建模者
计算机科学
解算器
涡轮机
网络微积分
稳健性(进化)
气体压缩机
工作流程
转子(电动)
控制工程
机械工程
工程类
数据库
计算机网络
生物化学
化学
酶
服务质量
同源建模
基因
程序设计语言
作者
Davendu Kulkarni,Luca di Mare
出处
期刊:Journal of the Royal Aeronautical Society
[Cambridge University Press]
日期:2023-08-29
卷期号:127 (1317): 1993-2022
摘要
Abstract The complex and iterative workflow for designing the secondary air system (SAS) of a gas turbine engine still largely depends on human expertise and hence requires long lead times and incurs high design time-cost. This paper proposes an automated methodology to generate the whole-engine SAS flow network model from the engine geometry model and presents a convenient and inter-operable framework of the secondary air system modeller. The SAS modeller transforms the SAS cavities and flow paths into a 1D flow network model composed of nodes and links. The novel, object-oriented pre-processor embedded in the SAS modeller automatically assembles the conservation equations for all flow nodes and the loss correlations for all links. The twin-level, hierarchical SAS solver then solves the conservation equations of mass, momentum and energy supplemented with the correlations in the loss model library. The modelling swiftness, mathematical robustness and numerical stability of the present methodology are demonstrated through the results obtained from IP compressor rotor drum flow network model.
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