Incorporating Ion Temperature Measurements In the EPED Validation Database at DIII-D Tokamak

Accurate predictions of edge pressure behavior of high confinement mode (H-Mode) plasma are necessary to optimize tokamak performance. This research expands past research efforts by incorporating ion temperature measurements into a database of measured pedestal structure parameters from the DIII-D tokamak, which enables an experimental validation of pedestal structure predictions from the neural net version of the EPED model. Utilizing the one modeling framework for integrated tasks (OMFIT), we started with the TokSearch program to initialize a database that incorporates thousands of DIII-D shots before filtering to eliminate discharges with missing key values. The remaining shots are then sliced into 200 millisecond time intervals and filtered again to detect edge localized mode (ELM) instabilities. EPED then predicts the pedestal profile structure prior to the ELM onset. Through the inclusion of ion temperatures, we seek to better represent low collisionality plasmas by eliminating a previous assumption of equilibrated particle temperatures not seen in such conditions. The incorporation of ion temperature was successful and better agreement between experimental and predicted results was seen most notably in pressure where experimental values tended to increase with better representation of the full plasma operational space of DIII-D.