To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stabil...To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stability,this study introduces a‘Dynamic Event-Driven Co-Simulation’algorithm integrated with decision tree algorithms.This algorithm separates the overall coupling relationships and the main solver from the primary mod⁃el,utilizing a dynamic event monitoring module to adaptively adjust simulation strategies,including iteration pa⁃rameters,coupling relationships,and convergence criteria.This facilitates efficient adaptive simulations of dy⁃namic events while balancing solution accuracy and computational efficiency.The research focuses on a twinshaft turbofan engine,establishing six system-level models that encompass overall performance and various sub⁃systems based on three coupling methods,along with a multidisciplinary multi-fidelity simulation framework in⁃corporating a 3D CFD nozzle model.The study tests both model exchange and coupled simulation methods under a 14 s transient acceleration and deceleration scenario.In a 100%throttle condition,a high-fidelity nozzle model is used to analyze the sensitivity of different convergence criteria on computational efficiency and accuracy.Re⁃sults indicate that the accuracy and efficiency achieved with this method are comparable to those of PROOSIS soft⁃ware(18 s and 35 s,respectively),while being 71%more efficient than Simulink software(62 s and 120 s,re⁃spectively).Furthermore,appropriately relaxing the convergence criteria for the 0D model(from 10-6 to 10-4)while enhancing those for the 3D model(from 3000 steps to 6000 steps)can effectively balance computational accuracy and efficiency.展开更多
文摘To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stability,this study introduces a‘Dynamic Event-Driven Co-Simulation’algorithm integrated with decision tree algorithms.This algorithm separates the overall coupling relationships and the main solver from the primary mod⁃el,utilizing a dynamic event monitoring module to adaptively adjust simulation strategies,including iteration pa⁃rameters,coupling relationships,and convergence criteria.This facilitates efficient adaptive simulations of dy⁃namic events while balancing solution accuracy and computational efficiency.The research focuses on a twinshaft turbofan engine,establishing six system-level models that encompass overall performance and various sub⁃systems based on three coupling methods,along with a multidisciplinary multi-fidelity simulation framework in⁃corporating a 3D CFD nozzle model.The study tests both model exchange and coupled simulation methods under a 14 s transient acceleration and deceleration scenario.In a 100%throttle condition,a high-fidelity nozzle model is used to analyze the sensitivity of different convergence criteria on computational efficiency and accuracy.Re⁃sults indicate that the accuracy and efficiency achieved with this method are comparable to those of PROOSIS soft⁃ware(18 s and 35 s,respectively),while being 71%more efficient than Simulink software(62 s and 120 s,re⁃spectively).Furthermore,appropriately relaxing the convergence criteria for the 0D model(from 10-6 to 10-4)while enhancing those for the 3D model(from 3000 steps to 6000 steps)can effectively balance computational accuracy and efficiency.
