Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “variability analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Using Distributed Fiber-optic Strain Sensing to Estimate Generalized Modal Coordinates from Flight-test Data

Background and Motivation - Problem - Contemporary aircraft carry around structural mass so that the flutter instabilities lie well outside of the operational envelope. - Better methods of measuring the structural state could allow reduction of the extra structural weight - Modal filtering - Standard method in structural analysis - Deformations are a combination of mode shapes - Modal filtering is estimating these modal coordinates from data - Often ordinary least squares methods - Often applied to simpler test articles - Factor Analysis - Analysis method from psychology - Measurements are a combination of small number of unmeasurable variables. - Lessons from factor analysis can be adapted to improve the modal filtering methods

Jeffrey Ouellette↗
NASA NTRS1994

Analysis of a 7 year tropospheric ozone vertical distribution at the Observatoire de Haute Provence

A seven year (1984-90) climatology of tropospheric vertical ozone soundings, performed by electrochemical sondes at the OHP (44 deg N, 6 deg E, 700 m ASL) in Southern France, is presented. Its seasonal variation shows a broad spring/summer maximum in the troposphere. The contribution of photochemical ozone production and transport from the stratosphere to this seasonal variation are studied by a correlative analysis of ozone concentrations and meteorological variables, with emphasis on potential vorticity. This analysis shows the impact of dynamical and photochemical processes on the spatial and temporal ozone variability. In particular, a positive correlation (r = 04.0, significance greater than 99.9 percent) of ozone with potential vorticity is observed in the middle troposphere, reflecting the impact of stratosphere-troposphere exchange on the vertical ozone distribution.

Beekmann, Matthias↗
NASA NTRS1987

A search for RR Lyrae variables in NGC 147

An analysis of repeated deep CCD observations of a field in the Local Group dwarf elliptical galaxy NBC 147 has resulted in the detection of 34 variable stars. The periods and shapes of light curves obtained for 13 of these variables show nine of them to be RR Lyrae stars. An intensity-averaged phase-weighted-mean g magnitude of 25.15 (+ 0.17 or - 0.15) is found which indicates a distance modulus to NGC 147 of 23.85 (+ 0.22 or - 0.20), or 589 kpc.

Saha, A.↗
DOE OSTI2021

An efficient method to identify uncertainties of WRF-Solar variables in forecasting solar irradiance using a tangent linear sensitivity analysis

Uncertainty in predicting solar energy resources introduces major challenges in power system management and necessitates the development of reliable probabilistic solar forecasts. As the first part of the development of probabilistic forecasts based on the Weather Research and Forecasting model with solar extensions (WRF-Solar), this study presents a tangent linear approach to identify input variables responsible for the largest uncertainties in predicting surface solar irradiance and clouds. A tangent linear analysis is capable of efficiently investigating sensitivities of output variables with respect to various input variables of WRF-Solar because this approach avoids the computational burden of perturbing the initial conditions of individual input variables. We develop tangent linear models (TLMs) for six WRF-Solar physics packages that control the formation and dissipation of clouds and solar radiation, and we evaluate the validity of TLMs using a linearity test. The tangent linear sensitivity analysis is conducted under various scenarios based on satellite observations and model simulations to consider realistic input conditions. A simple method is used to quantify the impact of the uncertainty of input variables on the output variables from the TLMs. The results demonstrate that uncertainties in the output variables that are the focus of this study—including global horizontal irradiance, direct normal irradiance, cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes—are highly sensitive to uncertainties in 14 input variables. This study indicates that the tangent linear method can identify key variables of physics modules in WRF-Solar that can be stochastically perturbed to generate ensemble-based probabilistic forecasts.

14 SOLAR ENERGY↗
DOE OSTI2022

Atmospheric teleconnection associated with the Atlantic multidecadal variability in summer: assessment of the CESM1 model

Observational analysis shows that the Atlantic multidecadal variability (AMV) is associated with climate variability in the Northern Hemisphere through a zonal atmospheric teleconnection extending from the North Atlantic Ocean and propagating eastward around the Northern Hemisphere. Here, we studied the fidelity of model simulations in reproducing the observed summer AMV and the associated impacts on the mid-latitude climate by analysing simulations using the National Centre for Atmospheric Research Community Earth System Model Version 1 (CESM1), including CESM1 North Atlantic idealized and pacemaker simulations, CESM1 large ensemble twentieth century uninitialized simulations and large ensemble initialized CESM1 decadal predictions. To further compare the fidelity of CESM1, we also analysed large ensemble simulations from three other models. Our results suggest that the uninitialized large ensemble simulations from all models can produce an AMV time evolution and its regional climate impacts similar to the observations to certain degree. By initializing the observed oceanic condition in decadal prediction simulations, the simulated AMV and its regional impacts are closer to the observed ones than those in uninitialized ensemble simulations. In addition, the pacemaker simulations that nudged the time-evolving observed North Atlantic sea surface temperature anomalies produce spatiotemporal characteristics of the AMV and AMV climate impacts closer to the observed ones than the uninitialized simulations. We conclude that although coupled models can produce AMV and its regional impacts similar to observed, proper initialization and bias correction of the sea surface temperature spatial and temporal structure can improve this capability.

Initialization↗
NASA NTRS1997

Long-term variability in bright hard X-ray sources: 5+ years of BATSE data

The operation of the Compton Gamma Ray Observatory (CGRO)/burst and transient source experiment (BATSE) continues to provide data for inclusion into a data base for the analysis of long term variability in bright, hard X-ray sources. The all-sky capability of BATSE provides up to 30 flux measurements/day for each source. The long baseline and the various rising and setting occultation flux measurements allow searches for periodic and quasi-periodic signals with periods of between several hours to hundreds of days to be conducted. The preliminary results from an analysis of the hard X-ray variability in 24 of the brightest BATSE sources are presented. Power density spectra are computed for each source and profiles are presented of the hard X-ray orbital modulations in some X-ray binaries, together with amplitude modulations and variations in outburst durations and intensities in recurrent X-ray transients.

Robinson, C. R.↗
NASA NTRS1982

Structural tailoring of engine blades (STAEBL)

A mathematical optimization procedure was developed for the structural tailoring of engine blades and was used to structurally tailor two engine fan blades constructed of composite materials without midspan shrouds. The first was a solid blade made from superhybrid composites, and the second was a hollow blade with metal matrix composite inlays. Three major computerized functions were needed to complete the procedure: approximate analysis with the established input variables, optimization of an objective function, and refined analysis for design verification.

Platt, C. E.↗
NASA NTRS1996

Wind Variability in Intermediate Luminosity B Supergiants

This study used the unique spectroscopic diagnostics of intermediate luminosity B supergiants to determine the ubiquity and nature of wind variability. Specifically, (1) A detailed analysis of HD 64760 demonstrated massive ejections into its wind, provided the first clear demonstration of a 'photospheric connection' and ionization shifts in a stellar wind; (2) The international 'IUE MEGA campaign' obtained unprecedented temporal coverage of wind variability in rapidly rotating stars and demonstrated regularly repeating wind features originating in the photosphere; (3) A detailed analysis of wind variability in the rapidly rotating B1 Ib, gamma Ara demonstrated a two component wind with distinctly different mean states at different epochs; (4) A follow-on campaign to the MEGA project to study slowly rotating stars was organized and deemed a key project by ESA/NASA, and will obtain 30 days of IUE observations in May-June 1996; and (5) A global survey of archival IUE time series identified recurring spectroscopic signatures, identified with different physical phenomena. Items 4 and 5 above are still in progress and will be completed this summer in collaboration with Raman Prinja at University College, London.

Massa, Derck↗
NASA NTRS1989

Covariance of greenness and terrain variables over the Konza Prairie

An analysis is made of time-dependent covariance of the greenness vegetation index with mapped terrain variables over the Konza Prarie (Kansas) during the 1987 growing season. The analysis was part of an ongoing project to establish appopriate ground-sampling and data-integration strategies for satellite-based monitoring of land surface climate conditions. Greenness images for six dates between May and October were derived from atmospherically corrected thematic mapper (TM) data and coregistered with maps of woody vegetation, fire, and soils. Local variance in greenness peaked in mid-June, falling rapidly until mid-August, and declining gradually thereafter. Greenness images exhibited positive autocorrelation up to distances of 180-210 m, but the dominant scale of pattern occurred at a block size of 60 m by 60 m throughout the growing season. 40-44 percent of total scene variance in July and August was accounted for by the effects of woody vegetation (8.9 percent of the area), prairie burning, and soil type. The effect of these terrain variables was fairly consistent between June and late August and was manifested as additional high-frequency spatial variation in imagery from that period.

Davis, Frank W.↗
NASA NTRS1981

Evaluation of the Williams-type model for barley yields in North Dakota and Minnesota

The Williams-type yield model is based on multiple regression analysis of historial time series data at CRD level pooled to regional level (groups of similar CRDs). Basic variables considered in the analysis include USDA yield, monthly mean temperature, monthly precipitation, soil texture and topographic information, and variables derived from these. Technologic trend is represented by piecewise linear and/or quadratic functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test (1970-1979) demonstrate that biases are small and performance based on root mean square appears to be acceptable for the intended AgRISTARS large area applications. The model is objective, adequate, timely, simple, and not costly. It consideres scientific knowledge on a broad scale but not in detail, and does not provide a good current measure of modeled yield reliability.

Barnett, T. L.↗
DOE OSTI2022

Offering of Variable Resources in Regulation Markets with Performance Targets: An Analysis

To date, wind and solar power plants have mainly provided energy. Going forward, with the application of appropriate controls, they can offer additional grid services, such as regulating reserves. Additional grid services can present an opportunity for additional value streams to wind and solar power plants. However, the additional value might not be realized when operator-determined performance targets and settlement adjustments for the delivery of regulation capacity are disregarded. Additionally, this article studies the participation of variable resources in centralized regulation markets. We derive analytical results for regulation offers in terms of quantity and price considering that a variable resource does not want to risk being disqualified as a regulation provider, incurring losses, or foregoing more profitable opportunities. Our analysis suggests that U.S. operator-determined performance targets impose an upper bound on the quantity of a variable resource’s regulation offer; and settlement adjustments for the delivery of regulation affect the price at which variable resources offer and the calculations of opportunity costs in case of imperfect regulation delivery.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Multimodal Bayesian registration of noisy functions using Hamiltonian Monte Carlo

Functional data registration is a necessary processing step for many applications. The observed data can be inherently noisy, often due to measurement error or natural process uncertainty; which most functional alignment methods cannot handle. A pair of functions can also have multiple optimal alignment solutions, which is not addressed in current literature. In this paper, a flexible Bayesian approach to functional alignment is presented, which appropriately accounts for noise in the data without any pre-smoothing required. Additionally, by running parallel MCMC chains, the method can account for multiple optimal alignments via the multi-modal posterior distribution of the warping functions. To most efficiently sample the warping functions, the approach relies on a modification of the standard Hamiltonian Monte Carlo to be well-defined on the infinite-dimensional Hilbert space. In this work, this flexible Bayesian alignment method is applied to both simulated data and real data sets to show its efficiency in handling noisy functions and successfully accounting for multiple optimal alignments in the posterior; characterizing the uncertainty surrounding the warping functions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2015

Spatial Variability of Trace Gases During DISCOVER-AQ: Planning for Geostationary Observations of Atmospheric Composition

Results from an in-depth analysis of trace gas variability in MD indicated that the variability in this region was large enough to be observable by a TEMPO-like instrument. The variability observed in MD is relatively similar to the other three campaigns with a few exceptions: CO variability in CA was much higher than in the other regions; HCHO variability in CA and CO was much lower; MD showed the lowest variability in NO2All model simulations do a reasonable job simulating O3 variability. For CO, the CACO simulations largely under over estimate the variability in the observations. The variability in HCHO is underestimated for every campaign. NO2 variability is slightly overestimated in MD, more so in CO. The TX simulation underestimates the variability in each trace gas. This is most likely due to missing emissions sources (C. Loughner, manuscript in preparation).Future Work: Where reasonable, we will use these model outputs to further explore the resolvability from space of these key trace gases using analyses of tropospheric column amounts relative to satellite precision requirements, similar to Follette-Cook et al. (2015).

trace gas↗
DOE OSTI2026

Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories

Non-targeted liquid chromatography tandem highresolution mass spectrometry (LC−MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC−MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and featurebased molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC−MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.

DOM↗
NASA NTRS1972

Material variability as measured by low temperature electrical resistivity.

Low temperature electrical resistivity was used to determine the material variability (1) between different manufacturers, (2) between different heats from the same manufacturer, and (3) within a given heat for Al 2024, Al-5% Mg alloys, Inconel 718, A286 stainless, and AISI 316. Generally, the coefficient of variation for solution annealed alloys ranged from 1.2 to 14% between manufacturers, 0.8 to 5.1% between heats, and 0.1 to 1.6% within a heat with stainless steels at the low ends and Al 2024 at the high ends. The variability is increased if the material is in a precipitation-hardened condition. A statistical analysis suggests that the variability within a heat is non-normal.

Clark, A. F.↗
DOE OSTI2021

Nth-plant supply: corn stover supplies and costs in a fleet of biorefineries

Feedstock cost and cost variability is expected to increase with the number of biorefineries. To quantify this effect, this spatial-economic analysis simulates feedstock cost and cost variability of an industry based on corn stover as a function of the number of biorefineries. Results are reported for nine scenarios (a base case and sensitivity analysis of four variables – harvest efficiency, sustainability constraints, opportunity cost, and corn grain yield) under deterministic and stochastic simulations, assuming biorefineries using 658 000 Mg (725 000 tons) year- 1 of corn stover in 2019. The resulting supply curves are highly elastic (i.e. little change in cost) for the first 50 of the 121 biorefineries, with price increases in subsequent biorefineries depending on scenario. In the base-case deterministic scenario, weighted-average stover costs are $66 Mg -1 ($60 ton- 1 ), $69 Mg -1 ($62 ton -1 ), and $156 Mg -1 ($142 ton -1 ), at the first, 60th, and 121st biorefineries, respectively. The stochastic simulations, subject to observed 30-year corn yield variability, follow a similar pattern, with price distributions that vary by scenario. The base-case stochastic simulations illustrate minimal cost variability for the first 60 biorefineries, but rapid increases in cost variability in the second half of potential biorefineries, with similar patterns observed in the other scenarios. Of the four variables explored, price was most sensitive to harvest efficiency, followed by sustainability constraints, corn yield, and opportunity cost. Results suggest that, under conventional logistics, about half of the US corn stover resource is reliably available with minimum cost increase and variability. Interactive visualization is available at https://doi.org/10.11578/1828779.

09 BIOMASS FUELS↗
DOE OSTI2023

Solution and sensitivity analysis of nonlinear equations using a hypercomplex-variable Newton-Raphson method

Here, the classical Newton-Raphson (NR) method for solving nonlinear equations is enhanced in two ways through the use of hypercomplex variables and algebra. In particular, i) the Jacobian is computed in a highly accurate and automated way, and ii) the derivative of the solution to the nonlinear equations is computed with respect to any parameter contained within the system of equations. These advances provide two significant enhancements in that it is straightforward to provide an accurate Jacobian and to construct a reduced order model (ROM) of arbitrary order with respect to any parameter of the system. The ROM can then be used to approximate the solution for other parameter values without requiring additional solutions of the nonlinear equations. Several case studies are presented including 1D and 2D academic examples with fully functioning Python code provided. Additionally, a case of study of the catenary of an elastic cable subject to its own weight and a vertical point load. Derivatives up to 10th order were computed with respect to material, loading, and geometrical parameters. The derivatives were used to generate reduced order models of the cable deformation and reaction forces at its ends with respect to multiple input parameters. Results show that from a single hypercomplex evaluation of the cable under a single vertical point load, it is possible to generate an accurate reduced order model capable of predicting the cable deformation with 1.5 times the load in the opposite direction and with 3.5 times the load in the same direction without resolving the system of equations.

97 MATHEMATICS AND COMPUTING↗