Development of a Throughflow-Based Simulation Tool for Preliminary Compressor Design Considering Blade Geometry in Gas Turbine Engine

Liu, Xiaoheng; Wan, Ke; Jin, Donghai; Gui, Xingmin

doi:10.3390/app11010422

Cited by 12 publications

(4 citation statements)

References 18 publications

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“…In order to further evaluate the ability of FLAS to solve real-world applications, FLAS is compared with other well-performing MAs on many different engineering design problems. Two types of optimization problems are selected: (1) Box-constrained problems have only unique constraints on the upper and lower bounds of the variables, including gear transmission system design [44], and gas transmission compressor design [45]. (2) General-constrained problems have more complex constraints and include reducer design [46], three-bar truss design [47], piston rod optimization design [48], pressure vessel design [49], and stepped cone pulley problem [50].…”

Section: Engineering Examplesmentioning

confidence: 99%

Multi-Strategy Boosted Fick’s Law Algorithm for Engineering Optimization Problems and Parameter Estimation

Yan,

Hu,

Zhang

2024

Biomimetics

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To address the shortcomings of the recently proposed Fick’s Law Algorithm, which is prone to local convergence and poor convergence efficiency, we propose a multi-strategy improved Fick’s Law Algorithm (FLAS). The method combines multiple effective strategies, including differential mutation strategy, Gaussian local mutation strategy, interweaving-based comprehensive learning strategy, and seagull update strategy. First, the differential variation strategy is added in the search phase to increase the randomness and expand the search degree of space. Second, by introducing the Gaussian local variation, the search diversity is increased, and the exploration capability and convergence efficiency are further improved. Further, a comprehensive learning strategy that simultaneously updates multiple individual parameters is introduced to improve search diversity and shorten the running time. Finally, the stability of the update is improved by adding a global search mechanism to balance the distribution of molecules on both sides during seagull updates. To test the competitiveness of the algorithms, the exploration and exploitation capability of the proposed FLAS is validated on 23 benchmark functions, and CEC2020 tests. FLAS is compared with other algorithms in seven engineering optimizations such as a reducer, three-bar truss, gear transmission system, piston rod optimization, gas transmission compressor, pressure vessel, and stepped cone pulley. The experimental results verify that FLAS can effectively optimize conventional engineering optimization problems. Finally, the engineering applicability of the FLAS algorithm is further highlighted by analyzing the results of parameter estimation for the solar PV model.

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Section: Engineering Examplesmentioning

confidence: 99%

Multi-Strategy Boosted Fick’s Law Algorithm for Engineering Optimization Problems and Parameter Estimation

Yan,

Hu,

Zhang

2024

Biomimetics

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“…Studies have shown that the S-A model is an excellent engineering tool for predicting turbulence characteristics. NUMECA's solver is FINE/Turbo, which is based on the element-centric finite volume method and is associated with Jameson's central scheme as spatial discretization and the explicit Runge-Kutta time integration method [13]. The mass flow, velocity In order to effectively capture complex 3D flow patterns in the flow channel, HO topology is used in the rotor channel.…”

Section: Numerical Modelmentioning

confidence: 99%

Flow Characteristics and Loss Models of the Transonic Radial Turbine

2022

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A hydrogen turbo hybrid power system has the significant advantages of zero carbon emissions, high efficiency and high reliability. The need to increase the power density of hydrogen turbo hybrid power systems and improve the adaptability of turbines over a wide range of expansion ratios has encouraged the study of transonic turbines. This paper is aimed at analyzing the flow characteristics and developing the loss models of a transonic turbine. The main losses for a subsonic radial turbine are usually divided into four parts: incidence loss, passage loss, tip clearance loss and trailing edge loss. Nevertheless, when the expansion ratio of a turbine is greater than about 2.6, the turbine will choke and work in transonic conditions. A shock wave will occur at the trailing edge, which will cause a lot of losses. The loss caused by the shock wave at the trailing edge is ignored by previous loss models. This paper develops a shock wave-induced loss model to predict the performance in transonic conditions more accurately. With the developed shock wave-induced loss model, the predicted efficiency deviation in transonic conditions decreases from 10% to 3.5% maximally.

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“…A time-marching finite volume method is chosen to solve equations. The validation of CAM by NASA Rotor 67 and a high-loaded low speed fan TA36 can be found in references [31,32]. More details for CAM can also be reviewed in references [33,34].…”

Section: Numerical Model and Research Objectmentioning

confidence: 99%

Investigation of Seal Cavity Leakage Flow Effect on Multistage Axial Compressor Aerodynamic Performance with a Circumferentially Averaged Method

Jin

Gui

2021

Applied Sciences

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The seal cavity leakage flow has a considerable impact on the performance of the aeroengine, especially on the multistage compressor. Thus, a quasi-three-dimensional simulation program named CAM is developed basing on circumferentially averaged throughflow method. The program enables a rapid diagnosis for the performance degradation of multistage compressor caused by labyrinth wear. The coupling flow field between the seal cavity leakage flow and the main flow field at the root of the shrouded stator of a high-loading three-stage compressor with inlet guide vanes (IGV) was simulated by CAM and the results indicate that seal cavity leakage flow has a significant impact on the overall performance of the compressor. That is, for a 1% increase in the seal-tooth clearance-to-span ratio, the decrease in total pressure ratio was 2.6%, and the reduction in efficiency was 0.6%. Stage performance shows that the seal cavity leakage flow reduces the pressurization capacity of the current stator and the work capacity of the downstream rotor, but has little effect on the upstream blade row. Spanwise distribution of blade element performance shows that the leakage flow leads to an increased flow blockage near the hub, resulting in spanwise migration. The incidence of the stator and rear rotor then change through the entire span. The leakage flow leads to the flow blockage and migration and hence changes the incidence angle, which results in the deterioration of compressor performance.

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Development of a Throughflow-Based Simulation Tool for Preliminary Compressor Design Considering Blade Geometry in Gas Turbine Engine

Cited by 12 publications

References 18 publications

Multi-Strategy Boosted Fick’s Law Algorithm for Engineering Optimization Problems and Parameter Estimation

Multi-Strategy Boosted Fick’s Law Algorithm for Engineering Optimization Problems and Parameter Estimation

Flow Characteristics and Loss Models of the Transonic Radial Turbine

Investigation of Seal Cavity Leakage Flow Effect on Multistage Axial Compressor Aerodynamic Performance with a Circumferentially Averaged Method

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