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DOE OSTI2018

Automated generation and ensemble-learned matching of X-ray absorption spectra

X-ray absorption spectroscopy (XAS) is a widely used materials characterization technique to determine oxidation states, coordination environment, and other local atomic structure information. Analysis of XAS relies on comparison of measured spectra to reliable reference spectra. However, existing databases of XAS spectra are highly limited both in terms of the number of reference spectra available as well as the breadth of chemistry coverage. In this work, we report the development of XASdb, a large database of computed reference XAS, and an Ensemble-Learned Spectra IdEntification (ELSIE) algorithm for the matching of spectra. XASdb currently hosts more than 800,000 K-edge X-ray absorption near-edge spectra (XANES) for over 40,000 materials from the open-science Materials Project database. We discuss a high-throughput automation framework for FEFF calculations, built on robust, rigorously benchmarked parameters. FEFF is a computer program uses a real-space Green’s function approach to calculate X-ray absorption spectra. Here, we will demonstrate that the ELSIE algorithm, which combines 33 weak “learners” comprising a set of preprocessing steps and a similarity metric, can achieve up to 84.2% accuracy in identifying the correct oxidation state and coordination environment of a test set of 19 K-edge XANES spectra encompassing a diverse range of chemistries and crystal structures. The XASdb with the ELSIE algorithm has been integrated into a web application in the Materials Project, providing an important new public resource for the analysis of XAS to all materials researchers. Finally, the ELSIE algorithm itself has been made available as part of veidt, an open source machine-learning library for materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman alpha forest

We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-α(Lyα) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over 420 000 Lyα forest spectra and their correlation with the spatial distribution of more than 700 000 quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon (r d ), we measure the expansion at z eff = 2.33 with 2% precision, H(z eff ) = (239.2 ± 4.8) (147.09 Mpc /r d ) km/s/Mpc. Similarly, we present a 2.4% measurement of the transverse comoving distance to the same redshift, DM(z eff ) = (5.84 ± 0.14) (r d /147.09 Mpc) Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Comprehensive High Throughput One‐Pot Analysis of Glycoproteins through Tool for Rapid Analysis of Glycopeptide by Permethylation (TRAP) Method.

Glycoproteins plays key roles in various cellular functions such as protein folding, protein targeting, receptor function, cell–cell recognition, protein stability, signaling, and other cellular functions. Currently a comprehensive and universal tool for the automated analysis of glycopeptides through their tandem mass spectrometry and data processing is a tedious process. We recently developed a method, Tool for Rapid Analysis of glycopeptide by Permethylation (TRAP), that simplifies glycoprotein analysis by integrating glycan sequencing and glycopeptide analysis in a single experiment. We employed this approach for the detailed analysis of glycosidic linkages, composition, glycan sequencing, glycosylation site mapping and sequencing of peptide moiety of glycopeptides of glycoproteins from both prokaryotes and eukaryotes. Here we are presenting an easy to use, robust, suitable for large as well as small sample sets and also cost‐effective glycoprotein analysis tool through TRAP approach. A permethylation protocol which can be automated and suitable for reliable permethylation of glycopeptides from the protease digest of glycoproteins was developed. Initial studies on glycopeptides from a model glycoprotein bovine RNAse B indicates that improved sensitivity and throughput of permethylation reactions can be achieved in conducting the reaction in microscale. This approach would enable convenient, rapid, and reliable high‐throughput screening of protein glycosylation and can be employed as a cost‐effective kit for glycosylated biomarker discoveries. In order to improvise the comprehensive glycosylation analysis and throughput, we have also developed an LC‐MS/MS platform for the analysis of glycopeptides processed through TRAP. We have conducted the analysis of standard glycoproteins such as bovine RNase B, human transferrin, and bovine fetuin and our preliminary results indicate that TRAP hyphened with LC‐MS/MS enables characterization of isomers of each glycoform at each glycosylation sites of complex glycoprotein mixtures. Support or Funding Information This research was supported by the National Institutes of Health (NIH) funded research, Grant R21GM122633; resource for biomedical glycomics, Grant P41GM103490; instrument grant, Grant S10OD018530; and U.S. Department of Energy grant, Grant DE‐SC0015662, to the Complex Carbohydrate Research Center. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Shajahan, Asif↗

DOE OSTI2020

Modeling the Functional Forms of Grid Disturbances

This report introduces a functional form that may be used to quantitatively predict the impacts of new grid tools and changing system qualities on the likelihoods, durations, and depths of various grid disturbances. Each disturbance scenario is modeled to have three component stages—avoidance, reactance and recovery, which together parametrically estimate one disturbance’s impacts. The modeled scenario is then placed and replicated within an analysis period to represent the likelihood or frequency of the scenario and its consequent impacts. Whereas analysts have struggled to define and apply metrics for grid resilience, the functional form introduced by this report shares units of measurement with accepted grid-status measures (e.g., numbers of customers currently experiencing a service outage). Furthermore, the integrated and averaged functional form over an analysis period provides a meaningful normalized performance metric (e.g., customer outage minutes per year) that is ultimately independent of the duration of the period of. The approach may be applied similarly regardless of the severity or frequency of the disturbances that are being analyzed. Because metrics can be chosen to be identical in both the hypothetical future and the actual historical past, the historical past eventually becomes the test of the future predictions, at least in a statistical sense. The authors originally developed this approach to facilitate analysis of the effects of transactive energy (TE) systems effects on electric power grid resilience. TE systems invite energy suppliers and consumers to actively collaborate toward the discovery of, and their responses to, the locational value of energy. The findings from this process are often embodied as energy prices, the dynamics of which indicate the locational value of energy and can further represent important grid service needs. While some academic papers claim to quantify the value of a specific TE system design toward grid resilience, the answer, in general, has been elusive. Not only do multiple and conflicting definitions of resilience and reliability exist, but countless TE systems are being invented. We conclude the following: (1) The ideal analysis should harmonize rather than differentiate resilience and reliability. Therefore, this report uses the more general term disturbance whenever the overloaded terms resilience and reliability can be avoided. (2) The effectiveness of TE systems must be mapped to underlying qualities of a TE system, thereby avoiding presumptions that every TE design offers similar advantages. The authors seek to evaluate the parametric effects of TE system qualities (e.g., spatial granularity, granularity of time steps, length of future prediction horizon) on avoiding, reacting to, and recovering from grid disturbances. Furthermore, any advantages (or disadvantages) must be fairly compared with the many alternative tools, systems, and strategies that might offer comparable benefits.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

Comparison of a Traditional Probabilistic Risk Assessment Approach with Advanced Safety Analysis

As part of the Light Water Sustainability Program (LWRS) [1], the purpose of the Risk Informed Safety Margin Characterization (RISMC) [2] Pathway research and development (R&D) is to support plant decisions for risk-informed margin management with the aim to improve economics, reliability, and sustain safety of current NPPs. In this paper, we describe the RISMC analysis process illustrating how mechanistic and probabilistic approaches are combined in order to estimate a safety margin. We use the scenario of a “station blackout” (SBO) wherein offsite power and onsite power is lost, thereby causing a challenge to plant safety systems. We describe the RISMC approach, illustrate the station blackout modeling, and contrast this with traditional risk analysis modeling for this type of accident scenario. We also describe our approach we are using to represent advanced flooding analysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Practical Implementation of Synchrophasor Based Real-Time Contingency Analysis

Synchrophasor technology is increasingly accepted and adopted by the power industry. Linear State Estimator (LSE) is a recent development in the synchrophasor industry, and has been integrated and deployed at control centers, providing improved coverage and greater reliability from synchrophasor systems. This paper describes a first-of-a-kind synchrophasor based real-time contingency analysis (RTCA), which takes the LSE solved case as input, and then solves the what-if cases to provide timely information about impending grid problems to system operators. Test results on IEEE 39 bus and 300 bus system demonstrate the accuracy of the method for solving the RTCA problem using synchrophasor data. With this the synchrophasor measurement system provides an independent real-time monitoring and operation system which utilizes PMU data alone.

Nayak, Neeraj↗

DOE OSTI2019

Fleetwide data-enabled reliability improvement of wind turbines

Wind farms are an indispensable driver toward renewable and nonpolluting energy resources. However, as ideal sites are limited, placement in remote and challenging locations results in higher logistics costs and lower average wind speeds. Therefore, it is critical to increase the reliability of the turbines to reduce maintenance costs. Robust implementation requires a thorough understanding of the loads subject to the turbine's control. Yet, such dynamically changing multidimensional loads are uncommon with other machinery, and generally underresearched. Therefore, a multitiered approach is proposed to investigate the load spectrum occurring in wind farms. Our approach relies on both fundamental research using controllable test rigs, as well as analyses of real-world loading conditions in high-frequency supervisory control and data acquisition data. A method is introduced to detect operational zones in wind farm data and link them with load distributions. Additionally, while focused research further investigates the load spectrum, a method is proposed that continuously optimizes the farm's control protocols without the need to fully understand the loads that occur. A case of gearbox failure is investigated based on a vast body of past experiments and suspect loads are identified. Starting from this evidence on the cause and effects of dynamic loads, the potential of our methods is shown by analyzing real-world farm loading conditions on a steady-state case of wake and developing a preventive row-based control protocol for a case of cascading emergency brakes induced by a storm.

17 WIND ENERGY↗

DOE OSTI2023

Reliability Estimation for One-Shot Devices (Rev. 1)

We present an engineering-oriented summary of statistical methods for estimation of the reliability (or equivalently, failure probability) of one-shot devices such as explosive detonators and other weapon components. Estimates may be given as single points or intervals, based on pass/fail tests, margin analysis, computational models, expert judgment, or a combination of these. We focus on highly reliable devices for which few or no failures are expected to occur in testing.

42 ENGINEERING↗

DOE OSTI2023

Physics-embedded inverse analysis with algorithmic differentiation for the earth’s subsurface

Abstract Inverse analysis has been utilized to understand unknown underground geological properties by matching the observational data with simulators. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented with embedded physics and a technique known as algorithmic differentiation. We use a physics-embedded generative model, which takes statistically simple parameters as input and outputs subsurface properties (e.g., permeability or P-wave velocity), that embeds physical knowledge of the subsurface properties into inverse analysis and improves its performance. We tested the application of this approach on four geologic problems: two heterogeneous hydraulic conductivity fields, a hydraulic fracture network, and a seismic inversion for P-wave velocity. This physics-embedded inverse analysis approach consistently characterizes these geological problems accurately. Furthermore, the excellent performance in matching the observational data demonstrates the reliability of the proposed method. Moreover, the application of algorithmic differentiation makes this an easy and fast approach to inverse analysis when dealing with complicated geological structures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Nonparametric Prediction Intervals of Wind Power via Linear Programming

This letter proposes a machine learning-based linear programming model that quickly establishes the nonparametric prediction intervals of wind power by integrating extreme learning machine and quantile regression. The proportions of quantiles can be adaptively determined via sensitivity analysis. The proposed method has been proven to be significantly efficient and reliable, with a high application potential in power systems.

extreme learning machine↗

DOE OSTI2015

Reimagining What's Possible: How NREL's Energy Analysis and Decision Support Capabilities are Guiding Energy Systems Transformation at Home and Around the World; NREL (National Renewable Energy Laboratory)

This engaging brochure shows examples of how NREL enables energy system transformation through robust capabilities in energy analysis and decision support. By reimagining what's possible for renewable energy, NREL contributes to the Department of Energy mission to create energy systems that are cleaner, more reliable, and more secure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Advanced Performance Metrics and their Application to the Sensitivity Analysis for Model Validation and Calibration

High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the model-based simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. In this work, results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Toward integrating high-fidelity CFD approaches in the thermal-hydraulic analysis of turbulent dry cask systems

Nuclear power plants have been supplying resilient and reliable electricity for decades, contributing to energy independence of the U.S.. However, nuclear waste management remains one of the most significant challenges in the industry. The safety of dry cask storage systems relies heavily on their thermal-hydraulic performance. Computational Fluid Dynamics (CFD) simulations are often used to demonstrate this performance and ensure that the system design meets safety standards. This study presents reduced numerical models for various types of dry cask systems. These numerical models can produce efficient and fast results based on the employed modeling strategies. Additionally, the study uses a novel approach to high-fidelity simulations to evaluate modeling assumptions in dry cask modeling. Large Eddy Simulations (LES) are used for this purpose, particularly in regions where fluid velocity is relatively high and the turbulence characteristics become important. Furthermore, the results of these high-fidelity simulations will enhance the interpretation of outcomes produced from a lower-fidelity CFD model.

CFD↗

DOE OSTI2016

NLTE ANALYSIS OF HIGH-RESOLUTION H -BAND SPECTRA. I. NEUTRAL SILICON

We investigated the reliability of our silicon atomic model and the influence of non-local thermodynamical equilibrium (NLTE) on the formation of neutral silicon (Si i) lines in the near-infrared (near-IR) H -band. We derived the differential Si abundances for 13 sample stars with high-resolution H -band spectra from the Apache Point Observatory Galactic Evolution Experiment (APOGEE), as well as from optical spectra, both under local thermodynamical equilibrium (LTE) and NLTE conditions. We found that the differences between the Si abundances derived from the H -band and from optical lines for the same stars are less than 0.1 dex when the NLTE effects are included, and that NLTE reduces the line-to-line scatter in the H -band spectra for most sample stars. These results suggest that our Si atomic model is appropriate for studying the formation of H -band Si lines. Our calculations show that the NLTE corrections of the Si i H -band lines are negative, i.e., the final Si abundances will be overestimated in LTE. The corrections for strong lines depend on surface gravity, and tend to be larger for giants, reaching ∼−0.2 dex in our sample, and up to ∼−0.4 dex in extreme cases of APOGEE targets. Thus, the NLTE effects should be included in deriving silicon abundances from H -band Si i lines, especially for the cases where only strong lines are available.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Outage Analysis for Cooperative mmWave UAV Communications With Beam Training Overhead

In this letter, we investigate the tradeoff between reliability and beam training overhead in cooperative millimeter wave (mmWave) unmanned aerial vehicle (UAV) communications. In particular, we analyze how outage probability varies with the number of neighboring UAVs being probed as potential relays for relay selection. Unlike existing work, the limited number of UAV beams as well as UAV orientations are explicitly considered in our analysis. Here we derive the outage probability in closed form and verify our analysis via simulations. The results facilitate us to understand the fundamental limits of cooperative mmWave UAV communications.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2016

Screening sensitivity analysis of a PWR fuel assembly FEM structural model

Within the present project, computational methods to describe the static mechanical response of PWR fuel assemblies (FA) in the reactor core are developed. For this purpose a structural model of a PWR fuel assembly has been implemented with the Finite Element Method (FEM) using the ANSYS APDL Mechanical code. The purpose of the model is to investigate the long-term creep deformation of the fuel assemblies in the reactor core, commonly known as fuel assembly bow. FA bow is considered to be a complex process with a large number of influencing mechanisms and many only roughly known boundary conditions. Uncertainty and sensitivity analyses are a common way to investigate the predictive power and reliability of such complex models. Hence, as a first approach to understand the importance of the many model parameters, a qualitative sensitivity analysis of the model was conducted using the screening method proposed by Morris. In the first part of the paper, the FA structural model and its principal parameters are presented. The second part presents first the different simulation experiments used for the screening analyses. Based on the model description, relevant input parameters are then identified and a typical range of values is determined. The sensitivity analysis is performed in two subsequent steps. First, the model is screened for influential stiffness parameters with the objective of stiffening the FA structure. Second, the influence of the uncertain boundary conditions and material models on the FA creep deformation is tested. For the considered FA design it is concluded that the influence of the involved uncertainties is comparable to the influence of the parameters which can increase the stiffness. An integral approach accounting for these uncertainties is hence necessary to predict FA bow reliably in order to take additional measures for a further reduction of FA bow amplitudes. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2018

In-Vehicle Assessment of Human Exposure to EMFs from 25-kW WPT System Based on Near-Field Analysis: Preprint

Wireless power transfer (WPT) technology has the potential to be a convenient and reliable charging method for the light and heavy duty electric vehicles. However, the loosely coupling between the two sides results in strong near-electromagnetic fields (EMFs) around the system, which may have the possibility to impact human safety if the standard limits are exceeded. Therefore, comprehensive tests are necessary to ensure the electromagnetic fields are with in safe limits. Consequently, this paper presents a test methodology for the near-field from a 25 kW WPT system from Momentum Dynamics, which is installed in a heavy duty electric shuttle at the National Renewable Energy Laboratory (NREL). The paper describes in detail the measuring device, test setup and conditions. The misalignments between the two systems' sides are considered during the measurements. Test results for the regions of concern around and inside the bus are presented and compared with the reference levels defined by the international standards, including ICNIRP 2010 and IEEE C95.1. In addition, a finite-element model is developed for the wireless coupler and analyzed at the same conditions as the tests. Comparative analysis is presented between the simulated and experimental results. The measurements at the test points show adherence to the standard limits for the general public and occupational exposure.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2014

Contrast-Enhanced Proton Radiography for Patient Set-up by Using X-Ray CT Prior Knowledge

Purpose: To obtain a contrasted image of the tumor region during the setup for proton therapy in lung patients, by using proton radiography and x-ray computed tomography (CT) prior knowledge. Methods and Materials: Six lung cancer patients' CT scans were preprocessed by masking out the gross tumor volume (GTV), and digitally reconstructed radiographs along the planned beam's eye view (BEV) were generated, for a total of 27 projections. Proton radiographies (PR) were also computed for the same BEV through Monte Carlo simulations. The digitally reconstructed radiograph was subtracted from the corresponding proton image, resulting in a contrast-enhanced proton radiography (CEPR). Michelson contrast analysis was performed both on PR and CEPR. The tumor region was then automatically segmented on CEPR and compared to the ground truth (GT) provided by physicians in terms of Dice coefficient, accuracy, precision, sensitivity, and specificity. Results: Contrast on CEPR was, on average, 4 times better than on PR. For 10 lateral projections (±45° off of 90° or 270°), although it was not possible to distinguish the tumor region in the PR, CEPR offers excellent GTV visibility. The median ± quartile values of Dice, precision, and accuracy indexes were 0.86 ± 0.03, 0.86 ± 0.06, and 0.88 ± 0.02, respectively, thus confirming the reliability of the method in highlighting tumor boundaries. Sensitivity and specificity analysis demonstrated that there is no systematic over- or underestimation of the tumor region. Identification of the tumor boundaries using CEPR resulted in a more accurate and precise definition of GTV compared to that obtained from pretreatment CT. Conclusions: In most proton centers, the current clinical protocol is to align the patient using kV imaging with bony anatomy as a reference. We demonstrated that CEPR can significantly improve tumor visualization, allowing better patient set-up and permitting image guided proton therapy (IGPT)

62 RADIOLOGY AND NUCLEAR MEDICINE↗