Virtual Gas Turbines: A novel flow network solver formulation for the automated design-analysis of secondary air system

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...

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Bibliographic Details
Published inAeronautical journal Vol. 127; no. 1317; pp. 1993 - 2022
Main Authors Kulkarni, D.Y., di Mare, L.
Format Journal Article
LanguageEnglish
Published London Cambridge University Press 01.11.2023
Subjects
Automation
CAD
Compressor rotors
Computer aided design
Conservation equations
Cooling
Energy consumption
Flow paths
Gas turbine engines
Geometry
Human error
Iterative methods
Mathematical models
Microprocessors
Nodes
Numerical stability
Process controls
Robustness (mathematics)
Simulation
Solvers
Temperature
User interface
Variables
Velocity
Virtual gases
Workflow
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Summary: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.
ISSN:0001-9240
2059-6464
DOI:10.1017/aer.2023.70