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Next Generation Noble Liquid Detectors

The research program here combines Generic and Directed R\&D for Liquid Noble Gas detectors for neutrino physics and dark matter. In neutrino physics and dark matter research, we are addressing some of the most fundamental questions in particle physics today by studying these tiny particles in the electron family. To study them, detectors must be large, high precision, and ideally have the ability to collect detailed information from both charge and light from neutrino and dark matter interactions. Precision detection combined with large scales can be challenging. Liquid Argon detectors mitigate some of these challenges given the nature of its interaction medium and it’s relatively inexpensive cost per ton. Significant progress has been made in the last 15 years in developing these kinds of detectors to be built and operated at large scales. However there are still challenges and new ideas in moving these detectors from ton scale to kiloton scale. To be able to get the most out of these kinds of detectors directed questions with respect to specific components running and colleting data in the detectors must be understood. As well, new ideas on how to best combine charge and light measurements may lead to new ways to learn new things with these detectors. Experimental test stands to conduct this work, as is done in this proposal, to accomplish both of these goals are critical to address both of these questions. In the test stand enabled under this grant at Yale University’s Wright lab, new developments in efficient small scale setups were developed, instrumentation developed for running and future experiments (the SBND experiment at Fermilab at present, the DUNE experiment in the future) were and will be tested, and new ideas for charge and light determination for new measurements are under study. The long term impact of this work in neutrino physcis is both for the short and long baseline programs originating at Fermi National Accelerator Laboratory. At long baselines, the US flagship DUNE experiment will measure neutrino properties through neutrino oscillations using a beam originating at Fermilab and a massive LArTPC detector sited about a mile underground at the Sanford Underground Research Facility in Lead, South Dakota. Studies here on the high voltage for thes detectors, and ongoing work on charge and light production and collection in the TPC are relevant for the design and data taking of this and other LArTPC detectors to enable them to best measure the neutrinos created at Fermilab that then pass through the detector in South Dakota. What we learn in these detectors may ultimately change the course of how we understand neutrino’s impact in the early universe. What we learn about how to improve this detection technology and develop new ideas in Lar detectors in general may impact both future neutrino experiments and dark matter experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

RAFT: Reconfigurable Array of High-Efficiency Ducted Turbines for Hydrokinetic Energy Harvesting

Diversifying the energy harvesting portfolio is crucial to achieving the ambitious goal of transitioning to clean energy by 2030. Marine hydrokinetic energy has garnered renewed interest due to its high harvesting potential in the U.S., and the resource's reliability and predictability—remaining relatively constant on a daily basis and available 24/7. However, there are currently few commercial devices capable of harnessing the energy from flowing water. This project aims to bridge that gap by designing and evaluating a novel hydrokinetic turbine concept that can efficiently harvest energy from both rivers and tidal streams. The RAFT (Reconfigurable Array of High-Efficiency Ducted Turbines) concept introduces a duct surrounding the turbine rotor and creates an array of small 5-kW units. The duct serves two primary purposes: (1) it enhances hydrodynamic efficiency by accelerating flow to the rotor, and (2) it functions as a structural component, facilitating the formation of modular arrays that lower costs. This project focuses on demonstrating this concept and validating these benefits through simulations and scaled prototype testing. The project team includes 8 faculty members and over 20 students from 3 universities, organized into three core areas: hydrodynamics, electrical systems, and structural analysis, with additional teams dedicated to system integration, environmental assessment and risk management, and tech-to-market strategy. The team successfully demonstrated the increased hydrodynamic efficiency of a ducted turbine compared to an unducted version using high-fidelity simulations and prototype tests. Moreover, design optimization efforts led to surpassing the SHARKS program's goal of 60% reduction of the levelized cost of energy with a significant margin.

13 HYDRO ENERGY↗

Machine Learning for Automated Extraction of Building Geometry

As data science comes to buildings, the promise of using machine learning and novel sources of data has received much attention. Advances in machine learning and computer vision algorithms, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics – cost-effectively, and at scale. Acquisition of features such as footprint are time consuming and costly to acquire with today’s manual methods, but can be streamlined through intelligent software-based solutions applied to satellite images. When combined with aerial RGB and thermal images, full 3D geometries and thermal maps can be constructed to determine additional characteristics such as window to wall ratio, height, number of stories and envelope thermal characteristics. In this paper we present three contributions to accelerate these high potential opportunities: (1) a methodical analysis of how these features can be integrated into today’s simulation and data driven software tools to enhance efficiency measure identification and owner/operator decision making; (2) development and accuracy testing of open source deep neural network methods to extract building footprints from satellite imagery, including the curation and application of openly available GIS datasets for training and continued development by others; and (3) an open framework for drone-based image capture and creation of 3D building geometries. This work represents an important bridge between high-level studies that span diverse application areas and those that detail point solutions yet cannot be easily replicated or extended.

Touzani, Samir↗

Survey Corrosion Testing Methodologies for Additively Manufactured Materials – PNNL

The Advanced Materials and Manufacturing Technology (AMMT) Program intends to develop cross-cutting technologies in support of a broad range of nuclear reactor technologies, and to maintain U.S. leadership in materials and manufacturing technologies for nuclear energy applications. The overarching vision of the AMMT Program is to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy.

36 MATERIALS SCIENCE↗

Using convolutional neural networks to accelerate three-dimensional coherent synchrotron radiation computations

Calculating the effects of coherent synchrotron radiation (CSR) is one of the most computationally expensive tasks in accelerator physics. Here, we use convolutional neural networks (CNNs), along with a latent conditional diffusion (LCD) model, trained on physics-based simulations to speed up calculations. Specifically, we produce the 3D CSR wakefields generated by electron bunches in circular orbit in the steady-state condition. Two datasets are used for training and testing the models: wakefields generated by three-dimensional Gaussian electron distributions and wakefields from a sum of up to 25 three-dimensional Gaussian distributions. The CNNs are able to accurately produce the 3D wakefields ∼250–1000 times faster than the numerical calculations, while the LCD achieves a gain of a factor of ∼34. We also test the extrapolation and out-of-distribution generalization ability of the models. They generalize well on distributions with larger spreads than what they were trained on but struggle with smaller spreads.

43 PARTICLE ACCELERATORS↗

Computational Design of Alloys for Energy Technologies

Advanced materials that maintain their mechanical performance under elevated temperatures, corrosive environments, and a range of static and evolving stresses are needed to improve the efficiency and reduce the environmental impact of a wide spectrum of energy technologies. For instance, cost-efficient alloys that can withstand high temperatures (e.g., 700 °C) have a critical role in improving the efficiency and economics of power generation to support decarbonization of the energy sector; such is true of both the nuclear and fossil energy sectors. Considering both the threats of the energy crisis, namely soaring costs of greenhouse gas emission-producing energy and climate change, it is essential to increase the pace of material discovery and enable rapid paths for material qualification to advance clean energy technologies. Conventionally, alloy development has followed a slow Edisonian process that uses repeated cycles of making, characterizing, and modifying to arrive at optimum composition and processing conditions to achieve the desired component performance. This optimization is followed by the necessary stepwise materials qualification. Furthermore, the increasing adoption of sound data management and physics-informed machine learning represents the next step in the acceleration of materials design and development. In the integrated computational materials engineering (ICME) approach, computational modeling and simulation data from different length and time scales can be combined with complex microstructural details from multimodal experimental characterization and selective property testing to close the design loop for rapid alloy development.

Computational Design Of Materials↗

Two–Dimensional Idealized Hadley Circulation Simulation for Global High Resolution Model Development

A new framework for the development of global high resolution models using a vertical- meridional, two-dimensional pole-to-pole domain is proposed. Compared with the three-dimensional global model, the two-dimensional framework can simulate cloud-scale convection at significantly reduced computational cost, data volume, and turn-around time, and accelerate the development phase. Although idealized, it allows for simulation of various clouds and scale interactions under a wide range of environmental conditions, even though zonal waves such as mid latitude storms cannot be simulated. Physics schemes can be tested and assessed over a full array of simultaneously occurring cloud regimes. The framework can serve as an intermediate step between a one-dimensional simulation and a full three-dimensional global model. Using this framework, we analyze the resolution dependencies of simulated clouds and the Hadley circulation in a range of global high resolution models by performing multiple 1000-day simulations; for some resolutions tested, for example, 2 km horizontal resolution, three-dimensional simulation is not feasible at the present time. Analysis shows that both horizontal and vertical resolution determine the properties of the Hadley circulation and clouds, and that the differences among the simulated Hadley circulations are understood as differences in scale interactions influenced by resolution.

54 ENVIRONMENTAL SCIENCES↗

Strategies for Developing High-Volume Fly Ash Concrete with High Early-Age Strength for Precast Applications

Partial replacement of portland cement with supplementary cementitious materials (SCMs), such as fly ash, is an effective strategy for improving durability and reducing the CO 2 footprint of concrete. However, using high-volume fly ash (HVFA) binders in precast and prestressed concrete is currently limited; largely due to reduced early-age strength development that impedes rapid production and prestressing of precast concrete. To investigate and address this challenge, HVFA mortars with a minimum of 40% fly ash by mass of cementitious materials were developed and tested in this study. Two fresh fly ashes (an ASTM C618 Class F and a Class C) and a landfilled fly ash (Class F) were included. Various strategies for improving the early strength were evaluated, including gypsum optimization, chemical accelerators, steam curing, use of CSA cements, and adding other reactive SCMs like silica fume, calcined clay, and slag cement. Steam curing and the use of CSA cement at high dosages (40% of total binder) were found to be the most successful strategies across all three fly ashes. Additionally, significant improvements were observed with gypsum optimization (for Class C fly ash) and the use of accelerators (for Class F fly ashes), and these strategies are likely to be more feasible considering later-age strength and economic viability. Interestingly, HVFA mixtures made with the landfilled fly ash used in this study were able to achieve high early strengths with water-to-cementitious materials ratio adjustment alone. As a result, these HVFA mixtures were also found to be less responsive to accelerators when compared to the fresh Class F fly ash, highlighting an important distinction between the materials despite the similarity in chemical composition.

42 ENGINEERING↗

Electric accumulation of millicharged particles

A terrestrial population of millicharged particles that interact significantly with normal matter can arise if they make up a dark matter subcomponent or if they are light enough to be produced in cosmic-ray air showers. Such particles thermalize to terrestrial temperatures through repeated scatters with normal matter in Earth’s environment. We show that a simple electrified shell (for example, a Van de Graaff generator) functions as an efficient accumulator of such room-temperature millicharged particles, parametrically enhancing their local density by as much as 12 orders of magnitude. This can be used to boost the sensitivity of any detector housed in the shell’s interior, such as ion traps and tests of Coulomb’s law. In a companion paper, we apply this specifically to Cavendish tests of Coulomb’s law, and we show that a well-established setup can probe a large region of unexplored parameter space, with sensitivity to the irreducible density of millicharged particles generated from cosmic rays that outperforms future accelerator searches for sub-GeV masses.

Berlin, Asher [Fermilab] (ORCID:0000000211561482)↗

Spontaneous Cyclogenesis without Radiative and Surface-Flux Feedbacks

Tropical cyclones (TCs) are among the most intense and feared storms in the world. What physical processes lead to cyclogenesis remains the most mysterious aspect of TC physics. Here, we study spontaneous TC genesis in rotating radiative–convective equilibrium using cloud-resolving simulations over an f plane with constant sea surface temperature. Previous studies proposed that spontaneous TC genesis requires either radiative or surface-flux feedbacks. To test this hypothesis, we perform mechanism-denial experiments, in which we switch off both feedback processes in numerical simulations. We find that TCs can self-emerge even without radiative and surface-flux feedbacks. Although these feedbacks accelerate the genesis and impact the size of the TCs, TCs in the experiments without them can reach similar intensities as those in the control experiment. We show that TC genesis is associated with an increase in the available potential energy (APE) and that convective heating dominates the APE production. Overall, our result suggests that spontaneous TC genesis may result from a cooperative interaction between convection and circulation and that radiative and surface-flux feedbacks accelerate the process. Furthermore, we find that increasing the planetary rotation favors spontaneous TC genesis.

54 ENVIRONMENTAL SCIENCES↗

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity↗

Development of a Beam Halo Monitor

Muons, Inc. proposed improved Residual-Gas luminescent Beam Profile Monitors for Intense Beams by adding novel features including a mirascope, a light collecting device devised in the 16th century by an inventor of the telescope. A modern mirascope consists of 2 paraboloids. Light generated by the beam is collected by the paraboloids and creates a beam image. By placing a lens near the image it is possible to collect almost 100% of the emitted light, up to ten times better than existing fluorescence profilometers. Intense (multi-MW) proton beams pose a challenge for beam profile measurements. Solid-based beam intercepting instrumentation produces unallowable levels of radiation at these high powers. An alternative is to use a zero-or-low mass device such as a residual-gas profile monitor, either through collection of ionization or fluorescence. Fluorescence has an intrinsic advantage over the usual collection of ionized electrons in that it is not affected by the strong and variable electric and magnetic fields created by the beam that can distort profiles and make calibration difficult. For this reason, we proposed the fluorescence technique using the mirascope and other methods to enhance light collection and versatility by modifying the residual gas and its spatial distribution. In Phase I, we designed a mirascope and its electronics for commissioning and beam tests in a proposed Phase II. The design was based on optical simulations done in Phase I, and a physics run plan was developed for optimizing and testing. The Phase II experimental site and program have been planned and our goal is to produce a universal low cost Mirascope Residual-Gas Luminescent Beam Profile Monitor that can replace all other profile monitors currently used in accelerators.

43 PARTICLE ACCELERATORS↗

Software Deployment Process at NERSC: Deploying the Extreme-scale Scientific Software Stack (E4S) Using Spack at the National Energy Research Scientific Computing Center (NERSC)

One of the many benefits of using a high-performance computing (HPC) system at a Department of Energy (DOE) Office of Science (SC) HPC facility is the large number of software products, built and optimized for the system. The HPC center staff and HPC vendors provide optimized software such as libraries and even full scientific applications, ready to be used by users as building blocks to accelerate scientific discovery. Behind each provided packaged software module are a large number of decisions - which compiler, optimizations, variants/options - to build the software on the target system. And, even before the software gets deployed, the software must be developed, tested, and maintained, including deprecating old versions and ensuring compatibility across versions. The software lifecycle is complex and is further convoluted by a web of interdependencies on other software.

97 MATHEMATICS AND COMPUTING↗

Testing of PIP-II pre-production 650 MHz couplers in warm test stand and in cryomodule

650 MHz fundamental power couplers were developed for PIP-II project to deliver RF power for low-beta and high-beta elliptical cavities. Few prototypes were built and tested and after some modification we built 8 pre-production couplers (with few spares for vacuum side) for HB650 cryomodule. All couplers were successfully tested in pulse mode (up to 100kW) and in CW mode (up to 50kW) in test stand at full reflection at 8 phases. In baseline configuration with DC bias we do not see any multipactoring activity after short processing. We also tested power processing without bias for uncoated and TiN coated ceramic window. Results of these studies presented in this paper. One of the coupler was assembled on LB650 cavity and tested at cryogenic environment in STC cryostat at ~20kW power with full reflection at different reflection phase. We also demonstrated good result from power processing without bias for warm and cold cavity. Six couplers were assembled on HB650 cavities in pre-production cryomodule. Test results from cryomodule qualification is discussing in this paper.

43 PARTICLE ACCELERATORS↗

3D Display of Events on a Stack of CCDs and OSCURA MCMs Copper Box Redesign

A 3D event display algorithm was successfully implemented using CERN root to visualize muons, electrons, and photons within the CCD's from the OSCURA testing setup. The copper box from this setup was also redesigned to accommodate up to 21 MCMs, enabling a multi-layer sensor tracker orientation. This setup and algorithm aims to explore and search for millicharged particles (mCPs) in accelerators, leading to improved particle tracking precision and reduced background events.

Meza Quintero, Oscar↗

RaDIATE Collaboration for Material Studies

In the recent past, major accelerator facilities have been limited in beam power not by their accelerators, but by the beam intercepting device survivability. As next-generation accelerator target facilities (High Energy Physics, Spallation Sources, …) become increasingly more powerful and intense, high power target systems face key technical challenges. Beam-intercepting devices such as beam windows and secondary particle-production targets are continuously bombarded by high-energy high-intensity pulsed proton beams to produce secondary particles. Energy deposition from the primary beam induces near instantaneous heating (thermal shock) and microstructural changes (radiation damage) in the beam-intercepting materials. Both thermal shock and radiation damage ultimately degrade the performance and lifetime of targets and have been identified as the leading cross-cutting challenges of high-power target facilities. In order to operate reliable beam-intercepting devices in the framework of energy and intensity increase for next generation accelerators, the RaDIATE collaboration (Radiation Damage In Accelerator Target Environment) managed by Fermilab, brings together existing expertise in nuclear material and accelerator targets from 20 international institutions to execute a coordinated strategy for high power targetry R&D. This collaboration is generating new and useful materials data for application within the accelerator and the fission/fusion communities. I will give an overview of the RaDIATE R&D program and the achievement in the last few years on material studies in support of High Power Targetry development, including results obtained from irradiation test, development of novel materials and the prospective towards future irradiation campaign. A highlight will be given to the results in collaboration with our colleagues from J-PARC.

Pellemoine, Frederique↗