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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Test Results of the LQXFA/B02 and LQXFA/B03 Cryo-Assemblies for the High Luminosity LHC Upgrade

Here, the US High-Luminosity LHC Accelerator Upgrade Project (AUP) is responsible for delivering cryo-assemblies for the Q1/Q3 quadrupole optical components of the High Luminosity LHC upgrade at CERN. Total of 10 cryo-assemblies containing two Nb3Sn quadrupole magnets per cold mass will be delivered within this program. After the successful test of the first pre-series cryo-assembly in 2023, two more cryo-assemblies were tested at Fermilab's horizontal test facility. Production overview and the test results of the LQXFA/B02 and LQXFA/B03 cryo-assemblies are summarized in this paper. After the first test, to increase the capability of the horizontal test facility, various improvements have been made. These improvements are also described in this paper.

Chlachidze, Guram [Fermi National Accelerator Labo↗

Measurement of the Cathode Recess

The 113 MHz SRF gun for the coherent electron cooling is designed with adjustable position of the cathode vs. the nose piece of the quarter wave gun as it is shown in Fig. 1. By changing the cathode position we modify the profile of the accelerating field. By retracting the cathode, we reduce the surface field but increase the focusing component as it shown in Fig. 2. The optimal position is defined by the beam dynamics and is found based on simulations.

43 PARTICLE ACCELERATORS↗

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗

DESIGN ISSUES AND QUALIFICATION OF HYDROFORMED DOUBLE WALLED EXPANSION JOINTS IN VACUUM SERVICE

The Vacuum Auxiliary System for ITER is devoted to pumping out, venting, and purging the vacuum volumes of the tokamak. Over 5000 clients including the cryostat and vacuum vessel, at 8500 m3 and 1400 m3 respectively, are serviced by approximately 150 pumping stations through 6 km of pipework. The piping and functions provided to the clients include component operation, routing of potentially tritiated gases, and timely leak localization. Expansion joints are used to reduce loadings on pumps and piping stresses but also to qualify in-line components having low allowable design loads. The ITER project utilizes vacuum valves that are not designed to withstand typical piping system loadings and require detailed design and evaluation. Loading scenarios prescribed by governing system specifications must be considered. To maintain allowable design loads for components and to keep piping stresses below code requirements, double walled hydroformed expansion joints have been employed in the design. These are not standard items and require custom fabrication. Installation space constraints and adjacent pipe support attachment location availability at ITER limit standard expansion joint installation guidelines provided by the Expasion Joint Manufacturers Association (EJMA). Careful consideration must be given to the analysis model to ensure proper function and life expectancy of the component. These considerations include accurate accounting of thrust forces, thermal movements, seismic accelerations, equipment and building differential displacements. In addition to displacements, the process internal, external, and interspace pressures affect the qualification and selection of the double walled expansion joints. The calculation results shall confirm that deflections, forces, and moments are reasonable for the size and type required for the system’s demands as evaluated against the manufacturer’s design.

Clark, Forrest [ORNL] (ORCID:0009000678106843)↗

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↗

Gallium Arsenide Semiconductor Opening Switches: Enabling Nanosecond High Powering Pulsed Systems

The goal of this work awas to investigate design manufacturing semiconductor opening switches (SOS) in both silicon and gallium arsenide (GaAs). Solid-state opening switches are critical components for pulsed power systems and applications in directed energy, dielectric wall accelerators, and novel semiconductor manufacturing techniques. Under this funding, we have developed silicon SOS designs that suppresses an unwanted prepulse, increases the peak output voltage by about 10 percent, and reduces the pulse rise time by ~ 4x compared with more conventional profiles. Through this effort we have improved device fabrication and bonding techniques. Additionally, work on this the GaAs opening switch has defined a unique application space that these devices are suited for. GaAs opening switches have short risetimes and pulse widths compared to silicon devices, however the short carrier lifetime of GaAs makes the circuit design more challenging than in silicon. For high PRF operation, the lifetime of the GaAs is an advantage compared to silicon. TCAD simulations of GaAs devices have been used to optimize a GaAs profile. Additionally, we have designed pulsers with sub 50ns reserve pump times and tested GaAs COTs PIN diodes in them.

42 ENGINEERING↗

Uncertainty Quantification of Fatigue Behavior of Rough AM Surfaces and Microstructures to Enable Hydrogen Gas Turbine

Modifying fossil-fueled industrial gas turbines to utilize low or zero-carbon fuels, such as hydrogen or hydrogen-natural gas blends, is a complex endeavor. The successful implementation of this technology hinges on three key design criteria: (1) developing new fuel injectors capable of efficiently burning alternative fuels, (2) ensuring manufacturability to meet cost and time-to-market goals, and (3) achieving component durability in the demanding environment of an operating gas turbine. Additive manufacturing (AM) accelerates product development, yet concerns persist regarding the durability of parts with rough AM surfaces. A fully experimental approach to quantify the fatigue performance of rough AM microstructures is both costly and labor-intensive. To address this, ORNL and Solar Turbines Incorporated (Solar) employed a crystal plasticity finite element (CPFE) model to identify the factors influencing AM surface fatigue behavior. These CPFE findings, combined with targeted experimental data, were used to develop a computationally efficient surrogate model suitable for assessing the lifespan of gas turbine engine components.

08 HYDROGEN↗

Accelerating ion transport by dynamic asymmetry of alternating polymer electrolytes

Polymer based electrolytes allow the absence of volatile components in batteries thus increasing their safety. Yet, they exhibit drawbacks based on their low conductivity. We have used an alternating polymer consisting of dimethyl siloxane (DMS) and ethylene glycol (EG) blocks to circumvent known disadvantages of the usually used polyethylene glycol (PEG). Incorporating dimethyl siloxane lowers the glass-transition temperature and thus reduces the segmental relaxation time, by dynamic asymmetry or internal plasticization of the constituting polymer blocks. The alternating structure ensures miscibility of the different components and hinders crystallization. Furthermore, the pure polymer, P(DMS 3 -alt-EG 4 ), shows a segmental relaxation time well in the range needed for polymer electrolytes. Mixtures of LiClO 4 and P(DMS 3 -alt-EG 4 ) show a drastically reduced temperature dependence of their DC conductivity in comparison to PEG based systems, resulting in an increase by two orders of magnitude at T = 5 °C and even three to four orders of magnitude at T = 0 °C. Addition of coordinating (acetonitrile) or non-coordinating (toluene) solvent increases conductivity either via additional plasticization or by weakening the Li-binding yet looking at the dynamics at low concentrations of additional solvent the mobility of the polymer is reduced. In conclusion, the solvent addition leads only at higher solvent concentration to a reduction in relaxation time.

Jakobi, Bruno [Louisiana State Univ., Baton Rouge,↗

X-ray optics for the cavity-based X-ray free-electron laser

A cavity-based X-ray free-electron laser (CBXFEL) is a possible future direction in the development of fully coherent X-ray sources. CBXFELs consist of a low-emittance electron source, a magnet system with several undulators and chicanes, and an X-ray cavity. The X-ray cavity stores and circulates X-ray pulses for repeated FEL interactions with electron pulses until the FEL reaches saturation. CBXFEL cavities require low-loss wavefront-preserving optical components: near-100%-reflectivity X-ray diamond Bragg-reflecting crystals, outcoupling devices such as thin diamond membranes or X-ray gratings, and aberration-free focusing elements. In the framework of the collaborative CBXFEL research and development project of Argonne National Laboratory, SLAC National Accelerator Laboratory and SPring-8, we report here the design, manufacturing and characterization of X-ray optical components for the CBXFEL cavity, which include high-reflectivity diamond crystal mirrors, a diamond drumhead crystal with thin membranes, beryllium refractive lenses and channel-cut Si monochromators. All the designed optical components have been fully characterized at the Advanced Photon Source to demonstrate their suitability for the CBXFEL cavity application.

47 OTHER INSTRUMENTATION↗

Assessment of Vibration and Shock Loading Environments on Steels Used in Railroad Applications Considering Hydrogen Embrittlement

Studies that examine the combined effects of hydrogen and rail loading environments in the context of hydrogen embrittlement of steels have not been performed. Large-scale hydrogen storage requires either gaseous hydrogen stored in pressure vessels and tubing or liquid hydrogen in cryogenic, insulated tanks. Since the focus of this study is on steels, we examine the influence of hydrogen on stainless steel used for high pressure tubing and cryogenic tanks and Cr-Mo steel liners used in gaseous pressure vessels. Literature studies show that despite hydrogen degradation, these steels can be used effectively and safely if the stresses are managed. The shock and vibration environment on railcars present unique environments where stresses and loading rates can be high. A literature review was conducted to understand the accelerations experienced in rail by examining instrumented railcars of nuclear fuel casks. Hydrogen studies were examined that focused on steel pressure hardware with an emphasis on fatigue, fast loading rates, and low temperatures. A simplified fatigue assessment was performed to examine design cycles for three different hydrogen components: stainless steel tubing, stainless steel cryogenic tanks, and gaseous pressure vessels. The assessments were idealized and used bounding cases of accelerations in both normal rail conditions and coupling events. In normal shock and vibration environments when accelerations were less than 2 g, infinite design life was calculated. In extreme shock or coupling environments, finite design life was calculated which was shown to be dependent on unsupported lengths of pressure components. It was shown that adjusting the unsupported length can reduce the bending stress thereby increasing design life.

36 MATERIALS SCIENCE↗

New Virtual Test Bed Capabilities: Virtual DOME Model and New Updates to Repository

The Department of Energy (DOE) Office of Nuclear Energy National Reactor Innovation Center accelerates the deployment of novel reactor concepts by establishing both physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed represents the virtual arm of the National Reactor Innovation Center and is a joint effort with the DOE Nuclear Energy Advanced Modeling and Simulation Program. The Virtual Test Bed mission is to accelerate the deployment of advanced reactors by facilitating the adoption of cutting-edge DOE advanced modeling and simulation tools to design, evaluate, and license reactors. This is primarily achieved by storing example challenge problems in an externally available repository and by developing models to fill the M&S gaps needed for potential demonstrators. Activities conducted this fiscal year focused on developing of a Demonstration of Microreactor Experiments shield model to help accelerate the confirmatory analysis required for the reactor demonstration. This model and workflow will allow developers to leverage advanced modeling and simulation tools to ensure their reactor demonstration concept will meet dose requirements and that the surrounding shield will stay within concrete temperature limits during steady-state and transient operation conditions. An initial model has been developed to evaluate the temperature distribution in the concrete shield during steady-state operation, including neutron and gamma heating effects. Various modeling strategies have been examined to understand their applicability and limitations with different reactor designs to make the workflow as reactor-agnostic as possible and computationally effective to maximize its usability. In addition to describing the Demonstration of Microreactor Experiments shield model and associated results, this report summarizes other accomplishments regarding repository maintenance and improvement and new external models hosted on the repository.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

MTL_TX: A Multi-Task Transformer Model for Improved Radiation Time-Series Estimation

Controlling radiation doses at potential radioactive facilities is critical to ensuring the safety of both personnel and the public. At the Thomas Jefferson National Accelerator Facility (JLab), multiple sensors are deployed around the three experimental halls to monitor key parameters, including single-beam current, energy levels, current leakage, and radiation values during accelerator operations. In this study, we developed a Multi-task Transformer model, MTL_TX, to accurately estimate radiation doses at sensor locations based on historical data, with the aim of enhancing safety in accelerator facilities and surrounding public areas. To improve estimation accuracy, we integrated two innovative components into the proposed model: hierarchical feature embedding (HFE) and multi-level decomposition attention (MDA). Additionally, the multi-task learning (MTL) framework effectively leverages correlations among multiple sensors, enabling individual estimations for each sensor. MTL_TX achieved outstanding results on data collected in 2018, with an MSE of 0.1464, an RMSE of 0.2353, and an R 2 score of 0.8584. Furthermore, when trained on 2018 data, MTL_TX exhibited excellent generalization capability to unseen datasets from 2016 to 2019, achieving an MSE of 0.1407, an RMSE of 0.2263, and an R 2 score of 0.8831. These results demonstrate a significant improvement over existing state-of-the-art models.

Transformer↗

Design and Characterization of the 162.5 MHz RF Component Layout for Fermilab's PIP-II Reference Line

The Proton Improvement Plan II (PIP-II) Reference Line at Fermi National Accelerator Laboratory distributes phase-stable radio-frequency (RF) signals throughout the accelerator. PIP-II requires stable timing and phase reference signals so its accelerating cavities transfer energy to the particle beam at the correct point in each RF cycle. The full system includes 162.5, 325, and 650 MHz sections corresponding to the frequency sections of the PIP-II Linac, with this project focusing on the 162.5 MHz section. The Reference Line must provide a phase stable source signal while responding to phase changes caused by environmental conditions or system drift. Its RF components will be mounted on aluminum heat plates inside a temperature controlled enclosure to further limit temperature-driven phase changes. To prepare the system for manufacture, the project reviewed component functions and dimensions, developed a computer-aided design (CAD) model, and arranged the hardware to support short cable paths, grounding, fastener access, and maintenance. Several full scale, three dimensional printed prototypes allowed the available components to be mounted and inspected. These fit checks revealed mechanical conflicts and guided revisions to component placement, countersink geometry, labeling, and plate thickness. Electrical characterization was also performed on selected RF hardware to compare its measured behavior with the performance metrics that were set for our design. Overall, the project produced a manufacturable 162.5 MHz layout, physical fit-check prototypes, and documented electrical measurements that support review before metal fabrication. The 325 and 650 MHz layouts remain future work because they require additional minor mechanical changes.

Subedi, Harsheet [Unlisted, US, CA] (ORCID:0009000↗

Development of Digital Twin-Informed Predictive Maintenance for Critical Components in Advanced Reactors

Small modular reactors (SMRs) and microreactors, along with other advanced reactor (AR) technologies, are key to the future of nuclear energy. For these systems to achieve low operating costs, high reliability, and flexibility across applications, their operation and maintenance must be optimized. Digital twin (DT) technology is one of the technologies that enables real-time (or faster than real-time) monitoring and prognosis of critical components which are vital for operational efficiency, low costs, and enhanced safety of ARs, accelerating their deployment. DT technology provides dynamic virtual representation of physical assets by integrating real-time data, physics-based models, and advanced analytics, which is critical to optimizing the performance of the entire energy system throughout the life cycle. DTs empower engineers and operators to virtually explore different scenarios, configurations, and control strategies, allowing for the identification of optimal solutions that maximize reactor efficiency, safety, and economics.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Development of a Robust Reference Electrode in Aggressive Chemical and Radiation Environments in the Hanford Waste Tanks

The Hanford site stores more than 200 million liters of radioactive and chemically hazardous wastes from the production of weapons materials. The wastes are stored in 177 underground carbon-steel storage tanks, separated between 149 single shell tanks (SSTs) and 28 double shell tanks (DSTs). The DSTs provide critical retrieval and interim storage before the waste is vitrified in the Waste Treatment and Isolation Plant (WTP). The tanks will need to remain in-service far beyond the initial 40-year design life, and effective corrosion control practices must remain in force to extend the tanks’ lifespans. This effort includes direct measurements of corrosion rate (e.g., ultrasonic measurements and corrosion coupons) and electrochemical processes (e.g., linear polarization measurements and open circuit potential measurements). The Hanford site began monitoring the corrosion potential in select DSTs in 2008. Of the 45 reference electrodes that have been installed, 29 have failed and 6 others provided unreliable results. DOE-EM is supporting a 3-year program to develop a chemical and radiation resistant reference electrode for application in the Hanford tanks. The first year of the program focused on understanding the failure mechanism for the reference electrodes and identification of candidate construction materials that would mitigate degradation of the electrodes in the waste environment. During the second year of the program, the objectives were to: 1) test candidate materials under simulated waste conditions, 2) design components that will extend the service life of the electrode, 3) fabricate materials for prototype reference electrodes, and 4) assemble prototype reference electrodes for accelerated testing. The reference electrode is constructed of four principal parts: 1) junction, 2) casing, 3) inner chamber backfill materials, and 4) the sensing wire. Principally, improvements of the junction, casing, and inner chamber backfill materials are being pursued. The junction material at the interface between the waste and the inner chamber of the reference electrode was identified as a critical component in the failure of the reference electrodes. Nine candidate replacement junction materials were tested under simulated waste conditions to evaluate permeation rate. These materials included a variety of polymeric and ceramic materials, some of which were 3-D printed. Thus far, porous polyvinylidene fluoride materials have performed satisfactorily and are being considered for prototype development. The commercial electrode casing materials in general have performed well. Additionally, 3-D printing of chemically and mechanically stable materials is being investigated as a means for further improvement in fabrication consistency. SRNL has also investigated altering the reference electrode design to extend the service life. The new design of the interior of the reference electrode casing creates a longer, more tortuous path between the junction material and the electrode sensing wire. A finite element model was used to optimize the design without adversely impacting the circuit resistance of the electrode during the measurements, thus preserving the measurement accuracy while enhancing the service life. The inner chamber back fill materials are also critical to the performance of the reference electrode. Materials that are resistant to intruding tank waste and provide a conductive path to the sensing wire were investigated. Gel and powder materials that are interspersed with a conductive chloride bearing material were tested for their influence on diffusion and electrode resistance. All the investigated materials and components will be assembled, with collaboration from commercial vendors, to fabricate the initial prototypes. Accelerated testing of the prototypes will be initiated in Year 2 of the program and will be completed in Year 3. A recommendation on the materials of construction and the design of the new robust reference electrode will be presented to the Hanford tank farm facility.

Sykes, Kiana [Savannah River National Laboratory (↗

Deployment and validation of predictive 6-dimensional beam diagnostics through generative reconstruction with standard accelerator elements

Understanding the 6-dimensional phase space distribution of particle beams is essential for optimizing accelerator performance. Conventional diagnostics such as use of transverse deflecting cavities offer detailed characterization but require dedicated hardware and space. Generative phase space reconstruction (GPSR) methods have shown promise in beam diagnostics, yet prior implementations still rely on such components. Here we present the first experimental implementation and validation of the GPSR methodology, realized by the use of standard accelerator elements including accelerating cavities and dipole magnets, to achieve complete 6-dimensional phase space reconstruction. Through simulations and experiments at the Pohang Accelerator Laboratory X-ray Free Electron Laser facility, we successfully reconstruct complex, nonlinear beam structures. Furthermore, we validate the methodology by predicting independent downstream measurements excluded from training, revealing the reconstruction closely resembling ground truth. This advancement establishes a pathway for predictive diagnostics across beamline segments while reducing hardware requirements and expanding applicability to various accelerator facilities.

Kim, Seongyeol [Pohang Univ. of Science and Techno↗

Domain-specific text embedding model for accelerator physics

Accelerator physics presents unique challenges for natural language processing (NLP) due to its specialized terminology and complex concepts. A key component in overcoming these challenges is the development of robust text embedding models that transform textual data into dense vector representations, facilitating efficient information retrieval and semantic understanding. In this work, we introduce AccPhysBERT, a sentence embedding model fine-tuned specifically for accelerator physics. Our model demonstrates superior performance across a range of downstream NLP tasks, surpassing existing models in capturing the domain-specific nuances of the field. We further showcase its practical applications, including semantic paper-reviewer matching and integration into retrieval-augmented generation systems, highlighting its potential to enhance information retrieval and knowledge discovery in accelerator physics. Published by the American Physical Society 2025

Hellert, Thorsten (ORCID:0000000227970926)↗

Virtual Power Plants: Pilots, Challenges, and Innovations Shaping Future Development

Virtual Power Plants (VPPs) aggregate distributed energy resources (DERs) to provide grid services traditionally delivered by centralized power plants. This article reviews the current state of VPP deployment, highlighting business models, compensation mechanisms, and global pilot projects. While VPPs offer benefits such as grid flexibility, resilience, and cost savings, challenges remain in communication infrastructure, regulatory frameworks, market access, and customer engagement. To address these, we propose a scalable, privacy-preserving hierarchical VPP architecture that coordinates with distribution utilities and preserves customer data. We also present the Integrated T&D Control Room of the Future as a key test bed for validating and accelerating VPP adoption. These innovations can help transition VPPs from pilot programs to integral components of a modern, reliable power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗