A parameterized learning method based on data-driven and physical constraints for solving the fluid model of low-temperature plasma
Low-temperature plasma (LTP) plays an indispensable role in environmental remediation and energy conversion. Rapid prediction of state parameters in LTP is crucial for enhancing both pollutant degradation efficiency and fuel conversion performance. To address the high computational cost of traditional numerical methods...