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.
文摘目的:建立一个列线图来预测男性鼻咽鳞状细胞癌患者的生存率。方法:从SEER数据库下载和提取2010—2015年男性鼻咽鳞状细胞癌患者的临床资料,随机分为建模组(811例)和验证组(363例),最小绝对值选择与收缩算子(Least absolute shrinkage and selection operator,LASSO)回归对自变量进行筛选,采用Cox竞争风险模型进行多因素分析,构建列线图预测男性鼻咽鳞状细胞癌患者1年、3年、5年的生存率,采用一致性指数(C-index)、校准曲线、受试者工作特征曲线下面积(Area under a receiver operating characteristic curve,AUC)评估模型的区分度及准确度,临床决策曲线评估模型的临床实用价值,根据构建的模型,计算出模型的风险评分,以中位数水平将样本分为高风险组及低风险组,比较高风险组及低风险组生存率。结果:共纳入1 174例患者,建模组(n=811)和验证组(n=363)。经LASSO回归和Cox回归分析表明,T分期、M分期、年龄、脑转移、肝转移、肺转移是男性鼻咽鳞状细胞癌独立危险因素。建模组和验证组的C-index分别为0.676(95%CI:0.642~0.701)和0.668(95%CI:0.619~0.717)。建模组和验证组的AUC结果表明,这个列线图具有很高的准确性。校准曲线显示观察值与预测值高度一致,证明成功构建了预后模型。在建模组和验证组中,高风险组与低风险组的生存率差异均有统计学意义(P<0.000 1)。结论:T分期、M分期、年龄、脑转移、肝转移、肺转移是男性鼻咽鳞状细胞癌患者生存独立的预后因素。该模型有助于指导临床医师做出治疗方案的选择,延长患者生存率。
