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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Comprehensive Performance Calibration Guidance for Perovskites and Other Emerging Solar Cells

Emerging photovoltaic (PV) technologies (e.g., organic, perovskite, and solution processed quantum dot) have attracted remarkable attention with the rapid growth of their efficiencies, and their transition toward commercialization. Accurate and reliable efficiency measurements of these PV technologies are crucial, yet much more complicated than for conventional PV technologies due to the former's pronounced dynamic responses to changes in measurement conditions (e.g., current–voltage (I–V) scan rate and preconditioning) and their susceptibility to degradation. Adjustments to the measurement procedures are therefore necessary so that a reproducible “steady state” is reached during measurement. Furthermore, given the small size of many emerging cells, inappropriate device area definition and solar simulator setup can lead to measurement errors. Here, comprehensive efficiency calibration guidance is offered for emerging solar cells, including area measurement; spectral irradiance translation to standard test conditions; and steady-state electrical performance. The necessity of reporting steady-state efficiency is justified with a statistical performance comparison between conventional and steady-state I–V scans over hundreds of cells the group has received globally for efficiency certifications. The procedures described here do not require specialized measurement instrumentation; what matters most are changes to the measurement protocols. These described changes aim to enable better comparisons between reported efficiencies.

14 SOLAR ENERGY↗
DOE OSTI2017

Global reconstructed daily surge levels from the 20th Century Reanalysis (1871–2010)

Studying the effect of global patterns of wind and pressure gradients on the sea level variation (storm surge) is a key issue in understanding the recent climate change effect on the dynamical state of the ocean. The analysis of the spatial and temporal variability of storm surges from observations is a difficult task to accomplish since observations are not homogeneous in time, scarce in space, and moreover, their temporal coverage is limited. A recent global surge database developed by AVISO (DAC, Dynamic Atmospheric Correction) fulfilled the lack of data in terms of spatial coverage, but not regarding time extent, since it only includes the last two decades (1992–2014). In this work, we use the 20th Century Reanalysis V2 (20CR), which spans the years 1871 to 2010, to statistically reconstruct daily maximum surge levels at a global scale. A multivariate linear regression model is fitted between daily mean ERA-interim sea level pressure fields and daily maximum surge levels from DAC. Following, the statistical model is used to reconstruct daily surges using mean sea level pressure fields from 20CR. The verification of the statistical model shows good agreements between DAC levels and the reconstructed surge levels from the 20CR. The validation of the reconstructed surge with tide gauges, distributed throughout the domain, shows good accuracy both in terms of high correlations and small errors. A time series comparison is also depicted at specific tide gauges for the beginning of the 20th century, showing a high concordance. Therefore, this work provides to the scientific community, a daily database of maximum surge levels; which correspond to an extension of the DAC database, from 1871 to 2010. This database can be used to improve the knowledge on historical storm surge conditions, allowing the study of their temporal and spatial variability.

Geology↗
DOE OSTI2013

PRECIOUS METALS IN SDSS QUASAR SPECTRA. I. TRACKING THE EVOLUTION OF STRONG, 1.5 < z < 4.5 C IV ABSORBERS WITH THOUSANDS OF SYSTEMS

We have vastly increased the C IV statistics at intermediate redshift by surveying the thousands of quasars in the Sloan Digital Sky Survey (SDSS) Data-Release 7. We visually verified over 16,000 C IV systems with 1.46 < z < 4.55-a sample size that renders Poisson error negligible. Detailed Monte Carlo simulations show that we are approximately 50% complete down to rest equivalent widths W {sub r} Almost-Equal-To 0.6 A. We analyzed the sample as a whole and in 10 small redshift bins with approximately 1500 doublets each. The equivalent width frequency distributions f(W {sub r}) were well modeled by an exponential, with little evolution in shape. In contrast with previous studies that modeled the frequency distribution as a single power law, the fitted exponential gives a finite mass density for the C IV ions. The comoving line density dN{sub CIV}/dX evolved smoothly with redshift, increasing by a factor of 2.37 {+-} 0.09 from z = 4.55-1.96, then plateauing at dN{sub CIV}/dX{approx}0.34 for z = 1.96-1.46. Comparing our SDSS sample with z < 1 (ultraviolet) and z > 5 (infrared) surveys, we see an approximately 10-fold increase in dN{sub CIV}/dX over z Almost-Equal-To 6 {yields} 0, for W {sub r} {>=} 0.6 A. This suggests a monotonic and significant increase in the enrichment of gas outside galaxies over the 12 Gyr lifetime of the universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE DEMOGRAPHICS OF BROAD-LINE QUASARS IN THE MASS-LUMINOSITY PLANE. II. BLACK HOLE MASS AND EDDINGTON RATIO FUNCTIONS

We employ a flexible Bayesian technique to estimate the black hole (BH) mass and Eddington ratio functions for Type 1 (i.e., broad line) quasars from a uniformly selected data set of {approx}58, 000 quasars from the Sloan Digital Sky Survey (SDSS) DR7. We find that the SDSS becomes significantly incomplete at M {sub BH} {approx}< 3 Multiplication-Sign 10{sup 8} M {sub Sun} or L/L {sub Edd} {approx}< 0.07, and that the number densities of Type 1 quasars continue to increase down to these limits. Both the mass and Eddington ratio functions show evidence of downsizing, with the most massive and highest Eddington ratio BHs experiencing Type 1 quasar phases first, although the Eddington ratio number densities are flat at z < 2. We estimate the maximum Eddington ratio of Type 1 quasars in the observable universe to be L/L {sub Edd} {approx} 3. Consistent with our results in Shen and Kelly, we do not find statistical evidence for a so-called sub-Eddington boundary in the mass-luminosity plane of broad-line quasars, and demonstrate that such an apparent boundary in the observed distribution can be caused by selection effect and errors in virial BH mass estimates. Based on the typical Eddington ratio in a given mass bin, we estimate growth times for the BHs in Type 1 quasars and find that they are comparable to or longer than the age of the universe, implying an earlier phase of accelerated (i.e., with higher Eddington ratios) and possibly obscured growth. The large masses probed by our sample imply that most of our BHs reside in what are locally early-type galaxies, and we interpret our results within the context of models of self-regulated BH growth.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Deep Learning Experiments for Tropical Cyclone Intensity Forecasts

Reducing tropical cyclone (TC) intensity forecast errors is a challenging task that has interested the operational forecasting and research community for decades. To address this, we developed a deep learning (DL)-based multilayer perceptron (MLP) TC intensity prediction model. The model was trained using the global Statistical Hurricane Intensity Prediction Scheme (SHIPS) predictors to forecast the change in TC maximum wind speed for the Atlantic basin. In the first experiment, a 24-h forecast period was considered. To overcome sample size limitations, we adopted a leave one year out (LOYO) testing scheme, where a model is trained using data from all years except one and then evaluated on the year that is left out. When tested on 2010–18 operational data using the LOYO scheme, the MLP outperformed other statistical–dynamical models by 9%–20%. Additional independent tests in 2019 and 2020 were conducted to simulate real-time operational forecasts, where the MLP model again outperformed the statistical–dynamical models by 5%–22% and achieved comparable results as HWFI. The MLP model also correctly predicted more rapid intensification events than all the four operational TC intensity models compared. In the second experiment, we developed a lightweight MLP for 6-h intensity predictions. When coupled with a synthetic TC track model, the lightweight MLP generated realistic TC intensity distribution in the Atlantic basin. Therefore, the MLP-based approach has the potential to improve operational TC intensity forecasts, and will also be a viable option for generating synthetic TCs for climate studies.

58 GEOSCIENCES↗
DOE OSTI2014

Spectroscopic failures in photometric redshift calibration: cosmological biases and survey requirements

We use N-body-spectro-photometric simulations to investigate the impact of incompleteness and incorrect redshifts in spectroscopic surveys to photometric redshift training and calibration and the resulting effects on cosmological parameter estimation from weak lensing shear-shear correlations. The photometry of the simulations is modeled after the upcoming Dark Energy Survey and the spectroscopy is based on a low/intermediate resolution spectrograph with wavelength coverage of 5500{\AA} < {\lambda} < 9500{\AA}. The principal systematic errors that such a spectroscopic follow-up encounters are incompleteness (inability to obtain spectroscopic redshifts for certain galaxies) and wrong redshifts. Encouragingly, we find that a neural network-based approach can effectively describe the spectroscopic incompleteness in terms of the galaxies' colors, so that the spectroscopic selection can be applied to the photometric sample. Hence, we find that spectroscopic incompleteness yields no appreciable biases to cosmology, although the statistical constraints degrade somewhat because the photometric survey has to be culled to match the spectroscopic selection. Unfortunately, wrong redshifts have a more severe impact: the cosmological biases are intolerable if more than a percent of the spectroscopic redshifts are incorrect. Moreover, we find that incorrect redshifts can also substantially degrade the accuracy of training set based photo-z estimators. The main problem is the difficulty of obtaining redshifts, either spectroscopically or photometrically, for objects at z > 1.3. We discuss several approaches for reducing the cosmological biases, in particular finding that photo-z error estimators can reduce biases appreciably.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Rates of adsorption and desorption: Entropic contributions and errors due to mean-field approximations

We have performed exact classical rate calculations to compute adsorption and desorption rate constants with a model representative of a real system. We compute the desorption rate using transition-state theory by taking the dividing-surface far from the surface of the solid. We find that using a mean-field assumption, i.e., applying potential of mean force to transition state theory, could lead to two orders-of-magnitude errors in the rate constant owing to large fluctuations in the desorption barrier. Furthermore, we compute the adsorption rate by including a dynamical factor which reflects the probability of sticking to the solid surface. We find that the sticking probability is highly sensitive to the coverage. Also, we find that the adsorption rate computed from the mean-field assumption is not very different from the exact adsorption rate. We also compute entropic contribution to desorption rates and compare it to that obtained from two limiting models of adsorption—2D ideal gas and 2D ideal lattice gas. We show that at high temperatures (700 K), the entropic contribution to desorption rates computed from the exact calculations is very close to that obtained from the 2D ideal gas model. However, for lower to intermediate temperatures from 200 K to 500 K, the entropic contributions cover a wide range which lies in between the two limiting models and could lead to over two-orders-of-magnitude errors in the rate coefficient.

Activation energies↗
DOE OSTI2015

Application of fuzzy system theory in addressing the presence of uncertainties

In this paper, the combinations of fuzzy system theory with the finite element methods are present and discuss to deal with the uncertainties. The present of uncertainties is needed to avoid for prevent the failure of the material in engineering. There are three types of uncertainties, which are stochastic, epistemic and error uncertainties. In this paper, the epistemic uncertainties have been considered. For the epistemic uncertainty, it exists as a result of incomplete information and lack of knowledge or data. Fuzzy system theory is a non-probabilistic method, and this method is most appropriate to interpret the uncertainty compared to statistical approach when the deal with the lack of data. Fuzzy system theory contains a number of processes started from converting the crisp input to fuzzy input through fuzzification process and followed by the main process known as mapping process. The term mapping here means that the logical relationship between two or more entities. In this study, the fuzzy inputs are numerically integrated based on extension principle method. In the final stage, the defuzzification process is implemented. Defuzzification is an important process to allow the conversion of the fuzzy output to crisp outputs. Several illustrative examples are given and from the simulation, the result showed that propose the method produces more conservative results comparing with the conventional finite element method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty

Population estimates are critical for government services, development projects, and public health campaigns. Such data are typically obtained through a national population and housing census. However, population estimates can quickly become inaccurate in localized areas, particularly where migration or displacement has occurred. Some conflict-affected and resource-poor countries have not conducted a census in over 10 y. We developed a hierarchical Bayesian model to estimate population numbers in small areas based on enumeration data from sample areas and nationwide information about administrative boundaries, building locations, settlement types, and other factors related to population density. We demonstrated this model by estimating population sizes in every 10- m grid cell in Nigeria with national coverage. These gridded population estimates and areal population totals derived from them are accompanied by estimates of uncertainty based on Bayesian posterior probabilities. The model had an overall error rate of 67 people per hectare (mean of absolute residuals) or 43% (using scaled residuals) for predictions in out-of-sample survey areas (approximately 3 ha each), with increased precision expected for aggregated population totals in larger areas. This statistical approach represents a significant step toward estimating populations at high resolution with national coverage in the absence of a complete and recent census, while also providing reliable estimates of uncertainty to support informed decision making.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

How Well Do We Know the Neutron-Matter Equation of State at the Densities Inside Neutron Stars? A Bayesian Approach with Correlated Uncertainties

Here, we introduce a new framework for quantifying correlated uncertainties of the infinite-matter equation of state derived from chiral effective field theory (𝜒⁢EFT ). Bayesian machine learning via Gaussian processes with physics-based hyperparameters allows us to efficiently quantify and propagate theoretical uncertainties of the equation of state, such as 𝜒⁢EFT truncation errors, to derived quantities. We apply this framework to state-of-the-art many-body perturbation theory calculations with nucleon-nucleon and three-nucleon interactions up to fourth order in the 𝜒⁢EFT expansion. This produces the first statistically robust uncertainty estimates for key quantities of neutron stars. We give results up to twice nuclear saturation density for the energy per particle, pressure, and speed of sound of neutron matter, as well as for the nuclear symmetry energy and its derivative. At nuclear saturation density, the predicted symmetry energy and its slope are consistent with experimental constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Objective analysis of toolmarks in forensics

Since the 1993 court case of Daubert v. Merrell Dow Pharmaceuticals, Inc. the subjective nature of toolmark comparison has been questioned by attorneys and law enforcement agencies alike. This has led to an increased drive to establish objective comparison techniques with known error rates, much like those that DNA analysis is able to provide. This push has created research in which the 3-D surface profile of two different marks are characterized and the marks’ cross-sections are run through a comparative statistical algorithm to acquire a value that is intended to indicate the likelihood of a match between the marks. The aforementioned algorithm has been developed and extensively tested through comparison of evenly striated marks made by screwdrivers. However, this algorithm has yet to be applied to quasi-striated marks such as those made by the shear edge of slip-joint pliers. The results of this algorithm’s application to the surface of copper wire will be presented. Objective mark comparison also extends to comparison of toolmarks made by firearms. In an effort to create objective comparisons, microstamping of firing pins and breech faces has been introduced. This process involves placing unique alphanumeric identifiers surrounded by a radial code on the surface of firing pins, which transfer to the cartridge’s primer upon firing. Three different guns equipped with microstamped firing pins were used to fire 3000 cartridges. These cartridges are evaluated based on the clarity of their alphanumeric transfers and the clarity of the radial code surrounding the alphanumerics.

42 ENGINEERING↗
DOE OSTI2012

Comparison of XSUSA and "Two-Step" Approaches for Full Core Uncertainty Quantification

While there are multiple sources of error that are introduced into the standard computational regime for simulating reactor cores, rigorous uncertainty analysis methods are available primarily for quantifying the effects of cross section uncertainties. Two methods for propagating cross section uncertainties through core simulators are the XSUSA statistical approach and the 'Two-Step' method. The XSUSA approach, which is based on the SUSA code package, is fundamentally a stochastic sampling method. Alternatively, the Two-Step method utilizes generalized perturbation theory in the first step and stochastic sampling in the second step. The consistency of these two methods in quantifying uncertainties in the multiplication factor and in the core power distribution will be examined in the framework of phase I-3 of the UAM Benchmark. Using the TMI core as a base model for analysis, the XSUSA and Two-Step methods are applied with certain limitations and the results are compared to those produced by other stochastic sampling-based codes. Based on the uncertainty analysis results, conclusions are made for which method is currently a more viable option for computing uncertainties in burnup and transient calculations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Comparison of XSUSA and 'two-step' approaches for full-core uncertainty quantification

While there are multiple sources of error that are introduced into the standard computational regime for simulating reactor cores, rigorous uncertainty analysis methods are available primarily for quantifying the effects of cross section uncertainties. Two methods for propagating cross section uncertainties through core simulators are the XSUSA statistical approach and the 'Two-Step' method. The XSUSA approach, which is based on the SUSA code package, is fundamentally a stochastic sampling method. Alternatively, the Two-Step method utilizes generalized perturbation theory in the first step and stochastic sampling in the second step. The consistency of these two methods in quantifying uncertainties in the multiplication factor and in the core power distribution will be examined in the framework of phase 1-3 of the UAM Benchmark. Using the TMI core as a base model for analysis, the XSUSA and Two-Step methods are applied with certain limitations and the results are compared to those produced by other stochastic sampling-based codes. Based on the uncertainty analysis results, conclusions are made for which method is currently a more viable option for computing uncertainties in burnup and transient calculations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

A novel application of cosmic rays for spent nuclear fuel monitoring - 15738

Monitoring nuclear waste and controlling spent nuclear fuel at its source is one of the main strategies to minimize the risks of nuclear proliferation and reduce potential homeland threats. Storage of high level waste from a fission reactor typically involves placing spent fuel in sealed dry casks. After the spent nuclear fuel has been placed inside the dry cask, the cask is welded, not allowing for visual inspection. Conventional methods for examining the interior of materials e.g., X-rays, are limited by the fact that they cannot penetrate very dense well-shielded objects. Instead, cosmic ray muons have the potential to allow for assessment of spent nuclear fuel stored within sealed dense dry casks. Objectives: 1.Exploit the ability of cosmic ray muons to penetrate high density materials allowing the distribution of materials within the object to be inferred from the muon tracks. 2. Develop a monitoring system that tracks the path of cosmic ray muons, including their deflection and attenuation, to identify the contents of a closed dry cask. Methods: - Monte-Carlo simulations using Geant4; - Bayesian decision theory for signal classification; - Wavelet analysis for noise cancellation; - Chaotic Neural Networks for signal encryption. Results: 1. Preliminary statistical analysis proved that the method is feasible and has the ability to identify the presence of spent nuclear fuel in a dry cask. 2. Using monoenergetic muons, a dry cask with one fuel assembly missing can be correctly identified with error rate <1%. Broader merit: Once completed, the proposed project for cosmic ray muon transport will enable a new and potentially transformative approach towards efficient, inexpensive and remote cosmic ray muon applications in archaeology, medicine and safeguarding of nuclear materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

A GATE evaluation of the sources of error in quantitative {sup 90}Y PET

Purpose: Accurate reconstruction of the dose delivered by {sup 90}Y microspheres using a postembolization PET scan would permit the establishment of more accurate dose–response relationships for treatment of hepatocellular carcinoma with {sup 90}Y. However, the quality of the PET data obtained is compromised by several factors, including poor count statistics and a very high random fraction. This work uses Monte Carlo simulations to investigate what impact factors other than low count statistics have on the quantification of {sup 90}Y PET. Methods: PET acquisitions of two phantoms—a NEMA PET phantom and the NEMA IEC PET body phantom-containing either {sup 90}Y or {sup 18}F were simulated using GATE. Simulated projections were created with subsets of the simulation data allowing the contributions of random, scatter, and LSO background to be independently evaluated. The simulated projections were reconstructed using the commercial software for the simulated scanner, and the quantitative accuracy of the reconstruction and the contrast recovery of the reconstructed images were evaluated. Results: The quantitative accuracy of the {sup 90}Y reconstructions were not strongly influenced by the high random fraction present in the projection data, and the activity concentration was recovered to within 5% of the known value. The contrast recovery measured for simulated {sup 90}Y data was slightly poorer than that for simulated {sup 18}F data with similar count statistics. However, the degradation was not strongly linked to any particular factor. Using a more restricted energy range to reduce the random fraction in the projections had no significant effect. Conclusions: Simulations of {sup 90}Y PET confirm that quantitative {sup 90}Y is achievable with the same approach as that used for {sup 18}F, and that there is likely very little margin for improvement by attempting to model aspects unique to {sup 90}Y, such as the much higher random fraction or the presence of bremsstrahlung in the singles data.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Analytic variance estimates of Swank and Fano factors

Purpose: Variance estimates for detector energy resolution metrics can be used as stopping criteria in Monte Carlo simulations for the purpose of ensuring a small uncertainty of those metrics and for the design of variance reduction techniques. Methods: The authors derive an estimate for the variance of two energy resolution metrics, the Swank factor and the Fano factor, in terms of statistical moments that can be accumulated without significant computational overhead. The authors examine the accuracy of these two estimators and demonstrate how the estimates of the coefficient of variation of the Swank and Fano factors behave with data from a Monte Carlo simulation of an indirect x-ray imaging detector. Results: The authors' analyses suggest that the accuracy of their variance estimators is appropriate for estimating the actual variances of the Swank and Fano factors for a variety of distributions of detector outputs. Conclusions: The variance estimators derived in this work provide a computationally convenient way to estimate the error or coefficient of variation of the Swank and Fano factors during Monte Carlo simulations of radiation imaging systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

D-Factor: A Quantitative Model of Application Slow-Down in Multi-Resource Shared Systems

Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price - resource contention among jobs increases job completion time. In this paper, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job is characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We also show that the model can be integrated with an existing on-line scheduler to minimize the makespan of workloads.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Physics-based statistical learning approach to mesoscopic model selection

In materials science and many other research areas, models are frequently inferred without considering their generalization to unseen data. Here, we apply statistical learning using cross-validation to obtain an optimally predictive coarse-grained description of a two-dimensional kinetic nearest-neighbor Ising model with Glauber dynamics (GD) based on the stochastic Ginzburg-Landau equation (sGLE). The latter is learned from GD “training” data using a log-likelihood analysis, and its predictive ability for various complexities of the model is tested on GD “test” data independent of the data used to train the model on. Using two different error metrics, we perform a detailed analysis of the error between magnetization time trajectories simulated using the learned sGLE coarse-grained description and those obtained using the GD model. We show that both for equilibrium and out-of-equilibrium GD training trajectories, the standard phenomenological description using a quartic free energy does not always yield the most predictive coarse-grained model. Moreover, increasing the amount of training data can shift the optimal model complexity to higher values. Our results are promising in that they pave the way for the use of statistical learning as a general tool for materials modeling and discovery.

36 MATERIALS SCIENCE↗