Session NM09: Mini-Conference: Modeling of Sputtering, Impurity Migration, and Hydrogen Isotope Recycling

On the dynamic plasma-wall interactions

The physics of edge plasmas in magnetic confinement devices is very multifaceted and complex. It involves classical and anomalous plasma transport, atomic physics of hydrogenic species and different impurities, and plasma interactions with material surfaces of plasma facing components including the first wall and divertor targets [1].

            Till recently plasma-material interactions in most cases were described by some prescribed particle and energy reflection coefficients of the ions impinging onto material surface. However, in practice these coefficients depend on many dynamic factors including the constituency of the wall material, which is usually altered by the particle species trapped in the material, surface morphology, temperature, etc. Taking these dynamic effects into account allowing describing dynamic feedback effects of the wall physics on edge plasma. It includes the pedestal recovery after the ELM crash, the effect of neutrals on zonal flows regulating anomalous edge plasma transport, novel scrape-off layer plasma instability caused by plasma recycling [2-5].

            Here we review recent results on dynamic plasma-material interactions, discuss some important issues, and outline possible future developments in coupled plasma-wall physics.

 

[1] S. Krasheninnikov, A. Smolyakov, and A. Kukushkin, “On the Edge of Magnetic Fusion Devices”, (Springer Series in Plasma Science and Technology)  (Springer International Publishing Switzerland, Heidelberg, 2020).

[2] S. I. Krasheninnikov, et al. PPCF 57 (2015) 044009.

[3] Y. Zhang, S. I. Krasheninnikov, PPCF 62 (2020) 115018.

[4] Y. Zhang, S. I. Krasheninnikov, R. Masline, R. D. Smirnov, Nucl. Fusion 60 (2020) 106023

[5] S. I. Krasheninnikov, Plasma Physics Reports 47 (2021) 407-409.   

Model predictive control of boundary plasmas using reduced models derived from SOLPS-ITER

Time-dependent simulations of the tokamak boundary plasma are performed using the SOLPS-ITER transport code to develop reduced models and model-predictive control (MPC) of the upstream and divertor conditions actuated by main ion and impurity gas puff. The reduced models are based on DMD and SINDy methods, which are data-driven algorithms that extract dynamic behavior to describe the underlying physical system. With DMD, the time evolution is described by discrete operators, while SINDy results in a sparse set of coupled ordinary differential equations. In either case, the model is used to predict the evolution of the current plasma state over a rolling time horizon and determine an optimal actuation sequence to best produce a target trajectory, subject to constraints. Feed-forward MPC actuation sequences input to SOLPS using a DIII-D configuration have been found to agree well with a target density trajectory. When prediction error exceeds a prescribed threshold the model can be updated using past data over a set time window. The MPC method is being implemented into an efficient module that can be called from SOLPS as an online controller. The reduced models are also compared to analytic results and data-mined correlations extracted from simulation and experimental data.   

Integrated Multi-Scale Modeling of Impurity Migration and Plasma-Facing Material Evolution in Present and Future Tokamaks

Finding suitable plasma-facing materials is one of the great challenges in designing future fusion reactors, as unprecedented heat and particle fluxes will interact with the first wall, compromising the performance of both the plasma and wall components. These plasma-material interactions involve diverse plasma and materials physics, and further, are multi-scale in nature. To address this complex system, we have developed and validated an integrated computational model for interpretation and prediction of plasma-material interactions in plasma-facing materials. The model includes descriptions for the edge plasma, near-surface sheath, impurity erosion and redeposition, particle recycling, surface morphology and sub surface evolution. The model has already been used to interpret experiments in current devices, such as WEST, to predict the evolution of the ITER divertor under a range of operational conditions, as well as to explore the impact of plasma impurities in fuel recycling. Here, we present the latest applications of our model, including increased fidelity predictions for the evolution of the ITER divertor.   

Modeling dynamic wall recycling effects on edge plasma transport.

Plasma-wall interactions in tokamaks play an essential role in fusion plasma particle and energy balance via the plasma recycling process. Recycling is most intense in the divertor region and involves complex interactions between plasma and the wall material, which strongly depend on both plasma and wall conditions. Therefore, it is important to consider the plasma recycling process dynamically, in particular for transient phenomena, such as edge localized modes (ELMs), and edge plasma transport instabilities. We conduct dynamic 2D edge plasma-wall simulations using the plasma transport code UEDGE and the wall reaction-diffusion code FACE coupled within the Integrated Plasma Simulation (IPS) framework. The simulations demonstrate that the dynamic recycling affects the amplitude and phase relations between perturbations of plasma parameters at the plasma-wall interface, as compared to a conventional static wall model. The dynamic changes in recycling during ELMs and their feedback on ELM pulse evolution are analyzed. We also investigate the possibility of a recently proposed divertor plasma recycling instability mechanism related to ExB drifts [1].

[1] S.I. Krasheninnikov, Plasma Phys. Reports 47, 407 (2021).   

A 3D Unstructured Mesh-based Global Impurity Transport Code

This presentation will overview the GITRm code which is a fully 3D mesh-based impurity transport code based on the physics models contained in the GITR impurity transport code. GITRm builds on the PUMIPic library which is an unstructured mesh PIC infrastructure which supports the use of highly anisotropic meshes that allow for the effective distribution of calculation effort to critical regions of the domain. PUMIPic’s scalability is supported by the use of both distributed mesh and particle representations. The presentation will briefly introduce PUMIPic with a focus on the implementation of critical operations of importance to impurity transport calculations including particle containment search, distance to boundary in critical regions and dynamic load balancing to account for both the evolving distribution of particles and numbers of particles due to deposition as the simulation proceeds.  Scaling results for cases run on GPU-based supercomputers (e.g., Summit) will be presented. Finally, the status of results obtained to date using GITRm to address specific simulation scenarios will be presented.    

hPIC2: a GPU-accelerated, hybrid particle-in-cell code for plasma-material interactions in complex geometries

Many of the primary exascale supercomputers under construction rely on graphics processing unit (GPU) acceleration in order to reach their performance goals. While the particle-in-cell (PIC) method is an "embarrassingly parallelizable" algorithm for plasma simulation and well-suited to GPU acceleration, the range of device architectures to be implemented in future supercomputers often demands the use of unique parallel programming paradigms, threatening code portability. hPIC2 is a hybrid, electrostatic particle-in-cell code designed ab initio with shared-memory parallelism using the Kokkos performance portability framework, which allows for a single source code to be deployable to a diverse set of massively parallel architectures. hPIC2 is therefore scalable and performant on computing architectures ranging from a single core to many-core systems with GPU accelerators from all three major manufacturers. In addition, we have begun a number of preliminary explorations: parallelizing hybrid plasma simulation algorithms, which combine fluid and kinetic methods for a single species; modeling complex geometries, such as tokamak tile gaps, using implicit, non-uniform meshes; and coupling to RustBCA, a binary collision approximation (BCA) code for arbitrary ion-material interactions.