{'fraction_non_alphanumeric': 0.013832384052074858, 'fraction_numerical': 0.0008136696501220504, 'mean_word_length': 5.275510204081633, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Understanding control in microchannels to manipulate drop-drop interactions

Recently we proposed a simple, computationally inexpensive multi-agent simulation strategy to understand drop movement in a microchannel with Hele-Shaw flow geometry (2D). This has helped us understand the collective behavior of the drops in these systems. However, transitioning these systems to practice would require that strategies are developed to combat the inherent fluctuations that are a part of any physical system. In the present work we utilize the simulation strategy for understanding the impact of design choices in minimizing the effect of uncertainties, and the sensitivity of the device behavior to operational variables that can potentially be used as controlled variables. We study a control metric, time of contact, which is defined as the time spent by a drop in the microchannel when its distance from its neighboring drops is less than some critical value. By simplifying the model further we are able to analyze the contact time dynamics as a function of geometric parameters and operating conditions analytically. We also carry out the complete numerical simulation of our models to understand active control of drop clusters.