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A newly developed sensitivity-driven approach is employed to study the roleof energetic particles in suppressing turbulence-inducing micro-instabilitiesfor a set of realistic JET-like cases with NBI deuterium and ICRH $^3$He fastions. First, the efficiency of the sensitivity-driven approach is showcased forscans in a $21$-dimensional parameter space, for which only $250$ simulationsare necessary. The same scan performed with traditional Cartesian grids withonly two points in each of the $21$ dimensions would require $2^{21} =2,097,152$ simulations. Then, a $14$-dimensional parameter subspace isconsidered, using the sensitivity-driven approach to find an approximation ofthe parameter-to-growth rate map averaged over nine bi-normal wave-numbers,indicating pathways towards turbulence suppression. The respective turbulentfluxes, obtained via nonlinear simulations for the optimized set of parameters,are reduced by more than two order of magnitude compared to the referenceresults.

Turbulence suppression by energetic particles: A sensitivity-driven dimension-adaptive sparse grid framework for discharge optimization