Heavy Duty Gas Turbine Simulation: Global Performances Estimation and Secondary Air System Modifications

Carcasci, Carlo; Facchini, Bruno; Gori, Stefano; Bozzi, Luca; Traverso, Stefano

doi:10.1115/gt2006-90905

Cited by 9 publications

(3 citation statements)

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“…Many scholars have modeled and analyzed the whole secondary air system, considering each of its elements as a "black box" and establishing the connections among them. The network of the secondary air system is drawn, and the conditions of each element during different phases are predicted using analysis codes (e.g., ESMS) [10][11][12]. However, unlike those simplified quasi-one-dimensional models, the flow within the compressor bleed system is strongly three-dimensional and the different parts interact with each other.…”

Section: Introductionmentioning

confidence: 99%

Effects of Geometry of Plenum Chamber on Losses in the Bleed System of an Axial Compressor

Shi

Kong

Jia

2022

International Journal of Aerospace Engineering

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To study how the geometry of the plenum chamber in the bleed system of an axial compressor influences the losses therein and to establish a theoretical loss model for this system, a 1.5-stage axial compressor with a bleed system is studied numerically by means of computational fluid dynamics (CFD). The results show that losses in the bleed system occur mainly in the axisymmetric bleed slot and plenum chamber, accounting for ca. 85% of the total loss. For a bleed system with a vertical axisymmetric slot, the loss is more sensitive to the radial height than to the axial width of the plenum chamber. A loss model for each part of the bleed system is established via theoretical analysis, and then, a model of the overall bleed system is established by combining these submodels. The predictions of the theoretical loss model agree well with the CFD results: the maximum prediction error for the coefficient of the stagnation pressure loss in the bleed system is −1.38%, and the average prediction error is −0.8%. This loss model can be used when designing the geometry of a bleed system.

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Section: Introductionmentioning

confidence: 99%

Effects of Geometry of Plenum Chamber on Losses in the Bleed System of an Axial Compressor

Shi

Kong

Jia

2022

International Journal of Aerospace Engineering

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“…Their approach was able to be integrated directly in whole engine cycle performance model. Some others tried to couple SAS simulation and coolant calculation by matching the characteristic curves of secondary air circuit and the flow function of the blade cooling network to define the working point of the system [6]. As a result, it would be possible to investigate the effects of new design solutions on internal air system and on overall cycle performance [6].…”

Section: Introductionmentioning

confidence: 99%

“…Some others tried to couple SAS simulation and coolant calculation by matching the characteristic curves of secondary air circuit and the flow function of the blade cooling network to define the working point of the system [6]. As a result, it would be possible to investigate the effects of new design solutions on internal air system and on overall cycle performance [6]. Coupling between 1-D blades and vanes cooling flow codes in Matlab as well as 1-D cavity solver with overall SAS fluid network is another challenging area that covered by [7] and [8].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Approach to Simulate Gas Turbine Secondary Air System

Izadi¹,

Hosseini²,

Madani³

et al. 2021

Preprint

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One of the most critical parts of a modern gas turbine that its reliability and performance has a great influence on cycle efficiency is the secondary air system (SAS). Modern systems functions to supply not only cooling airflow for turbine blades and vanes but sealing flow for bearing chambers and turbine segments as well as turbine disks' purge flow in order to eliminate hot gas ingestion. Due to the various interactions between SAS and main gas, consideration of the former is substantially crucial in design and analysis of the whole engine. Geometrical complexities and centrifugal effects of rotating blades and disks, however, make the flow field and heat transfer of the problem so complicated AND too computationally costly to be simulated utilizing full 3-D CFD methods. Therefore, developing 1-D and 0-D tools applying network methods are of great interests.The present article describes a modular SAS analysis tool that is consisted of a network of elements and nodes. Each flow branch of a whole engine SAS network is substituted with an element and then, various branches (elements) intersect with each other just at their end nodes. These elements which might include some typical components such as labyrinth seals, orifices, stationary/rotating pipes, pre-swirls, and rim-seals, are generally articulated with characteristic curves that are extracted from high fidelity CFD modeling using commercial software such as Flowmaster or ANSYS-CFX. Having these curves, an algorithm is developed to calculate flow parameters at nodes with the aid of iterative methods.The procedure is based on three main innovative ideas. The first one is related to the network construction by defining a connectivity matrix which could be applied to any arbitrary network such as hydraulic or lubrication networks. In the second one, off-design SAS calculation will be proposed by introducing some SAS elements that their characteristic non-dimensional curves are influenced by their inlet total pressure. The last novelty is the integration of the blades coolant calculation process that incorporates external heat transfer calculation, structural conduction and coolant side modelling with SAS network simulation. Finally, SAS simulation of an industrial gas turbine is presented to illustrate the capabilities of the presented tool in design point and off-design conditions. NOMENCLATURE𝐶𝐶 𝑝𝑝 Specific heat capacity at constant pressure [kJ/kg℃] 𝐻𝐻 Specific Enthalpy [kJ/kg] ℎ 𝑐𝑐 Coolant heat transfer coefficient [W/m 2 K] 𝐾𝐾 Flow function = ṁ/Δp, Thermal conductivity ṁ Mass Flow Rate [kg/s] 𝑁𝑁 Gas turbine rotational speed [𝑟𝑟𝑟𝑟𝑟𝑟] 𝑃𝑃 Pressure [Pa] 𝑃𝑃𝑟𝑟 Pressure Ratio = P o, Out /P o, In Q ̇ Heat Flux [W/m^2] 𝑇𝑇 Temperature [K] 𝜂𝜂 Cooling efficiency 𝜀𝜀 Cooling effectiveness 𝛽𝛽 Non-dimensional coolant mass flow parameter Subscripts: 𝑏𝑏 Blade, vane or metal 𝑐𝑐, 𝑐𝑐𝑐𝑐 Coolant, Coolant side 𝐶𝐶𝐶𝐶/ 𝐶𝐶𝐶𝐶 Coolant Inlet/ Coolant Outlet 𝐺𝐺 Gas side

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Simulation of the secondary air system of turbofan engines: Insights from 1D-3D modeling

Yang

Jian

Dong

et al. 2023

Chinese Journal of Aeronautics

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Heavy Duty Gas Turbine Simulation: Global Performances Estimation and Secondary Air System Modifications

Cited by 9 publications

References 0 publications

Effects of Geometry of Plenum Chamber on Losses in the Bleed System of an Axial Compressor

Effects of Geometry of Plenum Chamber on Losses in the Bleed System of an Axial Compressor

An Integrated Approach to Simulate Gas Turbine Secondary Air System

Simulation of the secondary air system of turbofan engines: Insights from 1D-3D modeling

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