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At least 739 records · Page 41

CAST Technical Bulletin #002: Time Synchronization for Next Generation Power Delivery

This technical bulletin gives a description of the updated effort on Oak Ridge National Laboratory (ORNL) Center for Alternative Synchronization and Timing (CAST) project’s work investigating a terrestrial-based high precision timing infrastructure intended for time synchronization of the next generation power delivery infrastructures. We will provide a high-level description of the CAST application context, key protocols, critical architectural issues, and how GPS/timing data traverse through the system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Retrieval Augmented Generation for Robust Cyber Defense

In cybersecurity, the ability to efficiently analyze and respond to vulnerabilities, weaknesses, attack patterns, and threat tactics is critical for effective defense strategies. With the increasing complexity and volume of cybersecurity data, traditional methods of querying and retrieving information are often inadequate. To address this challenge, we implemented Retrieval-Augmented Generation (RAG) systems—CyRAG and GraphCyRAG—that integrate large language models (LLMs) with both structured data from relational databases and knowledge graphs such as Neo4j. CyRAG is designed to handle structured data, focusing on CVE (Common Vulnerabilities and Exposures) and CWE (Common Weakness Enumeration) entities to generate accurate and context-rich responses. In contrast, GraphCyRAG leverages Neo4j knowledge graphs to retrieve interconnected information from CVE, CWE, CAPEC (Common Attack Pattern Enumeration and Classification), and ATT&CK (Adversarial Tactics, Techniques, and Common Knowledge) datasets. By utilizing Neo4j’s graph-based framework, GraphCyRAG enables deeper traversal of relationships between vulnerabilities and attack patterns, providing cybersecurity analysts with more comprehensive insights into potential attack vectors and mitigation strategies. Our preliminary results demonstrate that integrating knowledge graphs with RAG significantly enhances both the accuracy and depth of threat analysis, allowing for the retrieval of dynamic, real-time data and the generation of contextually aware responses. This approach helps analysts uncover hidden relationships between cyber entities, predict exploit paths, and prioritize mitigation efforts effectively. The integration of RAG with cybersecurity knowledge graphs represents a significant advancement in cybersecurity threat intelligence, enabling more informed decision-making and stronger defense strategies.

97 MATHEMATICS AND COMPUTING↗

Verification of the EvaluateFlux Utility Program

The EvaluateFlux program is a post-processing utility program for DIF3D, specifically DIF3D-VARIANT which handles Cartesian and hexagonal geometries. The EvaluateFlux program was developed to allow users to obtain flux and power traverses through the geometry domain, and its initial purpose was to facilitate foil analysis by evaluating the flux solution from DIF3D-VARIANT and combining it with foil cross section data. The EvaluateFlux program can calculate the neutron flux, as well as the reaction rates, at any user provided evaluation point. It does this by identifying the spatial mesh associated with the evaluation point and then evaluates the polynomial based neutron flux moments stored in the NHFLUX file at that point. The output of EvaluateFlux varies depending on the input setup. The maximum output includes the neutron flux and microscopic and macroscopic reaction rates at each evaluation point. The purpose of this work is to verify the outputs of EvaluateFlux. Simple models that have hand calculatable results are first defined and used to verify the EvaluateFlux outputs. More complex cases are then added where a duplicate program of EvaluateFlux that uses PrintTables outputs of the binary files is used to verify the EvaluateFlux outputs. In those complex cases, hand calculations of selected evaluation points were also displayed to confirm the software verification. For all the tests done, the hand calculations agreed well with those calculated by EvaluateFlux. For the larger complex problems, the duplicate program that can process hundreds of evaluation points was able to identify that zero points within some meshes have large errors. This aspect was attributed to the truncation error on the input provided to the duplicate program and is not a concern for the accuracy of the EvaluateFlux software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Post-DTL Beam Delivery

Ensuring that the beam delivered from the upgraded Front-End (FE) meets the Key Performance Parameters (KPPs) at each user facility is critical to the success of the LANSCE Accelerator Modernization Project (LAMP). For a high-intensity, multi-user facility like LANSCE, compliance with beam loss and radiation thresholds is as important as the charge delivered to each target. While early LAMPF/LANSCE operations relied on iterative tuning to minimize losses from beam halo and tail particles, the new FE may introduce different beam distributions and loss modes—making predictive modeling essential. To manage this, the F2E (Front-End to End) effort is developing detailed particle-tracking models that reflect realistic beamline conditions, including halo formation and expected diagnostic readings. These "snapshot" simulations aim to benchmark live machine performance at a given moment. This will help quantify how beam quality from the new FE will propagate downstream through the facility. Only by validating these models can we confidently assess and mitigate the potential impacts of the LAMP FE on beam delivery. Post-DTL, the beam splits to serve five major user facilities. Historically, low-energy beam transport has been modeled using TRACE, and higher-energy sections with TRANSPORT. These have now been unified into MAD-X format and validated with codes such as Elegant, pyOrbit, XSuite, Impact-Z, and HPSim. The primary focus now is on accurate modeling of full particle distributions (including beam halo) as they traverse the accelerator and beamlines to each experimental station. All models are at various stages of validation with empirical data.

43 PARTICLE ACCELERATORS↗

Assessment of Self-interrogation Safeguards Signatures for Pebble Bed Reactor Fuel

New reactor designs, such as pebble-bed reactors, present challenges for the safeguarding of fissile material. Due to the multi-pass fuel circulation design and the non-uniform path a pebble may traverse through a pebble-bed reactor, there will be variations in the irradiation history of spent fuel pebbles. The standard approach of estimating actinide quantities based on fission gamma spectra or neutron emission paired with depletion modeling may yield uncertainties too large for safeguards and material accountancy. This project investigated, through modeling and experimentation, the potential of neutron self-interrogation of spent fuel pebbles as an innovative method to implement materials accountability. As an example, our feasibility studies indicate that the mass of U-235, U-238, Pu-239 and Pu-241 can be predicted to 4.1, 0.86, 13 and 13 % accuracy, respectively, when measuring 100 closely packed end-of-life spent fuel pebbles over approximately 12 days using a 4π counting geometry.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

TuFF internal WRAP for Rapid Pipeline Repair (TuFF iWRAP)

The goal of “TuFF internal WRAP for Rapid Pipeline Repair” (TuFF iWRAP) program was to develop a novel material system and placement process to fabricate structural pipe within the existing deteriorated pipelines without disruption of gas delivery. The team (University of Delaware – Center for Composite Materials (UD-CCM) and Plitzie Inc.) addressed this challenge by developing a new material feedstock and pipe in pipe (PIP) repair strategy. This allows the potential for significant cost reduction and has minimum operational impact on gas customers. The new robotic based placement design allows discontinuous placement of pipe sections creating a stand-alone structural liner within the legacy pipeline without the need for pipe shutdown. Here, the material is supplied using a tethered material feeding system and is placed and UV cured with the internal Wound Rapid Automated Placement (iWRAP) system. This provides maximum placement efficiency capable of traversing 90 angle bends in 12-inch pipe and overall design customization to meet pipe repair requirements (e.g., variable wall thickness, bridging gaps, etc.). UV-curable fiber reinforced composite material has been optimized to meet structural performance and placement/cure times. Superior strength and fatigue life has been demonstrated by improving fiber-matrix adhesion using new fiber sizing for UV resins. Rapid cure approaches using new liner and resins have been evaluated with industry. The appropriate design of the section joints has been developed and tested. We estimate coating time to be ~100 hours per mile enabling typical pipe repair within 1 week.

03 NATURAL GAS↗

Characterization of Gas Bremsstrahlung sources at the Electron-Ion Collider

This report estimates the potential impact of Gas Bremsstrahlung, generated as the electron beam traverses the straight sections of the storage ring and impinges onto selected locations of the Electron-Ion Collider. The source terms were calculated for routine operation scenarios at three different energies: 5, 10 and 18 GeV, using the FLUKA Monte Carlo particle transport and interaction code. The source term’s power distributions were validated and compared with the Gas Bremsstrahlung produced in the long straight sections of the National Synchrotron Light Source II storage ring.

43 PARTICLE ACCELERATORS↗

Impact of the Earth’s Density Profile on Atmospheric Neutrino Oscillations

As atmospheric neutrinos traverse the Earth, the matter potential influences their oscillation probabilities in intricate ways, enhancing and suppressing the conversion of one neutrino’s flavor to another along the propagation. Comprehending their behavior within Earth’s complex density profile, primarily described by the Preliminary Reference Earth Model (PREM) [1], is essential for accurately describing oscillations and determining expected atmospheric neutrino event rates in the DUNE Far Detector. In this study, we address this challenge by considering an ensemble of Earth models constrained by astronomical measurements of the planet’s mass and moment of inertia. We evaluate how variations in densities and layer boundaries can affect oscillation probabilities and event rates, and what implications this could have on various physics analyses.

Ismerio Oliveira, Marcelo [Rio de Janeiro, Pont. U↗

Neutrino Physics at a Muon Collider, and the Neutrino Kaleidoscope

Muon accelerators, a potential technology for enabling O(10 TeV) parton center of mass energy collisions, would also source an intense, collimated beam of neutrinos at TeV energies. There is currently a renewed effort to understand the possible scientific reach of such a neutrino beam in the context of neutrino physics. One possibility is the “Neutrino Kaleidoscope”: the pairing of a muon accelerator neutrino flux with a neutrino telescope detector. In particular, such a pairing would enable searches for non-standard oscillations of the beam neutrinos as they traverse the earth between source and detector. These non-standard neutrino oscillations could be sourced by Lorentz invariance violation, which a neutrino kaleidoscope could probe up to the quantum gravity-motivated Planck scale. Such a search would also have a reach on sterile neutrinos orders of magnitude beyond existing terrestrial limits. In this talk, I will introduce some of the exciting measurements being proposed with the neutrinos from a muon accelerator and then go into detail on the Neutrino Kaleidoscope concept (arxiv:2508.09249).

Putnam, Gray [Fermilab]↗

Air-sea interactions yielding rapid Beaufort Sea ice losses during the 2021 ONR THINICE Pilot Field Campaign

Seasonal sea ice coverage has declined in the Pacific Arctic region. Losses of the ice cover have modified the region’s surface heat and momentum fluxes providing weather systems more direct interaction with the upper ocean. For example, recent cyclones that have passed over these waters have initiated multiple air-sea interactions and have impacted mixed layer depth, wave properties, and sea ice mass budgets due to diabatic and/or advective processes. As a United States Office of Naval Research (ONR) Departmental Research initiative, one key component of the ONR THINICE program was to advance knowledge on Arctic cyclone coupling with the ocean surface, its ice cover, and understand how such coupling can lead to rapid ice loss. Leading up to the primary field campaign in August 2022, a pilot field campaign from 19 August to 13 September 2021 focused in Utqiagvik, Alaska and Longyearbyen, Svalbard was carried out. This period was marked by frequent Arctic cyclones, periods of strong low-level winds, and stints of extreme short-term Beaufort Sea ice area losses. Cyclones traversed these waters much more frequently than usual during this 26-day period, but did not exhibit extreme central pressures indicative of high intensity and impactful storms. Using ERA5 atmospheric reanalysis fields, CERES and AIRS surface flux retrievals, and in situ sensor data collected from ice-tethered profilers and ice mass balance buoys, we highlight air-sea-ice interactions in the Beaufort Sea during and between these cyclones leading up to extreme ice loss events. Our case study analysis is aimed at understanding how Arctic cyclones, including air-sea interactions prompted by their passage over the marginal ice zone, influence the end-of-summer ice conditions and ice loss events. This study provides an example where frequent, yet weak storms drive rather large marginal sea-scale losses albeit with heterogenous sea ice effects at local scales.

Ballinger, Thomas [International Arctic Research C↗

Evidence-based Graph Adversary Mapping (EGRAM) [Poster]

Cybersecurity companies such as CrowdStrike, Dragos, Microsoft and Unit 42 categorize Advanced Persistent Threats (APTs) using their own naming schemes. As a result, these APTs are mapped to different malware sources and campaigns, all from differing sources, leading to inconsistent mapping. Inconsistent mapping causes confusion and adds further obscurity around these groups, making it difficult to track and mitigate APT cyberattacks. The Evidence-based Graph Adversary Mapping (EGRAM) tool remediates the mapping challenge by collecting, updating and converting adversary data and their sources into a valid, codified STIX v2.1 bundle which is then stored in a Neo4j graph database. It utilizes graph traversal methods and centrality analysis to generate actionable information as a Structured Threat Intelligence Graph (STIG), based on user queries. EGRAM exists as Python code and a Jupyter Notebook that acts as a searchable, evidence-based, source of intelligence for APT groups’ artifacts and cyber campaigns.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Automated and Accelerated Continuum Model Development for Electrochemical Systems (Abbreviated Report)

Despite the availability of computational resources and advancements in numerical computing capabilities, the multiscale models core to understanding, predicting the behaviors of, and designing energy and environmental systems involving porous media are still 1.) developed through by-hand derivations and 2.) limited by many methodological assumptions employed during model derivation. As a result, the advancement of effective media models for engineering DOE mission-critical systems (e.g., batteries, flow batteries, electrolyzers, geothermal systems, subsurface chemical storage systems, etc.) is slow (i.e., it takes years for models to traverse from stages of “development” to “practical utilization”), hindering our ability to effectively optimize such systems and stay at the cutting-edge of the energy frontier. In this work, we aimed to address these limitations by 1.) automating and accelerating multiscale model derivation via symbolic computing and 2.) develop a novel multiscale modeling methodology for flow and transport through porous media that avoids the typical assumptions hindering previous models. As a result of our efforts, we 1.) developed a hybrid symbolic-numeric code called Fouriera for fully-automating the implementation of multiphysical and phase-field models via the Fourier spectral method for materials science research, and 2.) advanced a multiscale modeling methodology called The Method of Finite Averages that rigorously predicts the behaviors of flow and transport through heterogeneous porous media under the influence of non-local effects and strong advection. Ultimately, these deliverables provide strong foundations from which further efforts can advance multiscale modeling tools and capabilities that do not intrinsically rely on 1.) the speed and mathematical capabilities of humans, nor 2.) the methodological assumptions limiting current models.

36 MATERIALS SCIENCE↗

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 3 - Raw Data

Sequence 3: Tower Wake Measure (P) Sequence 3 used a downwind, rigid turbine with a 3.4° cone angle. The wind speeds for this sequence corresponded to subcritical [7 m/s], transitional [15 m/s], and supercritical [20 m/s] Reynolds number regimes for the circular cross-section tower. The yaw angle and blade tip pitch angles were selected to traverse the probe tip across the tower wake, while keeping the probe axis approximately parallel to the tunnel centerline. The rotor was parked with the instrumented blade at 180° azimuth. Blade and probe pressure measurements were collected.

17 WIND ENERGY↗

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 6 - Raw Data

Sequence 6: Shroud Wake Measure (P) This test sequence used a downwind, rigid turbine with a 3.4° cone angle. The wind speeds for this sequence corresponded to subcritical [7 m/s], transitional [15 m/s], and supercritical [20 m/s] Reynolds number regimes for the circular cross-section tower. The yaw angle and blade tip pitch angles were selected to traverse the probe tip across the tower wake while keeping the probe axis approximately parallel to the tunnel centerline. The rotor was parked with the instrumented blade at 180° azimuth. Blade and probe pressure measurements were collected. An airfoil-shaped aluminum shroud was placed on the tower below the 34% span five-hole probe. It extended below the 91% span five-hole probe. The turntable angle was adjusted to position the shroud at various angles relative to the flow.

17 WIND ENERGY↗

Towards Quantum Gravity in the Lab on Quantum Processors

The holographic principle and its realization in the AdS/CFT correspondence led to unexpected connections between general relativity and quantum information. This set the stage for studying aspects of quantum gravity models, which are otherwise difficult to access, in table-top quantum-computational experiments. Recent works have designed a special teleportation protocol that realizes a surprising communication phenomenon most naturally explained by the physics of a traversable wormhole. In this work, we have carried out quantum experiments based on this protocol on state-of-the-art quantum computers. The target quantum processing units (QPUs) included the Quantinuum's trapped-ion System Model H1-1 and five IBM superconducting QPUs of various architectures, with public and premium user access. We report the observed teleportation signals from these QPUs with the best one reaching 80% of theoretical predictions. We outline the experimental challenges we have faced in the course of implementation, as well as the new theoretical insights into quantum dynamics the work has led to. We also developed QGLab – an open-source end-to-end software solution that facilitates conducting the wormhole-inspired teleportation experiments on state-of-the-art and emergent generations of QPUs supported by the Q i s k i t and t k e t SDKs. We consider our study and deliverables as an early practical step towards the realization of more complex experiments for the indirect probing of quantum gravity in the lab.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum Energy Teleportation versus Information Teleportation

Quantum energy teleportation (QET) is the phenomenon in which locally inaccessible energy is activated as extractable work through collaborative local operations and classical communication (LOCC) with an entangled partner. It closely resembles the more well-known quantum information teleportation (QIT) where quantum information can be sent through an entangled pair with LOCC. It is tempting to ask how QET is related to QIT. Here we report a first study of this connection. Despite the apparent similarity, we show that these two phenomena are not only distinct but moreover are mutually competitive. We show a perturbative trade-off relation between their performance in a thermal entangled chaotic many-body system, in which both QET and QIT are simultaneously implemented through a traversable wormhole in an emergent spacetime. Motivated by this example, we study a generic setup of two entangled qudits and prove a universal non-perturbative trade-off bound. It shows that for any teleportation protocol, the overall performance of QET and QIT together is constrained by the entanglement resource. We discuss some explanations of our results.

Wang, Jinzhao [Stanford University, CA (United Sta↗