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DOE OSTI2022

Resistive wall tearing mode disruptions in DIII-D and ITER tokamaks

Disruptions are a serious problem in tokamaks, in which thermal and magnetic energy confinement is lost. This paper uses data from the DIII-D experiment, theory, and simulations to demonstrate that resistive wall tearing modes (RWTMs) produce the thermal quench (TQ) in a typical locked mode shot. Analysis of the linear RWTM dispersion relation shows the parameter dependence of the growth rate, particularly on the resistive wall time. Linear simulations of the locked mode equilibrium show that it is unstable with a resistive wall and stable with an ideally conducting wall. Nonlinear simulations demonstrate that the RWTM grows to sufficient amplitude to cause a complete thermal quench. The RWTM growth time is proportional to the thermal quench time. Here, the nonlinearly saturated RWTM magnetic perturbation amplitude agrees with experimental measurements. The onset condition is that the q = 2 rational surface is sufficiently close to the resistive wall. Collectively, this identifies the RWTM as the cause of the TQ. In ITER, RWTMs will produce long TQ times compared to present-day experiments. ITER disruptions may be significantly more benign than previously predicted.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

OPERATIONAL TOPOLOGY ESTIMATION OF THREE PHASE UNBALANCED POWER DISTRIBUTION SYSTEMS WITH OUTAGES

Distribution grid, in general, is constructionally loopy but a radially operated network. Opening and closing of suitable tie-switches allows transition from one radial topology to another. Tie-switches ensure reliability and provide restoration paths when faults (outages) occur. The estimation of the system's current operational topology is a precursor to implementing any optimal control actions (during normal operation) or restorative actions (during outage condition). The existing literature in topology detection suffers with several limitations including: (1) computationally intensive nonlinear formulations that are not scalable for large distribution systems, (2) methods requiring exhaustive search for the correct topology by enumerating the complete topological search space, and (3) approaches requiring large volumes of time-series measurements and are not applicable for estimating continuously changing operational topology. Furthermore, the existing literature on distribution grid topology estimation cannot be extended to estimate the operational topology during outage conditions. For operational topology estimation during outages, our objective is to estimate both energized radial feeder and the outaged sections. Starting with a radial topology, these methods identify outaged feeder sections and hence, are inapplicable when the current radial operational topology is not known. In this work, we present a mathematical programming approach to estimate the operational topology of a three-phase unbalanced power distribution system under both outage and normal operating conditions. The aforementioned limitations of existing literature were countered by modeling the problem as a mixed-integer linear programming (MILP) problem which minimizes the errors in available measurements while satisfying the power flow and structural constraints of the system. Specically, a minimum weighted least absolute value estimator is proposed that uses the instantaneous line flow measurements, historical/ forecasted load data, and ping measurements from a limited set of smart meters and solves an MILP to identify the operational topology based on a linearized three-phase unbalanced power flow model. The proposed approach is tested on IEEE 123-bus feeder and 1069 bus multi-feeder test system and the numerical results prove the applicability of the proposed method to large three phase unbalanced grids with high errors in measurements. It is observed that the approach performs well even at high percentages of measurement errors.

GANDLURU NAGA, ANANDINI↗

DOE OSTI2019

Probing Ultrafast Electron (De)localization Dynamics in Mixed Valence Complexes Using Femtosecond X-ray Spectroscopy (Final Report)

The overall goal of this research program was to understand valence electron and vibrational motion following metal-to-metal charge transfer (MMCT) excitation in the mixed valence complexes dissolved in aqueous solution. The project objectives were (i) to observe the time-dependent re-arrangement of d electrons across two transition metal sites and the bridging ligand following photoinduced MMCT excitation on a sub-50 femtosecond timescale using femtosecond X-ray pulses generated at LCLS (ii) to simulate femtosecond X-ray absorption and emission spectra of solvated, photo-excited, transition metal mixed valence complexes using a realistic treatment of multi-electron correlations/transitions, spin-orbit coupling and final state lifetime effects and to propose and study the feasibility of nonlinear X-ray experiments on solvated transition metal mixed valence systems using future X-FEL light sources and (iii) to determine the role of coupled electronic and vibrational motions during ultrafast photoinduced charge transfer. The final report highlights the scientific results obtained during this funding period.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Do the Tropics Rule? Assessing the State of Tropical Climate Science

A symposium honoring Mark Cane and his role in the advancement of climate science was held at the Lamont-Doherty Earth Observatory of Columbia University in October 2014. Over 150 climate scientists from the United States and abroad participated in the program. First day of the symposium began with a retrospective session on the development of tropical ocean?atmosphere interactions, equatorial wave dynamics, and a theory for ENSO. Steve Zebiak, David Halpern and Ed Sarachik, each provided historical context on the advances during the 1960s to 1980s that led to ENSO prediction. The first session of the second day was devoted to outstanding issues in paleoclimate dynamics. David Battisti. He revisited the question of why the ocean overturning circulation was situated in the Atlantic and not the Pacific, reviewing various hypotheses for why the Atlantic is the saltier ocean. The final session of the symposium highlighted the perspectives of climate dynamics from some key contributors to the field. Tim Palmer discussed nonlinear dynamics and regime shifts as a paradigm for understanding climate changes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Light Water Reactor Sustainability Program Interrogation of Alkali-Silica Reaction Degraded Concrete Samples using Acoustic and Thermal Techniques to Support Development of a Structural Health Monitoring Framework

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Health monitoring of concrete structures is performed to understand the current condition of a structure based on heterogeneous measurements and then produce high-confidence actionable information regarding structural integrity. This information can then be used to support operational and maintenance decisions. The proposed diagnosis and prognosis framework consists of four elements: health monitoring, data analytics, uncertainty quantification, and prognosis. The objectives of this ongoing research project focuses on health monitoring and data analytics of concrete slab cast, which is cured using four pockets of reactive aggregates: pure silica, wells, placitas, and spratt. A controlled concrete slab with four aggregates is cast at Vanderbilt University in representative conditions to accelerate degradation due to alkali-silica reaction (ASR). Four nondestructive evaluation (NDE) techniques (thermography, mechanical deformation measurements, nonlinear impact resonance-acoustic spectroscopy, and vibro-acoustic modulation) are used to examine the degraded concrete slab. Heterogeneous data from these techniques are analyzed for assessing ASRrelated degradation in concrete samples. In addition, this report discusses thermography assessment of three cement bricks cured under different conditions to accelerate ASR-related degradation. The application of the digital image correlation technique to study ASR-related degradation on a large concrete sample at the University of Tennessee Knoxville is discussed and initial observations are presented in this report. The results from the data analysis of the NDE techniques on concrete slab cured at Vanderbilt University are discussed in detail in this report. The major outcome of the analysis suggests that the nonlinear impact resonance acoustic spectroscopy is able to detect potential degradation in a concrete slab but is unable to locate or isolate the degradation. Alternatively, the vibro-acoustic technique is able to detect degradation and locate the damage in the concrete slab cast. The outcomes supports development of a structural health monitoring framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Exploring the Effects of Population and Employment Characteristics on Truck Flows: An Analysis of NextGen NHTS Origin-Destination Data

Truck transportation remains the dominant mode of US freight transportation because of its advantages, such as the flexibility of accessing pickup and drop-off points and faster delivery. Because of the massive freight volume transported by trucks, understanding the effects of population and employment characteristics on truck flows is critical for better transportation planning and investment decisions. The US Federal Highway Administration published a truck travel origin-destination data set as part of the Next Generation National Household Travel Survey program. This data set contains the total number of truck trips in 2020 within and between 583 predefined zones encompassing metropolitan and nonmetropolitan statistical areas within each state and Washington, DC. In this study, origin-destination-level truck trip flow data was augmented to include zone-level population and employment characteristics from the US Census Bureau. Census population and County Business Patterns data were included. The final data set was used to train a machine learning algorithm-based model, Extreme Gradient Boosting (XGBoost), where the target variable is the number of total truck trips. Shapley Additive ExPlanation (SHAP) was adopted to explain the model results. Results showed that the distance between the zones was the most important variable and had a nonlinear relationship with truck flows.

Uddin, Majbah↗

DOE OSTI2018

An efficient algorithm for the projection of a point on the intersection of two hyperplanes and a box in $\mathbb {R}^n$

Here, we present an efficient strongly polynomial algorithm for the projection of a point on the intersection of two hyperplanes and a box in $\mathbb {R}^n$ . Interior point methods are the most efficient algorithm in the literature to solve this problem. While efficient in practice, the complexity of interior-point methods is bounded by a polynomial in the dimension of the problem and in the accuracy of the solution. Moreover, their efficiency is highly dependent on a series of parameters depending on the specific method chosen (especially for nonlinear problems), such as step size, barrier parameter, accuracy, among others. We propose a new method based on the KKT optimality conditions. In this method, we write the problem as a function of the Lagrangian multipliers of the hyperplanes and seek to find the pair of multipliers that corresponds to the optimal solution. We prove that the algorithm has complexity $O(n^2 \log n)$ .

42 ENGINEERING↗

DOE OSTI2019

Innovative Approach to SCC Inspection and Evaluation of Canister in Dry Storage

This final report is summarized four years of work of awarded project number DE-NE0008442\IRP-15-9318, title as: “Innovative Approach to SCC Inspection and Evaluation of Canister in Dry” supported by Nuclear Energy University Program\Integrated Research Program, NEUP\IRP, where last year is an extension of no cost project. This research work is focused on the possible degradation of dry storage canister holding used nuclear fuel (UNF), due to exposure of marine atmospheric environment. The canister usually designed from a welded austenitic stainless-steel of types 304 or 316, encased in a concrete shell known as an overpack. This canister designed and licensed for 20 years with an extension period need to be determined, in addition 20 years or more. These casks are located throughout the country in Independent Spent Fuel Storage Installations (IFSFIs) often on the site close to nuclear power plants, that are often located in coastal or lake-side regions where a marine atmospheric salt air environment exist. As a result of several recent decisions, such as not pursuing Yucca Mountain as a long-term geologic repository storage facility for UNF and the cancellation of the construction of a reprocessing facility in the 1980s due to proliferation risks, interim dry storage facilities for long-term storage are vital option for the immediate future of nuclear energy technology. One of the primary concerns with respect to the long-term performance of the storage casks is the potential for corrosion initiation due to deliquescence of salts deposited on the canister surface as aerosols; in regions of high residual weld stresses, this may lead to localized stress corrosion cracking (SCC). Dust and aerosols in the air being drawn though ventilation openings in the overpacks of passively ventilated dry canister storage systems may be deposited on the stainless-steel canister outer surfaces. Under these conditions, localized corrosion attack can occur. Chlorides ions deliquescence on the canister surface, a process by which the salts essentially pull moisture out of the air, creating a concentrated salt brine on the canister surface. Chloride-induced stress corrosion cracking (CISCC) of welded zones is of special concern, as it a well-documented mode of attack for austenitic stainless steels marine environments, and many independent spent fuel storage installations (ISFSIs) are located in coastal areas. Recent canister inspections have shown that chloride salts are present on the surface of in-service canisters at near-marine settings. However, canister surface inspections of satisfactory resolution to detect SCC have never been carried out in details, because access to the canister surfaces through vents in the overpacks is extremely limited, and high radiation fields make removal of the canisters from the overpacks undesirable. Although no significant corrosion damage has not been detected up to date, there is concern that this may lead to pitting corrosion, which could in turn develop into stress corrosion cracking, causing canister structural failure. The initiation and propagation of pitting corrosion has been widely studied in full immersion conditions, but limited studies have been done on marine atmospheric conditions, which is a focus of this work, these includes laboratory and field experimentally and propagation rate modeling of pitting and transition to crack, and crack propagation rate. It is known, however, that the rate of atmospheric corrosion can be affected by variations in relative humidity (RH), salt density, salt type, droplet area, temperature and stainless-steel microstructure and residual stress particularly in welded zones of canisters. The integrated research program has identified potential deterioration mechanisms for the stainless-steel canisters containing the UNF in dry storage that require detailed research and investigation and will have an impact on the performance of long-term interim storage under the normal and extreme environmental conditions experienced during the duration of this storage. The prediction and monitoring of canister corrosion processes while in storage can provide important data for the assessment of interim storage performance and the safety to the public. This report comprises of mainly the published results in different journals and covering a wide range spectrum from susceptible stainless-steel types 304\316 microstructural analysis through the implant test at atmospheric environment, residual stress analysis of mockup canister and simulation, inspection methodology includes nonlinear ultrasound and vibro-thermography and stochastic modeling and simulation of pits propagation rates and transition to cracks. Description of field specimens installed at ISFSI of Main Yankee is given in the following chapters and will be analyzed in the coming future and serves as an important data for a stochastic analysis as it was drawn from the publications and reports described in this report. The purpose of this report is to bring together the project efforts that includes improving in our understanding of structural aging performance at current dry storage casks fleet at ISFSIs in the context of remedial maintenance and inspection applications technologies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Intraspecific Diversity in Thermal Performance Determines Phytoplankton Ecological Niche

ABSTRACT Temperature has a primary influence on phytoplankton physiology and ecology. We grew 12 strains of Gephyrocapsa huxleyi isolated from different‐temperature regions for ~45 generations (2 months) and characterised acclimated thermal response curves across a temperature range. Even with similar temperature optima and overlapping cell size, strain growth rates varied between 0.45 and 1 day −1 . Thermal niche widths varied from 16.7°C to 24.8°C, suggesting that strains use distinct thermal response mechanisms. We investigated the implications of this thermal intraspecific diversity using an ocean ecosystem simulation resolving phytoplankton thermal phenotypes. Model analogues of thermal ‘generalists’ and ‘specialists’ resulted in a distinctive global biogeography of thermal niche widths with a nonlinear latitudinal pattern. We leveraged model output to predict ranges of the 12 lab‐reared strains and demonstrated how this approach could broadly refine geographic range predictions. Our combination of observations and modelled biogeography highlights the capacity of diverse groups to survive temperature shifts.

Krinos, Arianna I. [Department of Biology Woods Ho↗

DOE OSTI2017

Coupled Physics Simulation of Expansive Reactions in Concrete with the Grizzly Code

The Grizzly code is being developed under the US Department of Energy’s Light Water Sustainability program as a tool to model aging mechanisms and their effects on the integrity of critical nuclear power plant components. An important application for Grizzly is the modeling of aging in concrete structures, which can be due to a number of mechanisms. Initial focus in this area has been on modeling expansive reactions due to alkali-silica reactions or radiation-induced volumetric expansion. Grizzly is an inherently multiphysics modeling platform that naturally permits including the effects of multiple coupled physics in a simulation. Models have been developed for transport of heat and moisture in concrete, and these have been coupled and used as inputs to models for expansive reactions. This paper summarizes this capability as well as work currently underway to couple it with mechanical deformation models that account for nonlinear constitutive behavior.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Generating Mixed Patterns of Residential Segregation: An Evolutionary Approach

The Schelling model of residential segregation has demonstrated that even the slightest preference for neighbors of the same race can be amplified into community-wide segregation. However, these models are unable to simulate mixed, coexisting patterns of segregation and integration, which have been seen to exist in cities. Using evolutionary model discovery we demonstrate how including social factors beyond racial bias when modeling relocation behavior enables the emergence of strongly mixed patterns. Our results indicate that the emergence of mixed patterns is better explained by multiple factors influencing the decision to relocate; the most important being the interaction of nonlinear, rapidly diminishing racial bias with a recent, historical tendency to move. Additionally, preference for less isolated neighborhoods or preference for neighborhoods with longer residing neighbors may produce weaker mixed patterns. Finally, this work highlights the importance of exploring the influence of multiple hypothesized factors of decision making, and their interactions, within agent rules, when studying emergent outcomes generated by agent-based models of complex social systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Statistical characteristics of cloud variability. Part 2: Implication for parameterizations of microphysical and radiative transfer processes in climate models

The effects of subgrid cloud variability on grid-average microphysical rates and radiative fluxes are examined by use of long-term retrieval products at the Tropical West Pacific, Southern Great Plains, and North Slope of Alaska sites of the Department of Energy's Atmospheric Radiation Measurement program. Four commonly used distribution functions, the truncated Gaussian, Gamma, lognormal, and Weibull distributions, are constrained to have the same mean and standard deviation as observed cloud liquid water content. The probability density functions are then used to upscale relevant physical processes to obtain grid-average process rates. It is found that the truncated Gaussian representation results in up to 30% mean bias in autoconversion rate, whereas the mean bias for the lognormal representation is about 10%. The Gamma and Weibull distribution function performs the best for the grid-average autoconversion rate with the mean relative bias less than 5%. For radiative fluxes, the lognormal and truncated Gaussian representations perform better than the Gamma and Weibull representations. The results show that the optimal choice of subgrid cloud distribution function depends on the nonlinearity of the process of interest, and thus, there is no single distribution function that works best for all parameterizations. Examination of the scale (window size) dependence of the mean bias indicates that the bias in grid-average process rates monotonically increases with increasing window sizes, suggesting the increasing importance of subgrid variability with increasing grid sizes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Nematic Colloidal Micro‐Robots as Physically Intelligent Systems

Abstract Physically intelligent micro‐robotic systems exploit information embedded in micro‐robots, their colloidal cargo, and their milieu to interact, assemble, and form functional structures. Nonlinear anisotropic fluids such as nematic liquid crystals (NLCs) provide untapped opportunities to embed interactions via their topological defects, complex elastic responses, and ability to dramatically restructure in dynamic settings. Here a four‐armed ferromagnetic micro‐robot is designed and fabricated to embed and dynamically reconfigure information in the nematic director field, generating a suite of physical interactions for cargo manipulation. The micro‐robot shape and surface chemistry are designed to generate a nemato‐elastic energy landscape in the domain that defines multiple modes of emergent, bottom‐up interactions with passive colloids. Micro‐robot rotation expands the ability to sculpt interactions; the energy landscape around a rotating micro‐robot is dynamically reconfigured by complex far‐from‐equilibrium dynamics of the micro‐robot's companion topological defect. These defect dynamics allow transient information to be programmed into the domain and exploited. Robust micro‐robotic manipulation strategies are demonstrated that exploit these diverse modes of nemato‐elastic interaction to achieve cargo docking, transport, release, and assembly of complex reconfigurable structures at multi‐stable sites. Such structures are of great interest to future developments of LC‐based advanced optical device and micro‐manufacturing in anisotropic environments.

Yao, Tianyi↗

DOE OSTI2024

MHD-induced beta limits in the Large Helical Device

Using the extended-magnetohydrodynamics code, M3D-C1, we perform a systematic numerical study of the effect of externally applied heating on the achievable plasma beta in a ten field-period heliotron. Heat sources of varying intensity are applied to a vacuum magnetic field that is representative of the standard configuration of the Large Helical Device, with R 0 = 3.66 m, where R 0 is the radial position of the magnetic axis in vacuum. As the system is driven to a state that is unstable to low-n magnetohydrodynamic (MHD) modes, nonlinear mode interactions lead to the formation of chaotic magnetic fields. With sufficiently strong heating, a collapse of the electron temperature profile is observed. This demonstrates the necessity of simulating the self-consistent evolution of plasma profiles, without imposing assumptions on the structure of the magnetic field, to accurately determine transport properties in stellarator plasmas. It also highlights the value of these advanced simulation capabilities for accelerating the development of high-performance stellarator operating scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Space Charge Driven Emittance Growth and the Effect of Octupoles in IOTA

The Integrable Optics Test Accelerator (IOTA) at Fermilab is a small machine dedicated to a broad frontier accelerator physics program. An important aspect of this program is to investigate the potential benefits of the resonance free tune spread achievable with integrable optics to store and accelerate high intensity proton beams for which space charge is significant. In this context, a good understanding of proton beam emittance growth and particle loss mechanisms is essential. Assuming nominal design parameters, simulations show that for a bunched beam, the bulk of emittance growth takes place immediately following injection, typically within tens of turns. We attempt to account for this growth using a simplified RMS mismatch theory; some of its limitations and possible improvements are briefly discussed. We then compare theoretical predictions to simulations performed using the PIC code pyORBIT. Further exploring ways to mitigate emittance growth and reduce particle loss, we compare two beam matching strategies: (1) matching at the injection point (2) matching at the center of the nonlinear (octupole) insertion region where $\beta_x = \beta_y$. To observe how nonlinearity affects emittance growth and whether it dominates growth due to mismatch, we track two different distributions. Finally, we explore the potential of using octupoles in a quasi-integrable configuration to mitigate growth using a variety of initial distributions both at reduced and full intensities.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Leveraging FPGA Advantages for Quicker Data Processing for LBNF

The Long Baseline Neutrino Facility (LBNF) will deliver a 2.4 MW muon neutrino beam from Fermilab to the Deep Underground Neutrino Experiment (DUNE), requiring unprecedented precision in beamline alignment to achieve DUNE's neutrino oscillation measurement goals. Vertical misalignments of beamline components as small as 0.5 mm can contribute 6-7\% uncertainty in predicted neutrino flux, necessitating sub-0.1 mm alignment monitoring capabilities. The Horn Location Sensor (HLS) system employs frequency sweep interferometry (FSI) in a distributed hydrostatic leveling network to achieve the required precision under harsh radiation conditions up to 5000 kRad/year. Traditional FSI implementations suffer from laser sweep nonlinearities that degrade resolution and require computationally intensive post-processing corrections using gas reference cells. This work presents a real-time FPGA-based implementation of the HLS data acquisition and processing system using a sweep tracker interferometer for dynamic sweep linearization. The system utilizes a PYNQ-Z2 FPGA with programmable logic implementing parallel 16k-point FFT processing across four channels, synchronized by the sweep tracker signal to eliminate post-processing requirements. Spectral performance testing demonstrates significant improvements in peak sharpness compared to traditional fixed-frequency digitization. The FPGA implementation enables real-time displacement monitoring with processing speeds orders of magnitude faster than software-based approaches, essential for the operational requirements of LBNF's eventual distributed sensor network. This advancement in real-time FSI processing directly supports DUNE's precision neutrino physics program by providing the rapid feedback necessary for maintaining stringent beamline alignment tolerances during high-power beam operations.

Rossel, Jacob↗

DOE OSTI2025

Real-Time FPGA Implementation For Frequency Sweep Interferometry In The LBNF Complex

Rossel, A. Jacob [Fermilab; Unlisted]↗