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DOE OSTI2017

Multiobjective Optimization of Regional and Teleseismic Data to Constrain the Source of the 12 September 2016 Mw 5.4 Earthquake in South Korea

In this paper, we propose a new approach for source inversion with automatic criteria for the station selection process and using a multiobjective optimization scheme combining teleseismic body-wave and regional surface-wave observations. To illustrate the approach, we determine the source parameters of the 12 September 2016 M w 5.4 South Korea earthquake, as well as its foreshock (same day) and its main aftershock on 19 September 2016. Available teleseismic (short period and broadband) and regional (broadband) seismograms from the Incorporated Research Institutions for Seismology International–Federation of Digital Seismograph Networks (IRIS-FDSN) webservice are selected (see Data and Resources). First, all teleseismic data with signal-to-noise ratio (SNR) above 2 in the 0.3–1.5 Hz frequency band are selected and a cepstrum function is blindly applied to help detect reflected wave arrivals inside a P coda. This method allows the identification of records with weak P-coda and clear depth phase (pP, sP) arrivals and can be used to select an optimal set of teleseismic seismograms to be used for the inversion. Second, regional seismograms are selected according to the fit between their observed and theoretical dispersion curves extracted from local 1D velocity model. Depending on the epicentral distance, two frequency bands are proposed for regional data: 15–50 s for epicentral distances smaller than 2° and 30–80 s otherwise. Finally, we explore the space parameters from exhaustive grid searches for the two objective functions Tf and Rf for teleseismic and regional data, respectively. We show that the seismic moment parameters can be exclusively derived from Rf and can be fixed for Tf. However, the depth parameter is not sensitive to Rf and can be simultaneously inverted from both. The selection of the optimal solution satisfying both cost functions uses the optimum Pareto front that allows a decrease in epistemic uncertainty. Lastly, we discuss the advantage of this approach for improving the characterization of moderate earthquake sources in areas with limited regional instrumentation.

58 GEOSCIENCES↗

DOE OSTI2024

Examining the self-interaction of dark matter through central cluster galaxy offsets

ABSTRACT While collisionless cold dark matter models have been largely successful in explaining a wide range of observational data, some tensions still exist, and it remains possible that dark matter possesses a non-negligible level of self-interactions. In this paper, we investigate a possible observable consequence of self-interacting dark matter: offsets between the central galaxy and the centre of mass of its parent halo. We examine 23 relaxed galaxy clusters in a redshift range of 0.1–0.3 drawn from clusters in the Dark Energy Survey and the Sloan Digital Sky Survey which have archival Chandra X-ray data of sufficient depth for centre and relaxation determination. We find that most clusters in our sample show non-zero offsets between the X-ray centre, taken to be the centroid within the cluster core, and the central galaxy position. All of the measured offsets are larger, typically by an order of magnitude, than the uncertainty in the X-ray position due to Poisson noise. In all but six clusters, the measured offsets are also larger than the estimated, combined astrometric uncertainties in the X-ray and optical positions. A more conservative cut on concentration to select relaxed clusters marginally reduces but does not eliminate the observed offset. With our more conservative sample, we find an estimated median X-ray to central galaxy offset of $\mu = 6.0 ^{+ 1.4}_{- 1.5}$ kpc. Comparing to recent simulations, this distribution of offsets is consistent with some level of dark matter self-interaction, though further simulation work is needed to place constraints.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Use of Machine Learning on PMU Data for Transmission System Fault Analysis

Synchrophasor technology has been used for monitoring, control, and protection of bulk power system for over 10 years. Deployment of phasor measurement units (PMUs) in the USA power system has surpassed 3000 units installed in the transmission substations as stand-alone intelligent electronic devices (IEDs) or as a software add-on to other devices such as digital protective relays (DPRs) or digital fault recorders (DFRs). By now, thousands of terabytes of PMU data may have been captured and stored by various transmission system operators (TSOs) and independent system operators (ISOs). This creates an opportunity to deploy advanced machine learning (ML) techniques to detect and classify faults recorded by PMUs automatically to be used by the system operators for rapid, critical decision-making when manual analysis of the past or unfolding events is not feasible. In this paper we offer a brief background on how the automated fault analysis may be done using DPR and/or DFR data, and compare some of the legacy approaches to the new ML approaches in the context of the system-wide PMU recordings. We then offer insights from developing practical ML solutions that have been applied on field recordings captured by close to 450 PMUs from all three US interconnections (Western, Eastern and ERCOT) over two years (2016-2017). We identify and illustrate ML challenges we addressed: inaccurate data, data with scarce and temporally imprecise fault labels, data recorded by PMUs sparsely located at substations resulting in the fault records taken afar from the ends of the faulted lines, data containing only positive sequence values, and data taken at different voltage levels. We then illustrate the ML model results for fault analysis under different application scenarios. The novelty of this study is not only in the design, implementation, and performance analysis of the ML algorithms, but also in the use of advanced fault modelling and simulation approaches to improve the training results when developing supervised ML models for fault detection and classification. Extensive simulations of faults were conducted on a 14-bus power system to create a training dataset with over 1400 accurately labelled faults. This dataset was applied to enhance the accuracy of fault detection and classification of machine learning-based models trained with small number of labelled faults in large datasets recorded in the grid interconnections ranging from 5,000 to 70,000 buses.

Synchrophasors, Machine Learning, Fault Analysis, ↗

DOE OSTI2025

Technical Assessment of the Application of Digital Twin and Prognostic Tools for Condition Monitoring

This report was prepared for the U.S. Nuclear Regulatory Commission (NRC) to present use cases of the application of advanced technologies toward meeting the current and future regulatory requirements for maintenance and condition monitoring of structures, systems, and components (SSCs). The advanced technologies considered in this work, collectively referred to as digital twin (DT) technologies, are advanced sensors and instrumentation, data analytics, machine learning and artificial intelligence (ML/AI), and physics-based models. The report presents two use cases of reactor coolant pumps (RCPs) and heat pipes in nuclear power plants (NPPs) with technical and regulatory considerations and opportunities in using advanced technologies for conditional monitoring. Key findings from the exploration of these considerations are as follows: - Uncertainties in sensor data and model predictions must be rigorously addressed through validation and verification processes - Regulatory compliance is paramount, necessitating data driven models to be developed in line with existing codes and standards, as well as considering potential future guidelines for advanced reactors - Explainability and transparency in ML/AI models are essential for developing operator trust and regulatory review, including methods that enhance the interpretability of complex data-driven predictions - Condition monitoring programs must be evaluated for their effectiveness in reducing maintenance-preventable function failures (MPFF) and aligning with plant performance criteria - The deployment of advanced technologies for condition monitoring could lead to a transition from periodic to continuous monitoring, thereby optimizing maintenance schedules - Collaborative efforts between industry stakeholders, regulatory bodies, and technology developers are crucial for the successful adoption of advanced technologies for condition monitoring systems in nuclear facilities In summary, the introduction of advanced technologies into condition monitoring programs represents a significant leap forward in the domain of NPP maintenance. By harnessing the capabilities of advanced sensors, data analytics, and ML/AI, NPP operators can transition from a time-based to a condition-based maintenance approach. This shift can potentially enhance the reliability and safety of critical plant components while optimizing maintenance efforts and minimizing unnecessary outages. The NRC is continuing to explore the regulatory aspects of advanced technologies as part of inservice inspection and inservice testing (ISI and IST) programs by pursuing additional research in this technical area.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Digital Twin: Visualizing the Future of the Power Grid [Slides]

The energy systems are generating data at a scale and complexity that increasingly outpaces our ability to analyze it. This talk argues that rigorous, large-scale visualization is a critical tool for meeting that challenge. Drawing on recent work in the Computational Science Center at the National Laboratory of the Rockies, we trace a progression of visualization research culminating in an immersive digital twin of a real campus power grid. Along the way, we examine why visualization matters at all, where widely-used techniques quietly fail, and what becomes analytically possible when you match the display environment to the scale of the problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Responder Technology Alert Monthly (Oct-Nov 2014)

As part of technology foraging for the Responder Technology Alliance, established by the Department of Homeland Science and Technologies First Responders Group, this report summarizes technologies that are relevant in the area of “wearables,” with the potential for use by first responders. The content was collected over the previous month(s) and reproduced from a general Internet search using the term wearables. Additional information is available at the websites provided. This report is not meant to be an exhaustive list nor an endorsement of any technology described herein. Rather, it is meant to provide useful information about current developments in the areas wearable technology. The content is organized by technology function including: Sensors – Devices that detect physiological, particle, and chemical activity; Displays – Heads-up and body-worn visual displays; Power – Wearable power systems including chargers, batteries, self-powering or harvesting technologies, and power supplies; Integrated Communications – Voice and data communications systems utilizing Bluetooth, wireless, hands-free, ergonomically optimized systems, noise-filtering digital speakers or microphones, etc.; Exoskeletons – Whole or partial body suit that enhances mobility and physical performance; Wearable Computers – Body-worn data processing devices; General – Miscellaneous technologies as well as emerging trends or recent advances in the field of wearables.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2016

Simulating Regional Groundwater Flow in the Vicinity of the Nevada National Security Site, Nye County, Nevada - 16104

The Death Valley Regional Groundwater Flow System (DVRFS) occupies an area of about 70,000 km{sup 2} in south-central Nevada and southeastern California. Interest in this system stems from the need to (1) understand the groundwater flow paths and travel times associated with potential migration of radioactive material from the Nevada National Security Site (NNSS) where underground nuclear testing was conducted from 1956 to 1992; (2) characterize the groundwater system in the vicinity of the proposed high-level radioactive waste repository at Yucca Mountain, Nev.; and (3) address a variety of potential effects from NNSS activities on users down gradient from the NNSS and Yucca Mountain. A single groundwater flow model of the DVRFS has been developed that integrates data and results of two previous regional-scale models and supports Department of Energy (DOE) programs at the NNSS. The numerical model was constrained by organizing hydrogeologic data and interpretations in three-dimensional (3D) geographic information systems and constructing a digital three-dimensional (3D) hydrogeologic framework model (HFM) to represent 27 hydrogeologic units (HGUs) and major structures in the DVRFS region. The 3D hydrogeologic data sets were discretized to 1,500 meters (m) grid cell resolution for input arrays required for the model. The DVRFS was simulated using the USGS 3D groundwater-flow modeling code MODFLOW-2000. Two examples showing how the DVRFS regional model is used by the DOE as part of waste management activities at the NNSS: (1) use of the regional model to provide the boundary conditions for site-scale models, and (2) use of the regional model to assess changes in hydraulic gradient and flow paths in the regional flow system resulting from changes in pumping in various areas of interest. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Automated electrosynthesis reaction mining with multimodal large language models (MLLMs)

Leveraging the chemical data available in legacy formats such as publications and patents is a significant challenge for the community. Automated reaction mining offers a promising solution to unleash this knowledge into a learnable digital form and therefore help expedite materials and reaction discovery. However, existing reaction mining toolkits are limited to single input modalities (text or images) and cannot effectively integrate heterogeneous data that is scattered across text, tables, and figures. In this work, we go beyond single input modalities and explore multimodal large language models (MLLMs) for the analysis of diverse data inputs for automated electrosynthesis reaction mining. We compiled a test dataset of 65 articles (MERMES-T24 set) and employed it to benchmark five prominent MLLMs against two critical tasks: (i) reaction diagram parsing and (ii) resolving cross-modality data interdependencies. The frontrunner MLLM achieved ≥96% accuracy in both tasks, with the strategic integration of single-shot visual prompts and image pre-processing techniques. We integrate this capability into a toolkit named MERMES (multimodal reaction mining pipeline for electrosynthesis). Our toolkit functions as an end-to-end MLLM-powered pipeline that integrates article retrieval, information extraction and multimodal analysis for streamlining and automating knowledge extraction. This work lays the groundwork for the increased utilization of MLLMs to accelerate the digitization of chemistry knowledge for data-driven research.

Leong, Shi Xuan↗

DOE OSTI2012

THE MASSIVE DISTANT CLUSTERS OF WISE SURVEY: THE FIRST DISTANT GALAXY CLUSTER DISCOVERED BY WISE

We present spectroscopic confirmation of a z = 0.99 galaxy cluster discovered using data from the Wide-field Infrared Survey Explorer (WISE). This is the first z {approx} 1 cluster candidate from the Massive Distant Clusters of WISE Survey to be confirmed. It was selected as an overdensity of probable z {approx}> 1 sources using a combination of WISE and Sloan Digital Sky Survey DR8 photometric catalogs. Deeper follow-up imaging data from Subaru and WIYN reveal the cluster to be a rich system of galaxies, and multi-object spectroscopic observations from Keck confirm five cluster members at z = 0.99. The detection and confirmation of this cluster represents a first step toward constructing a uniformly selected sample of distant, high-mass galaxy clusters over the full extragalactic sky using WISE data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Digital Pulse-Shape Discrimination Applied to an Ultra-Low-Background Gas-Proportional Counting System: First Results

Abstract A new ultra-low-background proportional counter (ULBPC) design was recently developed at Pacific Northwest National Laboratory (PNNL). This design, along with an ultra-low-background counting system (ULBCS) which provides passive and active shielding with radon exclusion, has been developed to complement a new shallow underground laboratory (~30 meters water-equivalent) constructed at PNNL. After these steps to mitigate dominant backgrounds (cosmic rays, external gamma-rays, radioactivity in materials), remaining background events do not exclusively arise from ionization of the proportional counter gas. Digital pulse-shape discrimination (PSD) is thus employed to further improve measurement sensitivity. In this work, a template shape is generated for each individual sample measurement of interest, a "self-calibrating" template. Differences in event topology can also cause differences in pulse shape. In this work, the temporal region analyzed for each event is refined to maximize background discrimination while avoiding unwanted sensitivity to event topology. This digital PSD method is applied to sample and background data, and initial measurement results from a biofuel methane sample are presented in the context of low-background measurements currently being developed.

signal processing, pulse-shape discrimination, pro↗

DOE OSTI2019

Calculation of the cross and auto power spectral densities for low neutron counting from pulse mode detectors

Here, this report introduces a methodology to calculate the prompt neutron decay constant of a subcritical assembly from the cross and auto power spectral densities of detectors operating in pulse mode when the neutron counting is low. The pulse operation mode allows the easy discrimination of the gamma contribution to the detector signal by the pulse height or shape techniques. The methodology is based on a MATLAB script that allows to change arbitrary parameters at any time after the experiment is performed. This technique requires list mode data and is much more flexible than programming the digital acquisition system because in the latter case the arbitrary parameters are set prior to the experiment and cannot be changed any longer after the experiment is performed. The MATLAB script processes all the detectors timestamps from several thousand pulses of the particle accelerator and redistributes them into a time interval that spreads over only 10 particle accelerator pulses. This pulses collapsing procedure has been performed because of the low neutron counting.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Graphene overcoats for ultra-high storage density magnetic media

Hard disk drives (HDDs) are used as secondary storage in digital electronic devices owing to low cost and large data storage capacity. Due to the exponentially increasing amount of data, there is a need to increase areal storage densities beyond ~1 Tb/in 2 . This requires the thickness of carbon overcoats (COCs) to be <2 nm. However, friction, wear, corrosion, and thermal stability are critical concerns below 2 nm, limiting current technology, and restricting COC integration with heat assisted magnetic recording technology (HAMR). Here we show that graphene-based overcoats can overcome all these limitations, and achieve two-fold reduction in friction and provide better corrosion and wear resistance than state-of-the-art COCs, while withstanding HAMR conditions. Thus, we expect that graphene overcoats may enable the development of 4–10 Tb/in 2 areal density HDDs when employing suitable recording technologies, such as HAMR and HAMR+bit patterned media.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Economical Laue x-ray diffraction using photographic film and orientation of single crystals

Many Laue x-ray diffraction systems using the Polaroid XR-7 Land Diffraction Cassette camera became inactive after production of the required high sensitivity Polaroid T-57 instant film ceased. This Tutorial reports on a low-cost solution using the readily available replacement film with push processing to increase the effective film speed. The use of this film in the polaroid camera is described along with film development and digitization. The orientation of single crystals with the obtained data and free software is explained. A simple method to prepare single crystals with surfaces perpendicular to a desired crystallographic orientation is described. The content of this Tutorial may prove beneficial for educational and research laboratories.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Advanced Reactor Control and Operations (ARCO): A University Research Facility for Developing Optimized Digital Control Rooms

The Advanced Reactor Control and Operations (ARCO) facility was constructed in January 2018 to serve as a test bed for advanced reactor control rooms and operator support systems. Since then, it has supported human-machine interface user experience research, fault detection and mitigation technology development, control room concept of operations development, and remote operations research. ARCO serves as the control room for the Compact Integral Effects Test (CIET) facility, which replicates the primary-side flow paths and thermal-hydraulic behavior of a fluoride-salt-cooled high-temperature reactor (FHR) using simulant fluids and scaling principles. New reactor designs feature different operating conditions and scenarios than those in existing reactors. ARCO supports the research and development of digital tools for operator communications, intuitive real-time data analysis, online health monitoring and prognostics, and control room cybersecurity. By integrating these different technologies, ARCO acts as a prototypical control system to iteratively develop methods and tools of operation in advanced small modular nuclear reactors. This paper describes the features of and challenges to operating advanced small modular reactors underlying the design basis for ARCO and its operator support systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

Multifrequency spectrum analysis using fully digital G Mode-Kelvin probe force microscopy

Since its inception over two decades ago, Kelvin probe force microscopy (KPFM) has become the standard technique for characterizing electrostatic, electrochemical and electronic properties at the nanoscale. In this work, we present a purely digital, software-based approach to KPFM utilizing big data acquisition and analysis methods. General Mode (G-Mode) KPFM, works by capturing the entire photodetector data stream, typically at the sampling rate limit, followed by subsequent de-noising, analysis and compression of the cantilever response. We demonstrate that the G-Mode approach allows simultaneous multi-harmonic detection, combined with on-the-fly transfer function correction required for quantitative CPD mapping. The KPFM approach outlined in this work significantly simplifies the technique by avoiding cumbersome instrumentation optimization steps (i.e. lock in parameters, feedback gains etc.), while also retaining the flexibility to be implemented on any atomic force microscopy platform. We demonstrate the added advantages of G-Mode KPFM by allowing simultaneous mapping of CPD and capacitance gradient (C') channels as well as increased flexibility in data exploration across frequency, time, space, and noise domains. As a result, G-Mode KPFM is particularly suitable for characterizing voltage sensitive materials or for operation in conductive electrolytes, and will be useful for probing electrodynamics in photovoltaics, liquids and ionic conductors.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The completed SDSS-IV extended baryon oscillation spectroscopic survey: geometry and growth from the anisotropic void–galaxy correlation function in the luminous red galaxy sample

ABSTRACT We present an analysis of the anisotropic redshift-space void–galaxy correlation in configuration space using the Sloan Digital Sky Survey extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 luminous red galaxy (LRG) sample. This sample consists of LRGs between redshifts 0.6 and 1.0, combined with the high redshift z > 0.6 tail of the Baryon Oscillation Spectroscopic Survey Data Release 12 CMASS sample. We use a reconstruction method to undo redshift-space distortion (RSD) effects from the galaxy field before applying a watershed void-finding algorithm to remove bias from the void selection. We then perform a joint fit to the multipole moments of the correlation function for the growth rate fσ8 and the geometrical distance ratio DM/DH, finding $f\sigma _8(z_\rm {eff})=0.356\pm 0.079$ and $D_M/D_H(z_\rm {eff})=0.868\pm 0.017$ at the effective redshift $z_\rm {eff}=0.69$ of the sample. The posterior parameter degeneracies are orthogonal to those from galaxy clustering analyses applied to the same data, and the constraint achieved on DM/DH is significantly tighter. In combination with the consensus galaxy BAO and full-shape analyses of the same sample, we obtain fσ8 = 0.447 ± 0.039, DM/rd = 17.48 ± 0.23, and DH/rd = 20.10 ± 0.34. These values are in good agreement with the ΛCDM model predictions and represent reductions in the uncertainties of $13{{\ \rm per\ cent}}$, $23{{\ \rm per\ cent}}$, and $28{{\ \rm per\ cent}}$, respectively, compared to the combined results from galaxy clustering, or an overall reduction of 55 per cent in the allowed volume of parameter space.

Nadathur, Seshadri↗

DOE OSTI2020

Testing general relativity on cosmological scales at redshift z ∼ 1.5 with quasar and CMB lensing

ABSTRACT We test general relativity (GR) at the effective redshift $\bar{z} \sim 1.5$ by estimating the statistic EG, a probe of gravity, on cosmological scales $19 - 190\, h^{-1}{\rm Mpc}$. This is the highest redshift and largest scale estimation of EG so far. We use the quasar sample with redshifts 0.8 < z < 2.2 from Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 16 as the large-scale structure (LSS) tracer, for which the angular power spectrum $C_\ell ^{qq}$ and the redshift-space distortion parameter β are estimated. By cross-correlating with the Planck 2018 cosmic microwave background (CMB) lensing map, we detect the angular cross-power spectrum $C_\ell ^{\kappa q}$ signal at $12\, \sigma$ significance. Both jackknife resampling and simulations are used to estimate the covariance matrix (CM) of EG at five bins covering different scales, with the later preferred for its better constraints on the covariances. We find EG estimates agree with the GR prediction at $1\, \sigma$ level over all these scales. With the CM estimated with 300 simulations, we report a best-fitting scale-averaged estimate of $E_G(\bar{z})=0.30\pm 0.05$, which is in line with the GR prediction $E_G^{\rm GR}(\bar{z})=0.33$ with Planck 2018 CMB + BAO matter density fraction Ωm = 0.31. The statistical errors of EG with future LSS surveys at similar redshifts will be reduced by an order of magnitude, which makes it possible to constrain modified gravity models.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Abell 1033: birth of a radio phoenix

We report that extended steep-spectrum radio emission in a galaxy cluster is usually associated with a recent merger. However, given the complex scenario of galaxy cluster mergers, many of the discovered sources hardly fit into the strict boundaries of a precise taxonomy. This is especially true for radio phoenixes that do not have very well defined observational criteria. Radio phoenixes are aged radio galaxy lobes whose emission is reactivated by compression or other mechanisms. Here in this paper, we present the detection of a radio phoenix close to the moment of its formation. The source is located in Abell 1033, a peculiar galaxy cluster which underwent a recent merger. To support our claim, we present unpublished Westerbork Synthesis Radio Telescope and Chandra observations together with archival data from the Very Large Array and the Sloan Digital Sky Survey. We discover the presence of two subclusters displaced along the N–S direction. The two subclusters probably underwent a recent merger which is the cause of a moderately perturbed X-ray brightness distribution. A steep-spectrum extended radio source very close to an active galactic nucleus (AGN) is proposed to be a newly born radio phoenix: the AGN lobes have been displaced/compressed by shocks formed during the merger event. This scenario explains the source location, morphology, spectral index, and brightness. Finally, we show evidence of a density discontinuity close to the radio phoenix and discuss the consequences of its presence.

79 ASTRONOMY AND ASTROPHYSICS↗