MHD Analysis on the Physics Design of CFETR Baseline Scenarios
Not provided.
Nuclear Science & Technology↗
Engineering topics
Fang, Yu
Publications and source records attributed to Fang, Yu.
BFEMP: Interpenetration-free MPM–FEM coupling with barrier contact
Not Available
Li, Xuan (ORCID:0000000306778369)↗
Tunable Plasma Linearizer for Compensation of Nonlinear Energy Chirp
The removal of undesired nonlinear time-energy correlation (energy chirp) present in relativistic electron beams is crucial for many accelerator-based scientific applications, such as free-electron lasers, high-energy electron radiography, and MeV ultrafast electron microscopy. Here, we propose and demonstrate that a low-density plasma section can be used as a passive “linearizer” to significantly compensate for the nonlinear energy chirp imprinted on a beam by the curvature of the radio-frequency field in a conventional accelerator. Physically, the passage of the beam through the plasma excites a strong quasi-cosinoidal longitudinal decelerating wakefield that acts to mitigate the beam’s nonlinear energy chirp by superimposing a reverse chirp on the beam. Time-resolved phase-space measurements, combined with high-fidelity three-dimensional particle-in-cell simulations show that the longitudinal phase space of the beam core is almost completely linearized, leading to a fourfold reduction of the beam overall energy spread from 0.148% to 0.036% (FWHM).
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
High-throughput injection-acceleration of electron bunches from a linear accelerator to a laser wakefield accelerator
Plasma-based accelerators (PBAs) driven by either intense lasers (laser wakefield accelerators, LWFAs) or particle beams (plasma wakefield accelerators, PWFAs), can accelerate charged particles at extremely high gradients compared to conventional radio-frequency (RF) accelerators. In the past two decades, great strides have been made in this field, making PBA a candidate for next-generation light sources and colliders. However, these challenging applications necessarily require beams with good stability, high quality, controllable polarization and excellent reproducibility. To date, such beams are generated only by conventional RF accelerators. As such, it is important to demonstrate the injection and acceleration of beams first produced using a conventional RF accelerator, by a PBA. In some recent studies on LWFA staging and external injection-acceleration in PWFA only a very small fraction (from below 0.1% to few percent) of the injected charge (the coupling efficiency) was accelerated. For future colliders where beam energy will need to be boosted using multiple stages, the coupling efficiency per stage must approach 100%. Here we report the first demonstration of external injection from a photocathode-RF-gun-based conventional linear accelerator (LINAC) into a LWFA and subsequent acceleration without any significant loss of charge or degradation of quality, which is achieved by properly shaping and matching the beam into the plasma structure. Furthermore, this is an important step towards realizing a high-throughput, multi-stage, high-energy, hybrid conventional-plasma accelerator.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Measurements of the Growth and Saturation of Electron Weibel Instability in Optical-Field Ionized Plasmas
The temporal evolution of the magnetic field associated with electron thermal Weibel instability in optical-field ionized plasmas is measured using ultrashort (1.8 ps), relativistic (45 MeV) electron bunches from a linear accelerator. The self-generated magnetic fields are found to self-organize into a quasistatic structure consistent with a helicoid topology within a few picoseconds and such a structure lasts for tens of picoseconds in underdense plasmas. Here, the measured growth rate agrees well with that predicted by the kinetic theory of plasmas taking into account collisions. Magnetic trapping is identified as the dominant saturation mechanism.
Electric & magnetic plasma measurements↗
A massively parallel and scalable multi-CPU material point method
Harnessing the power of modern multi-GPU architectures, we present a massively parallel simulation system based on the Material Point Method (MPM) for simulating physical behaviors of materials undergoing complex topological changes, self-collision, and large deformations. Our system makes three critical contributions. First, we introduce a new particle data structure that promotes coalesced memory access patterns on the GPU and eliminates the need for complex atomic operations on the memory hierarchy when writing particle data to the grid. Second, we propose a kernel fusion approach using a new Grid-to-Particles-to-Grid (G2P2G) scheme, which efficiently reduces GPU kernel launches, improves latency, and significantly reduces the amount of global memory needed to store particle data. Finally, we introduce optimized algorithmic designs that allow for efficient sparse grids in a shared memory context, enabling us to best utilize modern multi-GPU computational platforms for hybrid Lagrangian-Eulerian computational patterns. We demonstrate the effectiveness of our method with extensive benchmarks, evaluations, and dynamic simulations with elastoplasticity, granular media, and fluid dynamics. In comparisons against an open-source and heavily optimized CPU-based MPM codebase [Fang et al. 2019] on an elastic sphere colliding scene with particle counts ranging from 5 to 40 million, our GPU MPM achieves over 100x per-time-step speedup on a workstation with an Intel 8086K CPU and a single Quadro P6000 GPU, exposing exciting possibilities for future MPM simulations in computer graphics and computational science. Moreover, compared to the state-of-the-art GPU MPM method [Hu et al. 2019a], we not only achieve 2x acceleration on a single GPU but our kernel fusion strategy and Array-of-Structs-of-Array (AoSoA) data structure design also generalizes to multi-GPU systems. Our multi-GPU MPM exhibits near-perfect weak and strong scaling with 4 GPUs, enabling performant and large-scale simulations on a 10243 grid with close to 100 million particles with less than 4 minutes per frame on a single 4-GPU workstation and 134 million particles with less than 1 minute per frame on an 8-GPU workstation.
Wang, Xinlei↗