Improving the Representation of Hydropower in Production Cost Models
This report is a joint piece by PNNL and NREL describing two similar projects and complementary approaches to improving the representation of hydropower in production cost models.
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This report is a joint piece by PNNL and NREL describing two similar projects and complementary approaches to improving the representation of hydropower in production cost models.
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The NOvA Transformer Energy Estimator (Transformer_EE) is a universal machine learning tool currently used to infer the incoming beam neutrino energy and the outgoing lepton energy in both near andfar detectors. It uses a unique, highly flexible framework for simultaneous multivariate prediction that supports many possible loss functions. A spectral reweighting and flattening scheme lessens training bias. A feature noising subroutine enables adversarial-like training, mitigating sensitivities to certain systematic effects at marginal resolution loss at inference time. The state of the Transformer_EE will be reviewed, and its robustness with respect to several NOvA Near and Far Detector systematics highlighted.
NOvA is a long-baseline neutrino experiment at Fermilab that studies neutrino oscillations via electron neutrino appearance and muon neutrino disappearance. The NOvA Near Detector, located 1 km from the NuMI target, records a high rate of neutrino interactions in the energy range of 1-5 GeV. One of the limitations in precise extraction of oscillations is the large systematic uncertainty on neutrino-nucleus interactions. The high rate of neutrino interactions in the NOvA Near Detector provides the opportunity to probe various neutrino interaction processes and nuclear models, via the extraction of cross sections of particular final states. Nuclear models can be improved by measuring neutrino-nucleus cross sections with respect to kinematic variables which are known to be more sensitive to nuclear effects, such as transverse kinematic imbalance (TKI) variables. Usage of TKI variables allows for more direct constraints on models of neutrino scattering, as these variables can more directly investigate, for instance, effects of Fermi motion and final state interactions. In this work, we describe progress towards a method of identifying and reconstructing protons in the NOvA near detector to enable the cross section measurement of charged current neutrino interactions with a visible muon and a proton in the final state, reported in TKI variables.
The~300T NOvA Near Detector (ND) utilizes segmented liquid scintillator to reconstruct interacting neutrinos arriving from the NuMI Beamline at Fermilab. Given NuMI’s intensity and the ND’s relatively short baseline, NOvA has recorded some of the world’s highest statistics for neutrino interactions around ~2GeV, in great similarity to the forthcoming DUNE experiment. This energy regime is replete with resonant interactions, which will form the plurality of final states in DUNE. NOvA seeks to empower the community with measurements of processes for both semi-exclusive and semi-inclusive charged pion production across muon kinematics and pion angle via single-and multidifferential neutrino scattering cross sections. This poster will review current progress across several related analyses, and look forward to future results.
Joint Theory-Experiment Neutrino Physics Meeting
The forthcoming Deep Underground Neutrino Experiment (DUNE) requires precise modeling of neutrino--nucleus interactions to achieve its neutrino-oscillation measurement goals. GENIE, the Monte Carlo event generator used by DUNE and other Fermilab-based experiments as a central value model for neutrino-nucleus cross sections, exhibits known discrepancies in comparison to MicroBooNE cross section data, especially when considering neutrino scattering events' transverse kinematic imbalance (TKI). For quasielastic-like measurements, the data show a larger transverse missing momentum tail while maintaining a peak similar to that predicted by the baseline GENIE model. Previous attempts at a solution include variations of final-state interaction (FSI) strengths, incorrectly decreasing both the peak and tail, thus leaving the discrepancy unresolved. This work investigates whether inconsistencies between local and global treatments of intranuclear physics contribute to the observed mismodeling. In this work, GENIE FSI routines have been modified to directly utilize intranuclear particle positions, thereby introducing a newly localized momentum treatment in correlation with the nominal density in both the hA and hN intranuclear cascade models for their 2018 and 2025 variants. Meson-exchange-current (MEC) localization was also tested for the hN 2018 model. Comparisons of the intranuclear nucleons' ("scattering center") momentum and its radial dependence validate the localization implementation. However, while such consistent localization produces modest changes in the proton momentum spectrum at low-to-medium momenta, only small changes are observed in the TKI distributions. These changes are insufficient to account for the discrepancy with MicroBooNE data. Although a localized treatment improves the internal consistency of the GENIE model, the origin of the TKI discrepancy remains unresolved by such a solution.
The Deep Underground Neutrino Experiment (DUNE) requires precise modeling of neutrino--nucleus interactions to achieve its neutrino-oscillation measurement goals. GENIE, the Monte Carlo event generator used by DUNE, exhibits a known discrepancy with MicroBooNE measurements of transverse kinematic imbalance (TKI): the data display a larger high-TKI tail while maintaining a peak similar to that predicted by the baseline GENIE model. Previous variations of final-state interaction (FSI) strength affected both the peak and the tail and therefore did not resolve the discrepancy. This work investigates whether inconsistencies between local and global treatments of intranuclear physics contribute to the observed mismodeling. The GENIE FSI routines were modified to use the particle position when generating nucleons, thereby introducing a local-density treatment in the hA and hN intranuclear models for their 2018 and 2025 implementations. Meson-exchange-current (MEC) localization was also tested for the hN 2018 model. Comparisons of the intranuclear scattering-center momentum and its radial dependence confirm that the localization was implemented as intended. Localization produces modest changes in the proton momentum spectrum, primarily at low momentum, but only a small change in the TKI distribution between approximately \SI{0.25}{\giga\electronvolt} and \SI{0.40}{\giga\electronvolt}. These changes are insufficient to account for the discrepancy with MicroBooNE data. Although a localized treatment improves the internal consistency of the GENIE model, the origin of the TKI discrepancy remains unresolved.
The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) comprehensively analyzes possible pathways for Puerto Rico to achieve its renewable energy goals while incorporating stakeholder perspectives and advancing energy resilience for all Puerto Ricans. PR100 is a wide-ranging and in-depth examination of Puerto Rico's energy system investment options. The findings are the culmination of two years of stakeholder engagement, scenario modeling, and impact analysis. The PR100 report and Implementation Roadmap contain a range of results and actions that reflect Puerto Rico's priorities around energy justice, resilience, and reliability. Led by the U.S. Department of Energy's Grid Deployment Office with funding from the Federal Emergency Management Agency, the PR100 study leveraged and integrated dozens of best-in-class models and in-depth analyses from researchers across six national laboratories: National Renewable Energy Laboratory (which led the study), along with Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and Sandia National Laboratories (which conducted the study). For more information, please see the "PR100 Project Website" resource below.
The European Spallation Source, currently under construction in Lund, Sweden, is a multidisciplinary international laboratory. Once completed to full specifications, it will operate the world’s most powerful pulsed neutron source. Supported by a 3 million Euro Research and Innovation Action within the EU Horizon 2020 program, a design study (HighNESS) has been completed to develop a second neutron source located below the spallation target. Compared to the first source, designed for high cold and thermal brightness, the new source has been optimized to deliver higher intensity, and a shift to longer wavelengths in the spectral regions of cold (CN, 2–20 Å), very cold (VCN, 10–120 Å), and ultracold (UCN, >500 Å) neutrons. The second source comprises a large liquid deuterium moderator designed to produce CN and support secondary VCN and UCN sources. Various options have been explored in the proposed designs, aiming for world-leading performance in neutronics. These designs will enable the development of several new instrument concepts and facilitate the implementation of a high-sensitivity neutron-antineutron oscillation experiment (NNBAR). This document serves as the Conceptual Design Report for the HighNESS project, representing its final deliverable.
A key aim of the HighNESS project for the European Spallation Source is to enable cutting-edge particle physics experiments. This volume presents a conceptual design report for the NNBAR experiment. NNBAR would exploit a new cold lower moderator to make the first search in over thirty years for free neutrons converting to anti-neutrons. The observation of such a baryon-number-violating signature would be of fundamental significance and tackle open questions in modern physics, including the origin of the matter-antimatter asymmetry. This report shows the design of the beamline, supermirror focusing system, magnetic and radiation shielding, and anti-neutron detector necessary for the experiment. A range of simulation programs are employed to quantify the performance of the experiment and show how background can be suppressed. For a search with full background suppression, a sensitivity improvement of three orders of magnitude is expected, as compared with the previous search. Civil engineering studies for the NNBAR beamline are also shown, as is a costing model for the experiment.
Remote communities are increasingly adopting renewable energy, such as wind, as they transition away from diesel energy generation. It is important to understand the benefits and costs of wind energy to isolated systems so that decision-makers can optimize their choices in these communities. There are few examples of valuation of wind energy as a distributed resource and numerous differences in valuation approaches, especially in the inclusion of environmental and economic impacts. We apply a distributed wind valuation framework to calculate the benefits and costs of wind in St. Mary’s, Alaska, to the local electric cooperative and to society, finding that the project does not have a favorable benefit-to-cost ratio unless societal benefits are included, in which case the benefit-to-cost ratio is nearly double. Government funding is important to reducing the initial capital expenditures of this wind project and will likely be the case for projects with similar characteristics. Additional fuel savings benefits are potentially possible for this project through technological additions such as energy storage and advanced controls.
The Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents.
This paper investigates the feasibility of using a linear current sensing (LCS) technique integrated on an unmanned aerial system (UAS) for detecting and mapping underground infrastructure rapidly and cost-effectively. The LCS technique is based on data from a wide band of electromagnetic induction frequencies (50 kHz to 2 MHz) using a vector magnetic field gradiometer. This technique takes advantage of a slowly decaying secondary magnetic field in order to achieve greater standoff detection distance ($\frac{1}{R^2}$ vs. $\frac{1}{R^6}$ for compact metallic targets during EMI sensing, where R is the distance from a target to the sensor). These secondary magnetic fields are produced by the excite current on long conductors, allowing detection at a distance of 10 meters or more. The system operates between tens of kHz to a few MHz and uses either an active EMI source or existing EM fields to excite this linear current on a long metallic subsurface target. Once excited, these linear currents produce a secondary magnetic field that is detected with an above ground triaxial magnetic field gradiometer. By moving and tracking its geolocation, the system outputs rich datasets sufficient to support high-fidelity forward and inverse EMI models for estimating the depth and orientation of deep underground long linear metallic infrastructure. The system’s hardware and its integration to a UAS system are outlined, along with the formulation of LCS theory, and numerical and experimental data are presented. The results illustrate that the LCS technique offers large standoff detection, is adaptable to UAS, and could be used effectively for detecting deep underground infrastructure such as wires and pipes.
While emission line flux ratio diagnostics are the most common technique for identifying active galactic nuclei (AGNs) in optical spectra, applying this approach to single-fiber spectra of galaxies can omit entire subpopulations of AGNs. Here, we use spatially resolved spectroscopy from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey to construct a sample of 10 galaxies where Baldwin–Philips–Terlevich line flux ratio diagnostics classify each galaxy’s central 3" spectrum as LINER or star-forming, while >10% of the spaxels in the galaxy’s MaNGA footprint are classified as Seyfert. We obtain Chandra observations of these 10 galaxies with off-nuclear Seyfert regions to determine whether AGNs are actually present in them. Our main result is that 7–10 (depending on strictness of criteria) of the galaxies host one or more X-ray AGNs, even though none of them were classified as AGNs based on their single-fiber optical spectra. We find that these AGNs were not identified in the single-fiber spectra because they are AGNs in the nuclei of companion galaxies, low-luminosity AGNs, dust-obscured AGNs, and/or flickering AGNs. In summary, we find that off-nuclear AGN signatures may increase the number of known AGNs by a factor of two over what conventional single nuclear fiber spectra identify. Our results show that spatially resolved spectroscopy can be leveraged to reveal a more complete census of AGNs that are traditionally missed by single-fiber spectra.
Abstract We analyze the circumgalactic medium (CGM) for eight commonly-used cosmological codes in the AGORA collaboration. The codes are calibrated to use identical initial conditions, cosmology, heating and cooling, and star formation thresholds, but each evolves with its own unique code architecture and stellar feedback implementation. Here, we analyze the results of these simulations in terms of the structure, composition, and phase dynamics of the CGM. We show properties such as metal distribution, ionization levels, and kinematics are effective tracers of the effects of the different code feedback and implementation methods, and as such they can be highly divergent between simulations. This is merely a fiducial set of models, against which we will in the future compare multiple feedback recipes for each code. Nevertheless, we find that the large parameter space these simulations establish can help disentangle the different variables that affect observable quantities in the CGM, e.g., showing that abundances for ions with higher ionization energy are more strongly determined by the simulation’s metallicity, while abundances for ions with lower ionization energy are more strongly determined by the gas density and temperature.
To facilitate new studies of galaxy merger driven fueling of active galactic nuclei (AGNs), we present a catalog of 387 AGNs that we have identified in the final population of over $10,000$$z<0.15$ galaxies observed by the SDSS-IV integral field spectroscopy survey Mapping Nearby Galaxies at Apache Point Observatory (MaNGA). We selected the AGNs via mid-infrared WISE colors, Swift/BAT ultra hard X-ray detections, NVSS and FIRST radio observations, and broad emission lines in SDSS spectra. By combining the MaNGA AGN catalog with a new SDSS catalog of galaxy mergers that were identified based on a suite of hydrodynamical simulations of merging galaxies, we study the link between galaxy mergers and nuclear activity for AGNs above a limiting bolometric luminosity of $10^{44.4}$ erg s$^{-1}$. We find an excess of AGNs in mergers, relative to non-mergers, for galaxies with stellar mass $\sim10^{11}$$M_{\odot}$, where the AGN excess is somewhat stronger in major mergers than in minor mergers. Further, when we combine minor and major mergers and sort by merger stage, we find that the highest AGN excess occurs in post-coalescence mergers in the highest mass galaxies. However, we find no evidence of a correlation between galaxy mergers and AGN luminosity or accretion rate. In summary, while galaxy mergers overall do appear to trigger or enhance AGN activity more than non-mergers, they do not seem to induce higher levels of accretion or higher luminosities. We provide the MaNGA AGN Catalog and the MaNGA Galaxy Merger Catalog for the community here.
In this fourth paper from the AGORA Collaboration, we study the evolution down to redshift z = 2 and below of a set of cosmological zoom-in simulations of a Milky Way mass galaxy by eight of the leading hydrodynamic simulation codes. We also compare this CosmoRun suite of simulations with dark matter-only simulations by the same eight codes. We analyze general properties of the halo and galaxy at z = 4 and 3, and before the last major merger, focusing on the formation of well-defined rotationally supported disks, the mass–metallicity relation, the specific star formation rate, the gas metallicity gradients, and the nonaxisymmetric structures in the stellar disks. Codes generally converge well to the stellar-to-halo mass ratios predicted by semianalytic models at z ~ 2. We see that almost all the hydro codes develop rotationally supported structures at low redshifts. Most agree within 0.5 dex with the observed mass–metallicity relation at high and intermediate redshifts, and reproduce the gas metallicity gradients obtained from analytical models and low-redshift observations. We confirm that the intercode differences in the halo assembly history reported in the first paper of the collaboration also exist in CosmoRun, making the code-to-code comparison more difficult. We show that such differences are mainly due to variations in code-dependent parameters that control the time stepping strategy of the gravity solver. We find that variations in the early stellar feedback can also result in differences in the timing of the low-redshift mergers. All the simulation data down to z = 2 and the auxiliary data will be made publicly available.