Cross-machine assessment of real-time boronization by solid boron injection

Experiments in tokamaks (ASDEX-Upgrade, DIII-D, EAST, KSTAR, WEST) and stellarators (LHD, W7-X), have demonstrated solid B injection as a means of coating plasma facing components and improving plasma operation. However, a quantitative prediction of the amount of B required for wall conditioning on a next-step fusion device such as ITER or a Fusion Power Plant (FPP) remains elusive. We present a multi-machine dataset focusing on the improvements observed in various wall conditions figures of merit (FOM), such as O or W concentration. Since FOM improvements tend to develop as exponential decays as a function of the cumulative mass of injected B, they can be captured by the characteristic e-folding mass µ_B, i.e. the mass of B sufficient to change the FOM by a factor of e. A database of experimental values of µB is built to assess its dependence on machine operation parameters, such as PFC surface, plasma wetted area, auxiliary power, plasma volume, etc. Through regression analysis, the dependence is expressed as a power law scaling, allowing for prediction of the minimal cumulative mass of B required to maximize the improvement on a given FOM. Estimates for the relevant cases of ITER and a compact FPP device will be discussed.