Data re-use for preliminary thermal-mechanical design of gas turbine engines

Gan, Lu; Wang, Feng; Mare, Luca di; Moss, Mike; May, Gordon

doi:10.1017/aer.2017.137

Cited by 6 publications

(2 citation statements)

References 34 publications

(49 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…9 Therefore, a coupling model is needed to analyze the turbofan engine as a robust design for the whole engine requires several runs to account for variations in boundary conditions. 10 Some papers have investigated mutual interactions utilizing 3D finite element approaches. Wu et al 11 applied a 1D-3D coupled model to simulate a SAS whereby a 1D code was used to model the standard components with regular geometric characteristics, and a finite element code was used to compute the nonstandard components.…”

Section: Introductionmentioning

confidence: 99%

Turbofan engine performance prediction methodology integrated high-fidelity secondary air system models

Yang

Jian

Dong

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

This research studies the performance of an ultra-high bypass ratio turbofan engine, and specifically its secondary air system (SAS). A co-simulation methodology is explored whereby a high-fidelity SAS model and an engine performance code featuring flexible modules can be coupled and interactively executed. The percentage of bleed flows and boundary conditions for the SAS are updated at each iteration step. For this purpose, a SAS model including different elements is developed. Furthermore, a commercial computational fluid dynamics (CFD) solver is adopted to capture the complex flow field in the pre-swirl system. The credibility of cycle calculation and SAS elements is validated by comparing with publicly available data. Subsequently, an elaborately designed SAS is modeled and co-simulated with the AGTF30 engine using a flow network simulation method. The coupling effect between the engine performance and the SAS is studied for eight different flight conditions. The correlation and prediction of engine performance due to seal clearance change is presented. The co-simulation approach clarifies the mutual interactions between the engine overall parameters and the SAS. The results reveal that the enhanced flow network model can improve the simulation accuracy of engine performance over a wide range of operating conditions.

show abstract

Section: Introductionmentioning

confidence: 99%

Turbofan engine performance prediction methodology integrated high-fidelity secondary air system models

Yang

Jian

Dong

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

show abstract

“…This allows the fan to run at a lower rotational speed and to decrease the number of compressor and turbine blades and stages, reducing the fuel consumption and noise emissions. Finally, by decreasing the rotational speed of the fan, the blades tip speed decreases, which in turn reduces the appearance of shock [2]. This effect allows the fan blade diameter and therefore the bypass ratio, to increase even more.…”

Section: Introductionmentioning

confidence: 99%

Physics-Based Thermal Model for Power Gearboxes in Geared Turbofan Engines

Jafari

Nikolaidis

Heerden

et al. 2020

Volume 1: Aircraft Engine; Fans and Blowers

View full text Add to dashboard Cite

Ultra-High Bypass Ratio Geared (UHBRG) turbofan technology allows a significant reduction in fuel burn, noise and emissions — key metrics for aircraft engine performance. However, one of the main challenges in this technology is the large amount of waste heat generated by the Power Gearbox (PGB). Therefore, having a practical tool for precise prediction of the PGB-generated thermal loads in UHBRGs is becoming a necessity. Such a tool would assist in analyzing engine performance, as well as ensuring that engine physical limitations/restrictions are not breached (e.g. over-temperature in fuel and oil, cocking, etc.). This paper presents a methodological approach to mathematically model the waste heat generated by a PGB on a UHBRG for different points on a typical flight profile. To do this, the total power loss in a PGB system is firstly defined as the summation of load-dependent and load-independent losses. Physics-based equations for each heat loss mechanism are introduced and, through a combination of the associated equations, a simulation model for the thermal loads calculation in PGBs is developed. In addition, the heat losses and efficiency of the PGB has been analyzed across a simulated flight. The developed PGB model calculates the main power losses generated in a gear reduction system of a turbofan engine. It is found that in a typical flight, the heat loss generated by the PGB can reach about 80% of the total waste heat generated by the engine. The values of the mechanical efficiency calculated by the tool at different flight points are above 97% which is in good agreement with publicly available data for planetary gearboxes. This tool is intended to be utilized by engine thermal management system designers to predict and analyze the heat loads generated by the PGB at different flight conditions.

show abstract

Virtual Gas Turbines Part I: A Top-Down Geometry Modeling Environment for Turbomachinery Application

Kulkarni

Liu

Wang

et al. 2021

Journal of Engineering for Gas Turbines and Power

View full text Add to dashboard Cite

The gas turbine engine design involves multi-disciplinary, multi-fidelity iterative design-analysis processes. These highly intertwined processes are nowadays incorporated in automated design frameworks to facilitate high-fidelity, fully coupled, large-scale simulations. The most tedious and time-consuming step in such simulations is the construction of a common geometry database that ensures geometry consistency at every step of the design iteration, is accessible to multi-disciplinary solvers and allows system-level analysis. This paper presents a novel design-intent-driven geometry modelling environment that is based on a top-down feature-based geometry model generation method. The geometry features in this modelling environment are organised in a turbomachinery feature taxonomy. They produce a tree-like logical structure representing the engine geometry, wherein abstract features outline the engine architecture, while lower-level features define the detailed geometry. This top-down flexible feature-tree arrangement enables the design intent to be preserved throughout the design process, allows the design to be modified freely and supports the design intent variations to be propagated throughout the geometry model automatically. The application of the proposed feature-based geometry modelling environment is demonstrated by generating a whole-engine computational geometry model. This geometry modelling environment provides an efficient means of rapidly populating complex turbomachinery assemblies. The generated engine geometry is fully scalable, easily modifiable and is re-usable for generating the geometry models of new engines or their derivatives. This capability also enables fast multi-fidelity simulation and optimisation of various gas turbine systems.

show abstract

Data re-use for preliminary thermal-mechanical design of gas turbine engines

Cited by 6 publications

References 34 publications

Turbofan engine performance prediction methodology integrated high-fidelity secondary air system models

Turbofan engine performance prediction methodology integrated high-fidelity secondary air system models

Physics-Based Thermal Model for Power Gearboxes in Geared Turbofan Engines

Virtual Gas Turbines Part I: A Top-Down Geometry Modeling Environment for Turbomachinery Application

Contact Info

Product

Resources

About