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PTRANSP. Predictive Upgrades for TRANSP. US Predictive Modeling Effort. R. Budny, S. Jardin, C. Kessel, L. P. Ku, D. McCune ( PPPL ). H. St. John ( GA ). D. P. Grote, L. Lodestro, L. D. Pearlstein, T. D. Rognlien ( LLNL ). G. Bateman, F. Halpern, A. Kritz ( Lehigh ). J. Carlsson ( Tech-X ).

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Ptransp

PTRANSP

Predictive Upgrades for TRANSP


Us predictive modeling effort

US Predictive Modeling Effort

  • R. Budny, S. Jardin, C. Kessel, L. P. Ku, D. McCune (PPPL).

  • H. St. John (GA).

  • D. P. Grote, L. Lodestro, L. D. Pearlstein, T. D. Rognlien (LLNL).

  • G. Bateman, F. Halpern, A. Kritz (Lehigh).

  • J. Carlsson (Tech-X).


Ptransp plan

PTRANSP Plan

  • Leverage TRANSP:

    • Well validated source models (NBI, alphas, ICRF, LH, ECH/ECCD).

    • Strong connection to experimental data.

    • Fusion Grid production facility.

  • Add predictive capabilities to TRANSP:

    • Robust transport equation solver.

    • Free boundary equilibrium.

    • Connection to edge model.

  • Reuse existing software to extent possible.


Design principles 1

Design Principles - 1

  • Reuse TRANSP and Fusion Simulation Project (FSP) software (to minimize costs).

  • Two driver configurations:

    • Free boundary: (TRANSP computes sources; analyzes free boundary code results).

    • Prescribed boundary: traditional TRANSP with:

      • New transport solvers (FSP Solver, GCNM-P).

      • New MHD equilibrium solvers (FSP, TEQ).


Design principles 2

Design Principles - 2

  • Modular design: interchangeability of critical parts (create/use NTCC modules):

    • Transport solvers.

    • MHD equilibrium solvers.

    • Sources.

  • Leverage TRANSP archives:

    • Access to experimental data for validation.

    • NTCC module provided for data access.


Ptransp

PTRANSP Schematic

XPLASMA (FSP upgrade in progress)

TRDATBUF (access to experimental data)

Plasma State

Solver

Equilibrium

Sources

GCNMP

TEQ

TRANSP

Sawtooth

FSP-Sol

FSP-Equ

FSP-Src

Porcelli-L

Porcelli-P

ESC

Controller

Edge Pedestal

Lehigh

TRANSP-based controller

PPPL

FSP-based controller

Postprocessing (initially)

Bootstrap Curr

NCLASS

Stability Analysis

Edge Analysis

Hirsh-Sig.

DCON

UEDGE

PEST-2

DEGAS-2


Transport solver dilemma

Transport Solver Dilemma

  • Current predictive transport models (e.g. GLF-23) are very stiff.

  • Standard numerical integration methods suffer severe oscillations and instability.

  • Attempts to “smooth” GLF-23 directly significantly changes prediction results.

  • Therefore: serious solver upgrade effort.

    • GCNM-P (General Atomics) & FSP (PPPL).


Transport solvers

Transport Solvers

  • GCNM – Globally Convergent Newton Method – ONETWO Solver (St. John, GA).

    • Very general stiff PDE integrator.

    • Use of Jacobian, O(n**2) execution cost.

  • FSP Solver (Jardin & Ku, PPPL).

    • “Local” Newton method– forward implicit use of dependence of transport on grad(Ti,Te,…).

    • O(n) but may not be as stable as GCNM.


The ptransp fsp solver 1 this has been implemented in the full solver in the fsp

The PTRANSP FSP Solver - 1This has been implemented in the full solver in the FSP:

Without linearization

With linearization

  • ITER simulation

  • Linearization of dependence of GLF-23 fluxes on temperature gradients.

  • Behavior reproducible in simplified single-T analytic transport model.

  • Caveat: DIII-D experimental data validation attempt– not yet fully stable.

S. Jardin / L. P. Ku


The ptransp fsp solver 2 convergence tests

The PTRANSP FSP Solver - 2Convergence Tests:

3 Newton iterations per timestep

Base case: 1 Newton iteration per timestep

Reduce timestep by 3

Double # of zones

S. Jardin / L. P. Ku


Results for a 500s iter run

Results for a 500s ITER run:

ions

electrons

Chi Values for entire run

Chi vs radius at 250s

ions

electrons

Profiles at 250s

Powers vs time

S. Jardin / L. P. Ku


Ptransp progress 1

PTRANSP Progress - 1

  • Predictive Solver Improvement (as shown).

    • Both FSP solver and GCNM at GA.

  • TRANSP Improvements:

    • Export of source calculation results.

    • Accommodation of free boundary equilibrium.

    • Modification of internal loop structure to allow import of stiff transport solver results.

  • Trdatbuf_lib NTCC module– access to TRANSP input data (experimental data).


Ptransp progress 2

PTRANSP Progress - 2

  • LLNL’s TEQ free boundary solver module in TRANSP.

    • NTCC module standards with error handling enhancement.

    • Time dependent NSTX test results look good.

  • UEDGE/TRANSP coupling:

    • LLNL design and prototype in place.

    • Includes TRANSP/UEDGE data exchange schema.


Ptransp progress 3

PTRANSP Progress - 3

  • NTCC PEDESTAL module– predictive boundary condition option.

    • Lehigh University team making direct modifications to TRANSP (in progress).

    • Prototype installation in BALDUR.

    • Experience with L to H transition dynamics.


Ptransp s next step aps

PTRANSP’s Next Step – APS

  • Drive TRANSP with ITER free boundary simulation:

    • TRANSP provides heating and current drive.

    • TRANSP uses free boundary simulation predicted temperatures and equilibria.

      • Architecture compatible with density prediction but testing of this capability likely to be postponed.

    • TRANSP archive produced:

      • Available as input to UEDGE, linear stability solvers, etc.


Summary

Summary

  • The PTRANSP project will provide a community predictive transport code with state-of-the-art capabilities.

  • Like TRANSP itself, it will run as a Fusion Grid production service with world wide access.

  • Control options will be provided for prescribed boundary or free boundary operation.

  • Example of integrated ITER simulation with realistic sources by APS-2006.


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