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DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2017

Characterizing half‐a‐degree difference: a review of methods for identifying regional climate responses to global warming targets

The Paris Agreement long‐term global temperature goal refers to two global warming levels: well below 2°C and 1.5°C above preindustrial. Regional climate signals at specific global warming levels, and especially the differences between 1.5°C and 2°C, are not well constrained, however. In particular, methodological challenges related to the assessment of such differences have received limited attention. This article reviews alternative approaches for identifying regional climate signals associated with global temperature limits, and evaluates the extent to which they constitute a sound basis for impacts analysis. Four methods are outlined, including comparing data from different greenhouse gas scenarios, sub‐selecting climate models based on global temperature response, pattern scaling, and extracting anomalies at the time of each global temperature increment. These methods have rarely been applied to compare 2°C with 1.5°C, but some demonstrate potential avenues for useful research. Nevertheless, there are methodological challenges associated with the use of existing climate model experiments, which are generally designed to model responses to different levels of greenhouse gas forcing, rather than to model climate responses to a specific level of forcing that targets a given level of global temperature change. Novel approaches may be required to address policy questions, in particular: to differentiate between half degree warming increments while accounting for different sources of uncertainty; to examine mechanisms of regional climate change including the potential for nonlinear responses; and to explore the relevance of time‐lagged processes in the climate system and declining emissions, and the resulting sensitivity to alternative mitigation pathways. WIREs Clim Change 2017, 8:e457. doi: 10.1002/wcc.457 This article is categorized under: Assessing Impacts of Climate Change > Scenario Development and Application

James, Rachel↗

DOE OSTI2020

New soil carbon sequestration with nitrogen enrichment: a meta-analysis

Background and aims: Through agriculture and industry, humans are increasing the deposition and availability of nitrogen (N) in ecosystems worldwide. Carbon (C) isotope tracers provide useful insights into soil C dynamics, as they allow to study soil C pools of different ages. In this study we evaluated to what extent N enrichment affects soil C dynamics in experiments that applied C isotope tracers. Methods: Using meta-analysis, we synthesized data from 35 published papers. We made a distinction between “new C” and “old C” stocks, i.e., soil C derived from plant C input since the start of the isotopic enrichment, or unlabeled, pre-existing soil C. Results: Averaged across studies, N addition increased new soil C stocks (+30.3%), total soil C stocks (+6.1%) and soil C input proxies (+30.7%). Although N addition had no overall, average, effect on old soil C stocks and old soil C respiration, old soil C stocks increased with the amount of N added and respiration of old soil C declined. Nitrogen-induced effects on new soil C and soil C input both decreased with the amount of extraneous N added in control treatments. Conclusion: Although our findings require additional confirmation from long-term field experiments, our analysis provides isotopic evidence that N addition stimulates soil C storage both by increasing soil C input and (at high N rates) by decreasing decomposition of old soil C. Furthermore, we demonstrate that the widely reported saturating response of plant growth to N enrichment also applies to new soil C storage.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Quantification of silicon carbide grain structure in TRISO fuel by BSE image analysis

The grain structure of the silicon carbide (SiC) layer in tristructural-isotropic (TRISO) fuels has commonly been qualified in fuel specifications based on a qualitative comparison to visual standards to ensure undesirable microstructure are not produced. This approach is inherently dependent on subjective judgement and provides limited data for analysis or comparison. An alternative method to rapidly quantify (i.e., provide a numeric measure of) the grain structure of the SiC layer in TRISO fuels has been developed. This method relies on the identification of silicon carbide grain boundaries based on brightness variation in backscattered electron (BSE) images through the application of automated image processing algorithms. The speed with which the requisite BSE imaging and analysis may be completed enables the practical use of this method on an industrial scale as a part of qualifying TRISO fuel to meet a given specification on silicon carbide grain structure, which is an important parameter for TRISO fuel performance. The method is benchmarked by comparison to prior Electron-Backscattered Diffraction (EBSD) results for TRISO particles from the Advanced Gas Reactor (AGR) program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Long-range collectivity in small collision systems with two- and four-particle correlations at STAR

New STAR measurements of two- and four-particle (c 2 {4}) azimuthal angle correlations are reported for p+Au collisions at 200 GeV and d+Au collisions from 19.6 to 200 GeV. A negative c 2 {4}, consistent with collective anisotropic flow, is observed in high multiplicity d+Au events at 62.4 and 200 GeV where the statistical significance of the data allows an analysis. A template fitting method, employed to subtract non-flow contributions to the two-particle correlations, allows the extraction of the anisotropy coefficients (ν 2 ) for these systems at their respective energies. The ν 2 results for different energies show a common dependence on the charged particle multiplicity density ( < dN ch /dη > ), which provide important insight on the nature of collective behavior in small collision systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

Charge carrier dynamics in nanocrystalline Dy substituted ceria based oxygen ion conductors

Nano-crystalline Ce{sub 1-x}Dy{sub x}O{sub 2-δ} (x = 0.1-0.5) materials were prepared using the low temperature citrate auto-ignition method. The Rietveld analysis of the XRD data confirmed the single phase cubic fluorite structure. The particle sizes of the sintered samples are in nano range and lattice parameter increases with Dy concentration. Polydispersed and agglomerated particles are observed by SEM. The EDAX spectra show good stoichiometry of the different atoms in the samples. The conductivity is found to have both grain and grain boundary contribution and shows highest value at x= 0.2. The frequency dependence of dielectric permittivity has been analyzed using Havrilliak-Negami formalism. The variation in different electrical properties has been explained by formation defect associates and their interaction with charge carriers.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Comparative analysis of the methods for quantitative determination of water content in skin from diffuse reflectance spectroscopy data

The predictive properties of methods aimed for estimating the water content in skin from the spectral diffuse reflection characteristics near the water absorption line in the near-IR spectral range are analysed. Numerical simulation data, experimental data on diffuse reflection from human skin phantoms, and data from the reference data set of human skin reflectance spectra are used to consider the possibility of gaining additional information about the water distribution in skin. The influence of variations in the scattering coefficient and oxyhaemoglobin concentration on the water content estimates is investigated. (paper)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

COSMIC MICROWAVE BACKGROUND LIKELIHOOD APPROXIMATION FOR BANDED PROBABILITY DISTRIBUTIONS

We investigate sets of random variables that can be arranged sequentially such that a given variable only depends conditionally on its immediate predecessor. For such sets, we show that the full joint probability distribution may be expressed exclusively in terms of uni- and bivariate marginals. Under the assumption that the cosmic microwave background (CMB) power spectrum likelihood only exhibits correlations within a banded multipole range, Δl{sub C}, we apply this expression to two outstanding problems in CMB likelihood analysis. First, we derive a statistically well-defined hybrid likelihood estimator, merging two independent (e.g., low- and high-l) likelihoods into a single expression that properly accounts for correlations between the two. Applying this expression to the Wilkinson Microwave Anisotropy Probe (WMAP) likelihood, we verify that the effect of correlations on cosmological parameters in the transition region is negligible in terms of cosmological parameters for WMAP; the largest relative shift seen for any parameter is 0.06σ. However, because this may not hold for other experimental setups (e.g., for different instrumental noise properties or analysis masks), but must rather be verified on a case-by-case basis, we recommend our new hybridization scheme for future experiments for statistical self-consistency reasons. Second, we use the same expression to improve the convergence rate of the Blackwell-Rao likelihood estimator, reducing the required number of Monte Carlo samples by several orders of magnitude, and thereby extend it to high-l applications.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Accurate spectroscopic characterization of oxirane: A valuable route to its identification in Titan's atmosphere and the assignment of unidentified infrared bands

In an effort to provide an accurate spectroscopic characterization of oxirane, state-of-the-art computational methods and approaches have been employed to determine highly accurate fundamental vibrational frequencies and rotational parameters. Available experimental data were used to assess the reliability of our computations, and an accuracy on average of 10 cm{sup –1} for fundamental transitions as well as overtones and combination bands has been pointed out. Moving to rotational spectroscopy, relative discrepancies of 0.1%, 2%-3%, and 3%-4% were observed for rotational, quartic, and sextic centrifugal-distortion constants, respectively. We are therefore confident that the highly accurate spectroscopic data provided herein can be useful for identification of oxirane in Titan's atmosphere and the assignment of unidentified infrared bands. Since oxirane was already observed in the interstellar medium and some astronomical objects are characterized by very high D/H ratios, we also considered the accurate determination of the spectroscopic parameters for the mono-deuterated species, oxirane-d1. For the latter, an empirical scaling procedure allowed us to improve our computed data and to provide predictions for rotational transitions with a relative accuracy of about 0.02% (i.e., an uncertainty of about 40 MHz for a transition lying at 200 GHz).

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2014

Reverberation mapping of the Seyfert 1 galaxy NGC 7469

A large reverberation-mapping study of the Seyfert 1 galaxy NGC 7469 has yielded emission-line lags for Hβ λ4861 and He II λ4686 and a central black hole mass measurement M {sub BH} ≈ 1 × 10{sup 7} M {sub ☉}, consistent with previous measurements. A very low level of variability during the monitoring campaign precluded meeting our original goal of recovering velocity-delay maps from the data, but with the new Hβ measurement, NGC 7469 is no longer an outlier in the relationship between the size of the Hβ-emitting broad-line region and the luminosity of the active galactic nucleus. It was necessary to detrend the continuum and Hβ and He II λ4686 line light curves and those from archival UV data for different time-series analysis methods to yield consistent results.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Accurate gravities of F, G, and K stars from high resolution spectra without external constraints

We demonstrate a new procedure to derive accurate and precise surface gravities from high resolution spectra without the use of external constraints. Our analysis utilizes Spectroscopy Made Easy with robust spectral line constraints and uses an iterative process to mitigate degeneracies in the fitting process. We adopt an updated radiative transfer code, a new treatment for neutral perturber broadening, a line list with multiple gravity constraints and separate fitting for global stellar properties and abundance determinations. To investigate the sources of temperature dependent trends in determining log g noted in previous studies, we obtained Keck HIRES spectra of 42 Kepler asteroseismic stars. In comparison to asteroseismically determined log g our spectroscopic analysis has a constant offset of 0.01 dex with a rms scatter of 0.05 dex. We also analyzed 30 spectra which had published surface gravities determined using the a/R{sub ∗} technique from planetary transits and found a constant offset of 0.06 dex and rms scatter of 0.07 dex. The two samples covered effective temperatures between 5000 and 6700 K with log g between 3.7 and 4.6.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Fast inference of Boosted Decision Trees in FPGAs for particle physics

We describe the implementation of Boosted Decision Trees in the hls4ml library, which allows the translation of a trained model into FPGA firmware through an automated conversion process. Thanks to its fully on-chip implementation, hls4ml performs inference of Boosted Decision Tree models with extremely low latency. With a typical latency less than 100 ns, this solution is suitable for FPGA-based real-time processing, such as in the Level-1 Trigger system of a collider experiment. These developments open up prospects for physicists to deploy BDTs in FPGAs for identifying the origin of jets, better reconstructing the energies of muons, and enabling better selection of rare signal processes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

ALICE luminosity determination for Pb–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

Luminosity determination within the ALICE experiment is based on the measurement, in van der Meer scans, of the cross sections for visible processes involving one or more detectors (visible cross sections). In 2015 and 2018, the Large Hadron Collider provided Pb–Pb collisions at a centre-of-mass energy per nucleon pair of $\sqrt{s_{NN}}$ = 5.02 TeV. Two visible cross sections, associated with particle detection in the Zero Degree Calorimeter (ZDC) and in the V0 detector, were measured in a van der Meer scan. This article describes the experimental set-up and the analysis procedure, and presents the measurement results. The analysis involves a comprehensive study of beam-related effects and an improved fitting procedure, compared to previous ALICE studies, for the extraction of the visible cross section. The resulting uncertainty of both the ZDC-based and the V0-based luminosity measurement for the full sample is 2.5%. The inelastic cross section for hadronic interactions in Pb–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV, obtained by efficiency correction of the V0-based visible cross section, was measured to be 7.67 ± 0.25 b, in agreement with predictions using the Glauber model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Optimizing spin dressing sensitivity for the nEDMSF experiment

nEDMSF aims to measure the neutron electric dipole moment (d n ) with unprecedented precision. In this paper we explore the experiment's sensitivity when operating with an implementation of the critical dressing method in which the angle between the neutron and Helium-3 spins (ϕ 3n ) is subjected to a square modulation by an amount ϕ d (the “dressing angle”). Several parameters can be tuned to optimize sensitivity. We find roughly 10% improvement over a previous estimate, resulting primarily from the addition of a waiting period between the π/2 pulse that initiates d n -driven ϕ 3n growth and the start of ϕ3n modulation. We find negligible further improvement by allowing ϕ d to vary continuously over the course of a run, and no degradation resulting from the addition of an in situ background measurement into each ϕ3n modulation sequence. A complete simulation confirms a 300 live-day sensitivity ofσ = 1.45×10 -28 e ·cm. At this level of sensitivity, σ ϕ3n0 = 1 mrad precision on the initial n/ 3 He angle difference is not negligible.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Tools for unbinned unfolding

Machine learning has enabled differential cross section measurements that are not discretized. Going beyond the traditional histogram-based paradigm, these unbinned unfolding methods are rapidly being integrated into experimental workflows. Here, in order to enable widespread adaptation and standardization, we develop methods, benchmarks, and software for unbinned unfolding. For methodology, we demonstrate the utility of boosted decision trees for unfolding with a relatively small number of high-level features. This complements state-of-the-art deep learning models capable of unfolding the full phase space. To benchmark unbinned unfolding methods, we develop an extension of existing dataset to include acceptance effects, a necessary challenge for real measurements. Additionally, we directly compare binned and unbinned methods using discretized inputs for the latter in order to control for the binning itself. Lastly, we have assembled two software packages for the OmniFold unbinned unfolding method that should serve as the starting point for any future analyses using this technique. One package is based on the widely-used RooUnfold framework and the other is a standalone package available through the Python Package Index (PyPI).

47 OTHER INSTRUMENTATION↗

DOE OSTI2026

Neural posterior unfolding

Differential cross section measurements are the currency of scientific exchange in particle and nuclear physics. A key challenge for these analyses is the correction for detector distortions, known as deconvolution or unfolding. Binned unfolding of cross section measurements traditionally rely on the regularized inversion of the response matrix that represents the detector response, mapping pre-detector (`particle level') observables to post-detector (`detector level') observables. In this paper we introduce Neural Posterior Unfolding, a modern, Bayesian approach that leverages normalizing flows for unfolding. By using normalizing flows for neural posterior estimation, NPU offers several key advantages including implicit regularization through the neural network architecture, fast amortized inference that eliminates the need for repeated retraining, and direct access to the full uncertainty in the unfolded result. In addition to introducing NPU, we implement a classical Bayesian unfolding method called Fully Bayesian Unfolding (FBU) in modern Python so it can also be studied. These tools are validated on simple Gaussian examples and then tested on simulated jet substructure examples from the Large Hadron Collider (LHC). We find that the Bayesian methods are effective and worth additional development to be analysis ready for cross section measurements at the LHC and beyond.

Analysis and statistical methods↗

DOE OSTI2021

Anomaly detection in the Zwicky Transient Facility DR3

We present results from applying the SNAD anomaly detection pipeline to the third public data release of the Zwicky Transient Facility (ZTF DR3). The pipeline is composed of three stages: feature extraction, search of outliers with machine learning algorithms, and anomaly identification with followup by human experts. Our analysis concentrates in three ZTF fields, comprising more than 2.25 million objects. A set of four automatic learning algorithms was used to identify 277 outliers, which were subsequently scrutinized by an expert. From these, 188 (68 per cent) were found to be bogus light curves – including effects from the image subtraction pipeline as well as overlapping between a star and a known asteroid, 66 (24 per cent) were previously reported sources whereas 23 (8 per cent) correspond to non-catalogued objects, with the two latter cases of potential scientific interest (e.g. one spectroscopically confirmed RS Canum Venaticorum star, four supernovae candidates, one red dwarf flare). Moreover, using results from the expert analysis, we were able to identify a simple bi-dimensional relation that can be used to aid filtering potentially bogus light curves in future studies. We provide a complete list of objects with potential scientific application so they can be further scrutinised by the community. These results confirm the importance of combining automatic machine learning algorithms with domain knowledge in the construction of recommendation systems for astronomy. Our code is publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗