A comparison of spectral element and finite difference methods using statically refined nonconforming grids for the MHD island coalescence instability problem

A recently developed spectral-element adaptive refinement incompressible magnetohydrodynamic (MHD) code [Rosenberg, Fournier, Fischer, Pouquet, J. Comp. Phys. 215, 59-80 (2006)] is applied to simulate the problem of MHD island coalescence instability (MICI) in two dimensions. MICI is a fundamental MHD process that can produce sharp current layers and subsequent reconnection and heating in a high-Lundquist number plasma such as the solar corona [Ng and Bhattacharjee, Phys. Plasmas, 5, 4028 (1998)]. Due to the formation of thin current layers, it is highly desirable to use adaptively or statically refined grids to resolve them, and to maintain accuracy at the same time. The output of the spectral-element static adaptive refinement simulations are compared with simulations using a finite difference method on the same refinement grids, and both methods are compared to pseudo-spectral simulations with uniform grids as baselines. It is shown that with the statically refined grids roughly scaling linearly with effective resolution, spectral element runs can maintain accuracy significantly higher than that of the finite difference runs, in some cases achieving close to full spectral accuracy.Comment: 19 pages, 17 figures, submitted to Astrophys. J. Supp

Synthesis of 3-D coronal-solar wind energetic particle acceleration modules

1. Introduction Acute space radiation hazards pose one of the most serious risks to future human and robotic exploration. Large solar energetic particle (SEP) events are dangerous to astronauts and equipment. The ability to predict when and where large SEPs will occur is necessary in order to mitigate their hazards. The Coronal-Solar Wind Energetic Particle Acceleration (C-SWEPA) modeling effort in the NASA/NSF Space Weather Modeling Collaborative [Schunk, 2014] combines two successful Living With a Star (LWS) (http://lws. gsfc.nasa.gov/) strategic capabilities: the Earth-Moon-Mars Radiation Environment Modules (EMMREM) [Schwadron et al., 2010] that describe energetic particles and their effects, with the Next Generation Model for the Corona and Solar Wind developed by the Predictive Science, Inc. (PSI) group. The goal of the C-SWEPA effort is to develop a coupled model that describes the conditions of the corona, solar wind, coronal mass ejections (CMEs) and associated shocks, particle acceleration, and propagation via physics-based modules. Assessing the threat of SEPs is a difficult problem. The largest SEPs typically arise in conjunction with X class flares and very fast (\u3e1000 km/s) CMEs. These events are usually associated with complex sunspot groups (also known as active regions) that harbor strong, stressed magnetic fields. Highly energetic protons generated in these events travel near the speed of light and can arrive at Earth minutes after the eruptive event. The generation of these particles is, in turn, believed to be primarily associated with the shock wave formed very low in the corona by the passage of the CME (injection of particles from the flare site may also play a role). Whether these particles actually reach Earth (or any other point) depends on their transport in the interplanetary magnetic field and their magnetic connection to the shock

Synovial fluid fingerprinting in end-stage knee osteoarthritis: A novel biomarker concept to assess disease modifying therapies

Osteoarthritis (OA) is a common and debilitating condition with no cure. The lack of disease-modifying treatments is linked to a deficiency in suitable biomarkers. This study aimed to combine multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee osteoarthritis

Toward exascale whole-device modeling of fusion devices: Porting the GENE gyrokinetic microturbulence code to GPU

GENE solves the five-dimensional gyrokinetic equations to simulate the development and evolution of plasma microturbulence in magnetic fusion devices. The plasma model used is close to first principles and computationally very expensive to solve in the relevant physical regimes. In order to use the emerging computational capabilities to gain new physics insights, several new numerical and computational developments are required. Here, we focus on the fact that it is crucial to efficiently utilize GPUs (graphics processing units) that provide the vast majority of the computational power on such systems. In this paper, we describe the various porting approaches considered and given the constraints of the GENE code and its development model, justify the decisions made, and describe the path taken in porting GENE to GPUs. We introduce a novel library called gtensor that was developed along the way to support the process. Performance results are presented for the ported code, which in a single node of the Summit supercomputer achieves a speed-up of almost 15× compared to running on central processing unit (CPU) only. Typical GPU kernels are memory-bound, achieving about 90% of peak. Our analysis shows that there is still room for improvement if we can refactor/fuse kernels to achieve higher arithmetic intensity. We also performed a weak parallel scalability study, which shows that the code runs well on a massively parallel system, but communication costs start becoming a significant bottleneck

Observation and Simulation of Chorus Waves Generation at the Gradients of Magnetic Holes

International audienceThe Magnetospheric Multiscale (MMS) mission observed chorus waves at the gradients of magnetic holes on the dayside magnetosheath. The magnetic holes are nonlinear mirror structures which are anticorrelated with particle density. We used expanding box Particle-in-cell simulations and produced the mirror instability magnetic holes. We show that chorus waves are generated at the gradients of magnetic holes in our simulations which is in agreement with MMS observations. We investigate the possible mechanism for enhancing the electron temperature anisotropy at the magnetic field gradients. We analyze the electron pitch angle distributions and electron distribution functions in our simulations and compare it with MMS observations. We also measure the Poynting flux to investigate how much energy is carried away by the fields via chorus waves