Progress, since the ITER Physics Basis publication (ITER Physics Basis Editors et al 1999 Nucl. Fusion 39 2137–2664), in understanding the processes that will determine the properties of the plasma edge and its interaction with material elements in ITER is described. Experimental areas where significant progress has taken place are energy transport in the scrape-off layer (SOL) in particular of the anomalous transport scaling, particle transport in the SOL that plays a major role in the interaction of diverted plasmas with the main-chamber material elements, edge localized mode (ELM) energy deposition on material elements and the transport mechanism for the ELM energy from the main plasma to the plasma facing components, the physics of plasma detachment and neutral dynamics including the edge density profile structure and the control of plasma particle content and He removal, the erosion of low- and high-Z materials in fusion devices, their transport to the core plasma and their migration at the plasma edge including the formation of mixed materials, the processes determining the size and location of the retention of tritium in fusion devices and methods to remove it and the processes determining the efficiency of the various fuelling methods as well as their development towards the ITER requirements. This experimental progress has been accompanied by the development of modelling tools for the physical processes at the edge plasma and plasma–materials interaction and the further validation of these models by comparing their predictions with the new experimental results. Progress in the modelling development and validation has been mostly concentrated in the following areas: refinement in the predictions for ITER with plasma edge modelling codes by inclusion of detailed geometrical features of the divertor and the introduction of physical effects, which can play a major role in determining the divertor parameters at the divertor for ITER conditions such as hydrogen radiation transport and neutral–neutral collisions, modelling of the ion orbits at the plasma edge, which can play a role in determining power deposition at the divertor target, models for plasma–materials and plasma dynamics interaction during ELMs and disruptions, models for the transport of impurities at the plasma edge to describe the core contamination by impurities and the migration of eroded materials at the edge plasma and its associated tritium retention and models for the turbulent processes that determine the anomalous transport of energy and particles across the SOL. The implications for the expected performance of the reference regimes in ITER, the operation of the ITER device and the lifetime of the plasma facing materials are discussed.

/pdf/chapter-4-power-and-particle-control-3l68lj0fxw.pdf

Chapter 4: Power and particle control

The EIRENE neutral gas transport Monte Carlo code has been developed initially for TEXTOR since the early 1980s. It is currently applied worldwide in most fusion laboratories for a large variety of...

/pdf/the-eirene-and-b2-eirene-codes-2mb9x8sy18.pdf

The EIRENE and B2-EIRENE Codes

Markov chain Monte Carlo methods are used to estimate mortality rates under a Bayesian hierarchical model. Spatial correlations are introduced to examine spatial effects relative to both regional and regional changes over time by groups. A special feature of the models is the inclusion of longitudinal variables which will describe temporal trends in mortality or incidences for different population groups. Disease maps are used to illustrate the role of different parameters in the model and pinpointing areas of interesting patterns. The methods are demonstrated by male cancer mortality data from the state of Missouri during 1973-1992. Of special interest will be the geographic variations in the trend of lung cancer mortality over the recent past. Marginal posterior distributions are used to examine effects due to spatial correlations and age difference in temporal trends. Numerical results from the Missouri data show that although spatial correlations exist, they do not have a large effect on the estimated mortality rates.

Spatio‐temporal interaction with disease mapping

A low density H-mode plasma has been selected for detailed inter-ELM modelling by the SOLPS code package, with the coupled treatment of its plasma (fluid code B2) and neutral (Monte-Carlo code Eirene) parts. Good quality measured midplane density and temperature profiles, covering the pedestal region and stretching far into the SOL, as well as several other parameters and profiles measured in the divertor, have enabled testing the consistency of code solutions with experiment. Once the upstream, midplane profiles have been fitted, and the global parameters (e.g. input power into the computational grid, radiated power) matched, the code reproduces experimental profiles and control parameters in the divertor with an accuracy within a factor of 2. Deviations of modelled parameters from the experiment were found around the strike point position where most of the power was deposited on the target. The deviations are consistent among themselves and all point to one common problem with the modelling: the predicted divertor electron temperature is too low and the density too high, compared with the experiment. The largest inconsistency between the code and experiment was in the magnitude of the peak Hα radiation in the outer divertor, which was larger by a factor of 2 in the code simulations. In addition, the code predicts a somewhat higher sub-divertor neutral flux but lower carbon impurity content in the edge plasma than in the experiment, as well as lower CIII emission. The discrepancy between Hα profiles can to a large degree be attributed to profile effects: the simulated Hα emission profiles are narrower than in the experiment, reflecting the tendency of the neutral–plasma mix to congregate excessively around the strike point in the modelling. At the same time, the integrated Hα emission matches very well with the experiment.Extensive sensitivity studies of the influence of variations in input parameters and assumptions of the code on the modelled divertor conditions have been conducted. They have not resulted in an identification of any SOLPS input/control parameters capable of removing the main disagreement between the code output and experiment. A possibility of parallel transport effects related to low collisionality to increase the effective plasma temperature near the strike point position or of increased perpendicular transport by neutrals (due to some missing reactions in Eirene) to widen the target profiles, will be explored in the future.

/pdf/solps-modelling-of-asdex-upgrade-h-mode-plasma-5a7txpoecx.pdf

SOLPS modelling of ASDEX upgrade H-mode plasma

An analytic model, derived from coupled continuity equations for the electron and neutral deuterium densities, is consistent with many features of edge electron density profiles in the DIII-D tokamak [J. L. Luxon et al., Plasma Physics and Controlled Fusion Research, 1986, Vol. I (International Atomic Energy Agency, Vienna, 1987), p. 159]. For an assumed constant particle diffusion coefficient, the model shows that particle transport and neutral fueling produce electron and neutral density profiles that have the same characteristic scale lengths at the plasma edge. For systematic variations of density in high-mode (H-mode) discharges, the model predicts that the width of the electron density transport barrier decreases and the maximum gradient increases, as observed in the experiments. The widths computed from the model agree quantitatively with the experimental widths for conditions in which the model is valid. These results support models of transport barrier formation in which the H-mode particle barri...

The role of neutrals in high-mode (H-mode) pedestal formation

/pdf/a-comparison-of-neutral-gas-models-for-divertor-plasmas-4o4t3l60ec.pdf

A Comparison of Neutral Gas Models for Divertor Plasmas

Benchmarks of DEGAS 2 against EIRENE yield agreement to within 5% and comparable single processor run times. DEGAS 2 demonstrates a nearly linear increase in processing speed with the number of parallel processors. That speed is put to practical use here in the first runs of UEDGE coupled to DEGAS 2. The results of the coupled codes match those of coupled UEDGE and EIRENE. Additional algorithmic improvements such as use of the correlated sampling technique promise to make runs of the coupled UEDGE - DEGAS 2 codes practical for everyday use.

Coupling of Parallelized DEGAS 2 and UEDGE Codes

Operational details are given for the two-dimensional UEDGE edge-plasma transport code. The model applies to nearly fully-ionized plasmas in a strong magnetic field. Equations are solved for the plasma density, velocity along the magnetic field, electron temperature, ion temperature, and electrostatic potential. In addition, fluid models of neutrals species are included or the option to couple to a Monte Carlo code description of the neutrals. Multi-species ion mixtures can be simulated. The physical equations are discretized by a finite-difference procedure, and the resulting system of algebraic equations are solved by fully-implicit techniques. The code can be used to follow time-dependent solutions or to find steady-state solutions by direct iteration.

/pdf/users-manual-for-the-uedge-edge-plasma-transport-code-4ifka1rj0i.pdf

Users manual for the UEDGE edge-plasma transport code

The transport of particles and energy from the core of a tokamak to nearby material surfaces is an important problem for understanding present experiments and for designing reactor-grade devices. A number of fluid transport codes have been developed to model the plasma in the edge and scrape-off layer (SOL) regions. This report will focus on recent model improvements and illustrative results from the UEDGE code. Some geometric and mesh considerations are introduced, followed by a general description of the plasma and neutral fluid models. A few comments on computational issues are given and then two important applications are illustrated concerning benchmarking and the ITER radiative divertor. Finally, we report on some recent work to improve the models in UEDGE by coupling to a Monte Carlo neutrals code and by utilizing an adaptive grid.

/pdf/models-and-applications-of-the-uedge-code-yd0sirjrx6.pdf

Models and applications of the UEDGE code

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

M. E. Rensink

Author Tools

Chat about Author

Papers

A Comparison of Neutral Gas Models for Divertor Plasmas

Coupling of Parallelized DEGAS 2 and UEDGE Codes

Coupling of Parallelized DEGAS 2 and UEDGE Codes

Users manual for the UEDGE edge-plasma transport code

Models and applications of the UEDGE code