Applications of Large-Scale Computation to Particle Accelerators
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Herrmannsfeldt, W.↗
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Proof-of-principle demonstration of Nb{sub 3}Sn superconducting radiofrequency cavities for high Q{sub 0} applications
Many future particle accelerators require hundreds of superconducting radiofrequency (SRF) cavities operating with high duty factor. The large dynamic heat load of the cavities causes the cryogenic plant to make up a significant part of the overall cost of the facility. This contribution can be reduced by replacing standard niobium cavities with ones coated with a low-dissipation superconductor such as Nb{sub 3}Sn. In this paper, we present results for single cell cavities coated with Nb{sub 3}Sn at Cornell. Five coatings were carried out, showing that at 4.2 K, high Q{sub 0} out to medium fields was reproducible, resulting in an average quench field of 14 MV/m and an average 4.2 K Q{sub 0} at quench of 8 × 10{sup 9}. In each case, the peak surface magnetic field at quench was well above H{sub c1}, showing that it is not a limiting field in these cavities. The coating with the best performance had a quench field of 17 MV/m, exceeding gradient requirements for state-of-the-art high duty factor SRF accelerators. It is also shown that—taking into account the thermodynamic efficiency of the cryogenic plant—the 4.2 K Q{sub 0} values obtained meet the AC power consumption requirements of state-of-the-art high duty factor accelerators, making this a proof-of-principle demonstration for Nb{sub 3}Sn cavities in future applications.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Magnets for Muon 6D Cooling Channels
The Helical Cooling Channel (HCC), an innovative technique for six-dimensional (6D) cooling of muon beams using a continuous absorber inside superconducting magnets, has shown considerable promise based on analytic and simulation studies. The implementation of this revolutionary method of muon cooling requires high field superconducting magnets that provide superimposed solenoid, helical dipole, and helical quadrupole fields. Novel magnet design concepts are required to provide HCC magnet systems with the desired fields for 6D muon beam cooling. New designs feature simple coil configurations that produce these complex fields with the required characteristics, where new high field conductor materials are particularly advantageous. The object of the program was to develop designs and construction methods for HCC magnets and design a magnet system for a 6D muon beam cooling channel. If successful the program would develop the magnet technologies needed to create bright muon beams for many applications ranging from scientific accelerators and storage rings to beams to study material properties and new sources of energy. Examples of these applications include energy frontier muon colliders, Higgs and neutrino factories, stopping muon beams for studies of rare fundamental interactions and muon catalyzed fusion, and muon sources for cargo screening for homeland security.
43 PARTICLE ACCELERATORS↗
Hollow electron lenses for beam collimation at the High-Luminosity Large Hadron Collider (HL-LHC)
Electrons lenses produce a high-intensity electron beam and have a variety of applications to circular hadron accelerators. Electron beams of different transverse cross sections and distributions may be designed, depending on the desired application, and they are produced and steered along the orbit of the hadron beam, overlapping with it for typical distances of a few meters before being deflected away and disposed of. Hollow electron beams find applications to high-intensity beam collimation for machines like the CERN Large Hadron Collider (LHC). Such devices can be integrated in a collimation system to improve the halo-cleaning performance through an active control of the halo dynamics: the annular distribution of the electrons excites resonantly the beam tails surrounding the beam core, while the core itself remains unperturbed, as ideally it only “sees” the field-free “hole” in the electron distribution. Hollow electron lenses are part of the upgrade baseline of the High-Luminosity project of the LHC (HL-LHC) and will be installed in the machine during a long shutdown in 2025–2027 to mitigate effects from beam losses so to improve the collimation system performance. This paper describes the hollow electron lens project within the HL-LHC collimation upgrade.
43 PARTICLE ACCELERATORS↗
EXPERIMENTAL DEMONSTRATION OF A STRAIGHT-MERGER BEAMLINE
Beamlines capable of merging beams with different energies are critical to many applications related to advanced accelerator concepts and energy recovery linacs (ERLs). A straight merger system composed of a transverse deflecting cavity with a superimposed dipole magnet was proposed and recently tested at the Argonne Wakefield Accelerator. This paper reports on the experimental demonstration of the concept along with detailed beam dynamics investigations of the merger concept and its ability to conserve the beam brightness associated with the fresh bunch. Possible applications to ERL and beam-driven wakefield accelerators are also discussed.
Phillips, C.↗
EXPERIMENTAL DEMONSTRATION OF A STRAIGHT-MERGER BEAMLINE
Beamlines capable of merging beams with different energies are critical to many applications related to advanced accelerator concepts and energy recovery linacs (ERLs). A straight merger system composed of a transverse deflecting cavity with a superimposed dipole magnet was proposed and recently tested at the Argonne Wakefield Accelerator. This paper reports on the experimental demonstration of the concept along with detailed beam dynamics investigations of the merger concept and its ability to conserve the beam brightness associated with the fresh bunch. Possible applications to ERL and beam-driven wakefield accelerators are also discussed.
Phillips, C.↗
High Performance Computing Modeling Advances Accelerator Science for High-Energy Physics
The development and optimization of particle accelerators are essential for advancing our understanding of the properties of matter, energy, space, and time. Particle accelerators are complex devices whose behavior involves many physical effects on multiple scales. Therefore, advanced computational tools utilizing high-performance computing are essential for accurately modeling them. In the past decade, the US Department of Energy's SciDAC program has produced accelerator-modeling tools that have been employed to tackle some of the most difficult accelerator science problems. The authors discuss the Synergia framework and its applications to high-intensity particle accelerator physics. Synergia is an accelerator simulation package capable of handling the entire spectrum of beam dynamics simulations. Our authors present Synergia's design principles and its performance on HPC platforms.
43 PARTICLE ACCELERATORS↗
Parametric study of an ODW scramaccelerator for hypersonic test facilities
A parametric study has been conducted for an oblique detonation-wave (ODW) 'scramaccelerator' suitable for projectile aerothermodynamics studies in real gas hypersonic test facilities. The results of the present analytical design evaluation indicate that an ODW scramaccelerator using conventional gaseous propellants can accelerate projectiles of 0.1 to 1000 kg masses to speeds in the 6-10 km/sec range. Potential applications for such an accelerator encompass a hypersonic ballistic test range, kinetic energy weapon accelerators, mass drivers to LEO, projectile terminal ballistics testing, projectile/target interaction studies, inertial welders, and shock compactors.
Humphrey, Joseph W.↗
Laser-plasma ion beam booster based on hollow-channel magnetic vortex acceleration
Laser-driven ion acceleration provides ultrashort, high-charge, low-emittance beams, which are desirable for a wide range of high-impact applications. Yet after decades of research, a significant increase in maximum ion energy is still needed. This paper introduces a quality-preserving staging concept for ultraintense ion bunches that is seamlessly applicable from the nonrelativistic plasma source to the relativistic regime. Full three-dimensional particle-in-cell simulations prove robustness and capture of a high-charge proton bunch, suitable for readily available and near-term laser facilities.
43 PARTICLE ACCELERATORS↗
Vacuum laser acceleration of super-ponderomotive electrons using relativistic transparency injection
Abstract Intense lasers can accelerate electrons to very high energy over a short distance. Such compact accelerators have several potential applications including fast ignition, high energy physics, and radiography. Among the various schemes of laser-based electron acceleration, vacuum laser acceleration has the merits of super-high acceleration gradient and great simplicity. Yet its realization has been difficult because injecting free electrons into the fast-oscillating laser field is not trivial. Here we demonstrate free-electron injection and subsequent vacuum laser acceleration of electrons up to 20 MeV using the relativistic transparency effect. When a high-contrast intense laser drives a thin solid foil, electrons from the dense opaque plasma are first accelerated to near-light speed by the standing laser wave in front of the solid foil and subsequently injected into the transmitted laser field as the opaque plasma becomes relativistically transparent. It is possible to further optimize the electron injection/acceleration by manipulating the laser polarization, incident angle, and temporal pulse shaping. Our result also sheds light on the fundamental relativistic transparency process, crucial for producing secondary particle and light sources.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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↗
Cyclotron resonance thrustor design and diagnostics techniques.
Electron cyclotron resonance plasma accelerator design for thrustor application and measuring techniques
ELECTRIC PROPULSION↗
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)↗
Fast Track NTR Systems Assessment for NASA's First Lunar Outpost Scenario
Integrated systems and mission study results are presented which quantify the rationale and benefits for developing and using nuclear thermal rocket (NTR) technology for returning humans to the moon in the early 2000's. At present, the Exploration Program Office (ExPO) is considering chemical propulsion for its 'First Lunar Outpost' (FLO) mission, and NTR propulsion for the more demanding Mars missions to follow. The use of an NTR-based lunar transfer stage, capable of evolving to Mars mission applications, could result in an accelerated schedule, reduced cost approach to moon/Mars exploration. Lunar mission applications would also provide valuable operational experience and serve as a 'proving ground' for NTR engine and stage technologies. In terms of performance benefits, studies indicate that an expendable NTR stage powered by two 50 klbf engines can deliver approximately 96 metric tons (t) to trans-lunar injection (TLI) conditions for an initial mass in low earth orbit (IMLEO) of approximately 199 t compared to 250 t for a cryogenic chemical TLI stage. The NTR stage liquid hydrogen (LH2) tank has a 10 m diameter, 14.8 m length, and 68 t LH2 capacity. The NTR utilizes a 'graphite' fuel form consisting of coated UC2 particles in a graphite substrate, and has a specific impulse capability of approximately 870 s, and an engine thrust-to-weight ratio of approximately 4.8. The NTR stage and its piloted FLO lander has a total length of approximately 38 m and can be launched by a single Saturn V-derived heavy lift launch vehicle (HLLV) in the 200 to 250 t-class range. The paper summarizes NASA's First Lunar Outpost scenario, describes characteristics for representative engine/stage configurations, and examines the impact on engine selection and vehicle design resulting from a consideration of alternative NTR fuel forms and lunar mission profiles.
Borowski, Stanley K.↗
Solid-propellant motors for high-incremental-velocity low-acceleration maneuvers in space
The applicability of solid-propellant rockets into a regime of high-performance long-burning tasks beyond the capability of existing motors is discussed. Successful static test firings have demonstrated the feasibility of: (1) utilizing fully case-bonded end-burning propellant charges without mechanical stress relief; (2) using an all-carbon radiative nozzle markedly lighter than the flight-weight ablative nozzle it replaces, and (3) producing low spacecraft acceleration rates during the thrust transient through a controlled-flow igniter that promotes operation below the previous combustion limit.
Shafer, J. I.↗
Efficient Machine Learning Approach for Optimizing Scientific Computing Applications on Emerging HPC Architectures
Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-ow and irregular memory accesses. Furthermore, these applications are often iterative with dependency between steps, and thus making it hard to parallelize across steps. As a result, parallelism in these applications is often limited to a single step. Numerical simulation of charged particles beam dynamics is one such application where the distribution of work and memory access pattern at each time step is irregular. Applications with these properties tend to present significant branch and memory divergence, load imbalance between different processor cores, and poor compute and memory utilization. Prior research on parallelizing such irregular applications have been focused around optimizing the irregular, data-dependent memory accesses and control-ow during a single step of the application independent of the other steps, with the assumption that these patterns are completely unpredictable. We observed that the structure of computation leading to control-ow divergence and irregular memory accesses in one step is similar to that in the next step. It is possible to predict this structure in the current step by observing the computation structure of previous steps. In this dissertation, we present novel machine learning based optimization techniques to address the parallel implementation challenges of such irregular applications on different HPC architectures. In particular, we use supervised learning to predict the computation structure and use it to address the control-ow and memory access irregularities in the parallel implementation of such applications on GPUs, Xeon Phis, and heterogeneous architectures composed of multi-core CPUs with GPUs or Xeon Phis. We use numerical simulation of charged particles beam dynamics simulation as a motivating example throughout the dissertation to present our new approach, though they should be equally applicable to a wide range of irregular applications. The machine learning approach presented here use predictive analytics and forecasting techniques to adaptively model and track the irregular memory access pattern at each time step of the simulation to anticipate the future memory access pattern. Access pattern forecasts can then be used to formulate optimization decisions during application execution which improves the performance of the application at a future time step based on the observations from earlier time steps. In heterogeneous architectures, forecasts can also be used to improve the memory performance and resource utilization of all the processing units to deliver a good aggregate performance. We used these optimization techniques and anticipation strategy to design a cache-aware, memory efficient parallel algorithm to address the irregularities in the parallel implementation of charged particles beam dynamics simulation on different HPC architectures. Experimental result using a diverse mix of HPC architectures shows that our approach in using anticipation strategy is effective in maximizing data reuse, ensuring workload balance, minimizing branch and memory divergence, and in improving resource utilization.
Arumugam, Kamesh↗
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↗
High Level Synthesis of RDF Queries for Graph Analytics
In this paper we present a set of techniques that enable the synthesis of efficient custom accelerators for memory intensive, irregular applications. To address irregular applications challenges (large memory footprints, unpredictable fine- grained data accesses, and high synchronization intensity), and exploit their opportunities (thread level parallelism, memory level parallelism), we propose a novel accelerator design which take advantage of an adaptive and Distributed Controller (DC) architecture, and a Memory Interface (MI) that supports parallel memory subsystems. Among the multitude of algorithms that may benefit from our solution, we focus on the acceleration of graph analytics applications, and in particular, on the syn- thesis of SPARQL queries on Resource Description Framework (RDF) databases. We achieve this objective by incorporating the synthesis techniques into Bambu, an Open Source high- level synthesis tools, and interfacing the system with GEMS, the Graph database Engine for Multithreaded Systems. The front- end of GEMS generates optimized C implementations of the input queries, modeled as pattern matching routines, which are then automatically synthesized by Bambu. We validate our approach synthesizing several SPARQL queries from the Lehigh University Benchmark (LUBM).
HLS, FPGA, Convey, RDF, GEMS, Memory-intensive,↗