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At least 343 records · Page 19

Transversely pumped laser driven particle accelerator

We present a novel acceleration scheme capable of accelerating electrons and ions in an underdense plasma. Transversely Pumped Acceleration (TPA) uses multiple arrays of counter-propagating laser beamlets that focus onto a central acceleration axis. Tuning the injection timing and the spacing between the adjacent beamlets allows for precise control over the position and velocity of the intersection point of the counter-propagating beam arrays. This results in an accelerating structure that propagates orthogonal to the direction of laser propagation. We present the theory that sets the injection timing of the incoming pulses to accelerate electrons and ions with a tunable phase velocity plasma wave. Simulation results are also presented which demonstrate 1.12 GeV proton beams accelerated in 3.6 mm of plasma and electron acceleration gradients on the order of 1 TeV/m in a scheme that circumvents dephasing. This work has potential applications as a compact accelerator for medical physics and high energy physics colliders.

Laser-produced plasmas↗

Mesh-based multiphysics coupling acceleration for fusion neutronics through clustering for fusion blanket applications

Accurate modeling of particle transport within fusion blankets is essential for predicting performance metrics such as heat deposition and the tritium breeding ratio (TBR). However, high-fidelity coupling of thermal fluids from computational fluid dynamics (CFD) to neutronics simulations often incurs significant computational costs due to the complexity of surface intersection calculations in Monte Carlo codes. This paper presents an accelerated multiphysics coupling method for neutronics that utilizes hierarchical agglomerative clustering to map complex material property distributions to a neutronics model. Implemented within the fusion reactor design and assessment (FREDA) framework, the method leverages existing Python packages to automate the creation of clustered geometries for OpenMC. The approach is demonstrated on a sector model of an ARC-class tokamak with an immersion molten salt blanket, and an simple geometry with varying isotopic concentrations. Results show that the clustering method significantly reduces computational burden without compromising fidelity, providing a foundation for agile iteration of neutronics simulations involving multiple coupled material properties.

Bae, Jin Whan [ORNL] (ORCID:0000000326548907)↗

AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators

Tensor algebra operations represent an important class of algorithms used across many applications, including machine learning, scientific computing, and data analytics. As a result, the efficient generation of custom accelerators for tensor operations has received increased attention. Previous efforts have produced automated tools enabling users to prototype and explore optimized accelerators. However, little effort has been focused on the host-accelerator interaction in these tools. Efficient use of hardware accelerators requires knowledge about the accelerator's capabilities (operations, data formats, and opcode support), the host CPU microarchitecture (e.g., memory hierarchy), the host-accelerator interface, and the application's features (which code regions should be mapped onto an accelerator). Manually rewriting the original applications to facilitate improved custom accelerator mapping is an error-prone and time-consuming endeavor. To cope with this, we propose AXI4MLIR, a new framework to automatically generate and optimize the communication between the host CPU and arbitrary accelerators that implement linear algebra algorithms. AXI4MLIR extends the MLIR compiler framework to automatically generate efficient host-accelerator driver code for accelerators with AXI-based interfaces. Our compiler extensions enable automatic driver code generation while carefully considering the host's memory hierarchy and target accelerator features. To demonstrate the flexibility and utility of AXI4MLIR, we test it with diverse use cases that include different types of accelerators, tiling scenarios, and dataflow schemes. We compare our experimental results to manual implementations of host-accelerator driver code and find that our approach can reduce CPU cache references by 56% and deliver up to a 1.65x speedup.

Bohm Agostini, Nicolas↗

Development of a cryocooler conduction-cooled 650 MHz SRF cavity operating at ~10 MV/m cw accelerating gradient

SRF cavities for particle acceleration are conventionally operated immersed in a bath of liquid helium at 4.2 K and below. Although this cooling configuration is practically and economically viable for large scientific accelerator installations, it may not be so for smaller accelerators intended for industrial applications such as the treatment of wastewater, sludge, flue gases, etc. In this paper, we describe a procedure to operate SRF cavities without liquid helium that can be used to construct electron-beam sources for industrial applications of electron irradiation (1-10 MeV electron energy). In this procedure, an elliptical single-cell 650 MHz niobium-tin coated niobium cavity is coupled to a closed-cycle 4.2 K cryocooler using high purity aluminum thermal links. The cryocooler conductively extracts heat (RF dissipation) from the cavity without requiring liquid helium around the cavity. We present construction details of this cryocooler conduction-cooling technique and systematic experiments that have demonstrated ~10 MV/m cw gradient on the cavity. By straightforward scaling up the cavity length and number of cryocoolers, the technique will provide the complete range of 1-10 MeV electron energy for industrial applications.

43 PARTICLE ACCELERATORS↗

CEBAF Accelerator Tunnel Robot Project

Advancements in the field of robotics allow for the use of remotely controlled robots to perform tasks that have typically required human intervention. Jefferson Lab has explored the possibilities of robots placed in the accelerator tunnel to perform remote inspections that would otherwise require powering down equipment and completing lengthy radiological surveys that impact beam operations. A robotic solution ? driven by a human operator ? could not only reduce accelerator down time but also support the Lab's radiation exposure policy (known as "ALARA" - As Low As Reasonably Acceptable) by handling routine tunnel and beamline investigations in place of a human being. However, operating a remote device in a radioactive, high electronic-noise area is not a trivial task and drop-in solutions are rarely as simple as they seem. We will present the past prototypes that were tested as well follow-on technology developed from the project. We will also briefly survey current applications of robots at accelerator facilities with an eye toward future applications.

McGuckin, Theodore↗

Detection of uranium-photofission neutrons with a 4 He scintillation detector

The use of photon active interrogation to detect special nuclear material has held significant theoretical promise, as the interrogating source particles, photons, are fundamentally different from one of the main signatures of special nuclear material: neutrons produced in nuclear fission. However, neutrons produced by photonuclear reactions in the accelerator target, collimator, and environment can obscure the fission neutron signal. These (γ, n) neutrons could be discriminated from fission neutrons by their energy spectrum, but common detectors sensitive to the neutron spectrum, like organic scintillators, are typically hampered by the intense photon background characteristic of photon-based active interrogation. In contrast, high-pressure 4 ⁢He-based scintillation detectors are well-suited to photon active interrogation, as they are similarly sensitive to fast neutrons and can measure their spectrum, but show little response to gamma rays. Here, in this work, a photon active interrogation system utilizing a 4 ⁢He scintillation detector and a 9 MeV linac-bremsstrahlung x-ray source was experimentally evaluated. The detector was shown to be capable of operating in intense gamma-ray environments and detecting photofission neutrons from 238 ⁢U when interrogated by this x-ray source. The photofission neutrons show clear spectral separation from (γ, n) neutrons produced in lead, a common shielding material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Simulating Electron Impact Ionization using a General Particle Tracer (GPT) Custom Element

A new C++ custom element has been developed with the framework of General Particle Tracer (GPT) to simulate electron impact ionization of residual gas molecules. The custom element uses Monte-Carlo routines to determine both the ion production rate and the secondary electron kinetic energy based on user-defined gas densities and theoretical values for the ionization cross section and the secondary electron differential cross section. It then uses relativistic kinematics to track the secondary electron, the scattered electron, and the newly formed ion after ionization. The ion production rate and the secondary electron energy distribution determined by the custom element have been benchmarked against theoretical calculations and against simulations made using the simulation package IBSimu. While the custom element was originally built for particle accelerator simulations, it is readily extensible to other applications. The custom element will be described in detail and examples of applications at the Thomas Jefferson National Accelerator Facility will be presented for ion production in a DC high voltage photo-gun.

Yoskowitz, J. T.↗

Towards Agentic AI on Particle Accelerators

As particle accelerators grow in complexity, traditional control methods face increasing challenges in achieving optimal performance. This paper envisions a paradigm shift: a decentralized multi-agent framework for accelerator control, powered by Large Language Models (LLMs) and distributed among autonomous agents. We present a proposition of a self-improving decentralized system where intelligent agents handle high-level tasks and communication and each agent is specialized control individual accelerator components. This approach raises some questions: What are the future applications of AI in particle accelerators? How can we implement an autonomous complex system such as a particle accelerator where agents gradually improve through experience and human feedback? What are the implications of integrating a human-in-the-loop component for labeling operational data and providing expert guidance? We show two examples, where we demonstrate viability of such architecture.

43 PARTICLE ACCELERATORS↗

An Accelerated Creep Testing (ACT) Program for Advanced Creep Resistant Alloys for High Temperature Fossil Energy (FE) Applications (Final Report)

The research objective of this study is to develop an accelerated creep testing (ACT) program for advanced creep resistant alloys for high temperature FE applications. This research produced a new ACT for metallic materials based on Time-Temperature-Stress Superposition (TTSSP). In TTSSP, there exists a fundamental relationship between creep resistance, time, temperature, and stress that can be manipulated to reduce test durations. In our study, the stepped isostress method was employed where step increases of load during creep testing accelerated the time-to-rupture. Well-posed constitutive models including sin-hyperbolic and Wilshire-Cano-Stewart where calibrated using the SSM data and employed to predict the conventional creep response of the material. In our best experiments, <100-hour tests on lnconel 718 at 750 deg C produced over a 64x acceleration of data when compared to conventional data from Japan's National Institute of Materials Science. The ACTs enable the rapid screening of candidate materials, where a small test matrix of short duration tests can be employed to determine the creep resistance (minimum-creep-strain-rate, stress-rupture, and creep deformation) of a material across decades.

20 FOSSIL-FUELED POWER PLANTS↗

A Massive, Position-Resolving, High-Energy-Resolution Detector for Non-Accelerator Cosmic and Intensity Frontier Particle Physics

We proposed to take the first steps in the development of a detector that promises energy resolution of tens of eV FWHM combined with robust nuclear-recoil discrimination and high fidelity, mm-precision position reconstruction for applications in non-accelerator particle physics at the Cosmic and Intensity Frontiers. The detector would obtain these excellent resolutions by sensing athermal phonons produced by particle interactions in crystalline, dielectric targets using a sensitive, highly multiplexable superconducting phonon sensor, the kinetic inductance detector (KID). This detector would be applicable to: the search for low-mass particle dark matter candidates with masses below 5~GeV via direct detection of scattering of dark matter particles with terrestrial nuclei; detection of coherent elastic neutrino-nucleus scattering to test for new physics such as a non-standard value of the weak nuclear charge, non-standard neutrino interactions (perhaps driven by a neutrino magnetic moment), or the existence of sterile neutrinos; and, searches for neutrinoless double-beta decay. During the funding period, we demonstrated scaling up of the detector concept from a 22-mm by 22-mm by 1-mm, 1-g prototype with 0.9~keV FWHM energy resolution to a 75-mm diameter by 1-mm, 9-g prototype while improving the inferred energy resolution to 0.7~keV~FWHM. In the process, we solved many problems associated with scaling device fabrication to large wafers and vastly reduced the fraction of the surface occupied by inactive but energy-absorbing metal. We also demonstrated a new technique that substantially simplifies the process of characterizing a new detector. These results provide a good foundation for future work scaling up the design to 4-mm thickness substrates and improving the resolution to reach 0.035~keV~FWHM, yielding a detector with compelling potential for the above applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analog Signal Multiplexing System for the Iota Proton Injector

The Fermilab Accelerator Science and Technology (FAST) Facility at FNAL is a dedicated research and development center focused on advancing particle accelerator technologies for future applications worldwide. Currently, a key objective of FAST Operations is to commission the 2.5 MeV IOTA Proton Injector (IPI) and enable proton injection into the Integrable Optics Test Accelerator (IOTA) storage ring. The low and medium-energy sections of the IPI include four frame-style dipole trims and two multi-function correctors with independently controlled coils, requiring readout of 32 analog channels for current and voltage monitoring in total. To reduce cost and optimize rack space within the PLC-based control system, a 32-to-4 analog signal multiplexing system was designed and implemented. This system enables real-time readback of excitation parameters from all magnetic correctors. This paper presents the design, construction, implementation, and performance of the multiplexing system.

MacLean, Daniel R. [Fermilab] (ORCID:0000000210103↗

Ferroelectric FET-based context-switching FPGA enabling dynamic reconfiguration for adaptive deep learning machines

Field programmable gate array (FPGA) is widely used in the acceleration of deep learning applications because of its reconfigurability, flexibility, and fast time-to-market. However, conventional FPGA suffers from the trade-off between chip area and reconfiguration latency, making efficient FPGA accelerations that require switching between multiple configurations still elusive. Here, we propose a ferroelectric field-effect transistor (FeFET)–based context-switching FPGA supporting dynamic reconfiguration to break this trade-off, enabling loading of arbitrary configuration without interrupting the active configuration execution. Leveraging the intrinsic structure and nonvolatility of FeFETs, compact FPGA primitives are proposed and experimentally verified. The evaluation results show our design shows a 63.0%/74.7% reduction in a look-up table (LUT)/connection block (CB) area and 82.7%/53.6% reduction in CB/switch box power consumption with a minimal penalty in the critical path delay (9.6%). Besides, our design yields significant time savings by 78.7 and 20.3% on average for context-switching and dynamic reconfiguration applications, respectively.

97 MATHEMATICS AND COMPUTING↗

Analog Signal Multiplexing System for the IOTA Proton Injector

he Fermilab Accelerator Science and Technology (FAST) Facility at FNAL is a dedicated research and development center focused on advancing particle accelerator technologies for future applications worldwide. Currently, a key objective of FAST Opera-tions is to commission the 2.5 MeV IOTA Proton Injec-tor (IPI) and enable proton injection into the Integrable Optics Test Accelerator (IOTA) storage ring. The low and medium-energy sections of the IPI include four frame-style dipole trims and two multi-function cor-rectors with independently controlled coils, requiring readout of 32 analog channels for current and voltage monitoring in total. To reduce cost and optimize rack space within the PLC-based control system, a 32-to-4 analog signal multiplexing system was designed and implemented. This system enables real-time readback of excitation parameters from all magnetic correctors. This paper presents the design, construction, implementation, and performance of the multiplexing system.

MacLean, Daniel R. [Fermilab] (ORCID:0000000210103↗

Nb₃Sn Coating of Twin Axis Cavity for SRF Applications

The twin axis cavity with two identical accelerating beams has been proposed for energy recovery linac (ERL) applications. Nb₃Sn is a superconducting material with a higher critical temperature and a higher critical field as compared to Nb, which promises a lower operating cost due to higher quality factors. Two niobium twin axis cavities were fabricated at JLab and were proposed to be coated with Nb₃Sn. Due to their more complex geometry, the typical coating process used for basic elliptical cavi-ties needs to be improved to coat these cavities. This development advances the current coating system at JLab for coating complex cavities. Two twin axis cavities were coated recently for the first time. This contribution dis-cusses initial results from coating of twin axis cavities, RF testing and witness sample analysis with an overview of the current challenges towards high performance Nb₃Sn coated twin axis cavities.

43 PARTICLE ACCELERATORS↗

Performance Portable Graphics Processing Unit Acceleration of a High-Order Finite Element Multiphysics Application

The Lawrence Livermore National Laboratory (LLNL) will soon have in place the El Capitan exascale supercomputer, based on advanced micro devices (AMD) graphics processing units (GPUs). As part of a multiyear effort under the National Nuclear Security Administration (NNSA) Advanced Simulation and Computing (ASC) program, we have been developing marbl, a next generation, performance portable multiphysics application based on high-order finite elements. In previous years, we successfully ported the Arbitrary Lagrangian–Eulerian (ALE), multimaterial, compressible flow capabilities of marbl to nvidia GPUs as described in Vargas et al. Here, in this paper, we describe our ongoing effort in extending marbl's GPU capabilities with additional physics, including multigroup radiation diffusion and thermonuclear burn for high energy density physics (HEDP) and fusion modeling. We also describe how our portability abstraction approach based on the raja Portability Suite and the mfem finite element discretization library has enabled us to achieve high performance on AMD based GPUs with minimal effort in hardware-specific porting. Throughout this work, we highlight numerical and algorithmic developments that were required to achieve GPU performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fast and Scalable FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices with Application to Linear Inverse Problems Governed by Autonomous Dynamical Systems

In this work, we present an efficient and scalable algorithm for performing matrix-vector multiplications (matvecs) for block Toeplitz matrices. Such matrices, which are shift-invariant with respect to their blocks, arise in the context of solving inverse problems governed by autonomous systems, and time-invariant systems in particular. In this article, we consider inverse problems that infer unknown parameters from observational data of a linear time-invariant dynamical system given in the form of partial differential equations (PDEs). Matrix-free Newton-conjugate-gradient methods are often the gold standard for solving these inverse problems, but they require numerous actions of the Hessian on a vector. Matrix-free adjoint-based Hessian matvecs require solution of a pair of linearized forward/adjoint PDE solves per Hessian action, which may be prohibitive for large-scale inverse problems. Time invariance of the forward PDE problem leads to a block Toeplitz structure of the discretized parameter-to-observable (p2o) map defining the mapping from inputs (parameters) to outputs (observables) of the PDEs. This block Toeplitz structure enables us to exploit two key properties: (1) compact storage of the p2o map and its adjoint, and (2) efficient fast Fourier transform–based Hessian matvecs. The proposed algorithm is mapped onto large multi-GPU clusters and achieves more than 80% of peak bandwidth on NVIDIA A100 GPUs. Excellent weak scaling is shown for up to 48 A100 GPUs. For the targeted problems, the implementation executes Hessian matvecs within fractions of a second, which is orders of magnitude faster than can be achieved by conventional matrix-free Hessian matvecs via forward/adjoint PDE solves.

97 MATHEMATICS AND COMPUTING↗