Predicting time evolution of hydrogen co-deposition in ITER based on self consistent global impurity transport modeling

Relaterede dokumenter
Statistical information form the Danish EPC database - use for the building stock model in Denmark

Generalized Probit Model in Design of Dose Finding Experiments. Yuehui Wu Valerii V. Fedorov RSU, GlaxoSmithKline, US

Basic statistics for experimental medical researchers

Hydrogen Burning in Stars-II

PARALLELIZATION OF ATTILA SIMULATOR WITH OPENMP MIGUEL ÁNGEL MARTÍNEZ DEL AMOR MINIPROJECT OF TDT24 NTNU

Portal Registration. Check Junk Mail for activation . 1 Click the hyperlink to take you back to the portal to confirm your registration

Constant Terminal Voltage. Industry Workshop 1 st November 2013

APPENDIX E.3 SHADOW FLICKER CALCULATUIONS. 70 m TOWERS & 56 m BLADES

DoodleBUGS (Hands-on)

Statistik for MPH: 7

X M Y. What is mediation? Mediation analysis an introduction. Definition

Den nye Eurocode EC Geotenikerdagen Morten S. Rasmussen

Privat-, statslig- eller regional institution m.v. Andet Added Bekaempelsesudfoerende: string No Label: Bekæmpelsesudførende

Frequency Dispersion: Dielectrics, Conductors, and Plasmas

Linear Programming ١ C H A P T E R 2

Unitel EDI MT940 June Based on: SWIFT Standards - Category 9 MT940 Customer Statement Message (January 2004)

Vina Nguyen HSSP July 13, 2008

Engineering of Chemical Register Machines

Reexam questions in Statistics and Evidence-based medicine, august sem. Medis/Medicin, Modul 2.4.

28 April 2003 Retrospective: Semicore Visit

Applications. Computational Linguistics: Jordan Boyd-Graber University of Maryland RL FOR MACHINE TRANSLATION. Slides adapted from Phillip Koehn

The GAssist Pittsburgh Learning Classifier System. Dr. J. Bacardit, N. Krasnogor G53BIO - Bioinformatics

Appendix 1 Properties of Fuels

User Manual for LTC IGNOU

A multimodel data assimilation framework for hydrology

applies equally to HRT and tibolone this should be made clear by replacing HRT with HRT or tibolone in the tibolone SmPC.

Statistik for MPH: oktober Attributable risk, bestemmelse af stikprøvestørrelse (Silva: , )

RoE timestamp and presentation time in past

Slot diffusers. Slot diffusers LD-17, LD-18

Global carbon cycle studies with LPJ-GUESS

Aktivering af Survey funktionalitet

Remote Sensing til estimering af nedbør og fordampning

The effects of occupant behaviour on energy consumption in buildings

Small Autonomous Devices in civil Engineering. Uses and requirements. By Peter H. Møller Rambøll

Besvarelser til Lineær Algebra Reeksamen Februar 2017

The soil-plant systems and the carbon circle

Particle-based T-Spline Level Set Evolution for 3D Object Reconstruction with Range and Volume Constraints

WindPRO version Nov 2013 Printed/Page :45 / 1. SHADOW - Main Result

Investigation of «vortex self turbulence» and Reynolds number effects for wake decay and transport IGE

Vindpark Øster Børsting. Bilag 7 Vindberegninger og vurderinger

CHAPTER 8: USING OBJECTS

to register

Bachelorprojekt. Forår 2013 DMD10

SKRIFTLIG EKSAMEN I NUMERISK DYNAMIK Bygge- og Anlægskonstruktion, 7. semester Torsdag den 19. juni 2003 kl Alle hjælpemidler er tilladt

On the complexity of drawing trees nicely: corrigendum

Black Jack --- Review. Spring 2012

FIRE DTU BYG. Performance -Based Design Fully-Developed Fires DTU

Rødsand laboratoriet et samarbejde mellem KU, Femern & DHI

Status of & Budget Presentation. December 11, 2018

ATEX direktivet. Vedligeholdelse af ATEX certifikater mv. Steen Christensen

Measuring the Impact of Bicycle Marketing Messages. Thomas Krag Mobility Advice Trafikdage i Aalborg,

ECE 551: Digital System * Design & Synthesis Lecture Set 5

what is this all about? Introduction three-phase diode bridge rectifier input voltages input voltages, waveforms normalization of voltages voltages?

Project Step 7. Behavioral modeling of a dual ported register set. 1/8/ L11 Project Step 5 Copyright Joanne DeGroat, ECE, OSU 1

DIVAR VIGTIGT! / IMPORTANT! MÅL / DIMENSIONS. The DIVAR wall lamp comes standard. with 2.4 m braided cord and a plug in power supply (EU or UK).

Totally Integrated Automation. Totally Integrated Automation sætter standarden for produktivitet.

Quantum Biochemistry. Jan H. Jensen Department of Chemistry University of Copenhagen. Slides can be found at: DOI: /m9.figshare.

Motorway effects on local population and labor market

Resource types R 1 1, R 2 2,..., R m CPU cycles, memory space, files, I/O devices Each resource type R i has W i instances.

DANMARKS NATIONALBANK

Skriftlig Eksamen Kombinatorik, Sandsynlighed og Randomiserede Algoritmer (DM528)

Det bedste sted - en undersøgelse med cirkler

Wander TDEV Measurements for Inexpensive Oscillator

Terrain ETRS 89 Zone: 32 East North Name of wind Type Wind energy Mean wind speed Equivalent

Fremtidsbilleder i energisektoren

Selection of a Laser Source for Magnetic Field Imaging Using Magneto-optical Films

mandag den 23. september 13 Konceptkommunikation

Help / Hjælp

The X Factor. Målgruppe. Læringsmål. Introduktion til læreren klasse & ungdomsuddannelser Engelskundervisningen

Shooting tethered med Canon EOS-D i Capture One Pro. Shooting tethered i Capture One Pro 6.4 & 7.0 på MAC OS-X & 10.8

Hudevad P200. Technical datasheet

Sign variation, the Grassmannian, and total positivity

Sport for the elderly

Challenges for the Future Greater Helsinki - North-European Metropolis

Trolling Master Bornholm 2012

Economics of Occasional Tillage St. Francis, KS December 2018

ME6212. High Speed LDO Regulators, High PSRR, Low noise, ME6212 Series. General Description. Typical Application. Package

Løsning af skyline-problemet

The River Underground, Additional Work

Nærskibsfart med bundlinieeffekt: Klima og miljø. Hans Otto Kristensen. Tlf: alt

LED STAR PIN G4 BASIC INFORMATION: Series circuit. Parallel circuit HOW CAN I UNDERSTAND THE FOLLOWING SHEETS?

NYC Reservoir System Current Operations December 14, 2010

DONG-område Resten af landet

Midlertidig ændring af vandstand som redskab til vedligeholdelse af lobeliesøer

USERTEC USER PRACTICES, TECHNOLOGIES AND RESIDENTIAL ENERGY CONSUMPTION

Melbourne Mercer Global Pension Index

Financial Literacy among 5-7 years old children

UNISONIC TECHNOLOGIES CO.,

Alexander Krivov, Sebastian Müller, Torsten Löhne, Harald Mutschke

Climate model results from the VR-LANDCLIM project

Eric Nordenstam 1 Benjamin Young 2. FPSAC 12, Nagoya, Japan

Skriftlig eksamen Science statistik- ST501

Dynamic Stick-Slip at the Base of Ice Sheets Generates Massive Internal Deformation

Observation Processes:

IBM Network Station Manager. esuite 1.5 / NSM Integration. IBM Network Computer Division. tdc - 02/08/99 lotusnsm.prz Page 1

Pollution from shipping in Denmark

Evaluating Germplasm for Resistance to Reniform Nematode. D. B. Weaver and K. S. Lawrence Auburn University

Experience. Knowledge. Business. Across media and regions.

Remember the Ship, Additional Work

Procuring sustainable refurbishment

Transkript:

Max-Planck-Institut für Plasmaphysik Predicting time evolution of hydrogen co-deposition in ITER based on self consistent global impurity transport modeling K. Schmid M. Reinelt, K. Krieger

Outline Motivation Model description Input data Results Surface composition evolution Be influx onto targets Impurity influx into SOL D co-deposition Summary

Motivation Current predictions for co-deposition in ITER are based on local simulations at the CFC targets Requires ad-hoc assumption about Be influx No global flux or material balance Ignores co-deposition at other locations in the divertor Use WallDYN[1] to perform self consistent, global erosion deposition modeling of Be, C and W in ITER Self consistently calculates impurity fluxes (Be, C, W) onto the wall and erosion fluxes back to the plasma. Calculates the time evolution of the surface composition Maintains a global material and flux balance Calculates deposition of Be, C and W over the entire poloidal circumference of the ITER first wall [1] K. Schmid et Al An integrated model of impurity migration and wall composition dynamics for tokamaks PSI-19

Model description Subdivide the first wall into N-tiles Wall tiles Be, C, W, D, He Be, C, W Reaction zone Bulk Plasma ~Ion range Plasma model: Time scale of plasma transport is short compared to time scale of wall evolution Impurity concentrations in the plasma are low enough not to disturb the plasma Plasma transport can be characterized by a re-deposition matrix: r m,q i, j Surface model: from tile Fraction of j that ends eroded flux of up on tile i element m at charge state Reaction zone composition is variable, Bulk composition is constant All erosion & deposition is assumed to occur homogeneously in the reaction zone Total areal density of the reaction zone is kept constant via exchange with Bulk q

Model description Influx from plasma transport Defines an algebraic equation system for the incident fluxes Redistribution matrix from plasma transport code e.g DIVIMP = Fraction of element ei eroded at wr that ends up on ws at charge state qi

Model description Change in areal density [1] of element ei on wall wr For non depositing species e.g D no surface composition is calculated Additional material loss losschannels and and sources can canbe beadded addedhere Simulate chemical reactions (see (seem. M. Reinelt PSI-19) total areal density: NElem δ TOT = δ, wr ei= 1 ei, wr In net erosion cases material has to be moved from the bulk to the reaction zone to keep the total areal density constant In net deposition cases material has to be moved to the bulk from the reaction zone to keep the total areal density constant [1] K. Schmid et al., Nuclear Technology, 159, No. 3, (2007) 238

Z (m) 6 4 2 0-2 -4-6 Input data High power & high density ITER case [1]: iter812 WallDYN wall and B2/E grid boundary 0 7 19 14 4 6 8 10 12 14 R (m) 50 0 40 32 23 Wall B2/E grid edge Wall grid distance (m) Grid Grid wall wall distance up up to to 60 60 cm! cm!? Extrapolation of of plasma plasma to to wall wall? Te, Te, Ti Ti D, D, He, He, C fluxes fluxes 10 1 0.1 0.01 Main Wall Grid-Wall distance Outer baffle Outer strike PFR Inner strike Inner baffle 1E-3 0 25 50 Wall element index [1] A. S. Kukushkin et al. Journal of Nuclear Materials 337 339 (2005) 50 54

Input data Ion fluxes and plasma parameters at the wall 100 Main Wall Flat extrapolation from B2/E calculation grid to wall Outer baffle Outer strike PFR Inner strike Inner baffle 105 104 Main Wall Outer baffle Outer strike PFR Inner strike Inner baffle Temperature (ev) 10 Te Ti D ion flux 1020 m-2 s-1 103 102 101 1 100 10-1 0 10 20 30 40 50 0 10 20 30 40 50 Wall element index Wall element index Very high Te, Ti at W baffles and main chamber Strong physical sputtering Gap between grid and wall ~ 5 cm at baffles and ~ 20 cm at main wall Significant decay decay of of flux flux & temperatures is is likely likely

Input data Decay of ion fluxes and plasma temperatures towards the wall Flux decays exponentially with a decay length λ λ = D c s l l 180 m 2 10 m D s λ 5 c 10 m s s Drop by factor ½ on average 0.1m Temperature decay is more complicated, depends on χ parallel Ti ~ constant due to fast transport in gap (blobs) Te drops due to parallel heat loss (high χ parallel for e - ) By By how how much much?

Input data Drop in Te from grid to wall based on radial Te evolution in the B2/E solution 200 150 Te Exp-fit Temperature (ev) 100 50 λ Te = 0.013 m 0 0.00 0.01 0.02 0.03 0.04 Distance from separatrix (m) Radial Te, evolution well represented by exponential decay Use this λ values to extrapolate Te across the gap [1] A. S. Kukushkin et al. Journal of Nuclear Materials 337 339 (2005) 50 54

Input data Resulting plasma parameters at wall due to Te decay 100 Main Wall Exp. decay of plasma parameters from B2/E calculation grid to wall Outer baffle Outer strike PFR Inner strike Inner baffle 105 104 Main Wall Outer baffle Outer strike PFR Inner strike Inner baffle Temperature (ev) 10 Te Exp. decay Te Flat extrap. Ti D ion flux 1020 m-2 s-1 103 102 101 Flux decay Flat extrapolation 1 100 0 10 20 30 40 50 Wall element index 10-1 0 10 20 30 40 50 Wall element index Decay affects main wall, divertor dome and baffle Lower Be source at main wall Less mitigation of C erosion

Input data New ITER design case [1]: F57_Series 1511 Flat plasma extrapolation 68 0 29 Wall B2/E grid edge 17 Temperature (ev) 40 35 30 25 20 15 10 5 Main Wall Te Ti D+1-Flux Outer baffle Outer strike 0 0 10 20 30 40 50 60 70 Wall element index Similar D ion fluxes but plasma temperatures are lower by factor ~3 (Grid extends farther outward) Smaller difference between flat extrapolation and plasma decay [1] H.D. Pacher, A.S. Kukushkin et Al, J. Nucl. Mat. 3909-391 (2009) p. 259 PFR Inner tgt Inner baffle Main Wall 1.0x104 8.0x103 6.0x103 4.0x103 2.0x103 D-Flux 1020 m-2 s-1

Input data Plasma model input data the redistribution matrix calculated by DIVIMP Destination wall index 50 40 30 20 10 Launch impurities at a poloidal position Record impact position and charge state Be r i, j Be charge state integrated Inner baffle Inner strike Divertor dome Outer strike Outer baffle Main Wall Charge state resolved re-deposition matrix Strong diagonal Transport is step wise Most material ends up in inner divertor 10 20 30 40 50 Source wall index

Input data Given the redistribution matrices, where is eroded material qualitatively transported to Material is transported in small steps and generally ends up at: But that does not mean it stays there! In the divertor material is recycling

Input data Surface model input data Erosion yields as function energy and surface composition Reflection yields as function energy and surface composition? 20 Years of MD, TRIM & Experimental data yield a solid basis for a scaling law based parameterization of the required yields Current approach: Fit TRIDYN data with scaling law Composition dependence Energy dependence (Bohdansky formula) Similar approach also for reflection yield

Results Calculations produce huge amount of information difficult to visualize Only excerpts & averages are shown Old and new ITER design B2/E backgrounds yield qualitatively the same results Not ever result will be shown for every case Only examples of observed effects will be shown Main influence on results comes from different extrapolation of main wall plasma Comparison of flat extrapolation with plasma decay case High Te, Ti & flux Strong Be source Low Te, Ti & flux Weak Be source

Surface composition evolution Erosion fluxes of Be, C & W vary with time due to changes surface composition Impurity influx varies with time There is no constant set of fluxes to be used in a local simulation Equilibrium state can only be found in a global simulation Old ITER design flat extrapolation Main Wall Outer baffle Outer target Dome Inner target Inner baffle

Be influx onto targets Be influx onto divertor targets as function of time Be flux fraction 1 0.1 0.01 1E-3 1E-4 1E-5 1E-6 Outer target 1E-7 24 26 28 30 40 42 44 46 48 50 52 Wall element index Inner target Self consisten model at time (s) 0 1 100 1000 Old, local simulations Old calculations Be flux fraction varies by orders of magnitude vs. time and position Old ITER design flat extrapolation Old predictions based on constant Be flux fraction overestimate Be flux overestimate Be deposition overestimate co-deposition by Be underestimate co-deposition by C Self consistent calculations yield less Be deposition More C erosion C co-deposition dominates

Impurity influx into SOL Erosion fluxes of Be, C & W for the equilibrium surface composition Erosion flux #/m-tor s 1E20 1E19 1E18 Be (flat extrapolation) Be (Plasma decay) C (flat extrapolation) C (Plasma decay) C erosion flux depends on Be source Old ITER design 1E17 Outer wall Outer baffle Outer target Dome Inner target Inner baffle Inner wall Poloidal location For flat extrapolation the main wall Be erosion is higher by an order of magnitude. C erosion is more mitigated by Be deposition in flat extrapolation case Divertor region is still C erosion flux dominated in both cases W Sputtering is low in both cases and limited to the outer baffle

D co-deposition Calculated deposition of Be, C and W Growth rate #/m-tor s 1E21 1E20 1E19 1E18 1E17 Be (flat extrapolation) Be (plasma decay) C (flat extrapolation) C (plasma decay) New ITER design 1E16 1E15 Outer wall Outer baffle Outer target Dome Inner target Inner baffle Inner wall Poloidal position Be deposition mainly in inner divertor C deposition at divertor floor (dome) and outer main chamber Amount of C deposition depends on C erosion mitigation by Be i.e on the Be source C dominates deposition in all cases

Input data Based on net deposition rates (m -2 s -1 ) at each poloidal position + D/C, D/W and D/Be ratios [1] the D accumulation rate can be calculated D/C, D/W and D/Be ratios as functions of D/x flux ratio, T(K) and D-energy D x = New ITER design (Plasma decay) D/C ~ 0.2 D/Be ~ 5E-2 D/W ~5E-3 α Γ E + D D + e ΓBe Poloidal location Inner wall Inner baffle Inner target Dome Outer target Outer baffle β γ T D/W D/C D/Be D/x flux ratio, T(K) and D-energy were clamped to validity range Assumed temperatures Pos. Inner strikep. Outer strikep. Dome T(K) 800 1200 600 Outer wall 0.0 0.1 0.2 0.3 D/x ratio [1] R.P. Doerner et. Al, Nucl. Fusion 49 (2009) 035002 Baffles Main wall 600 600

D co-deposition D co-deposition rate #/s D co-deposition rates from D/x ratios (D/s) 1E22 1E21 1E20 1E19 1E18 1E17 D co-deposition rate with Be (Flat extrapolation) Be (Plasma decay) C (Flat extrapolation) C (Plasma decay) New ITER design 1E16 Outer wall Outer baffle Outer target Dome Inner target Inner baffle Inner wall Poloidal position Highest D co-deposition rate located at divertor floor next to targets due chemical sputtering at target plates below strike C dominates total D co-deposition A high Be source partially mitigates C erosion and thus D co-deposition

D co-deposition Time to T-accumulation limit due to co-deposition Different C erosion mitigation by Be deposition Flux and Te decay Iter812 (old design) F57_1511 (new design) Flat plasma extrapolation Iter812 (old design) F57_1511 (new design) J. Roth et. al, J. Nucl. Mat. 390 391 (2009) p. 1 Self Self consistent model model of of Be Be flux flux drops drops # of of ITER ITER shots shots by by up up to to factor factor ~10! ~10! Most Most retention now now due due to to C Divertor floor floor should should be be kept kept HOT HOT New New ITER ITER design design yields yields same same result result as as old old design design

Summary The WallDYN code allows to calculate the evolution of the first tiles coupled via plasma transport Maintaining material and flux balance it self consistently calculates erosion and redeposition and the impurity influx into the plasma Based on the calculated deposition rates and D/x ratios from literature the D inventory due to co-deposition can be calculated Compared to previous estimates most of the co-deposition is due to C not due to Be. (Old local simulations overestimated Be influx) The deposition of Be eroded from the main chamber leads to a strong reduction of C erosion in the inner and partly also in the outer divertor. A high Be source mitigates C erosion and thus D co-deposition The calculation was performed both for the old and the new ITER design yielding essentially the same results: Co-deposition with C instead of Be reduces # of ITER discharges to reach T limit A lot of assumptions about the fluxes and plasma temperatures at the wall have to be made. More experiments are required to improve modeling main wall erosion