3 papers
eess.IV2026
Deep Learning-Based Characterization of Detonation-Cell Size Distributions in Soot-Foil Records
Mingyang Bu, Robson A. Schneider, Karl P. Chatelain +5
The geometric size and regularity of detonation cells are key physical parameters for characterizing detonation waves. Traditional manual measurement of soot foils is time-consumin…
physics.plasm-ph2026
An Interpretable Operator-Learning Model for Electric Field Profile Reconstruction in Discharges Based on the EFISH Method
Zhijian Yang, Edwin Setiadi Sugeng, Mhedine Alicherif +1
Machine learning (ML) models have recently been used to reconstruct electric field distributions from EFISH signal profiles-the 'inverse EFISH problem'. This addresses the line-of-…
physics.plasm-ph2026
Toward Quantitative Electric-Field Measurements of Inception Clouds in Nanosecond Discharges Using E-FISH Assisted by Machine Learning
Mhedine Alicherif, Edwin Sugeng, Zhijan Yang +2
This study investigates the spatio-temporal evolution of the electric field during the early stages of a nanosecond positive corona discharge in atmospheric-pressure air by combini…