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NASA NTRS2018

Flux Cancelation as the Trigger of Coronal Hole Jet Eruptions

Coronal jets are frequent magnetically-channeled narrow eruptions. They occur in various solar environments: quiet regions, coronal holes and active regions. All coronal jets observed in EUV and X-ray images show a bright spire with a base brightening, also known as jet bright point (JBP). Recent studies show that coronal jets are driven by small-scale filament eruptions (e.g. Hong et al. 2011, Shen et al. 2012, Adams et al. 2014, Sterling et al 2015). We (Panesar et al. 2016b) found in on disk quiet regions that coronal jets originate at a neutral line between dominant-polarity flux and a patch of canceling minority-polarity flux.

Panesar, Navdeep K.↗

NASA NTRS2018

Studies in Support of Venus Aerocapture Utilizing Drag Modulation

Aerocapture has been extensively studied and these studies have shown the benefit for planetary exploration missions. While the traditional approach to aerocapture with lifting configurations and lift-guided modulations have been assessed to be technologically feasible, aerocapture using purely drag modulation was proposed and studied by Prof. Braun and his students. These studies show that if one can assess the feasibility of aerocapture using drag modulation at Venus, and develop tall pole technologies needed at Venus, then this concept is much easier to execute at all other relevant destinations. Based on the above finding, partnered proposals were submitted by Adam Nelessen at JPL and Ethiraj Venkatapathy at Ames in collaboration with Prof. Braun at the University of Colorado, Boulder (UCB). Under this partnership, Ames Research Center (ARC) is working to address some of the key entry technology challenges associated with drag modulation aerocapture at Venus. Drag modulation aerocapture is a simple, scalable, and likely cost-effective way to enhance planetary science missions. The approach envisioned is to design a small spacecraft, that would most likely be a secondary payload, with a removable drag skirt. The vehicle would enter the atmosphere at Venus with a low ballistic coefficient, decelerate rapidly, drop the skirt resulting in a smaller vehicle with a higher ballistic coefficient which would skip out of the atmosphere and enter into a desired orbit. ARC's role in this collaboration is multifold. First of which is to perform design studies on various pre- and post-jettison geometries utilizing a 3-DOF trajectory code to determine the aerodynamics and aerothermodynamics of the vehicles and evaluate viable thermal protection material system designs. Once these design studies are complete, Ames will then perform higher fidelity CFD and TPS sizing to further design the vehicles. Second, the multi-body separation dynamics of the drag modulation event will be explored using both CFD simulations (CART3-D and US3D) as well as possible ballistic range testing. ARC's tools and expertise have been used to assess and advise on the selection of the separating configuration. In addition to the preliminary evaluation, ARC will provide tools and expertise to UCB team members to further assess aerodynamic interactions between the separating bodies and provide guidance as to the feasibility of stable transition.

Beck, Robin↗

NASA NTRS2014

The X-15 3-65 Accident: An Aircraft Systems and Flight Control Perspective

Despite the NASA X-15 program's outstanding success in developing and operating the first manned hypersonic research platform, the program suffered a fatal accident on November 15, 1967, when X-15-3, the only aircraft outfitted with advanced pilot displays and an adaptive flight control system, was lost after entering uncontrolled flight at an altitude of 230,000 feet and a velocity near Mach 5. The pilot, Major Michael J. Adams, was incapacitated by the aircraft accelerations and was killed either during the ensuing breakup or upon ground impact. In light of mitigating risk to current and emerging manned aerospace vehicles, a comprehensive systems level analysis of the accident is presented with a focus on the electrical power, flight control, and instrumentation failures that affected not only the vehicle dynamics but substantially impacted the pilot decisions that led to an inevitable loss of control. Insights based on reconstructed flight data as well as analysis and simulation of the X-15's unique adaptive control system, yield new conclusions about the reasons for the control systems anomalous behavior and the system-level interactions and human-machine interface design oversights that led to the accident.

Accident Investigation↗

NASA NTRS2017

An Evaluation of Structural Analysis Methodologies for Space Deployable Structures

Benchmarks are introduced for evaluating the performance of numerical simulations of space deployable structures. These benchmarks embody the key challenges of interest to future large space deployable structures, including large angle motion, contact between flexible bodies, and the presence of both soft and stiff mechanical components. The benchmarks were used in companion studies to evaluate the ADAMS multibody dynamics code, the LS-Dyna nonlinear finite element code, and the Sierra large-scale parallel nonlinear finite element code. In the past, only multibody codes would have been considered for this application. This study found that all three codes could be used for these benchmarks, a finding that may lead to larger scale, higher fidelity simulations in the future.

Mobrem, Mehran↗

NASA NTRS2020

Revised and extended benchmark results for Rayleigh scattering of sunlight in spherical atmospheres

While most of traditional Earth-atmosphere satellite remote sensing relies on radiative transfer in the plane parallel geometry, effects of sphericity are important at high sun and view zenith angles. Broad understanding of these effects is limited and, contrary to the plane-parallel case, finding accurate numerical results to test spherical RT codes is not easy. This paper aims to partially fill in this gap. Using the full-spherical RT code MYSTIC (Monte Carlo), and the plane-parallel RT code VLIDORT (discrete ordinates) corrected for atmospheric sphericity in the single and multiple scattering, we reproduced with better accuracy and extended the benchmark results by Adams & Kattawar [1978].

spherical atmospheres↗

NASA NTRS1993

Magnetic Field Structure in Monoceros R2

For some time now it has been suspected that magnetic fields play a major role in determining the mass spectrum of stars formed in molecular clouds. Theoretical models of protostellar evolution in a quiescent environment invoke magnetic fields as one form of cloud support and one which has a decisive effect on the minimum stellar mass formed (cf. Shu, Adams and Lizano 1987; Shu et al. 1988). The magnetic field also might act as an angular momentum dampening mechanism---a vital requirement for gravitational collapse and subsequent star formation (Gillis, Mestel and Paris 1974; Mouschovias 1978). Empirical evidence of the contribution of magnetic fields to the total energetics of molecular clouds comes from analysis of Zeeman splitting of OH absorption and thermal emission lines originating from dense (n greater than 10^4 cm^(-3)) cloud cores (Myers and Goodman 1988; Heiles et al. 1991, and references therein)...

Goldsmith, P.F.↗

NASA NTRSDate not supplied

Dust Particle Aeroheating Calculations for Mars Entry Hypersonic Flows

The purpose of the current research effort is to predict particle trajectories in a hypersonic flowfield while accounting for all relevant particle-fluid and particle-particle interactions. The resulting particle solver is titled DUst Simulation & Tracking (DUST) and works in conjunction with the US3D CFD flow solver. The key elements underpinning the current work are an efficient mesh-localiztion algorithm, time-driven hard-sphere model, point-to-point MPI framework, coarse-graining using computational parcels, and high-order Adams-Bashforth time stepping. The coupled US3D-DUST framework will be applied to conduct a multi-physics examination of dust-laden flows around the the Schiarparelli capsule.

Dusty Flows↗

NASA NTRSDate not supplied

Dust Particle Aeroheating Calculations for Mars Entry Hypersonic Flows

Dusty Flows↗

NASA NTRS2022

Further Development of a Function Generator Technique

Further features and properties of functions generated by generalization of the process originally uncovered to describe the evolution of pressure in a rigid volume due to outgassing or desorption are explored. Properties presented include development of a general Maclaurin series associated with these functions, a limitation in using integration by parts to produce asymptotic expansions, and a general description of an implicit Adams-Moulton method for numerical quadrature of transformed functions. These developments are then applied to develop and explore functions that solve the Sievert integral and the modified Bessel function of the first kind, order zero. Features of the error function and the incomplete lower gamma function are also considered.

Michael S. Woronowicz↗

NASA NTRSDate not supplied

VERNE: Revealing the Mysteries and Histories of Venus

Introduction: The three Venus missions that were recently selected for upcoming flight (VERITAS, DAVINCI+, and EnVision) will be incredibly valuable to our understanding of Venus’ history, geology, and atmosphere. However, even once completed, key gaps in our knowledge of Venus, and more generally the formation and active processes on rocky, Earth-like planets, will still persist. Remaining questions include 1) how global intrinsic magnetic fields might be maintained on rocky worlds, and how they could then go extinct, and 2) what role atmospheric sulfur chemistry plays in climates of Earth-like planets, which is an increasingly timely subject as Earth’s own atmospheric sulfur content is climbing due to human activity. These questions require in-situ observations from Venus’ cloud deck, at the altitudes at which the UV absorber exists. The Venus Environment Research and Novel Exploration (VERNE) mission will address these questions with an aerial platform that will drift around the equatorial region of the planet for 9 days. VERNE will collect data to determine the identity of the mysterious UV absorber, while also taking magnetic field measurements over the tesserae, the regions on Venus that are most likely to retain remanent crustal magnetization, in order to understand the potential role of a past intrinsically-generated global magnetic field on Venus. Mission Objectives: The two major science objectives that drive the VERNE mission are: 1) Determine the identity of the Venusian unknown ultraviolet absorber(s). First observed approximately a century ago [1], the composition of Venus’ ultraviolet (UV) absorber is one of the oldest mysteries in Venus atmospheric chemistry [2,3]. While several candidate UV absorbers (mostly sulfur species) have been proposed, no consensus has been reached on its composition and its specific interactions with the atmosphere. Determining the identity of the UV absorber will aid climate models by showing how and where incident solar energy is absorbed by the atmosphere and make progress towards understanding the chemical and energetic processes taking place above Venus’ upper cloud deck [4]. 2) Determine if Venus retains evidence of a past, internally-generated magnetic field. While Venus does not currently have an intrinsically-generated magnetic field, evidence for the existence of a past field on Venus and a timeline of its decay will fill in a more holistic picture of the evolution of Venus’ geological record and atmosphere. As the oldest geologic units on the surface, Venus’ tesserae may still have remanent crustal magnetization signatures within the rocky composition [5]. In any case, the signatures detected will provide insight into Venus’ past geological and core dynamo activity. Mission Summary: VERNE includes a 3-part flight system made up of 1) an entry system with a HEEET (Heatshield for Extreme Entry Environment Technology) aeroshell, 2) an orbiter for data relay, and 3) an in-situ balloon and gondola. After entry into Venus’ atmosphere, the balloon will be deployed within the upper cloud deck, at an altitude of 62 km, over a tesserae region. The in-situ data collection will last for the duration of 2 full circumnavigations of the planet, which will take ~9 days. Instrumentation Suite: The four instruments that comprise VERNE’s instrument payload will enable the identification of the unknown UV absorber and the detection of remanent crustal magnetization if it exists in the tesserae. The proposed instrument suite cycle during mission operations is shown in Fig. 1. The four instruments are described below: 1) Adams (ion neutral mass spectrometer) has a range of 18-257 AMU and will detect and distinguish the mixing ratios of O₂, H₂O, H₂SO₄, S, S₂, S₃, S₄, S₅, S₆, S₇, S₈, SO, SO₂, OSSO, SO₃, Cl₂, FeCl₃ and other trace sulfur and organic species. The spatial (longitudinal) and temporal (day/night) variations will be observed throughout 2 circumnavigations with a sample cadence of 12 minutes. 2) Shelley (nephelometer) will determine the size distribution of the aerosols (0.4 to 36 um) in the atmosphere. With a size resolution of <0.7 um, it can determine which mode of H2SO4 is present and characterize the large (>30 um) organic particles previously detected by the Venera and Galileo missions [6,7]. 3) Herbert (UV imager) will measure UV radiance at 283 nm (the wavelength of SO2 absorption) and 365 nm (the unknown part of the absorber). UV images will be taken concurrently with the INMS and nephelometer to correlate UV absorption with abundances of the UV absorber species. 4) Vonnegut (magnetometer) has a range of >600 nT and a precision and accuracy of 1 nT. If magnetized by a past field, the crust may have retained a magnetization of up to 3 A/m2 [5]. With a noise floor of 10 nT, the magnetometer will be able to detect RCM from an altitude of 62 km, even if the thickness of the magnetized crust is just 1 km (Fig. 2). Mission Concept Design: VERNE will be launched with a mass of 3300 kg in an intermediate-high performance class vehicle with a 4-m fairing. The 475-day mission includes 466 days for the cruise, coasting, and orbit initialization phases before entry, descent, and balloon deployment. During the 9-day science phase, the aerial platform will make 2 circumnavigations of the planet at an altitude of 62 km. The INMS and the nephelometer will acquire data for 2 hours during the daytime and nighttime during each circumnavigation, while the UV imager will be on for the duration of the daytime, and the magnetometer will be operational throughout the entirety of the science phase. Data will be stored and processed with the JPL-designed Sphinx command and data handling system. Data will be sent from the balloon to the orbiter using an S-band relay link, stored on the orbiter, and then forwarded to Earth where it will be received by the DSN. Conclusion: VERNE will fill key gaps in our understanding of the history and ongoing processes related to the geology and atmosphere of Venus and rocky worlds in general. Even with adequate flight system contingencies and expected costs below the $900M New Frontiers cost cap, VERNE is not without its risks and challenges. Further trade spaces to explore include 1) using solely battery power vs. including solar panels to increase the mission duration and 2) investigating the use of lightweight materials and 3D-printed structures to reduce the gondola mass, among others. Acknowledgments: We would like to thank the JPL Planetary Science Summer School, especially our mentors Troy Hudson, Karl Mitchell, and Leslie Lowes, as well as our Team-X study lead Al Nash and the members of Team-X. We’d additionally like to thank our review panel for asking insightful questions and providing valuable feedback. References: [1] Ross, F. E. (1928) Astrophysical J., 68, 57-92. [2] Rossow, W. B. et al. (1980) J. Geophysical Research, 85, 8107-8128. [3] Pinto, J. P. et al. (2021) Nature Communications, 12, 175. [4] Titov, D. V. et al. (2007) Cosmic Research, 21, 401. [5] O’Rourke, J. et al. (2019) Geophysical Research Lett., 46, 5768–5777. [6] Limaye, S. S. et al. (2018) Astrobiology, 18(9), 1181-1198. [7] Grinspoon, D. H. et al. (2013) Planetary and Space Sci., 41(7), 515-542. [8] Parker, R. L. (2003) J. Geophysical Research, 108, 5006. *The cost information contained in this document is of a budgetary and planning nature and is intended for informational purposes only. It does not constitute a commitment on the part of JPL and/or Caltech.

H Alpert↗

NASA NTRS2017

The Detection of 6.9 µm Emission Features in the Infrared Spectra of IRAS 04296+3429, IRAS 05341+0852, IRAS 22272+5435: Evidence for the Presence of Hn-PAHs in Post AGB Stars

Polycyclic aromatic hydrocarbons (PAHs) are generally believed to be ubiquitous in space and responsible for numerous telltale interstellar infrared emission bands. In Sandford et al., (2013), we suggested that polycyclic aromatic hydrocarbons with excess hydrogenation at their periphery (Hn-PAHs) may be an important subclass of these molecules in some astrophysical environments. These molecules are candidates to explain objects with anomalously large 3.4 μm features, which are presumed to be associated with the aliphatic C—H stretching vibrations of the excess hydrogen. In that work, we suggest that for Hn-PAHs to be a viable candidate as the source for this 3.4 μm feature, we must also expect to observe methylene scissoring modes at 6.9 μm. In this work, we continue to develop the Hn-PAH hypothesis with a focus on the 6.9 μm feature. We also present some new observations of three post-asymptotic giant branch (post- AGB) objects with abnormally large 3.4 μm features, IRAS 04296+3429, IRAS 05341+0852, IRAS 22272+5435, in addition to one post-AGB object with normal PAH emissions, IRAS 20000+3239. These observations were made using the FORCAST instrument in grism mode on the Stratospheric Observatory for Infrared Astronomy (SOFIA) aircraft (Adams et al. 2010) and demonstrate the presence of a 6.9 μm feature for the three objects with abnormally large 3.4 μm features and no detectable 6.9 μm feature for the normal PAH emitter. These results are consistent with the hypothesis that Hn-PAHs are a possible source of these infrared emission bands.

ISM↗

NASA NTRSDate not supplied

Low-Speed Testing of the 5.2% Semispan CRM-HL in the DNW-NWB Wind Tunnel

In this paper the wind tunnel test of the 5.2% CRM-HL in the DNW-NWB low speed wind tunnel is described. The tunnel test campaign is settled in the DLR project ADaMant, in which it is of interest to generate qualitative data for CFD validation to improve the predictive accuracy, efficiency, and usability of physical modeling in CFD codes at the borders of the flight envelope. Different configurations of the CRM-HL were tested in a closed as well as in an open test section of the wind tunnel. Several measurement techniques were used to generate validation data including forces and moments, pressures, flow visualization with tufts and oil painting, and infrared thermography for boundary layer transition detection. The evaluation of the results focuses on these techniques in the closed test section. The test comprises Mach numbers from 0.15 to 0.23 and Reynolds numbers from 1.2x10 6 to 1.2x10 6 . Some results are also compared to data from the NASA Langley Research Center 14x22 Foot wind tunnel to assess the repeatability of measurements of the same model in different wind tunnels.

DLR↗

NASA NTRSDate not supplied

Objective Structured Clinical Evaluation (OSCE) of an Artificial Intelligence (AI) Clinical Decision Support System (CDSS) Tool

BACKGROUND Objective Structured Clinical Evaluations (OSCEs) have long been established as a robust methodology for summative assessment of clinical skills and decision-making during medical education. The recent integration of Artificial Intelligence (AI) into clinical decision-making processes has prompted the need for novel evaluation frameworks to assess the efficacy and reliability of AI clinical decision support system (CDSS) tools. This abstract outlines the process of quantitatively evaluating a novel CDSS (“Doc in a Box” Google 2024) trained on curated medical spaceflight data in the psychomotor domain as it interfaces with a human volunteer acting as the crew medical officer (CMO). PURPOSE The AI CDSS under review was developed as part of the Lunar Command and Control Interoperability (LuCCI) project, which is intended to address a gap in how Lunar Surface Systems (LSS) would interoperate across multiple programs, commercial partners, and international partners. The project objective is to define, prototype, integrate, and evaluate an interoperable lunar command, control, data, and software reference architecture to enable autonomy and informatics capability through common standards across LSS. A multi-modal AI-based CDSS compatible with Federated LSS will assist clinicians in diagnosing and managing complex medical conditions by providing evidence-based recommendations through predictive analytics. Given the critical role of decision-support as NASA continues to evolve its Earth-independent medical operations (EIMO), it is imperative to ensure that such AI tools perform reliably and align with clinical standards during progressive lunar and Martian exploration class missions. METHODS The OSCE framework, traditionally used for evaluating human clinicians, was adapted to assess the AI tool's decision-making capabilities in simulated clinical scenarios. In this adapted OSCE, the AI CDSS was tested across a series of structured clinical scenarios designed to mimic real-life spaceflight patient cases. These scenarios included a range of conditions and complexities, allowing for comprehensive assessment of the tool's performance. Key evaluation metrics included accuracy of diagnosis, timeliness of decision-making, and appropriate recommendations for therapies. The OSCE was scored by human physician evaluators who assessed the AI's recommendations in comparison with expert clinicians' medical decision making to ensure alignment with best practices and the standard of care. RESULTS Preliminary results indicate that the AI CDSS demonstrated high accuracy in diagnostic recommendations and decision support across various scenarios. However, certain limitations were noted, such as occasional discrepancies in handling complex or nuanced cases that required a more contextual understanding. Additionally, the tool scored higher on the diagnostic portion of the rubric, with lower scores in the therapeutic recommendations. These findings highlight the importance of continuous refinement and validation of AI tools through rigorous evaluation frameworks like the OSCE. The adaptation of OSCEs for AI tools presents several advantages, including a structured and reproducible approach to evaluation, the ability to test AI systems in diverse clinical scenarios, and the opportunity to benchmark AI performance against established clinical standards to permit charting of future progress as aerospace medicine evolves as a discipline. Remaining challenges include ensuring that these evaluations capture the full spectrum of clinical decision-making scenarios that will be confronted by CMOs during missions and adequately reflecting real-world variability of the austere spaceflight environment. CONCLUSION Employing OSCEs to evaluate AI clinical decision support tools offers a promising approach to validating their clinical utility and efficacy. This methodology not only provides insights into the tool's performance but also fosters ongoing improvement and alignment with standard of care practices. Future research should focus on refining these evaluation processes and addressing limitations to enhance the integration of AI tools in clinical spaceflight settings. REFERENCES Scott S, Hearns V, Barker MA. Testing Clinical Skills: A Look at the OSCE and USMLE Clinical Skills Exams. S D Med. 2019 Oct;72(10):451-453. Majumder MAA, Kumar A, Krishnamurthy K, Ojeh N, Adams OP, Sa B. An evaluative study of objective structured clinical examination (OSCE): students and examiners perspectives. Adv Med Educ Pract. 2019 Jun 5;10:387-397. Karam VY, Park YS, Tekian A, Youssef N. Evaluating the validity evidence of an OSCE: results from a new medical school. BMC Med Educ. 2018 Dec 20;18(1):313.

Ariana M Nelson↗

DOE OSTI2025

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

A geometric framework for momentum-based optimizers for low-rank training

Low-rank pre-training and fine-tuning have recently emerged as promising techniques for reducing the computational and storage costs of large neural networks. Training low-rank parameterizations typically relies on conventional optimizers such as heavy ball momentum methods or Adam. In this work, we identify and analyze potential difficulties that these training methods encounter when used to train low-rank parameterizations of weights. In particular, we show that classical momentum methods can struggle to converge to a local optimum due to the geometry of the underlying optimization landscape. To address this, we introduce novel training strategies derived from dynamical low-rank approximation, which explicitly account for the underlying geometric structure. Our approach leverages and combines tools from dynamical low-rank approximation and momentum-based optimization to design optimizers that respect the intrinsic geometry of the parameter space. We validate our methods through numerical experiments, demonstrating faster convergence, and stronger validation metrics at given parameter budgets.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

DOE OSTI2024

The DUNE Far Detector Vertical Drift Technology. Technical Design Report

DUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

DUNE Phase II: scientific opportunities, detector concepts, technological solutions

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a “Module of Opportunity”, aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

The Zooplankton International Geospatial dataset: A global repository of spatiotemporal freshwater zooplankton community composition data from lakes and reservoirs to support ecological research

Zooplankton transfer substantial energy in aquatic food webs and are used as indicators of environmental change. Syntheses of zooplankton community dynamics globally require datasets that span a wide range of environmental gradients; however, these datasets are limited due to methodological differences across programs, taxonomic inconsistencies, and a lack of standardized metadata. To reconcile these challenges, we created the Zooplankton International Geospatial (ZIG) dataset, which includes original zooplankton, water physical and chemical variables, and lake morphometric data from 311 inland lakes and reservoirs. ZIG includes waterbodies ranging in size from 0.005 to 82,100 km2 and spanning broad latitudinal (−47.26 to 64.90) and longitudinal ranges (−165.04 to 176.53). Temporal coverage for individual waterbodies ranges between 1 and 60 yr with sampling frequency ranging from annually to weekly. With its extensive coverage and content, we consider ZIG to be a cornerstone for future investigations of global scale lake biodiversity change.

Figary, Stephanie [Cornell University, Ithaca, NY]↗