Multidisciplinary design optimization of long-range slender guided rockets considering aeroelasticity and subsidiary loads

Wei, Zhao; Li, Teng; Shi, Renhe; Tang, Yifan; Li, Huaijian

doi:10.1016/j.ast.2019.06.039

Cited by 9 publications

(2 citation statements)

References 28 publications

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“…With the increasingly complex operational requirements, the pump design has to meet higher design requirements [25][26][27]. A multi-disciplinary design optimization [28] method can combine hydraulic design and structural design, so that it can get the optimized impeller to match the complex operating conditions. This present study solved some key technical problems in the MDO process of the axial-flow impeller.…”

Section: Discussionmentioning

confidence: 99%

Multi-Disciplinary Optimization Design of Axial-Flow Pump Impellers Based on the Approximation Model

et al. 2020

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This study adopts a multi-disciplinary optimization design method based on an approximation model to improve the comprehensive performance of axial-flow pump impellers and fully consider the interaction and mutual influences of the hydraulic and structural designs. The lightweight research on axial-flow pump impellers takes the blade mass and efficiency of the design condition as the objective functions and the head, efficiency, maximum stress value, and maximum deformation value under small flow condition as constraints. In the optimization process, the head of the design condition remains unchanged or varies in a small range. Results show that the mass of a single blade was reduced from 0.947 to 0.848 kg, reaching a decrease of 10.47%, and the efficiency of the design condition increased from 93.91% to 94.49%, with an increase rate of 0.61%. Accordingly, the optimization effect was evident. In addition, the error between the approximate model results and calculation results of each response was within 0.5%, except for the maximum stress value. This outcome shows that the accuracy of the approximate model was high, and the analysis result is reliable. The results provide guidance for the optimal design of axial-flow pump impellers.

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Section: Discussionmentioning

confidence: 99%

Multi-Disciplinary Optimization Design of Axial-Flow Pump Impellers Based on the Approximation Model

et al. 2020

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“…Multidisciplinary optimization technology is commonly used in turbo-machinery with compressor, airfoil and turbine working medium as compressible fluid. [14][15][16][17][18][19][20][21][22][23][24] For example, Li et al 14 used multidisciplinary optimization design software to optimize the aerodynamic performance of a wind turbine airfoil. After optimization, the lift-drag ratio of the airfoil was increased by 15.9%.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of blade in pump as turbine based on multidisciplinary feasible method

Miao

Hong-Biao

Wang³

et al. 2020

Science Progress

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In order to make the pump as turbine (PAT) run efficiently and safely, a multidisciplinary optimization design method for PAT blade, which gives consideration to both the hydraulic and intensity performances, is proposed based on multidisciplinary feasibility (MDF) optimization strategy. This method includes blade parametric design, Latin Hypercube Sampling (LHS) experimental design, CFD technology, FEA technology, GA-BP neural network and NSGA-II algorithm. Specifically, a parameterized PAT blade with cubic non-uniform B-spline curve is adopted, and the control point of blade geometry is taken as the design variable. The LHS experimental design method obtains the sample points of training GA-BP neural network in the design space of variables. The hydraulic performance of each sample point (including the hydraulic pressure load on the blade surface) and the strength performance analysis of blades are completed by CFD and FEA technology respectively. In order to save calculation time of the whole optimization design, the multi-disciplinary performance analysis of each sample in the optimization process is completed by single-coupling method. Then, GA-BP neural network is trained. Finally, the multi-disciplinary optimization design problem of PAT blade is solved by the optimization technology combining GA-BP neural network and NSGA-II algorithm. Based on this optimization method, the PAT blade is optimized and improved. The efficiency of the optimized PAT is improved by 1.71% and the maximum static stress on the blade is reduced by 7.98%, which shows that this method is feasible.

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Multistage rocket preliminary design and trajectory optimization using a multidisciplinary approach

Morgado

Marta

Gil

2022

Struct Multidisc Optim

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Multidisciplinary design optimization of long-range slender guided rockets considering aeroelasticity and subsidiary loads

Cited by 9 publications

References 28 publications

Multi-Disciplinary Optimization Design of Axial-Flow Pump Impellers Based on the Approximation Model

Multi-Disciplinary Optimization Design of Axial-Flow Pump Impellers Based on the Approximation Model

Optimal design of blade in pump as turbine based on multidisciplinary feasible method

Multistage rocket preliminary design and trajectory optimization using a multidisciplinary approach

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