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Towards validated multiscale simulations for fusion.

O O Luk1, J Lakhlili1, O Hoenen1

  • 1Max-Planck-Institut für Plasmaphysik, Garching, Germany.

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|March 29, 2021
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Summary
This summary is machine-generated.

Researchers developed a multiscale fusion workflow to model tokamak plasma, using EasyVVUQ for verification, validation, and uncertainty quantification (VVUQ). This ensures simulation accuracy against experimental data for reliable fusion energy research.

Keywords:
fusion plasmamultiscale modellingnuclear fusionuncertainty quantificationvalidation

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Area of Science:

  • Computational plasma physics
  • Nuclear fusion energy research
  • Scientific computing

Background:

  • Thermonuclear fusion offers a clean energy potential but faces significant modeling challenges.
  • Accurate simulation of fusion plasma is crucial for developing viable fusion energy sources.
  • Verification, Validation, and Uncertainty Quantification (VVUQ) are essential for reliable computational models.

Purpose of the Study:

  • To present the Verification, Validation, and Uncertainty Quantification (VVUQ) work conducted on a multiscale fusion workflow (MFW).
  • To demonstrate the application of the EasyVVUQ software library in assessing simulation accuracy.
  • To explore distribution similarity as a validation metric for fusion plasma simulations.

Main Methods:

  • Development of a component-based, multiscale workflow for simulating tokamak plasma.
  • Implementation of the EasyVVUQ software library for VVVUQ processes.
  • Utilizing similarity of distributions between simulation and experimental data as a validation metric.

Main Results:

  • The multiscale fusion workflow (MFW) was successfully coupled with the EasyVVUQ library.
  • Initial validation measures, including distribution similarity, were applied to assess simulation accuracy.
  • The VVVUQ process provided insights into the reliability of the fusion plasma model.

Conclusions:

  • The VVVUQ approach, aided by EasyVVUQ, is vital for ensuring the accuracy and reliability of fusion energy simulations.
  • Distribution similarity serves as a valuable metric for validating simulation results against experimental data.
  • This work contributes to the advancement of trustworthy computational science in fusion energy research.