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DOE OSTI2025

A Life Cycle Analysis Framework for Point Source Capture Systems

NETL studies the costs and benefits of PSC for electricity, industry, and mobile applications. Mobile point source capture (MPSC) and storage applied to freight modes captures emissions directly from exhaust. This poster presents a framework for conducting LCA of PSC systems applied to heavy-duty trucks, freight trains, and marine vessels. The framework defines a wheels-to-storage (gate-to-grave) boundary, including energy demands (electricity, heat, and cooling requirements), solvent use and cycling, onboard system components, carbon storage in a saline aquifer, and upstream manufacturing impacts for equipment, with a suggested functional unit of 1 tonne-km. Potential data sources for analysis include material, energy, and operational data from Oak Ridge National Laboratory, GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model, and scientific literature. The suggested analytical approach includes comparison to publicly available business-as-usual systems without capture across all modes of transportation, sensitivity to composition of the capture solvent, and sensitivity to capture rate variation, all of which would support a wholistic PSC business case analysis. For future consideration, analysis can be augmented with consideration of different sources of electricity (e.g., nuclear), fuel substitution, deploying supportive infrastructure such as pipeline offloading points, and downstream applications like enhanced oil recovery (EOR).

life cycle analysis (LCA)↗

DOE OSTI2018

An automated, high-throughput method for standardizing image color profiles to improve image-based plant phenotyping

High-throughput phenotyping has emerged as a powerful method for studying plant biology. Large image-based datasets are generated and analyzed with automated image analysis pipelines. A major challenge associated with these analyses is variation in image quality that can inadvertently bias results. Images are made up of tuples of data called pixels, which consist of R, G, and B values, arranged in a grid. Many factors, for example image brightness, can influence the quality of the image that is captured. These factors alter the values of the pixels within images and consequently can bias the data and downstream analyses. Here, we provide an automated method to adjust an image-based dataset so that brightness, contrast, and color profile is standardized. The correction method is a collection of linear models that adjusts pixel tuples based on a reference panel of colors. We apply this technique to a set of images taken in a high-throughput imaging facility and successfully detect variance within the image dataset. In this case, variation resulted from temperature-dependent light intensity throughout the experiment. Using this correction method, we were able to standardize images throughout the dataset, and we show that this correction enhanced our ability to accurately quantify morphological measurements within each image. We implement this technique in a high-throughput pipeline available with this paper, and it is also implemented in PlantCV.

47 OTHER INSTRUMENTATION↗

NASA NTRS2009

Systematics in the Electron Spectrum Measured by ATIC

An analysis of different parameters to separate electrons from protons in the ATIC experiment has been performed. Five separate discriminants were studied by different Monte Carlo programs, leading to a variety of results. Application to the ATIC data indicates the range of variation possible in the interpretation of the data. The results of this analysis, when compared with the published results [5], show good agreement in the most interesting region of energy (from 90 GeV to 600 GeV). The measured electron spectrum is compared with the recent data reported by Fermi/LAT, and there is no major disagreement between ATIC s results and Fermi/LAT. Finally, possible systematics-free, short energy scale features of the ATIC electron spectrum are mentioned. Keywords: ATIC, electron spectrum, fine structure

Panov, A. D.↗

DOE OSTI2017

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42 x compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines.

Biochemistry & Molecular Biology↗

NASA NTRS2017

Re-Organizing Earth Observation Data Storage to Support Temporal Analysis of Big Data

The Earth Observing System Data and Information System archives many datasets that are critical to understanding long-term variations in Earth science properties. Thus, some of these are large, multi-decadal datasets. Yet the challenge in long time series analysis comes less from the sheer volume than the data organization, which is typically one (or a small number of) time steps per file. The overhead of opening and inventorying complex, API-driven data formats such as Hierarchical Data Format introduces a small latency at each time step, which nonetheless adds up for datasets with O(10^6) single-timestep files. Several approaches to reorganizing the data can mitigate this overhead by an order of magnitude: pre-aggregating data along the time axis (time-chunking); storing the data in a highly distributed file system; or storing data in distributed columnar databases. Storing a second copy of the data incurs extra costs, so some selection criteria must be employed, which would be driven by expected or actual usage by the end user community, balanced against the extra cost.

data storage↗

DOE OSTI2021

A Spatially Explicit Individual-Based Modeling Approach to Evaluate the Cumulative Effects of Wind Energy Development on the Greater Sage-Grouse: Sensitivity Analysis and Validation of Key Parameters

To address the need for an approach to evaluate cumulative ecological impacts of wind energy development, particularly those on critical wildlife habitats and species, the authors developed a proof-of-concept, landscape-based, spatially explicit individual-based modeling (IBM) framework for populations of the greater sage-grouse (Centrocercus urophasianus) in Albany County, Wyoming, based on published and other available information on the life history of the species. This sage-grouse IBM estimates the spatial and temporal movements of sage-grouse based on modeled effects of habitat characteristics and developments on sage-grouse condition, survivorship, and reproduction. After completing the initial version of the model, we conducted a series of sensitivity analyses of key model parameters and validation of lek occurrences and spatial distributions to better understand performance of the model relative to observed values of important life history characteristics. The parameter sensitivity analysis was conducted as a series of one-factor-at-a-time tests in which the values of selected parameters were individually varied to evaluate the corresponding effects on model output. We examined the model’s response to changes in parameter values to gain insight into the overall robustness of the model, identify key driver parameters, and initiate qualitative validation. Five functions selected for sensitivity analyses were (1) the rate of change in body condition in relationship to habitat suitability index (HSI) of occupied habitat (condition change rate), (2) the effect of competition between individuals with overlapping home ranges expressed as a percentage reduction in HSI (competition factor), (3) value of condition at which survivorship probability is equal to zero (zero survivorship condition), (4) the relationship between female body condition and clutch size, and (5) the relationship between female body condition and nest success. We varied the parameter values to be tested for the sensitivity analysis around the original value used in the model (i.e., tested values were higher and lower than the model’s original value) to examine the effect of this variation on the predicted output of the model. Model outputs evaluated in the sensitivity analysis included (1) predicted age-class distribution (as measured by the percentage of immature individuals within the population); (2) predicted sex ratio; (3) predicted age-sex class distribution (percent of population in each of six age-sex classes, i.e., male and female juveniles, yearlings, and adults); (4) lifespan; (5) population size; and (6) spatial distribution. Of the five parameters analyzed, condition change rate, survivorship, clutch size, and nest success did not substantially affect any of the evaluated model outputs. For the predicted age-class distribution, the percentage of immature individuals predicted by the model for these four parameters ranged from 61.9% to 65.0%, which was reasonable with respect to the reference values of 51.4 to 57.8% in published studies. The ratio of females to males ranged from 1.09 to 1.14, which was comparable to the reference values of 1.2 to 3.0 presented in an existing study. The predicted mean lifespan ranged from 1.62 to 1.74 years, which appears to be reasonable with respect to the reference values of 0.9 to 1.1 years for sharp-tail grouse and greater prairie chickens presented by published studies. The predicted population size ranged from 1,877 to 3,140. This prediction would be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county. The predicted spatial distribution was not substantially affected by the parameter values examined. In our sensitivity analyses, the only tested parameter that had a noticeable effect on model output was competition factor. Over the range of values tested for this parameter, predicted population size exhibited the largest range (from 1,833 to 4,737) of all parameters tested. As the competition factor increased, the predicted population size decreased. This reflects the effect competition had on the number of individuals that could co occur in high-quality habitat patches. Despite this apparently significant effect, the range of values appears to be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county.

17 WIND ENERGY↗

DOE OSTI2016

EVIDENCE FOR PERIODICITY IN 43 YEAR-LONG MONITORING OF NGC 5548

We present an analysis of 43 years (1972 to 2015) of spectroscopic observations of the Seyfert 1 galaxy NGC 5548. This includes 12 years of new unpublished observations (2003 to 2015). We compiled about 1600 H β spectra and analyzed the long-term spectral variations of the 5100 Å continuum and the H β line. Our analysis is based on standard procedures, including the Lomb–Scargle method, which is known to be rather limited to such heterogeneous data sets, and a new method developed specifically for this project that is more robust and reveals a ∼5700 day periodicity in the continuum light curve, the H β light curve, and the radial velocity curve of the red wing of the H β line. The data are consistent with orbital motion inside the broad emission line region of the source. We discuss several possible mechanisms that can explain this periodicity, including orbiting dusty and dust-free clouds, a binary black hole system, tidal disruption events, and the effect of an orbiting star periodically passing through an accretion disk.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1982

The periodic variation of spokes in Saturn's rings

The discovery of a periodic variation in spoke activity in Saturn's rings from the analysis of Voyager images is reported. A Fourier power spectrum was computed using a data set generated by quantifying spoke activity observed on the morning (western) half of the rings in Voyager images spanning 5.5 days (about 12 Saturn rotations). A peak approximately 14 sigma above the noise in the frequency domain was found at a period of 621 + or - 22 min. Within the formal error, this value is consistent with the 639.4-min rotation period of Saturn's magnetic field. Maximum spoke activity is most likely to be observed on the morning half of the rings when a particular magnetic field sector coincides with this area. This magnetic sector contains the region which is aligned with local noon at the time of the emission of the SKR (Saturn kilometric radiation). These results suggest that the fundamental period of spoke variation is that of Saturn's magnetic field, and that spoke activity is associated with the region of the field which gives rise to the SKR. Passage of this region through Saturn's shadow may play a significant role in the creation and/or rejuvenation of spokes.

Porco, C. C.↗

NASA NTRS1985

Temporal characteristics of the solar UV flux and He I line at 1083 nm

It is pointed out that the solar UV flux in the 170- to 210-nm range is important because it photodissociates O2 in the terrestrial atmosphere and thereby initiates the production of ozone and other odd-oxygen chemistry in the stratosphere. The 210- to 290-nm solar UV flux heats the stratosphere. There is consequently a great interest in the temporal variations of the solar UV flux and its relation to ground-based measures of solar activity which may be useful in estimating the UV flux variations. The present investigation is concerned with daily values of 205-nm solar UV flux data measured with the aid of the Nimbus 7 satellite during the period from November 1978 to November 1982, taking into account also measurements of the equivalent width of the He I solar absorption line at 1083 at the National Solar Observatory. Attention is given to an analysis of the data, episodes of activity, and long-term variations.

Donnelly, R. F.↗

DOE OSTI2017

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems]

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whose sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.

42 ENGINEERING↗

NASA NTRS1977

The effects of the atmospheric point-spread 'seeing' function on spatially resolved spectra of Jupiter

We present the results of an analysis of the effects of atmospheric seeing and of instrumental spectral and spatial resolution on the observed variation of absorption-line profiles across the disk of Jupiter. The technique described may be applied equally well to the analysis of observations of any extended astronomical source. These results show the necessity of obtaining accurate point-spread-function information during the course of observations of this nature. We also point out that in order to avoid the uncertainties and ambiguities inherent in attempts at deconvolution of observational data, one must properly convolve the appropriate spatial and spectral resolution functions with the models being tested and then compare the results with the observational data.

Gelfand, J.↗

NASA NTRS1991

Spacecraft design optimization using Taguchi analysis

The quality engineering methods of Dr. Genichi Taguchi, employing design of experiments, are important statistical tools for designing high quality systems at reduced cost. The Taguchi method was utilized to study several simultaneous parameter level variations of a lunar aerobrake structure to arrive at the lightest weight configuration. Finite element analysis was used to analyze the unique experimental aerobrake configurations selected by Taguchi method. Important design parameters affecting weight and global buckling were identified and the lowest weight design configuration was selected.

Unal, Resit↗

DOE OSTI2025

Solar cities: A case study analysis of city-level enablers of expanded solar energy access

Rooftop solar photovoltaic (PV) adoption can benefit households by reducing electricity bills and enhancing energy resiliency. Low and moderate-income (LMI) households have been less likely to adopt PV and experience these benefits in the United States than higher-income households. Adopter income trends are often explored through quantitative analysis with limited explanatory power. Our quantitative analysis only explains around one-third of city-level variation in LMI adoption trends through socioeconomic factors such as median home values and income inequality and PV market factors such as cumulative adoption and incentives. We implement semi-structured interviews in three case studies of cities with relatively high rates of LMI PV adoption to better understand the factors that explain PV adopter income trends. The case studies partly reiterate findings from quantitative analysis, such as the role of PV incentives. The case studies reveal a broader set of LMI adoption drivers that are missed in quantitative analyses. The case studies show how city contexts can affect LMI adoption, such as the role of supportive city governments. The case studies also reveal the importance of partnerships, such as partnerships between city governments and state LMI PV program implementers. Finally, interviewees emphasized the importance of building trust among prospective LMI PV adopters. Interviewees suggested that partnerships, outreach, and consumer protection measures were crucial to building trust in PV installers among LMI households.

Adoption↗

NASA NTRS1985

Fabrication and analysis of dot junction silicon solar cells

A design of solar cells with reduced junction area on the cell surface is investigated for reduction of saturation current and increase in open-circuit voltage. Equidiameter dot junctions distributed across the surface of the cell offer an efficient alternative, with variations in dot diameter and in the spacing between dots giving the required variations in the ratio of junctions area to total surface area. A simplified analysis for short-circuit current and other cell parameters, which enables cell design optimization, is presented. Efficiencies beyond 18 percent are obtainable in flat-plate terrestrial applications. Experimental solar-cell performance results, as functions of different area ratios, and bulk doping are presented. It is shown that saturation current reduction and open-circuit voltage increase is obtained by reduced junction area.

Crotty, G. T.↗

NASA NTRS2014

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a generalized stability metric for time-varying loop=gain perturbations is needed for the AAC.

VanZwieten, Tannen↗

DOE OSTI2022

Unsupervised learning of ferroic variants from atomically resolved STEM images

An approach for the analysis of atomically resolved scanning transmission electron microscopy data with multiple ferroic variants in the presence of imaging non-idealities and chemical variabilities based on a rotationally invariant variational autoencoder (rVAE) is presented. We show that an optimal local descriptor for the analysis is a sub-image centered at specific atomic units, since materials and microscope distortions preclude the use of an ideal lattice as a reference point. The applicability of unsupervised clustering and dimensionality reduction methods is explored and is shown to produce clusters dominated by chemical and microscope effects, with a large number of classes required to establish the presence of rotational variants. Comparatively, the rVAE allows extraction of the angle corresponding to the orientation of ferroic variants explicitly, enabling straightforward identification of the ferroic variants as regions with constant or smoothly changing latent variables and sharp orientational changes. This approach allows further exploration of the chemical variability by separating the rotational degrees of freedom via rVAE and searching for remaining variability in the system. The code used in this article is available at https://github.com/saimani5/ferroelectric_domains_rVAE.

30 DIRECT ENERGY CONVERSION↗

NASA NTRSDate not supplied

Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing

Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters related to grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed. Through GSA, the most important input parameters are identified based on their influence on the statistical distributions of microstructural metrics that influence mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on what experiments are necessary to quantify and control PSP uncertainties, particularly those associated with the more challenging input parameters.

additive manufacturing↗

NASA NTRS2002

Study of Tropospheric Ozone and UV Reflectivity Using TOMS Data

Perhaps the single most important result from the study of Chuang and Yung is that the interannual variability of the Earth's albedo (especially in Spring) on land is dominated by snow/ice, and not by clouds. This interannual variability could be the major driver of changes in the atmosphere and the biosphere. It is plausible that the interannual variability of snow/ice, through interactions with the atmosphere and biosphere, is responsible for the interannual variability of atmospheric CO2. By carefully studying the albedo variations off the Peru coast, we found evidence for indirect aerosol effect on clouds. Based on a detailed analysis of the cloud data obtained by the International Satellite Cloud Climatology Project (SCCP) in the years 1983-1991, we show that besides the reported 3 % variation in global cloudiness, the global mean cloud optical thickness (MCOT) also has significant variation which is out of phase with that of the global cloudiness. The combined effect of the two opposing variations may be a null effect on the cloud reflectivity. These results are consistent with the Total Ozone Mapping Spectrometer (TOMS) reflectively measurements. The MCOT variation is further shown to be correlated with both the solar cycle and the ENSO (El Nino Southern Oscillation) cycle. Our present analysis cannot distinguish which of the above two provides better correlation, although independent data from the High resolution Infrared Radiation Sounder (HIRS) from 1990 to 1996 favor the solar cycle. Future data are needed to identify the true cause of these changes.

Yung, Yuk L.↗