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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

An updated estimate of the Mu2e experiment sensitivity

The Mu2e experiment at Fermilab will search for the conversion of a negative muon into an electron inside the field of a nucleus. This process does not conserve charged-lepton flavour and is heavily suppressed in the Standard Model (SM), with a branching ratio < 10-50. Any evidence of it would be an undeniable evidence of new physics beyond the SM. The project sets out to achieve a single event sensitivity of $\sim 3 × 10^{-17}$ on the ratio between the probability for a conversion of a negative muon into an electron and the one for a muon capture by the nucleus. Such a sensitivity would represent a 4 orders of magnitude improvement on the previous upper limit for the process, making possible to test predictions of different extensions of the SM. Mu2e uses three superconducting solenoids to produce and measure the muon conversions. In the first solenoid, the Production Solenoid, pions and kaons are produced, together with other secondary products, by 8 GeV kinetic energy proton interactions in a tungsten target. A gradient magnetic field is specifically designed to direct low momentum particles into the Transport Solenoid, an S-shaped magnet that filters out particles with unwanted charge and momentum. Muons, produced by pion and kaon decays, finally reach the aluminum Stopping Target in the Detector Solenoid, where they eventually stop and convert. The result of the conversion process is a monochromatic electron of ~105 MeV/c momentum. The Detector Solenoid also hosts the two main detectors: a straw tube tracker and two CsI calorimeter disks, both providing measurement of event kinematics. A germanium detector and a LaBr crystal are located downstream of the Detector Solenoid to measure the X and gamma rays produced by the muon captures in the Stopping Target. A veto system of scintillators covering the Detector Solenoid and half of the Transport Solenoid is used to identify and reject cosmic rays interactions. With respect to the initial project, the Mu2e running plan has evolved to a staged configuration with 2 years at reduced intensity before the 2025 accelerator shutdown for the neutrino beam upgrade and 2 or 3 years at full intensity after that. This, together with geometry changes and a better knowledge of detector performances obtained by the first slice tests, has required a full revision of the signal over background selection that is the subject of this thesis. In order to achieve a new estimate of Mu2e sensitivity, the simulation of the data corresponding to the first 2 years of data acquisition has been performed. This includes both conversion electrons (CE) and the main sources of background: cosmics, decay-in orbits (DIO), radiative pion captures (RPC) and antiprotons. The characteristics of the signal and of the main backgrounds have been studied to define the best selection variables for CE. A special effort has been devoted to the evaluation of the antiproton background. The lack of experimental data for antiproton production cross section makes the systematic uncertainty on this background significant. A new parameterization of the cross section has been developed to fit the existing data and to provide a more reliable estimate of the systematic uncertainty by comparing the results of the old and the new model. A special effort has been devoted to the optimization of the antiprotons Monte Carlo generator. This study has also revealed that the dominant component within this background is represented by antiprotons produced in the opposite direction with respect to the Transport Solenoid entrance and then redirected to it by back-scattering processes in the Production Target. This ultimately highlights the sensitivity of the background estimate to the G4 handling of antiproton interactions in the 1 to 3 GeV/c momentum range. Finally, the final experimental sensitivity has been studied. The momentum and time selection have been optimized to obtain the 5-sigma discovery reach or, in case of no signal, the upper limit on conversion probability. The results confirm that, in the firs t two years of data taking, Mu2e will be able to improve the current experimental sensitivity for muon-to-electron conversion in an atomic field by more than 3 order of magnitudes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

FORTE Measurements of Global Optical Lightning Waveforms and Implications for Optical Lightning Detection

Lightning processes generate a diverse collection of optical pulses from current traversing the lightning channels. These signals are then broadened spatially and temporally via scattering in the clouds. The resulting waveforms measured from space with instruments like the photodiode detector (PDD) on the Fast On-orbit Recording of Transient Events (FORTE) satellite have a variety of shapes. In this study, we use coincident optical and Radio-Frequency measurements to document the properties of optical PDD waveforms associated with different types of lightning, estimate delays from scattering in the clouds, and comment on how pulse shape impacts optical lightning detection. We find that the attributes of optical pulses recorded by the PDD are consistent with prior studies, but vary globally and with event amplitude. The most powerful lightning tends to be single-peaked with faster rise times (median: ~100 µs) and shorter effective widths (median: ~400 µs) than normal lightning. Particularly dim events, meanwhile, include cases of broad optical waveforms with sustained optical emission throughout the PDD record, which the pixelated FORTE Lightning Location System (LLS) instrument has difficulty detecting. We propose that this is due to the optical signal being divided between individual LLS pixels that are each, individually, not bright enough to trigger. We use PDD waveforms and Monte Carlo radiative transfer modeling to demonstrate that increasing the temporal and spatial resolution of a pixelated lightning imager will make it more difficult to detect these broad/dim pulses as their energy becomes divided between additional pixels/integration frames.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Classification and Localization of Fracture-Hit Events in Low-Frequency Distributed Acoustic Sensing Strain Rate with Convolutional Neural Networks

Summary Distributed acoustic sensing (DAS) has been used in the oil and gas industry as an advanced technology for surveillance and diagnostics. Operators use DAS to monitor hydraulic fracturing activities, examine well stimulation efficacy, and estimate complex fracture system geometries. Particularly, low-frequency DAS can detect geomechanical events such as fracture hits because hydraulic fractures propagate and create strain rate variations in the rock. Analysis of DAS data today is mostly done post-job and subject to interpretation methods. However, the continuous and dense data stream generated live by DAS poses the opportunity for more efficient and accurate real-time data-driven analysis. The objective of this study is to develop a machine learning-based workflow that can identify and locate fracture-hit events in simulated strain rate responses correlated with low-frequency DAS data. In this paper, “fracture hit” refers to a hydraulic fracture originating from a stimulated well intersecting an offset well. We start with building a single fracture propagation model to produce strain rate patterns observed at a hypothetical monitoring well. This model is used to generate two sets of strain rate responses with one set containing fracture-hit events. The labeled synthetic data are then used to train a custom convolutional neural network (CNN) model for identifying the presence of fracture-hit events. The same model is trained again for locating the event with the output layer of the model replaced with linear units. We achieved near-perfect predictions for both event classification and localization. These promising results prove the feasibility of using CNN for real-time event detection from fiber-optic sensing data. Additionally, we use edge detection techniques to recognize fracture-hit event patterns in strain rate images. The fracture-hit location can be identified using recognized pixels in the image. The accuracy of edge detection-based location identification is also plausible, but edge detection is dependent on the assumption of pattern shape and image quality, hence it is less robust compared to CNN models. This comparison further supports the need for CNN applications in image-based real-time fiber-optic sensing event detection.

Engineering↗
DOE OSTI2023

Seismoacoustic Analysis of the Large Surface Explosion Coupling Experiment Using a Large- N Seismic Array

Seismoacoustic signals at local distance (<~10 km) are widely used as important constraints on source parameters for near-surface events, yet the seismoacoustic wave generation and energy partitioning are not fully understood. Spatially dense sensors could provide observations in high resolution to capture the full wavefield for better understanding wave propagation and improving source estimation. Recently, spatially dense observations of the local seismoacoustic wavefield produced by a pair of 1-ton surface explosions have been recorded using a large-N seismic array. This large-N array consists of 446 geophones and covers an area of approximately 2×2.5 km 2 . The two surface explosions occur at the same location but at different times with different atmospheric conditions. Both seismic and air–ground coupled acoustic waves from the two surface explosions are well observed. Analyses of signals recorded by the large-N seismic array show different acoustic wave speed and amplitude for the two explosions. A strong spatial variability in acoustic wave speed and amplitude for each explosion is also observed. Finally, the observations suggest the important role of local atmosphere state on wave propagation and source estimation and demonstrate how the use of a large-N capability can improve characterization of the propagation medium and source.

58 GEOSCIENCES↗
DOE OSTI2022

Variability and Spectral Characteristics of Three Flaring Gamma-Ray Quasars Observed by VERITAS and Fermi-LAT

Flat-spectrum radio quasars (FSRQs) are the most luminous blazars at GeV energies but only rarely emit detectable fluxes of TeV gamma rays, typically during bright GeV flares. We explore the gamma-ray variability and spectral characteristics of three FSRQs that have been observed at GeV and TeV energies by Fermi-LAT and VERITAS, making use of almost 100 hr of VERITAS observations spread over 10 yr: 3C 279, PKS 1222+216, and Ton 599. We explain the GeV flux distributions of the sources in terms of a model derived from a stochastic differential equation describing fluctuations in the magnetic field in the accretion disk and estimate the timescales of magnetic flux accumulation and stochastic instabilities in their accretion disks. We identify distinct flares using a procedure based on Bayesian blocks and analyze their daily and subdaily variability and gamma-ray energy spectra. Using observations from VERITAS, as well as Fermi, Swift, and the Steward Observatory, we model the broadband spectral energy distributions of PKS 1222+216 and Ton 599 during very high energy (VHE)–detected flares in 2014 and 2017, respectively, strongly constraining the jet Doppler factors and gamma-ray emission region locations during these events. Finally, we place theoretical constraints on the potential production of PeV-scale neutrinos during these VHE flares.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Modeling Subsurface Explosions Recorded on a Distributed Fiber Optic Sensor

Fiber optic distributed acoustic sensors (DAS) are becoming a widely used tool for seismic sensing. Here we examine recordings of two subsurface chemical explosions, DAG-1 and DAG-3, each of which was about one metric ton (TNT equivalent), that were recorded from a helical fiber installed in two boreholes 80 m away from the source location. Several clear phases including the initial P wave, a weak S wave, and a surface reflected P wave are observed on the helical DAS data. We estimate a velocity model using arrival times measured from the fiber. The DAS waveform data were compared with colocated accelerometers at specific depths in both frequency and time domains. Furthermore, the spectra of the DAS data matched spectra estimated from the accelerometer records. Comparisons of observed waveform shape between the accelerometer records and the fiber measurements (strain-rate) show reasonable agreement except for the data near the event depth. The DAS data and the accelerometer agreed in relative amplitudes but we had difficulties in matching absolute amplitudes, possibly due to errors in metadata. Synthetic strain-rate waveforms were calculated using a 2D wavenumber algorithm and matched the waveform shape and relative amplitudes. In general, DAS is effective at recording strong ground motions at high spatial density. Comparison of the synthetic seismograms with observed data indicate that the waveforms are not consistent with a pure isotropic explosion source and that the observed S waves originate from very near the source region.

58 GEOSCIENCES↗
DOE OSTI2022

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Consumer Benefits of Clean Energy: The resilience value of residential solar + storage systems in the continental U.S.

Meeting national and state decarbonization goals requires a transition to clean energy technologies. Energy efficiency, demand flexibility, renewable energy and storage can reduce consumers’ electricity bills, lower total electricity system costs, and provide health and resilience benefits. Berkeley Lab developed a series of briefs that explore these consumer benefits of a clean energy transition. Clean energy resources that are located behind the meter have the potential to benefit the hosting customers by providing affordability, environmental, and reliability and resilience value. Solar plus storage systems (PVESS) are clean energy resources that can supply backup power without requiring fuel resupply or increasing local emissions. This report examines the regional value of PVESS for resilience by calculating a benefit-cost ratio (BCR) that considers the annual resiliency benefits of PVESS and the annualized cost of the investment. In addition, we estimate the expected technical mitigation potential of PVESS systems at the county-level to these expected events, and characterize the customer interruption costs by determining the value of lost load at the state level.

14 SOLAR ENERGY↗
DOE OSTI2024

Insights on seasonal solifluction processes in warm permafrost Arctic landscape using a dense monitoring approach across adjacent hillslopes

Solifluction processes in the Arctic are highly complex, introducing uncertainties in estimating current and future soil carbon storage and fluxes, and assessment of hillslope and infrastructure stability. This study aims to enhance our understanding of triggers and drivers of soil movement of permafrost-affected hillslopes in the Arctic. To achieve this, we established an extensive soil deformation and temperature sensor network, covering 48 locations across multiple hillslopes within a 1 km² watershed on the Seward Peninsula, AK. We report depth-resolved measurements down to 1.8 m depth for May to September 2022, a period conducive to soil movement due to deepening thaw layers and frequent rain events. Over this period, surface movements of up to 334 mm were recorded. In general, these movements occur close to the thawing front, and are initiated as thawing reaches depths of 0.4 to 0.75 m. The largest movements were observed at the top of the south-east facing slope, where soil temperatures are cold (mean annual soil temperatures averaging -1.13°C) and slopes are steeper than 15°. Our analysis highlights three primary factors influencing movements: slope angle, soil thermal conditions, and thaw depth. The latter two significantly impact the generation of pore water pressures at the thaw–freeze interface. Specifically, soil thermal conditions govern the liquid water content, while thaw depth influences both the height of the water column and, consequently, the pressure at the thawing front. These factors affect soil properties, such as cohesion and internal friction angle, which are crucial determinants of slope stability. This underscores the significance of a precise understanding of subsurface thermal conditions, including spatial and temporal variability in soil temperature and thaw depth, when assessing and predicting slope instabilities. Based on our observations, we developed a Factor of Safety proxy that consistently falls below the triggering threshold for all probes exhibiting displacements exceeding 50 mm. This study offers novel insights into patterns and triggers of hillslope movements in the Arctic and provides a venue to evaluate their impact on soil redistribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Reassessing Double-Ended Guillotine Break Requirements: Evidence-Based Analysis of Regulatory Assumptions After Five Decades of Nuclear Operation

After five decades of nuclear power operation encompassing more than 20,000 reactor-years across 35 countries and 647 reactors, zero double-ended guillotine breaks (DEGBs) have been documented in commercial reactor coolant systems—despite DEGB being the fundamental design-basis assumption driving Emergency Core Cooling System (ECCS) sizing, structural protection requirements, and containment design specifications. This report examines the basis for DEGB requirements in nuclear power plant design. The DEGB postulate assumes the instantaneous, complete circumferential severance of the largest diameter pipes in reactor coolant systems, driving major design requirements under 10 Code of Federal Regulations 50.46, General Design Criterion 4 and containment design specifications. The United States (4,880 reactor-years) and France (2,505 reactor-years) contribute the largest operational datasets. Probabilistic assessments estimate direct DEGB occurrence probabilities with extremely low event frequencies, far below the 10-5/reactor-year thresholds typically used to define non-credible events in nuclear-safety analyses; i.e., events with probability this low fall into beyond-design-basis events. Current material-science knowledge demonstrates that the ductile steel materials used in nuclear piping systems exhibit stable crack-growth behavior fundamentally incompatible with instantaneous severance. International regulatory experience, particularly Germany’s comprehensive break-preclusion implementation, and successful leak-before-break (LBB) applications in almost all of U.S. pressurized water reactor units validate that alternatives can maintain safety performance while reducing economic burden. Current DEGB protection systems impose estimated lifetime costs of hundreds of millions of dollars per unit, over the life of a plant across the nuclear industry (including ongoing costs), representing substantial resource allocation toward scenarios with extremely low probability. Although this report acknowledges uncertainties regarding long-term aging effects, potential synergistic degradation mechanisms, and site-specific seismic considerations that warrant continued evaluation as regulatory policy evolves, there remains no documented evidence that a DEGB has occurred as a consequence of the conditions or mechanisms described in this report. This report acknowledges the Nuclear Regulatory Commission’s (NRC’s) recent efforts—outlined in the draft Interim Staff Guidance (ISG) NRC-DSS-ISG-2025-XX (“Treatment of Certain Loss-of-Coolant Accident Locations as Beyond-Design-Basis Accidents Draft Interim Staff Guidance”)—to reduce overly conservative requirements for large-break loss of coolant accidents through technical justifications and exemptions. However, extensive operating experience and validated methodologies—such as LBB and in-service inspection programs—demonstrate that the probability of a DEGB in reactor coolant-loop piping is extremely low, even under seismic conditions. The authors and reviewers of this report recommend that DEGB be removed as a design-basis event through formal rulemaking, rather than case-by-case exemptions, to better reflect credible failure modes, align with current data, and align with modern, risk-informed safety analysis.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Locating Partial Discharges in Power Transformers with Convolutional Iterative Filtering

The most common source of transformer failure is in the insulation, and the most prevalent warning signal for insulation weakness is partial discharge (PD). Locating the positions of these partial discharges would help repair the transformer to prevent failures. This work investigates algorithms that could be deployed to locate the position of a PD event using data from ultra-high frequency (UHF) sensors inside the transformer. These algorithms typically proceed in two steps: first determining the signal arrival time, and then locating the position based on time differences. This paper reviews available methods for each task and then propose new algorithms: a convolutional iterative filter with thresholding (CIFT) to determine the signal arrival time and a reference table of travel times to resolve the source location. The effectiveness of these algorithms are tested with a set of laboratory-triggered PD events and two sets of simulated PD events inside transformers in production use. Tests show the new approach provides more accurate locations than the best-known data analysis algorithms, and the difference is particularly large, 3.7X, when the signal sources are far from sensors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Social inequalities in climate change-attributed impacts of Hurricane Harvey

Climate change is already increasing the severity of extreme weather events such as with rainfall during hurricanes. But little research to date investigates if, and to what extent, there are social inequalities in climate change-attributed extreme weather event impacts. Here, we use climate change attribution science paired with hydrological flood models to estimate climate change-attributed flood depths and damages during Hurricane Harvey in Harris County, Texas. Using detailed land-parcel and census tract socio-economic data, we then describe the socio-spatial characteristics associated with these climate change-induced impacts. We show that 30 to 50% of the flooded properties would not have flooded without climate change. Climate change-attributed impacts were particularly felt in Latina/x/o neighborhoods, and especially so in Latina/x/o neighborhoods that were low-income and among those located outside of FEMA’s 100-year floodplain. Our focus is thus on climate justice challenges that not only concern future climate change-induced risks, but are already affecting vulnerable populations disproportionately now.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Beam Dump eXperiment

Hadronic matter makes about 14% of the known universe. The remaining 86% is Dark Matter (DM). Since it does not interact with the ordinary matter via electromagnetic force, DM is not visible and, to date, it escaped detection. The search for Dark Matter (DM) is one of the hottest topic in modern physics. Despite the increasing number of astrophysical and cosmological observations proving the existence, so far no particle physics experiment has detected DM yet. Up to now, most of the experimental efforts have been focused on the so called WIMP (Weakly Interacting Massive Particle) paradigm, which predicts heavy DM (10 GeV-10 TeV mass range) interacting with Standard Model (SM) particles via the weak force mediators (W or Z bosons). More recently, due to the lack of clear evidence of WIMPs, other models of DM gained the interest of the physics community. These models consider Light DM particles (LDM), in MeV-GeV mass range. Among LDM theories, the Dark Photon theory predicts the existence of a Dark Sector interacting with SM particles via a new massive vector boson (Dark Photon, Heavy Photon or A0), mediator of a new force. This scenario, despite being theoretically well motivated, is remarkably experimentally unexplored. The Beam Dump eXperiment (BDX), is an approved experiment at Jefferson Lab (JLab), aiming to discover the DM predicted witihn the Dark Photon theory. The experiment uses the CEBAF (Continuous Electron Beam Accelerator Facility) 11 GeV electron beam, impinging on the JLab Hall-A beam-dump, to produce a beam of DM particles, detected by a ~ 1 m3 detector made of thallium doped cesium iodide (CsI(Tl)) crystals located ~ 20 m downstream. In order to achieve excellent background rejection, the experimental setup includes active vetos and passive shielding surrounding CsI(Tl) crystals. Given the weakness of the DM-SM interaction, the scattering of a DM particle in the BDX detector is a rare event. Therefore, the characterization of the expected background is a critical aspect of the experiment. Both cosmogenic and penetrating SM particles produced by the beam interaction in the dump contribute to the background of the experiment. While the cosmogenic contribution can be measured during the experiment when the beam is off, beam-related background can only be estimated via Monte Carlo (MC) simulations. Therefore, a careful assessment of possible systematics introduced by the MC is needed. The beam-correlated background characterization was made by measuring the muon flux produced by the interaction of the CEBAF beam with Hall-A dump in a dedicated experimental campaign in spring 2018 [1]. The comparison to the ?ux predicted by MC allowed us to validate the BDX simulation framework. The reach of BDX, i.e. the region that the experiment can probe in the LDM theory parameter space, depends critically on the background rejection capability and signal detection effciency. For this reason, the detector setup was fine-tuned through a dedicated study. The response to LDM and background events was evaluated for different setups and selection cuts. As a result of this procedure, the configuration resulting in the best sensitivity was selected [2]. The reach calculation was performed taking into account the different LDM production mechanisms, including the contribution of secondary particles produced in the beam-dump. In particular, the effect of the secondary positrons annihilation was found to be extremely significant. In the majority of the sensitivity studies, this contribution is neglected, but recent results [3] [4] demonstrated that this process significantly enhances the sensitivity of lepton beam-dump experiments. Currently, the BDX collaboration is focused on the deployment and operation of a small detector, called BDX-MINI, built to perform a preliminary physics measurement searching for LDM at JLab. This test will pave the way to the realization of the full BDX experiment. The measurement is currently ongoing but results are expected by the end of this year. During my PhD I was involved in all aspects of the BDX experiment: design, simulation, prototyping and data analysis. The main results of my work are reported in this thesis. This manuscript is organized as follows: the first Chapter provides an introduction to the theory of LDM, with particular attention to the Dark Photon paradigm; the second Chapter illustrates the BDX experimental setup, the LDM production and detection mechanisms and the expected backgrounds; Chapter 3 and 4 describe, respectively, the BDX-HODO measurement, with a detailed description of the simulations, and the BDX experimental setup and analysis cuts optimization. Chapter 5 reports about BDXMINI detector characterization, calibration and sensitivity estimate. Finally, Chapter 6 describes in detail the calculation of the secondary positron annihilation contribution to the sensitivity of BDX and other electron-beam thick-target experiment.

Marsicano, Luca↗
DOE OSTI2020

Real Time Applications Using Linear State Estimation Technology (RTA/LSE)

Electric Power Group, LLC (EPG) was awarded DOE OE0000849 to design, develop, and demonstrate three real-time applications for monitoring power system stability. The applications use phasor measurements and processing by a linear state estimator (LSE) to improve system visibility and accuracy. These applications leverage the large and expanding phasor measurement systems being deployed by utilities throughout the world, and specifically in the United States. Phasor measurements provide a much more detailed view of the power systems than traditional SCADA systems, so can provide better visibility of events and an early warning of developing problems. These three applications are real-time contingency analysis (RTCA), area angle monitoring (AAM), and a voltage stability index (VSI). The project was fully completed as proposed. All three applications were successfully implemented and demonstrated. There were challenges the caused project delays, however. While the RTCA is based on well-known concepts and readily available tools, its deployment using phasor measurements meant it needed to be adapted to sometimes sparse measurements and limited coverage areas. EPG met these challenges with extensive modeling and testing. The AAM is based on unproven research, so EPG had to deal with a lot of unknowns and develop additional methods for practical implementation. These activities took more time than anticipated, so required extra time for development. In addition, there was difficulty getting adequate measurement locations for successful deployment and utility installation delays. Consequently, the project required a time extension to complete. These three real-time applications, RTCA, AAM, and VSI, use only phasor measurement input. Since they do not require the EMS or other measurement systems, they can serve as a backup and security check for the EMS. Phasor measurements are validated and extended by an LSE. The LSE will always produce an output even when some inputs are impaired, so the RT applications will operate even when the EMS state estimator does not converge and the applications it supports cannot function. Consequently, these RT applications can provide valuable additional reliability for control center operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Comparing generator predictions of transverse kinematic imbalance in neutrino-argon scattering

The largest uncertainties in estimating neutrino-nucleus interaction cross sections lie in the incomplete understanding of nuclear effects. A powerful tool to study nuclear effects is Transverse Kinematic Imbalance. This paper presents the first detailed comparison of the predictions of multiple event generators for distributions associated with Transverse Kinematic Imbalance for neutrino interactions on argon. Predictions for muon neutrinos interacting with an argon target are obtained using four standard neutrino event generation tools (GENIE, NuWro, GiBUU and NEUT). Example opportunities for discrimination between nuclear models leveraging future measurements are highlighted. The predictions shown in this paper are motivated by studying muon neutrinos from the Fermilab Booster Neutrino Beam interacting at the location of the MicroBooNE liquid argon time projection chamber, but the methods directly apply to other accelerator-based liquid argon neutrino experiments such as SBND, ICARUS and DUNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

An Overview of the State-of-the-Art Reactor Consequence Uncertainty Assessment Accident Progression Insights

The U.S. Nuclear Regulatory Commission (NRC) with Sandia National Laboratories (Sandia) have completed three uncertainty analyses (UAs) as part of the State-of-the-Art Reactor Consequence Analyses (SOARCA) program. The SOARCA UAs included an integrated evaluation of uncertainty in accident progression, radiological release, and offsite health consequence projections. The UA for Peach Bottom, a boiling-water reactor (BWR) with a Mark I containment located in the State of Pennsylvania, analyzed the unmitigated long-term station blackout SOARCA scenario. The UA for Sequoyah, a 4-loop Westinghouse pressurized-water reactor (PWR) located in the State of Tennessee, analyzed the unmitigated short-term station blackout SOARCA scenario, with a focus on issues unique to the ice condenser containment and the potential for early containment failure due to hydrogen deflagration. The UA for Surry, a 3-loop Westinghouse PWR with a sub-atmospheric large dry containment located in the State of Virginia, analyzed the unmitigated short-term station blackout SOARCA scenario including the potential for thermally-induced steam-generator tube rupture. These three UAs are currently documented in three NUREG/CR reports. This report provides input to planned NRC documentation on the insights and findings from the SOARCA UA program. The purpose of the summary report is to provide a useful reference for regulatory applications that require the evaluation of offsite consequence risk from beyond design basis event severe accidents. This report focuses on the accident progression and source term insights developed from the MELCOR analyses. MELCOR is the NRC's best-estimate, severe accident computer code used in the SOARCA UAs. In anticipation of the SOARCA UA insights work, NRC and Sandia benchmarked the response of the Peach Bottom model to selected reference calculations from the Peach Bottom SOARCA UA. Peach Bottom was the first SOARCA UA performed and was completed in 2015 using the MELCOR 1.8.6 code. The PWR SOARCA UAs evolved the original methodology and utilized the updated MELCOR 2.2 computer code. The Peach Bottom model has been systematically updated for other NRC research efforts and has been updated to MELCOR 2.2. computer code. The findings from the new reference calculations using the updated model with the MELCOR 2.2 code are also integrated into the report. A second objective is an assessment of the applicability of the results to the other nuclear reactors in the U.S. As the key findings are reviewed, judgments are presented on the applicability of the results to other U.S. nuclear power plants. An important objective of the SOARCA program relied on high- fidelity plant-specific modeling. However, the nature of the insights and conclusions allowed judgements to be made on the applicability of the various insights to the same general classification of plant (i.e., BWR or PWR) or the entire fleet of plants. Finally, the results from the SOARCA UA accident progression calculations contain a wealth of information not previously documented in the NUREG/CRs. This report includes new but related information that can be used to benchmark past or support future regulatory decisions related to severe accidents. The new work includes a benchmark of the NUREG-1465 licensing source term definitions, the variability of key accident progression events and timing to radionuclide release, and an improved understanding of the timing and source terms from consequential steam generator tube ruptures. iii ACKNOWLEDGEMENTS The Sandia authors gratefully acknowledge the significant technical and programmatic contributions from the NRC SOARCA team which are reflected throughout the report. Dr. Tina Ghosh has been involved throughout the SOARCA UAs, providing the primary managerial and technical oversight. The long lists of NRC and Sandia contributors from the SOARCA UAs are cited in the three NUREG/CRs and are also gratefully acknowledged by the small team of authors compiling the results of their efforts. Significant technical contributions, advice, and reviews were provided by Dr. Hossein Esmaili, Dr. Alfred Hathaway, and Dr. Edward Fuller (retired) of the NRC. Dr. Randal Gauntt (retired), Mr. Patrick Mattie, Mr. Joseph Jones (retired), and Dr. Doug Osborn from Sandia are recognized as the SOARCA UA managers guiding the past efforts. There is a comparable list of project managers at the NRC including Ms. Patricia Santiago, Dr. Salman Haq, and Mr. Jon Barr. Sadly, we have lost Mr. Charlie Tinkler and Mr. Robert Prato, who were important contributors to the original SOARCA project. Finally, Mr. Kyle Ross and Mr. Mark Leonard have also retired but were significant technical contributors. Mr. Kyle Ross was the technical lead on all three SOARCA UAs and the original pressurized water reactor SOARCA study. Mr. Leonard was the technical lead on the original boiling water reactor SOARCA study and a key contributor to the first Peach Bottom SOARCA UA. iv

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Radar-derived precipitation climatology for wind turbine blade leading edge erosion

Wind turbine blade leading edge erosion (LEE) is a potentially significant source of revenue loss for wind farm operators. Thus, it is important to advance understanding of the underlying causes, to generate geospatial estimates of erosion potential to provide guidance in pre-deployment planning, and ultimately to advance methods to mitigate this effect and extend blade lifetimes. This study focuses on the second issue and presents a novel approach to characterizing the erosion potential across the contiguous USA based solely on publicly available data products from the National Weather Service dual-polarization radar. The approach is described in detail and illustrated using six locations distributed across parts of the USA that have substantial wind turbine deployments. Results from these locations demonstrate the high spatial variability in precipitation-induced erosion potential, illustrate the importance of low-probability high-impact events to cumulative annual total kinetic energy transfer and emphasize the importance of hail as a damage vector.

Letson, Frederick (ORCID:0000000192750359)↗
DOE OSTI2025

Electrodermal activity as a proxy for sweat rate monitoring during physical and mental activities

Electrodermal activity has long been used for mental activity monitoring by measuring skin conductance at specific locations, such as fingertips, with high sweat gland density. However, electrodermal activity has not been considered useful for physical activity monitoring, where large sweat volumes are generated, resulting in the accumulation of sweat at the skin–electrode interface and, thus, preventing further dynamic response to sweating events. Here we show that electrodermal activity can be used as a proxy for sweat loss measurement under both low and high physical activity levels. We use wearable sweat sensors that consist of water-permeable electrodes and microfluidic-based sweat analysers, and show that skin conductance is proportional to the instantaneous sweat loss. We demonstrate that sweat loss during exercise can be estimated by integrating skin conductance over time, which can be applied to assess the body hydration status of exercisers. From multisite measurements of skin conductance, we show that the wrist, forearm and upper arm are reflective of physical activity levels, whereas the finger is indicative of mental activity. Simultaneous measurement of two different sites selectively decouples mental and physical activities.

Biomedical engineering↗