Layout optimization method for core holders in wax pattern mold of hollow turbine blade

In order to conform to the dimensional tolerances of wax pattern die-profile for turbine blade in investment casting process, an optimization method of geometric parameter for turbine blades based on inverse adjustment was proposed. The geometric parameters for optimizing were extracted, and the bending and torsional deformation can be compensation. Therefore the nonlinear deformation compensation during solidification and cooling procedure can be efficiently realized. This method finally exhibits its advantage over the traditional linear scaling method. It set the theoretical foundation on optimization method of die-cavity for turbine blade. The die-profile optimization system which was developed in this paper proves better effect for the die-cavity design.

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A wall-thickness compensation strategy for wax pattern of hollow turbine blade

Chinese Journal of Aeronautics ◽

10.1016/j.cja.2018.08.013 ◽

2019 ◽

Vol 32 (8) ◽

pp. 1982-1993 ◽

Cited By ~ 1

Author(s):

Kang CUI ◽

Wenhu WANG ◽

Ruisong JIANG ◽

Dezhong ZHAO

Keyword(s):

Turbine Blade ◽

Wall Thickness ◽

Compensation Strategy ◽

Hollow Turbine Blade ◽

Wax Pattern

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Wall thickness monitoring method for wax pattern of hollow turbine blade

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-015-7561-9 ◽

2015 ◽

Vol 83 (5-8) ◽

pp. 949-960 ◽

Cited By ~ 13

Author(s):

Rui-song Jiang ◽

Wen-hu Wang ◽

Ding-hua Zhang ◽

Zeng-qiang Wang

Keyword(s):

Turbine Blade ◽

Wall Thickness ◽

Monitoring Method ◽

Hollow Turbine Blade ◽

Wax Pattern

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A Cable Layout Optimization Method for Electronic Systems Based on Ensemble Learning and Improved Differential Evolution Algorithm

IEEE Transactions on Electromagnetic Compatibility ◽

10.1109/temc.2021.3075896 ◽

2021 ◽

pp. 1-10

Author(s):

Xu Yang ◽

Dejian Zhou ◽

Wei Song ◽

Yulai She ◽

Xiaoyong Chen

Keyword(s):

Differential Evolution ◽

Ensemble Learning ◽

Differential Evolution Algorithm ◽

Optimization Method ◽

Layout Optimization ◽

Electronic Systems ◽

Evolution Algorithm ◽

Improved Differential Evolution Algorithm

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Surrogate-Based Optimization of Horizontal Axis Hydrokinetic Turbine Rotor Blades

Energies ◽

10.3390/en14134045 ◽

2021 ◽

Vol 14 (13) ◽

pp. 4045

Author(s):

David Menéndez Arán ◽

Ángel Menéndez

Keyword(s):

Turbine Blade ◽

Design Method ◽

Optimization Method ◽

Turbine Rotor ◽

Computational Effort ◽

Rotor Blades ◽

Linear Functions ◽

Cavitation Inception ◽

Hydrokinetic Turbine ◽

Blade Geometry

A design method was developed for automated, systematic design of hydrokinetic turbine rotor blades. The method coupled a Computational Fluid Dynamics (CFD) solver to estimate the power output of a given turbine with a surrogate-based constrained optimization method. This allowed the characterization of the design space while minimizing the number of analyzed blade geometries and the associated computational effort. An initial blade geometry developed using a lifting line optimization method was selected as the base geometry to generate a turbine blade family by multiplying a series of geometric parameters with corresponding linear functions. A performance database was constructed for the turbine blade family with the CFD solver and used to build the surrogate function. The linear functions were then incorporated into a constrained nonlinear optimization algorithm to solve for the blade geometry with the highest efficiency. A constraint on the minimum pressure on the blade could be set to prevent cavitation inception.

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