Weight Reduction Design of Gear Drive Based on Parameter and Structural Optimization

2010 ◽  
Vol 139-141 ◽  
pp. 1406-1410 ◽  
Author(s):  
Ping Wang ◽  
Zhou Lan ◽  
Xiao Yang Shen
Keyword(s):  
Topology Optimization ◽  
Structural Optimization ◽  
Weight Reduction ◽  
Moment Of Inertia ◽  
Design Parameters ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Gear Drive

. For a medium or large-sized gear drive, in order to achieve the optimum weight reduction effect, an approach of weight reduction design is proposed that multi-objective optimization of gear parameters is carried out firstly, and then structural optimization is adopted to design the gear former. The rational design parameters of a gear drive are determined by the multi-objective optimization with minimizing the sum of gear volumes and the equivalent moment of inertia of input shaft (EMI) synchronously. Conceptual design of the former is given by structural topology optimization of the gear, and the reasonability of topology optimization can be demonstrated by static and dynamic analysis. The results indicate that for a double-reduction gearbox of 500KW co-rotating twin screw pulping extruder, the EMI of the gear drive reduces by 20.88% through the multi-objective optimization of gear parameters, and the moment of inertia of a bull gear reduces by 38.86% through structural topology optimization.

Innovative Design, Structural Optimization and Additive Manufacturing of New-Generation Turbine Blades

2021 ◽  
pp. 1-31
Author(s):  
Lorenzo Pinelli ◽  
Andrea Amedei ◽  
Enrico Meli ◽  
Federico Vanti ◽  
Benedetta Romani ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Structural Optimization ◽  
Turbine Blade ◽  
Turbine Blades ◽  
Topological Optimization ◽  
Mode Shapes ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
New Generation

Abstract The need for high performances is pushing the complexity of mechanical design at very high levels, especially for turbomachinery components. Structural topology optimization methods together with additive manufacturing techniques for high resistant alloys are considered very promising tools, but their potentialities have not been deeply investigated yet for critical rotating components like new-generation turbine blades. This research work proposes a methodology for the design, the optimization and the additive manufacturing of extremely stressed turbomachinery components like turbine blade-rows. The presented procedure pays particular attention to important aspects of the problems as fluid-structure interactions and fatigue of materials, going beyond the standard structural optimization approaches found in the literature. The numerical procedure shows robustness and efficiency, making the proposed methodology a good tool for rapid design and prototyping, and for reducing the design costs and the time-to-market typical of these mechanical elements. The procedure has been applied to a low-pressure turbine rotor to improve the aeromechanical behavior while keeping the aerodynamic performance. From the original geometry, mode-shapes, forcing functions and aerodynamic damping have been numerically evaluated and are used as input data for the following topological optimization. Finally, the optimized geometry has been verified in order to confirm the improved aeromechanical design. After the structural topology optimization, the final geometries provided by the procedure have been then properly rendered to make them suitable for additive manufacturing. Some prototypes of the new optimized turbine blade have been manufactured to be tested in terms of fatigue.

Innovative Design, Structural Optimization and Additive Manufacturing of New-Generation Turbine Blades

2020 ◽  
Author(s):  
Andrea Amedei ◽  
Enrico Meli ◽  
Andrea Rindi ◽  
Benedetta Romani ◽  
Lorenzo Pinelli ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Structural Optimization ◽  
Turbine Blade ◽  
Turbine Blades ◽  
Forced Response ◽  
Mode Shapes ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
New Generation

Abstract The need for high performances is pushing the complexity of mechanical design at very high levels, especially for turbomachinery components. In this field, structural topology optimization methods together with additive manufacturing techniques for high resistant alloys are considered very promising tools, but their potentialities have not been deeply investigated yet for critical rotating components like new-generation turbine blades. In this framework, this research work proposes a methodology for the design, the optimization and the additive manufacturing of extremely stressed turbomachinery components like turbine blade-rows. The presented procedure pays particular attention to important aspects of the problems as fluid-structure interactions (forced response and flutter phenomena) and fatigue of materials, going beyond the standard structural optimization approaches found in the literature. The new design strategy enables a substantial reduction of the component mass, limiting the maximum stress and improving the vibrational behaviour of the system in terms of eigenfrequencies, modal shapes and fatigue life. Furthermore, the numerical procedure shows robustness and efficiency, making the proposed methodology a good tool for rapid design and prototyping, and for reducing the design costs and the time-to-market typical of this kind of mechanical elements. The procedure has been applied to a low-pressure turbine rotor to improve the aeromechanical behavior while keeping the aerodynamic performance. From the original geometry, mode-shapes, forcing functions (due to rotor/stator interactions) and aerodynamic damping have been numerically evaluated and are used as input data for the following topological optimization. Finally, the optimized geometry has been verified in order to confirm the improved aeromechanical design. After the structural topology optimization, the final geometries provided by the procedure have been then properly rendered to make them suitable for additive manufacturing. Some prototypes of the new optimized turbine blade have been manufactured from aluminum to be tested mechanically and in terms of fatigue.

scholarly journals Genetic Algorithms As an Approach to Configuration and Topology Design

1993 ◽  
Author(s):  
Colin D. Chapman ◽  
Kazuhiro Saitou ◽  
Mark J. Jakiela
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Structural Optimization ◽  
Optimization Technique ◽  
Topology Design ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Element Analysis ◽  
Structure Topology ◽  
Design Representation

Abstract The Genetic Algorithm, a search and optimization technique based on the theory of natural selection, is applied to problems of structural topology optimization. Given a structure’s boundary conditions and maximum allowable design domain, a discretized design representation is created. Populations of genetic algorithm “chromosomes” are then mapped into the design representation, creating potentially optimal structure topologies. Utilizing genetics-based operators such as crossover and mutation, generations of increasingly-desirable structure topologies are created. In this paper, the use of the genetic algorithm (GA) in structural topology optimization is presented. An overview of the genetic algorithm will describe the genetics-based representations and operators used in a typical genetic algorithm search. After defining topology optimization and its relation to the broader area of structural optimization, a review of previous research in GA-based and non-GA-based structural optimization is provided. The design representations, and methods for mapping genetic algorithm “chromosomes” into structure topology representations, are then detailed. Several examples of genetic algorithm-based structural topology optimization are provided: we address the optimization of beam cross-section topologies and cantilevered plate topologies, and we also investigate efficient techniques for using finite element analysis in a genetic algorithm-based search. Finally, a description of potential future work in genetic algorithm-based structural topology optimization is offered.

Explicit structural topology optimization using BEM ‐based MMV approach

2021 ◽  
Author(s):  
Weisheng Zhang ◽  
Qingqing Jiang ◽  
Weizhe Feng ◽  
Sung‐Kie Youn ◽  
Xu Guo
Keyword(s):  
Topology Optimization ◽  
Structural Topology Optimization ◽  
Structural Topology

Multi-objective optimization of squirrel cage fan for range hood based on Kriging model

2021 ◽  
pp. 095440622199586
Author(s):  
Qianhao Xiao ◽  
Jun Wang ◽  
Boyan Jiang ◽  
Weigang Yang ◽  
Xiaopei Yang
Keyword(s):  
Flow Rate ◽  
Optimization Design ◽  
Volume Flow Rate ◽  
Kriging Model ◽  
Volume Flow ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Squirrel Cage

In view of the multi-objective optimization design of the squirrel cage fan for the range hood, a blade parameterization method based on the quadratic non-uniform B-spline (NUBS) determined by four control points was proposed to control the outlet angle, chord length and maximum camber of the blade. Morris-Mitchell criteria were used to obtain the optimal Latin hypercube sample based on the evolutionary operation, and different subsets of sample numbers were created to study the influence of sample numbers on the multi-objective optimization results. The Kriging model, which can accurately reflect the response relationship between design variables and optimization objectives, was established. The second-generation Non-dominated Sorting Genetic algorithm (NSGA-II) was used to optimize the volume flow rate at the best efficiency point (BEP) and the maximum volume flow rate point (MVP). The results show that the design parameters corresponding to the optimization results under different sample numbers are not the same, and the fluctuation range of the optimal design parameters is related to the influence of the design parameters on the optimization objectives. Compared with the prototype, the optimized impeller increases the radial velocity of the impeller outlet, reduces the flow loss in the volute, and increases the diffusion capacity, which improves the volume flow rate, and efficiency of the range hood system under multiple working conditions.

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