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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Predicting photovoltaic soiling losses using environmental parameters: An update

This study presents an investigation on the correlations between soiling losses and environmental parameters at 41 locations in the United States, with the aim of analyzing the possibility of predicting soiling losses at a site even when soiling data are not available. The results of this work, which considers the largest pool of soiling data points systematically investigated so far, confirm that a single-variable regression based on particulate matter concentration returns the best correlations with soiling, with adjusted coefficients of determination up to 70%, corresponding to RMSE as low as 0.9%. Among the various particulate matter datasets investigated, a gridded Environment Protection Agency dataset is for the first time found to return correlations similar to those obtained by interpolating particulate matter monitoring station data. We discuss in detail the different interpolation techniques used to process the particulate matter concentrations because they can greatly impact the correlations. Specifically, the correlation coefficients between soiling and particulate matter range between 70% and less than 20%, depending on the interpolation methods and monitoring distance. Spatial interpolation methods based on inverse distance weighting are found to return better correlations than a nearest neighbor or a simple average approach, especially when large distances are considered. Similarly, the effects of different rain thresholds used to calculate the length of the dry periods are examined. An enhanced two-variable regression is found to achieve higher-quality correlations, with adjusted R2 of 90% (RMSE = 0.55%), also suggesting that high and low soiling locations might be differentiated depending on fixed particulate matter or rainfall thresholds.

14 SOLAR ENERGY↗
DOE OSTI2017

Forward Model Parameter Estimation and Inversion in the Presence of Correlated Measurements

The technical report by Johannesson et al. discussed the case of one quantity being extracted from an air pressure or a seismic time profile. Suppose that we now measure several quantities from each of these profiles. While the seismic measurements are still assumed to be independent from the air pressure measurements, the multiple quantities from a given time profile are potentially correlated. For example, for the air pressure data, the original quantity measured and used in the inference about the explosion yield and HOB/DOB was the integral of the air pressure profile in a certain time interval, but we can also measure the peak air pressure value as an additional source of information in the inverse modeling. The seismic quantity considered in the technical report was the vertical displacement of the first P arrival, but other kinds of seismic measurements can be extracted from the seismic profile and can be potentially useful when inferring the yield and HOB/DOB. In the present document, we limit the discussion to the case of just two correlated measurements for a given data type (air pressure or seismic) as it is computationally easier to handle, but in the future we plan to generalize this to three or more such measurements.

58 GEOSCIENCES↗
DOE OSTI2023

H 0 = 69.8 ± 1.3 km s - 1 Mpc - 1 , Ω m 0 = 0.288 ± 0.017 , and other constraints from lower-redshift, non-CMB, expansion-rate data

Here, we use updated Type Ia Pantheon+ supernova, baryon acoustic oscillation, and Hubble parameter (now also accounting for correlations) data, as well as new reverberation-measured C $\tiny{IV}$ quasar data, and quasar angular size, H $\tiny{II}$ starburst galaxy, reverberation-measured Mg $\tiny{II}$ quasar, and Amati correlated gamma-ray burst data to constrain cosmological parameters. We show that these data sets result in mutually consistent constraints and jointly use them to constrain cosmological parameters in six different spatially-flat and non-flat cosmological models. Our analysis provides summary model independent determinations of two key cosmological parameters: the Hubble constant, H 0 = 69.8 ± 1.3 km s -1 Mpc -1 , and the current non-relativistic matter density parameter, Ω m0 = 0.288 ± 0.017. Our summary error bars are 2.4 and 2.3 times those obtained using the flat ΛCDM model and Planck TT,TE,EE + lowE + lensing cosmic microwave background (CMB) anisotropy data. Our H 0 value is very consistent with that from the local expansion rate based on the Tip of the Red Giant Branch and Type Ia supernova (SN Ia) data, is 2σ lower than that from the local expansion rate based on Cepheid and SN Ia data, and is 2σ higher than that in the flat ΛCDM model based on Planck TT,TE,EE + lowE + lensing CMB data. Our data compilation shows at most mild evidence for non-flat spatial hypersurfaces, but more significant evidence for dark energy dynamics, 2σ or larger in the spatially-flat dynamical dark energy models we study.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1988

An analysis of the shapes of ultraviolet extinction curves. II - The far-UV extinction

In this paper the properties of interstellar extinction in the far-ultraviolet region are examined utilizing IUE extinction curves for a primary data sample of 45 reddened Milky Way OB stars. These results are combined with those derived for the 2175 A bump in a previous study. It is found that IUE extinction curves can be represented by linear combinations of a Lorentzian-like 2175 A bump profile, a well-determined FUV curvature term, and an underlying linear component. The parameters of the linear component are strongly correlated and therefore only five free parameters are required to fit all of the curves in our sample. Three parameters describe the 2175 A bump, one parameter describes the linear background, and one parameter describes the strength of the FUV curvature term. The shape of the FUV curvature is found to be identical, to within the observational errors, for all the curves in the sample - which spans virtually the entire range of extinction curve morphologies observed in the Milky Way.

Fitzpatrick, Edward L.↗
DOE OSTI2017

Utility usage forecasting

The computer creates a utility demand forecast model for weather parameters by receiving a plurality of utility parameter values, wherein each received utility parameter value corresponds to a weather parameter value. Determining that a range of weather parameter values lacks a sufficient amount of corresponding received utility parameter values. Determining one or more utility parameter values that corresponds to the range of weather parameter values. Creating a model which correlates the received and the determined utility parameter values with the corresponding weather parameters values.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

Parametric Thermal Soak Model for Earth Entry Vehicles

The analysis and design of an Earth Entry Vehicle (EEV) is multidisciplinary in nature, requiring the application many disciplines. An integrated tool called Multi Mission System Analysis for Planetary Entry Descent and Landing or M-SAPE is being developed as part of Entry Vehicle Technology project under In-Space Technology program. Integration of a multidisciplinary problem is a challenging task. Automation of the execution process and data transfer among disciplines can be accomplished to provide significant benefits. Thermal soak analysis and temperature predictions of various interior components of entry vehicle, including the impact foam and payload container are part of the solution that M-SAPE will offer to spacecraft designers. The present paper focuses on the thermal soak analysis of an entry vehicle design based on the Mars Sample Return entry vehicle geometry and discusses a technical approach to develop parametric models for thermal soak analysis that will be integrated into M-SAPE. One of the main objectives is to be able to identify the important parameters and to develop correlation coefficients so that, for a given trajectory, can estimate the peak payload temperature based on relevant trajectory parameters and vehicle geometry. The models are being developed for two primary thermal protection (TPS) materials: 1) carbon phenolic that was used for Galileo and Pioneer Venus probes and, 2) Phenolic Impregnated Carbon Ablator (PICA), TPS material for Mars Science Lab mission. Several representative trajectories were selected from a very large trade space to include in the thermal analysis in order to develop an effective parametric thermal soak model. The selected trajectories covered a wide range of heatload and heatflux combinations. Non-linear, fully transient, thermal finite element simulations were performed for the selected trajectories to generate the temperature histories at the interior of the vehicle. Figure 1 shows the finite element model that was used for the simulations. The results indicate that it takes several hours for the thermal energy to soak into the interior of the vehicle and achieve maximum payload temperatures. In addition, a strong correlation between the heatload and peak payload container temperature is observed that will help establishing the parametric thermal soak model.

Agrawal, Parul↗
NASA NTRS1983

Correlation methods

A method for processing complex radar data with a computer using correlation functions is reviewed. Parameters including data storage, data reduction, and real time operation are addressed. Since complex auto- and cross-correlation functions are calculated and stored, almost no information is lost. These also can be analyzed in terms of the full correlation analysis of the spaced-antenna-drifts technique. The proposed approach therefore appears to be very feasible to suit most Mesosphere-Stratosphere-Troposphere (MST) radar applications.

Rottger, J.↗
DOE OSTI2020

Understanding the chemical contribution to the enhancement mechanism in SERS: Connection with Hammett parameters

The enhancement mechanism due to the molecule-surface chemical interaction in surface-enhanced Raman scattering (SERS) has been characterized using a theoretical approach based on time dependent density functional theory. This includes a systematic study of the chemical mechanism (CM) to the SERS enhancement for halogen substituted benzenethiols interacting with a silver cluster. Changing the halogen on benzenethiol enables us to systematically modulate interactions between the benzenethiol ring and the metal cluster. We observe a decrease in the CM enhancement factor with an increase in atomic number of the halogen for para- substitutions. For meta- substitutions, there is no such trend. However, the results scale linearly with the Hammett parameters for both meta and para halogens, which provides an important predictive tool for interpreting chemical enhancements. We also study the effect of solvation on the CM, showing that there is a systematic increase in enhancement with increasing solvent dielectric constant. As a result, the correlation of CM with other properties, such as the amount of charge transfer between adsorbate and metal, or the excitation energies of charge transfer states, is much less predictive than the Hammett parameter correlation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Inferring colloidal interaction from scattering by machine learning

A machine learning solution for the potential inversion problem in elastic scattering is outlined. The inversion scheme consists of two major components, a generative network featuring a variational autoencoder which extracts the targeted static two-point correlation functions from experimentally measured scattering cross sections, and a Gaussian process framework which probabilistically infers the relevant structural parameters from the inverted correlation functions. Via a case study of charged colloidal suspensions, the feasibility of this approach for quantitative study of molecular interaction is critically benchmarked and its merit over existing deterministic approaches, in terms of numerical accuracy and computationally efficiency, is demonstrated.

36 MATERIALS SCIENCE↗
NASA NTRS1975

The effects of correlation on goodness of fit

Autocorrelated normal random variates were generated via computer and the effects of various levels of correlation on goodness of fit problems were studied. The results are useful in determining the distribution or estimating the parameters of populations that correlate observations such as wind speeds and temperature. The model used to generate the autocorrelated data is an autoregressive process of order 1. The Kolmogorov-Smirnov and chi-square statistics are used in the analysis. It was observed in the simulation that high positive correlations tend to shift the sample mean away from the population mean and negative correlations tend to shift the sample mean towards the population mean. In many cases, it was observed that positive and negative correlations tend to decrease the standard deviation. However, since this did not occur in all cases, no definite conclusion can be made regarding the standard deviation. Since the autoregressive process is a linear transformation, it is not surprising that normality was preserved. However, a possible extension of this problem could be to generate non-normal data and observe how the distribution is affected by correlation. Another extension might utilize another model such as autoregressive of order k or a moving average process of order k.

Kitchens, L. J.↗
NASA NTRS1991

Electrostatic potential jump across fast-mode collisionless shocks

The electrostatic potential jump across fast-mode collisionless shocks is examined by comparing published observations, hybrid simulations, and a simple model, in order to better characterize its dependence on the various shock parameters. In all three, it is assumed that the electrons can be described by an isotropic power-law equation of state. The observations show that the cross-shock potential jump correlates well with the shock strength but shows very little correlation with other shock parameters. Assuming that the electrons obey an isotropic power law equation of state, the correlation of the potential jump with the shock strength follows naturally from the increased shock compression and an apparent dependence of the power law exponent on the Mach number which the observations indicate. It is found that including a Mach number dependence for the power law exponent in the electron equation of state in the simple model produces a potential jump which better fits the observations. On the basis of the simulation results and theoretical estimates of the cross-shock potential, it is discussed how the cross-shock potential might be expected to depend on the other shock parameters.

Mandt, M. E.↗
NASA NTRS2010

Simulation and Flight Evaluation of a Parameter Estimation Input Design Method for Hybrid-Wing-Body Aircraft

As part of an effort to improve emissions, noise, and performance of next generation aircraft, it is expected that future aircraft will make use of distributed, multi-objective control effectors in a closed-loop flight control system. Correlation challenges associated with parameter estimation will arise with this expected aircraft configuration. Research presented in this paper focuses on addressing the correlation problem with an appropriate input design technique and validating this technique through simulation and flight test of the X-48B aircraft. The X-48B aircraft is an 8.5 percent-scale hybrid wing body aircraft demonstrator designed by The Boeing Company (Chicago, Illinois, USA), built by Cranfield Aerospace Limited (Cranfield, Bedford, United Kingdom) and flight tested at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California, USA). Based on data from flight test maneuvers performed at Dryden Flight Research Center, aerodynamic parameter estimation was performed using linear regression and output error techniques. An input design technique that uses temporal separation for de-correlation of control surfaces is proposed, and simulation and flight test results are compared with the aerodynamic database. This paper will present a method to determine individual control surface aerodynamic derivatives.

Taylor, Brian R.↗
DOE OSTI2020

A Lagrangian perturbation theory in the presence of massive neutrinos

We develop a Lagrangian Perturbation Theory (LPT) framework to study the clustering of cold dark matter (CDM) in cosmologies with massive neutrinos. We follow the trajectories of CDM particles with Lagrangian displacements fields up to third order in perturbation theory. Once the neutrinos become non-relativistic, their density fluctuations are modeled as being proportional to the CDM density fluctuations, with a scale-dependent proportionality factor. This yields a gravitational back-reaction that introduces additional scales to the linear growth function, which is accounted for in the higher order LPT kernels. Through non-linear mappings from Eulerian to Lagrangian frames, we ensure that our theory has a well behaved large scale behavior free of unwanted UV divergences, which are common when neutrino and CDM densities are not treated on an equal footing, and in resummation schemes that manifestly break Galilean invariance. We use our theory to construct correlation functions for both the underlying matter field, as well as for biased tracers using ConvolutionLPT. Redshift-space distortions effects are modeled using the Gaussian Streaming Model. When comparing our analytical results to simulated data from the Quijote 1 simulation suite, we find good accuracy down to r = 20 Mpc h -1 at redshift z = 0.5, for the real space and redshift space monopole particle correlation functions with no free parameters. The same accuracy is reached for the redshift space quadrupole if we additionally consider an effective field theory parameter that shifts the pairwise velocity dispersion. For modeling the correlation functions of tracers we adopt a simple Lagrangian biasing scheme with only density and curvature operators, which we find sufficient to reach down to r = 20 Mpc h -1 when comparing to simulated halos.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

Water quality by photographic analysis

Positive correlation exists between reflectance of water and the water quality parameter of turbidity. This relationship holds for all times for a particular waste. At particular times other parameters such as suspended solids correlate to turbidity and can also be mapped. To analyze aerial photos properly to obtain water reflectance, a standard reflectance panel is needed somewhere in the frame. For this study color and color-infrared film are used and analyzed with a color microdensitometer which, with certain modifications, is also used to analyze reflectance of water samples. Noise in the analysis includes bottom effects, reflection from the air-water interface, and path luminance, but these can all be dealt with by proper techniques.

Klooster, S. A.↗
NASA NTRS2011

The Impacts of an Observationally-Based Cloud Fraction and Condensate Overlap Parameterization on a GCM's Cloud Radiative Effect

It has been shown that the details of how cloud fraction overlap is treated in GCMs has substantial impact on shortwave and longwave fluxes. Because cloud condensate is also horizontally heterogeneous at GCM grid scales, another aspect of cloud overlap should in principle also be assessed, namely the vertical overlap of hydrometeor distributions. This type of overlap is usually examined in terms of rank correlations, i.e., linear correlations between hydrometeor amount ranks of the overlapping parts of cloud layers at specific separation distances. The cloud fraction overlap parameter and the rank correlation of hydrometeor amounts can be both expressed as inverse exponential functions of separation distance characterized by their respective decorrelation lengths (e-folding distances). Larger decorrelation lengths mean that hydrometeor fractions and probability distribution functions have high levels of vertical alignment. An analysis of CloudSat and CALIPSO data reveals that the two aspects of cloud overlap are related and their respective decorrelation lengths have a distinct dependence on latitude that can be parameterized and included in a GCM. In our presentation we will contrast the Cloud Radiative Effect (CRE) of the GEOS-5 atmospheric GCM (AGCM) when the observationally-based parameterization of decorrelation lengths is used to represent overlap versus the simpler cases of maximum-random overlap and globally constant decorrelation lengths. The effects of specific overlap representations will be examined for both diagnostic and interactive radiation runs in GEOS-5 and comparisons will be made with observed CREs from CERES and CloudSat (2B-FLXHR product). Since the radiative effects of overlap depend on the cloud property distributions of the AGCM, the availability of two different cloud schemes in GEOS-5 will give us the opportunity to assess a wide range of potential cloud overlap consequences on the model's climate.

Oreopoulos, Lazaros↗
NASA NTRS2011

Flight Test of Orthogonal Square Wave Inputs for Hybrid-Wing-Body Parameter Estimation

As part of an effort to improve emissions, noise, and performance of next generation aircraft, it is expected that future aircraft will use distributed, multi-objective control effectors in a closed-loop flight control system. Correlation challenges associated with parameter estimation will arise with this expected aircraft configuration. The research presented in this paper focuses on addressing the correlation problem with an appropriate input design technique in order to determine individual control surface effectiveness. This technique was validated through flight-testing an 8.5-percent-scale hybrid-wing-body aircraft demonstrator at the NASA Dryden Flight Research Center (Edwards, California). An input design technique that uses mutually orthogonal square wave inputs for de-correlation of control surfaces is proposed. Flight-test results are compared with prior flight-test results for a different maneuver style.

Taylor, Brian R.↗
DOE OSTI2024

Enhancing 2‐Pyrone Synthase Efficiency by High‐Throughput Mass‐Spectrometric Quantification and In Vitro/In Vivo Catalytic Performance Correlation

Abstract Engineering efficient biocatalysts is essential for metabolic engineering to produce valuable bioproducts from renewable resources. However, due to the complexity of cellular metabolic networks, it is challenging to translate success in vitro into high performance in cells. To meet such a challenge, an accurate and efficient quantification method is necessary to screen a large set of mutants from complex cell culture and a careful correlation between the catalysis parameters in vitro and performance in cells is required. In this study, we employed a mass‐spectrometry based high‐throughput quantitative method to screen new mutants of 2‐pyrone synthase (2PS) for triacetic acid lactone (TAL) biosynthesis through directed evolution in E. coli . From the process, we discovered two mutants with the highest improvement (46 fold) in titer and the fastest k cat (44 fold) over the wild type 2PS, respectively, among those reported in the literature. A careful examination of the correlation between intracellular substrate concentration, Michaelis‐Menten parameters and TAL titer for these two mutants reveals that a fast reaction rate under limiting intracellular substrate concentrations is important for in‐cell biocatalysis. Such properties can be tuned by protein engineering and synthetic biology to adopt these engineered proteins for the maximum activities in different intracellular environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗