Intelligent prediction of gas-liquid two-phase flow fields in jet impact negative pressure reactors: An integrated DA-WOA-CNN framework based on CFD

Key Points

• Gas-liquid flow dynamics are effectively predicted using a novel DA-WOA-CNN framework.
• The model demonstrates an accuracy improvement by up to 25% compared to traditional methods in predicting flow fields.
• Assessment using computational fluid dynamics (CFD) to validate the new integrated prediction framework.
• This approach may enhance reactor efficiency, although further experimental validation is necessary.