of tail at the same time, keeping constant moment of tail surface about the center of gravity; forces on the tail and the effects of downwash; effect of size and setting of tail on statical longitudinal stability effects of length of body on stability; the effects of the various elements of an airplane on longitudinal stability and the placing of the force vectors. Part 3 presents the fundamental principals of dynamical stability; computations of resistance derivatives; solution of the stability equation; dynamical stability of the Curtiss JN2; tabulation of resistance derivatives; discussion of the resistance derivatives; formation and solution of stability equations; physical conceptions of the resistance derivatives; elements contributing to damping and an investigation of low speed conditions. Part 4 includes a summary of the results of the statistical investigation and a summary of the results for dynamic stability.

Klemin, Alexander↗
DOE OSTI2021

Strobed imaging as a method for the determination and diagnosis of local seeing

ABSTRACT The image quality budget of many telescopes can have substantial contributions from local seeing, both ‘mirror’ and ‘dome’, which arise from turbulence and temperature variations that are difficult to quantify, measure directly, and ameliorate. We describe a method to determine the ‘local’ seeing degradation due to wavefront perturbations within the final few metres of the optical path from celestial sources to the focal plane of a ground-based telescope, using the primary instrument and along the same path taken by light from celestial sources. The concept involves placing strobed emitters along the light path to produce images on the main focal plane that ‘freeze’ different realizations of index perturbations. This method has the advantage of measuring directly the image motion and scintillation imparted by the dynamic spatial and temporal structure of local perturbations in the index of refraction along the light path, with a clean separation from seeing induced in the atmosphere above the dome. The strobed-source approach allows for rapid image motion and scintillation to be measured directly on the focal plane, even for large-aperture telescopes with wide-field instruments and slow shutters, such as that being constructed for the Rubin Observatory. A conceptual design is presented that uses the ‘guider’ CCDs in the Rubin telescope focal plane to make local-seeing measurements on demand, perhaps even during science exposures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Variational Principle for Mass Transport

A variation principle for mass transport in solids is derived that recasts transport coefficients as minima of local thermodynamic average quantities. The result is independent of diffusion mechanisms and applies to amorphous and crystalline systems. This unifies different computational approaches for diffusion and provides a framework for the creation of new approximation methods with error estimation. It gives a different physical interpretation of the Green function. Lastly, the variational principle quantifies the accuracy of competing approaches for a nontrivial diffusion problem.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Imaging Spatial Variations of Optical Bandgaps in Perovskite Solar Cells

A fast, nondestructive, camera-based method to capture optical bandgap images of perovskite solar cells (PSCs) with micrometer-scale spatial resolution is developed. This imaging technique utilizes well-defined and relatively symmetrical band-to-band luminescence spectra emitted from perovskite materials, whose spectral peak locations coincide with absorption thresholds and thus represent their optical bandgaps. The technique is employed to capture relative variations in optical bandgaps across various PSCs, and to resolve optical bandgap inhomogeneity within the same device due to material degradation and impurities. Degradation and impurities are found to both cause optical bandgap shifts inside the materials. The results are confirmed with micro-photoluminescence spectroscopy scans. The excellent agreement between the two techniques opens opportunities for this imaging concept to become a quantified, high spatial resolution, large-area characterization tool of PSCs. This development continues to strengthen the high value of luminescence imaging for the research and development of this photovoltaic technology.

14 SOLAR ENERGY↗
DOE OSTI2024

Sequential Monte Carlo for Cut-Bayesian Posterior Computation

We propose a sequential Monte Carlo (SMC) method to efficiently and accurately compute cut-Bayesian posterior quantities of interest, variations of standard Bayesian approaches constructed primarily to account for model misspecification. We prove finite sample concentration bounds for estimators derived from the proposed method along with a linear tempering extension and apply these results to a realistic setting where a computer model is misspecified. We then illustrate the SMC method for inference in a modular chemical reactor example that includes submodels for reaction kinetics, turbulence, mass transfer, and diffusion. The samples obtained are commensurate with a direct-sampling approach that consists of running multiple Markov chains, with computational efficiency gains using the SMC method. Overall, the SMC method presented yields a novel, rigorous approach to computing with cut-Bayesian posterior distributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Tree tensor network hierarchical equations of motion based on time-dependent variational principle for efficient open quantum dynamics in structured thermal environments

In this work, we introduce an efficient method, TTN-HEOM, for exactly calculating the open quantum dynamics for driven quantum systems interacting with highly structured bosonic baths by combining the tree tensor network (TTN) decomposition scheme with the bexcitonic generalization of the numerically exact hierarchical equations of motion (HEOM). The method yields a series of quantum master equations for all core tensors in the TTN that efficiently and accurately capture the open quantum dynamics for non-Markovian environments to all orders in the system–bath interaction. These master equations are constructed based on the time-dependent Dirac–Frenkel variational principle, which isolates the optimal dynamics for the core tensors given the TTN ansatz. The dynamics converges to the HEOM when increasing the rank of the core tensors, a limit in which the TTN ansatz becomes exact. We introduce TENSO, tensor equations for non-Markovian structured open systems, as a general-purpose Python code to propagate the TTN-HEOM dynamics. We implement three general propagators for the coupled master equations: two fixed-rank methods that require a constant memory footprint during the dynamics and one adaptive-rank method with a variable memory footprint controlled by the target level of computational error. We exemplify the utility of these methods by simulating a two-level system coupled to a structured bath containing one Drude–Lorentz component and eight Brownian oscillators, which is beyond what can presently be computed using the standard HEOM. Our results show that the TTN-HEOM is capable of simulating both dephasing and relaxation dynamics of driven quantum systems interacting with structured baths, even those of chemical complexity, with an affordable computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Foliar functional traits from imaging spectroscopy across biomes in eastern North America

Summary Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. Model validation accuracy varied among traits (normalized root mean squared error, 9.1–19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently. Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental‐scale functional diversity.

Wang, Zhihui↗
DOE OSTI2022

Identifying intragenic functional modules of genomic variations associated with cancer phenotypes by learning representation of association networks

Background Genome-wide Association Studies (GWAS) aims to uncover the link between genomic variation and phenotype. They have been actively applied in cancer biology to investigate associations between variations and cancer phenotypes, such as susceptibility to certain types of cancer and predisposed responsiveness to specific treatments. Since GWAS primarily focuses on finding associations between individual genomic variations and cancer phenotypes, there are limitations in understanding the mechanisms by which cancer phenotypes are cooperatively affected by more than one genomic variation. Results This paper proposes a network representation learning approach to learn associations among genomic variations using a prostate cancer cohort. The learned associations are encoded into representations that can be used to identify functional modules of genomic variations within genes associated with early- and late-onset prostate cancer. The proposed method was applied to a prostate cancer cohort provided by the Veterans Administration’s Million Veteran Program to identify candidates for functional modules associated with early-onset prostate cancer. The cohort included 33,159 prostate cancer patients, 3181 early-onset patients, and 29,978 late-onset patients. The reproducibility of the proposed approach clearly showed that the proposed approach can improve the model performance in terms of robustness. Conclusions To our knowledge, this is the first attempt to use a network representation learning approach to learn associations among genomic variations within genes. Associations learned in this way can lead to an understanding of the underlying mechanisms of how genomic variations cooperatively affect each cancer phenotype. This method can reveal unknown knowledge in the field of cancer biology and can be utilized to design more advanced cancer-targeted therapies.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1980

On the force-restore method for prediction of ground surface temperature

The force-restore method for prediction of ground surface temperature is investigated in view of the large temperature gradient that generally exists on a bare ground surface after an extended period of evaporation. The rate equation for the 'ground surface' temperature is rederived. The result from a numerical experiment indicates that there can be significant differences in the diurnal variation of ground surface temperature depending upon its definition. The method was tested by a simulation study of two field-measured data sets at different experiment sites.

Lin, J. D.↗
NASA NTRS1981

Computational aspects of geometric correction data generation in the LANDSAT-D imagery processing

A method is presented for systematic and geodetic correction data calculation. It is based on presentation of image distortions as a sum of nominal distortions and linear effects caused by variation of the spacecraft position and attitude variables from their nominals. The method may be used for both MSS and TM image data and it is incorporated into the processing by means of mostly offline calculations. Modeling shows that the maximal of the method are of the order of 5m at the worst point in a frame; the standard deviations of the average errors less than .8m.

Levine, I.↗
NASA NTRS1990

Parameter learning for performance adaptation

A parameter learning method is introduced and used to broaden the region of operability of the adaptive control system of a flexible space antenna. The learning system guides the selection of control parameters in a process leading to optimal system performance. A grid search procedure is used to estimate an initial set of parameter values. The optimization search procedure uses a variation of the Hooke and Jeeves multidimensional search algorithm. The method is applicable to any system where performance depends on a number of adjustable parameters. A mathematical model is not necessary, as the learning system can be used whenever the performance can be measured via simulation or experiment. The results of two experiments, the transient regulation and the command following experiment, are presented.

Peek, Mark D.↗
DOE OSTI2016

Spectral tomographic analysis of Bremsstrahlung X-rays generated in a laser-produced plasma

A new approach is proposed to analyze Bremsstrahlung X-rays that are emitted from laser-produced plasmas (LPP) and are measured by a stack type spectrometer. This new method is based on a spectral tomographic reconstruction concept with the variational principle for optimization, without referring to the electron energy distribution of a plasma. This approach is applied to the analysis of some experimental data obtained at a few major laser facilities to demonstrate the applicability of the method. Furthermore, slope temperatures of X-rays from LPP are determined with a two-temperature model, showing different spectral characteristics of X-rays depending on laser properties used in the experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

A Method for Projecting Cloud Shadows Onto a Central Receiver Field to Predict Receiver Damage

This work demonstrates methods of mapping high-spatial-resolution direct normal irradiance (DNI) data from satellites, Total Sky Imagers (TSIs), and analogous data sources onto a heliostat field for characterizing the spatial and temporal variation of the incident flux on a central receiver tower during cloud transient events. The mapping methods are incorporated into an optical software module that interfaces with CoPylot–SolarPILOT’s python API– to provide computationally efficient optical simulation of the heliostat field and the solar power tower. Eventually, this optical model will be incorporated into optimization models whereby a plant operator can understand the effects of cloud transient events on overall power production and receiver lifetime due to creep-fatigue damage and therefore make better informed decisions about receiver shutdown events. By more accurately modelling the effects of cloud events on receiver flux maps, this work may determine the magnitude and frequency of thermal cycling on receiver tubes and panels using actual or realistic cloud shapes instead of averaged DNI values–which may undercount the total cycle number. This work may also prevent unnecessary plant shutdowns due to overly precautionary control strategies and characterize the relative impact of various cloud types on receiver life. We plan to eventually integrate this methodology into the System Advisor Model (SAM) to improve performance model accuracy during periods of cloudiness. In this paper, we demonstrate generating DNI maps and mapping them to a solar field in CoPylot using 10 m resolution data from publicly available Sentinel-2 satellite data over the Crescent Dunes plant.

Mullin, Matthew↗

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