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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Hydra: Computer Vision for Data Quality Monitoring

Hydra: Computer Vision for Data Quality Monitoring Mar 13, 2024, 4:15 PM 30m Charles B. Wang Center, Stony Brook University Poster Track 1: Computing Technology for Physics Research Poster session with coffee break Speaker Ayan Roy Description Hydra is an extensible framework for training, managing, and deploying machine learning models for near real-time data quality monitoring. It is designed to take some of the burden off of shift crews by providing ‘round-the-clock’ monitoring of plots representing the data being collected. The Hydra system is backed by a database which is leveraged for near push button training and is primarily controlled and viewed through a set of web interfaces. This web interface contains a simple-to-use web based GUI for labeling of the datasets used in training; making it possible to label thousands of images quickly and efficiently. To aid in the analysis of Hydra inferences gradCAM, a method of interpretability, is performed and overlaid on the target image, highlighting regions of interest, making diagnosis of problems much faster. Development began in 2019 for the GlueX Experiment in Hall-D, the Hydra system has grown to encompass all of the experimental halls at Jefferson Laboratory. This talk will focus on the features of Hydra as well as provide details of the challenges present with deploying to disparate experimental halls. With a roadmap of development established, Hydra aims to continue to grow in richness of feature set and expand to encompass other monitoring tasks in differing communities.

Roy, Ayan↗
DOE OSTI2023

Enhanced cutoff energies for direct and rescattered strong-field photoelectron emission of plasmonic nanoparticles

Abstract The efficient generation, accurate detection, and detailed physical tracking of energetic electrons are of applied interest for high harmonics generation, electron-impact spectroscopy, and femtosecond time-resolved scanning tunneling microscopy. We here investigate the generation of photoelectrons (PEs) by exposing plasmonic nanostructures to intense laser pulses in the infrared (IR) spectral regime and analyze the sensitivity of PE spectra to competing elementary interactions for direct and rescattered photoemission pathways. Specifically, we measured and numerically simulated emitted PE momentum distributions from prototypical spherical gold nanoparticles (NPs) with diameters between 5 and 70 nm generated by short laser pulses with peak intensities of 8.0 × 10 12 and 1.2 × 10 13 W/cm 2 , demonstrating the shaping of PE spectra by the Coulomb repulsion between PEs, accumulating residual charges on the NP, and induced plasmonic electric fields. Compared to well-understood rescattering PE cutoff energies for strong-field photoemission from gaseous atomic targets (10× the ponderomotive energy), our measured and simulated PE spectra reveal a dramatic cutoff-energy increase of two orders of magnitude with a significantly higher contribution from direct photoemission. Our findings indicate that direct PEs reach up to 93 % of the rescattered electron cutoff energy, in contrast to 20 % for gaseous atoms, suggesting a novel scheme for the development of compact tunable tabletop electron sources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A hardware-in-the-loop (HIL) testbed for cyber-physical energy systems in smart commercial buildings

In recent years, there has been a growing trend toward the development of smart buildings that rely on cyber-physical systems (CPS) to optimize occupant comfort, safety, and energy efficiency. To ensure the reliable and efficient operation of CPS with designed control strategies, it is important to evaluate their performance under various scenarios before deploying them in the real world. This is where a Hardware-in-the-loop (HIL) testbed designed for studying sensor and control-related studies in smart buildings can be highly valuable. With the growing threat of cyber-attacks and physical faults targeting smart buildings, it is essential to ensure the security of building operations. A HIL testbed can emulate cyber-attack and physical fault scenarios, allowing researchers to develop and test threat detection and mitigation algorithms. This enables researchers to identify potential issues and optimize the algorithms in a safe and controlled environment before they are deployed in real-world settings, reducing the risk of failures that can negatively impact occupant comfort, safety, and energy efficiency. Therefore, this paper developed a HIL testbed designed for cyber-physical energy systems (e.g. buildings automation system (BAS)) in smart commercial buildings. The HIL testbed is comprised of a real-time building and Heating, Ventilation, and Air-Conditioning (HVAC) emulator using Modelica-based dynamic models, a set of BAS controllers, and a BAS computer server. The data generation capability of the HIL testbed is demonstrated by tracking normal and faulty operating data in the BAS, as well as monitoring detailed network traffic in the local BAS network. Here, this study further demonstrates the HIL testbed’s capability by conducting case studies on real-time physical fault and cyber-attack experiments using a Department of Energy (DOE) prototype commercial building. It is anticipated that the fully functional HIL testbed will be utilized for a variety of sensor and control-related studies, including but not limited to testing, developing, validating of different HVAC control strategies, fault detection & diagnosis, energy monitoring and analysis, cyber security study, etc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Measuring Economy-Wide Circularity of the United States: An Input-Output Model in Mass Units

The ideal of creating closed material cycles by transforming the way we make, use and repurpose goods has become known as the circular economy. Besides its visionary appeal, material efficiency strategies central to circular economy can allow us to meet decarbonization goals that are otherwise out of reach. Production of basic materials such as cement, iron and steel and petrochemicals is one of the largest drivers of greenhouse gas emissions. Measuring circularity, and understanding its relationship with other sustainability metrics, however, is still difficult due to lack of data in mass units covering the entire economic system. Input-output (I-O) tables were originally created as a means of tracking the monetary flows that represent exchanges of goods and services within an economy, but have found additional uses in life cycle assessment and material flow accounts. In the traditional approach of environmentally extended I-O tables, emissions and energy data augment monetary flows. This approach can lead to price effects that distort physical quantities. Also, circular economy strategies and their goals relate to mass, not monetary flows. Therefore, it is best to simulate them using physical quantities. With these issues in mind, we have developed I-O tables in mass units to measure the flow of goods in the U.S. economy. This allows us to better measure how circular the economy really is, and how policy changes to affect this circularity may also affect decarbonization goals. Improving knowledge of these linkages could allow manufacturers to make changes in their production to achieve their sustainability and decarbonization targets. Our tool also provides a standard approach and public repository for data in physical units, making such data more available, useful, and meaningful. Following an established set of material flow metrics used by the European Union, we have used our tool to calculate material footprints over time differentiated by oil and gas versus other extractive industries. This approach also shows the relative trade balances of the U.S. in materials. We have developed a case study for the iron and steel sector, showing how different decarbonization scenarios affect not only economy-wide greenhouse gas emissions, but also total material use.

circular economy↗
DOE OSTI2022

A warm super-Neptune around the G-dwarf star TOI-1710 revealed with TESS, SOPHIE, and HARPS-N

We report the discovery and characterization of the transiting extrasolar planet TOI-1710 b. It was first identified as a promising candidate by the Transiting Exoplanet Survey Satellite. Its planetary nature was then established with SOPHIE and HARPS-N spectroscopic observations via the radial-velocity method. The stellar parameters for the host star are derived from the spectra and a joint Markov chain Monte-Carlo adjustment of the spectral energy distribution and evolutionary tracks of TOI-1710. A joint MCMC analysis of the TESS light curve and the radial-velocity evolution allows us to determine the planetary system properties. From our analysis, TOI 1710 b is found to be a massive warm super-Neptune (M p = 28.3 ± 4.7 M ⊕ and R p = 5.34 ± 0.11 R ⊕ ) orbiting a G5V dwarf star (T eff = 5665 ± 55 K) on a nearly circular 24.3-day orbit (e = 0.16 ± 0.08). The orbital period of this planet is close to the estimated rotation period of its host star P rot = 22.5 ± 2.0 days and it has a low Keplerian semi-amplitude K = 6.4 ± 1.0 m s -1 ; we thus performed additional analyses to show the robustness of the retrieved planetary parameters. With a low bulk density of 1.03 ± 0.23 g cm -3 and orbiting a bright host star (J = 8.3, V = 9.6), TOI-1710 b is one of the best targets in this mass-radius range (near the Neptunian desert) for atmospheric characterization via transmission spectroscopy, a key measurement in constraining planet formation and evolutionary models of sub-Jovian planets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

DATASET RELEASE AND QUALITY CONTROL REVIEW OF LIVERMORE NEVADA NETWORK (LNN) RECORDINGS OF A SUBSET OF NEVADA NUCLEAR SECURITY SITE NUCLEAR EXPLOSIONS FROM 1979 TO 1992.

Geophysical research on historical nuclear tests is an important aspect of future monitoring capabilities in seismic research. This research is challenging due to the limited number of digital seismic recordings during the peak of nuclear testing (1945-1992). These limited records are unique and non-reproducible data with potential high research impact. Releasing available nuclear explosion seismic records to the explosion monitoring community is thus of high value and is the motivation for this dataset release. The target of this effort was on compilation and quality control of regional seismic records of nuclear explosions recorded on Lawrence Livermore National Laboratory stations ELK, KNB, LAC, and MNV, known collectively as the Livermore National Network (LNN) (Figure 1). LNN was established in the early 1960s for the primary purpose of monitoring underground nuclear testing at the former Nevada Test Site (NTS), now known as the Nevada Nuclear Security Site (NNSS) following the signing of the Limited Test Ban Treaty (LTBT). LNN consisted initially of short-period vertical component Benioff’s recorded on film located at Mina, NV (MNV) and Kanab, Utah (KNB). LNN added two additional stations at Landers, CA (LAC) and Elko, NV (ELK) in 1967 and upgraded equipment to broadband seismometers recorded on frequency modulation (FM) tapes from 1967-1979, followed by digital recordings after 1979 (Jarpe, 1989). The digital recordings were on a variety of now obsolete media, including 9-track, Exabyte, and DAT tapes. Jarpe (1989) describes the seismic station instrumentation details over the period of deployment. LNN recorded valuable non-repeatable unique data of several hundreds of nuclear explosions at NNSS, as well as earthquakes and chemical and mining explosions (Walter, 2020). The details of these nuclear tests are provided in the Department of Energy Report NV-209 Rev 16 (DOE, 2015).

58 GEOSCIENCES↗
DOE OSTI2023

Design, construction, and validation of an in-situ groundwater trace element analyzer with applications in carbon storage

Abstract It is estimated that carbon emissions should reach net-zero by 2050 to meet important climate targets. Carbon capture is likely necessary to reach these targets, requiring a long-term storage solution such as geological carbon sequestration. However, as with any subsurface activity, leakage can occur, potentially impacting groundwater quality near the storage site. Rapid detection is essential to mitigate damage to this resource. Since CO 2 will acidify groundwater, the concentrations of acid soluble minerals and associated cations will increase. Thus, an in-situ, real-time element analysis system based on laser-induced breakdown spectroscopy (LIBS) is under development to monitor these elements. The system splits the traditional LIBS system into a miniature, all-optical sensor head built around a passively Q-switch laser fiber coupled to a control unit. Previous work has validated the LIBS technique for use at high pressure as well as the split system design. In this work, a fieldable prototype sensor is developed and tested in an onsite monitoring well where trace elements concentrations (approx. 0–3 ppm) were tracked over 20 days. These concentrations varied in response to local rainfall, diluting with increased rain, demonstrating the ability of a LIBS-based sensor to track trace elements under real-world conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Synthetic Pathway for Producing Carbon Dots for Detecting Iron Ions Using a Fiber Optic Spectrometer

Iron detection is of growing importance in the critical minerals sector, where unwanted iron ions are typically removed during the processing of target critical metals. The ideal sensor should utilize inexpensive, scalable materials along with a low-cost, robust, and easy-to-use analysis platform. Here, we demonstrate a simple acid–base synthesis of luminescent iron-responsive carbon dots by reacting ethanolamine, phosphoric acid, and m-phenylenediamine. The carbon dots exhibit selective, iron-specific emission quenching, with the ability to detect part-per-billion levels of iron ions even in 0.1 M HCl. After benchmarking the purified materials using a commercial spectrometer, a “low-cost” process is demonstrated in which carbon dots with minimal purification are coupled with a portable fiber-optic spectrometer for analyzing iron content. Carbon dot-coated paper strips are also evaluated as another convenient platform for iron analysis. Taken together, the sensing material and platforms demonstrated here are well-suited for detecting trace quantities of iron in environmentally relevant conditions, with potential applications in tracking iron removal processes during critical mineral production as one exciting area of interest.

acid mine draining↗
DOE OSTI2023

A Telomerase-Activated Magnetic Resonance Imaging Probe for Consecutively Monitoring Tumor Growth Kinetics and In Situ Screening Inhibitors

Telomerase has long been considered as a biomarker for cancer diagnosis and a therapeutic target for drug discovery. Detecting telomerase activity in vivo could provide more direct information of tumor progression and response to drug treatment, which, however, is hampered by the lack of an effective probe that can generate an output signal without a tissue penetration depth limit. Here in this study, using the principle of distance-dependent magnetic resonance tuning, we constructed a telomerase-activated magnetic resonance imaging probe (TAMP) by connecting superparamagnetic ferroferric oxide nanoparticles (SPFONs) and paramagnetic Gd-DOTA (Gd(III) 1,4,7,10- tetraazacyclododecane-1,4,7,10-tetraazacyclododecane-1,4,7,10-tet-raacetic acid) complexes via telomerase-responsive DNA motifs. Upon telomerase-catalyzed extension of the primer in TAMP, Gd-DOTA-conjugated oligonucleotides can be liberated from the surface of SPFONs through a DNA strand displacement reaction, restoring the T 1 signal of the Gd-DOTA for a direct readout of the telomerase activity. Here we show that, by tracking telomerase activity, this probe provides consistent monitoring of tumor growth kinetics during progression and in response to drug treatment and enables in situ screening of telomerase inhibitors in whole-animal models. This study provides an alternative toolkit for cancer diagnosis, treatment response assessment, and anticancer drug screening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

JGI Plant Gene Atlas: an updateable transcriptome resource to improve functional gene descriptions across the plant kingdom

Abstract Gene functional descriptions offer a crucial line of evidence for candidate genes underlying trait variation. Conversely, plant responses to environmental cues represent important resources to decipher gene function and subsequently provide molecular targets for plant improvement through gene editing. However, biological roles of large proportions of genes across the plant phylogeny are poorly annotated. Here we describe the Joint Genome Institute (JGI) Plant Gene Atlas, an updateable data resource consisting of transcript abundance assays spanning 18 diverse species. To integrate across these diverse genotypes, we analyzed expression profiles, built gene clusters that exhibited tissue/condition specific expression, and tested for transcriptional response to environmental queues. We discovered extensive phylogenetically constrained and condition-specific expression profiles for genes without any previously documented functional annotation. Such conserved expression patterns and tightly co-expressed gene clusters let us assign expression derived additional biological information to 64 495 genes with otherwise unknown functions. The ever-expanding Gene Atlas resource is available at JGI Plant Gene Atlas (https://plantgeneatlas.jgi.doe.gov) and Phytozome (https://phytozome.jgi.doe.gov/), providing bulk access to data and user-specified queries of gene sets. Combined, these web interfaces let users access differentially expressed genes, track orthologs across the Gene Atlas plants, graphically represent co-expressed genes, and visualize gene ontology and pathway enrichments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Neutrinos from the Galactic Center Hosting a Hypernova Remnant

Similar to star-forming galaxies or starburst galaxies, star-forming regions in our Galaxy can host cosmic-ray (CR) accelerators and rich gas as targets of hadronuclear interaction. By our estimations, the IceCube neutrino observatory might detect muon neutrinos from a CR accelerator associated with a molecular cloud complex in our Galaxy. The associated high-energy gamma-ray emission might be observed by the Cherenkov Telescope Array (CTA), High-Altitude Water Cherenkov Gamma-Ray Observatory (HAWC), and Large High Altitude Air Shower Observatory (LHAASO). Furthermore, taking the Galactic Center (GC) region as an example, we assume that a hypernova exploded in the past in the GC. We simulate the acceleration of CRs in the hypernova remnant (HNR) as well as their confinement and escape. The high-energy protons escape from the HNR, diffuse around the GC, interact with molecular clouds, and then produce gamma-rays and neutrinos. In the optimal cases, the GC would be a promising 100 TeV gamma-ray source for LHAASO’s one-month observation. We propose that neutrino-induced searching for starting track-like and high-energy starting events (HESEs) observed by IceCube, from the GC region with a radius of 1°.8, would help us discover the particle accelerator in the GC or constrain our models. Under the constraint from high-energy gamma-ray observations by the H.E.S.S. telescope, we estimate the exposure time needed to make a significant discovery for the optimal cases. The analysis combining observations of IceCube and ANTARES, starting track-like events and HESEs, future observations by neutrino detectors IceCube-Gen2 and KM3net, and gamma-ray telescopes CTA, HAWC, and LHAASO would help to constrain our models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Predicting tungsten erosion and leakage properties for the new V-shaped small angle slot divertor in DIII-D

Impurity transport modeling of the new tungsten (W)-coated, V-shaped small angle slot (SAS) divertor in the DIII-D tokamak was conducted using the SOLPS-ITER plasma edge code package and the DIVIMP impurity tracking code. The inboard baffle of the current SAS divertor will be shifted closer to the outboard baffle, creating a V-corner at the slot vertex. In addition, the outboard baffle will be coated with 10–15 μm of W for experiments studying high-Z sourcing and leakage in a closed divertor. Modeling of the 'SAS-VW' divertor predicts that these changes to the inner baffle will reduce W gross erosion by 40× relative to the existing SAS divertor when the outer strike point (OSP) is at the V-corner and the ion B × ∇B drift is towards the divertor, driven primarily by significant cooling near the slot vertex. Most W erosion in SAS-VW is expected to occur near the slot entrance, which may pose a higher risk to core contamination than W eroded deeper in the slot. Furthermore, adding a new sheath-based prompt redeposition model increases the sensitivity of redeposition estimates to near-target plasma conditions and may provide more accurate predictions of net erosion. Moving the OSP outboard from the slot vertex ~4 cm onto the W-coated region yields a 40× increase in the gross erosion rate and a 50% decrease in the core leakage fraction. Thus slight variations in strike point location may counteract the potential benefits of the tightly-baffled V slot on minimizing erosion. This impurity transport modeling provides useful guidance for future experiments on the SAS-VW divertor focused on high-Z erosion/redeposition, scrape-off layer transport, and core leakage.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Evaluation of a Sulfate Solubility Limit Greater Than 0.65 Weight Percent in Sludge Batch 10 Glasses

Previous laboratory-scale crucible testing with batch chemicals confirmed that the sulfate (SO 4 2- ) limit for Sludge Batch 10 (SB10) was 0.65 weight percent (wt.%) in glass. This limit signifies that 0.65 wt.% SO 4 2- can be retained in the glass without the formation of a sulfate phase. The Defense Waste Processing Facility imposes this constraint in the Material Tracking Program. Based on preliminary calculations to support the Material Tracking Program, it was anticipated that transfer volumes of the monosodium titanate/sludge solids (MST/SS) stream from the Salt Waste Processing Facility (SWPF) may need to be reduced to maintain projected sulfate concentrations below 0.65 wt.% in glass. Savannah River Mission Completion requested that the Savannah River National Laboratory perform additional sulfate testing to determine whether a sulfate solubility limit greater than 0.65 wt.% is feasible for SB10, which could allow for higher transfer volumes of the MST/SS stream. This report documents the results of the testing at higher sulfate concentrations for the glass composition region defined by the most recent SB10 projection (November 2022) and Frits 473 and 625. Frit 473 was recommended for SB10 and Frit 625 was used during SB9 processing and the SB9 to SB10 transition. A total of twenty-one glass compositions were developed based on the expected compositional variables, which include sludge-only (SO) and coupled processing with the SWPF, waste loading (WL), and frit composition. The target sulfate concentrations were varied from 0.65-0.85 wt.% at 32 and 40% WL. Each glass was prepared from reagent grade chemicals and melted at 1150 °C. Visual observations were used to confirm the presence of a sulfate salt phase on the cooled glass surfaces. Representative samples of each glass were submitted for chemical composition analysis by inductively coupled plasma-optical emission spectroscopy and Cs analysis by inductively coupled plasma-mass spectrometry. Overall the majority of mean measured values are consistent with the target values for each major oxide of interest with less than 5% error. The percent errors for the measured SO 4 2- concentrations are generally less than 10%, which is comparable with previous sulfate solubility study measurements and acceptable. Only the SO glasses based on Frit 625 formed a sulfate phase at a 0.80 wt.% SO 4 2- target concentration at both 32 and 40% WL. The remainder of the glasses did not form a sulfate layer. Due to the formation of the sulfate phase, the limit is conservatively set at 0.70 wt.% based on the measured sulfate concentrations of 0.71 wt.% and 0.75 wt.% for these two glasses. None of the SO or coupled operation glasses based on Frit 473 formed a sulfate salt phase, which supports a sulfate limit of 0.80 wt.%. The following SO 4 2- concentration limits are recommended during SO and coupled SB10 processing: (1) 0.70 wt.% during processing with Frit 625, and (2) 0.80 wt.% during processing with Frit 473.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Machine learning for detection of 3D features using sparse x-ray tomographic reconstruction

In many inertial confinement fusion (ICF) experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy suggests that there are three dimensional effects that may be significant. Sources of these effects include defects in the shells and defects in shell interfaces, the fill tube of the capsule, and the joint feature in double shell targets. Due to their ability to penetrate materials, x rays are used to capture the internal structure of objects. Methods such as computational tomography use x-ray radiographs from hundreds of projections, in order to reconstruct a three dimensional model of the object. In experimental environments, such as the National Ignition Facility and Omega-60, the availability of these views is scarce, and in many cases only consists of a single line of sight. Mathematical reconstruction of a 3D object from sparse views is an ill-posed inverse problem. These types of problems are typically solved by utilizing prior information. Neural networks have been used for the task of 3D reconstruction as they are capable of encoding and leveraging this prior information. We utilize half a dozen, different convolutional neural networks to produce different 3D representations of ICF implosions from the experimental data. Deep supervision is utilized to train a neural network to produce high-resolution reconstructions. These representations are used to track 3D features of the capsules, such as the ablator, inner shell, and the joint between shell hemispheres. Machine learning, supplemented by different priors, is a promising method for 3D reconstructions in ICF and x-ray radiography, in general.

Wolfe, Bradley T. (ORCID:0000000268301614)↗
DOE OSTI2022

Plasma Mirrors For High Power Lasers: A new approach for high repetition rates combined with realistic PIC simulations

We describe a research program to develop high quality plasma mirrors for use with high repetition rate, high power laser facilities to greatly facilitate experiments in high energy density physics, particularly when using solid density targets. A system delivering ultrathin, free standing liquid crystal films that could handle PW class laser pulses was developed that preserved the laser beam image quality and improved pulse contrast by over two orders of magnitude. The pulse contrast improvement was measured using a high dynamic range cross-correlation. The system operated at a repetition rate of several PMs formed in situ per minute. Extension to 1 Hz repetition rates should be possible. As a practical application, a PM system was used to separate laser accelerated electrons from the ultrashort pulse drive laser so that the electron beam emittance could be directly measured. The 20 nm thick PMs did not contribute significantly to emittance degradation. It was also demonstrated that the films could operate in the difficult plasma and laser environment present for GeV laser based electron acceleration. PM operation is still not well understood and much work with PMs is done empirically. Accordingly, we also demonstrated a particle-in-cell based simulation technique that would model PM operation, tracking the PM operation from cold, neutral atoms to a hot dense plasma by accounting for multiphoton ionization, plasma collisionality, and the dynamically changing index of refraction. Simulations in 3D were compared to a 2D based approach that was comparable. Finally, we developed a simpler model that can predict the intensity at which a plasma mirror will have its peak reflectivity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Measurement of $\nu_\mu$ CC Interactions With Two-Proton Final State in MINERvA

This dissertation presents a measurement of charged–current (CC) muon–neutrino interactions with exactly two protons and no pions in the final state (CC~$2p\,0\pi$), using data collected by the MINERvA detector in the NuMI medium–energy beam at Fermilab. Such two–proton topologies are a sensitive probe of nuclear dynamics in the few–GeV regime, including multi–nucleon correlations (npnh, notably $2p2h$) and intranuclear final–state interactions (FSI) such as pion absorption and nucleon rescattering. A precise experimental characterization of these processes is essential both for neutrino–interaction theory and for reducing systematic uncertainties in oscillation experiments that rely on accurate modeling of neutrino–nucleus interactions. Events are selected by requiring a $\nu_\mu$ CC interaction with a reconstructed $\mu^-$ and two proton tracks originating from a common vertex in MINERvA’s finely segmented scintillator tracker, with no reconstructed mesons. Muon charge and momentum are constrained by matching to the MINOS Near Detector, while proton identification exploits energy–loss profiles and stopping–proton features. Backgrounds from pion–producing channels that enter the signal region through FSI or reconstruction effects are constrained with data–driven sidebands (Michel–electron and isolated–cluster “blob” samples) and tuned via a simultaneous fit across signal and sideband regions. To correct detector resolution and acceptance effects, the analysis employs iterative Bayesian unfolding with extensive validation: statistical pseudo–experiments, and robustness checks against generator systematic “universes” and additional strong shape warps. Single–differential cross sections are reported for three observables tailored to the two–proton final state: the opening–angle cosine $\cos\!\left(\theta_{pp}\right)$, the leading–proton momentum, and the subleading–proton momentum. Systematic uncertainties include contributions from neutrino flux, interaction modeling (e.g., npnh and resonance parameters, pion FSI), and detector response (calibration, reconstruction efficiencies). The resulting distributions provide targeted constraints on the interplay of multi–nucleon dynamics and FSI that shape CC~$2p\,0\pi$ final states on hydrocarbon. Comparisons to modern GENIE–based simulations highlight kinematic regions where model components require refinement. These measurements thus inform generator tuning and improve the reliability of neutrino–energy reconstruction strategies for current and future long–baseline oscillation programs.

Syrotenko, Vladyslav S. [Tufts U.]↗
DOE OSTI2023

Offshore Wind Market Report: 2023 Edition

The Offshore Wind Market Report: 2023 Edition provides detailed information on the U.S. and global offshore wind energy industries to inform policymakers, researchers, and analysts about technology, economic, and market trends. The scope of the report covers the status of over 293 global operating offshore wind energy projects as well as the broader global pipeline of projects in various stages of development through December 31, 2022. To provide up-to-date information and discussion on this emerging industry in the United States, this report tracks the significant U.S. domestic industry progress and events from January 1, 2022, through May 31, 2023. The U.S. offshore wind energy project development pipeline has reached a potential generating capacity of over 52 gigawatts, and the industry has seen strong support from state and federal governments (such as from the Inflation Reduction Act of 2022 and the announced Floating Offshore Wind Shot to reduce the cost of floating wind by 70%). There are contracts for over 17 gigawatts of the electricity from these offshore wind projects and state policies are in place to procure over 42 gigawatts by 2040. Although some projects are facing economic headwinds due to rising costs and higher interest rates (corresponding to project cost increases of 11% - 30% in 2022), there has still been significant investment in a domestic supply chain (including manufacturing facilities, new vessels, and upgraded or planned ports). Technologies continue to evolve as offshore wind turbines in the 15-megawatt class advance towards commercial production. Key offshore wind energy market indicators, such as commercial leasing, state energy planning targets, procurement policies, offtake agreements, and federal support for U.S. jobs and supply chain development, point toward sustained market growth when viewed together, but the macroeconomic hurdles facing the first generation of commercial projects could significantly stunt that growth.

17 WIND ENERGY↗
DOE OSTI2022

CFD simulations of electric motor end ring cooling for improved thermal management

Proper thermal management of an electric motor for vehicle applications extends its operating range. One cooling approach is to impinge Automatic Transmission Fluid (ATF) onto the rotor end ring. Increased ATF coverage correlates to enhanced heat transfer. Computational Fluid Dynamics (CFD) analytical tools provide a mechanism to assess motor thermal management prior to hardware fabrication. The complexity of the fluid flow (e.g., jet atomization, interface tracking, wall impingement) and heat transfer makes these simulations challenging. Computational costs are high when solving these flows on high-speed rotating meshes. Typically, a Volume-of Fluid (VOF) technique (i.e., two-fluid system) is used to resolve ATF dynamics within this rotating framework. Suitable numerical resolution of the relevant physics for thin films under strong inertial forces at high rotor speeds is computationally expensive, further increasing the run times. In this work, a numerical study of rotor-ring cooling by ATF is presented using a patent automated Cartesian cut-cell based method coupled with Automatic Mesh Refinement (AMR). This approach automatically creates the Cartesian mesh on-the-fly and can effectively handle complex rotating geometries by adaptively refining the mesh based on local gradients in the flow field which results in better resolution of the air-ATF interface. A Single non-inertial Reference Frame (SRF) approach is used to account for the rotating geometry and to further improve the overall computational efficiency. Quasi-steady state conditions are targeted in the analysis of the results. Important physics such as ATF jet structure, velocity detail near the air-jet interface, ATF coverage/accumulation on the ring surface, and cooling capacity are presented for a low-resolution Reynolds averaged Navier-Stokes (RANS), high-resolution RANS, and high-resolution Large-Eddy Simulation (LES) models. Computations are scaled over hundreds of cores on a supercomputer to maximize turnaround time. Each numerical approach is shown to capture the general trajectory of the oil jet prior to surface impingement. The high-resolution LES simulation, however, is superior in capturing small scale details and heat transfer between the free jet and surrounding air.

42 ENGINEERING↗