📝 SummarXiv

Abstract

We present the results of models of impulsively heated coronal loops using the 1-D hydrodynamic Adaptively Refined Godunov Solver (ARGOS) code. The impulsive heating events (which we refer to as "nanoflares") are modeled by discrete pulses of energy along the loop. We explore the occurrence of cold condensations due to the effective equivalent of thermal non-equilibrium (TNE) in loops with steady heating, and examine its dependence on nanoflare timing and intensity and also nanoflare location along the loop, including randomized distributions of nanoflares. We find that randomizing nanoflare distributions, both in time/intensity and location, diminishes the likelihood of condensations as compared to distributions with regularly occurring nanoflares with the same average properties. The usual criteria that condensations are favored for heating near loop footpoints and with high cadences are more strict for randomized (as opposed to regular) nanoflare distributions, and for randomized distributions the condensations stay in the loop for a shorter amount of time. That said, condensations can sometimes occur in cases where the average values of parameters (frequency or location) are beyond the critical limits above which condensations do not occur for corresponding steady, non-randomized values of those parameters. These properties of condensations occurring due to randomized heating can be used in the future to investigate diagnostics of coronal heating mechanisms.