Multi-objective Optimization Design Method of the High-Speed Train Head

2017 ◽  
pp. 165-182
Author(s):  
Meng-ge Yu ◽  
Ji-ye Zhang ◽  
Wei-hua Zhang
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Design Method ◽  
Multi Objective Optimization ◽  
High Speed Train ◽  
Multi Objective

Multi-Objective Optimization for the Section Structure of Sandwich Plate Applied in the High-Speed Train Compartments

2014 ◽  
Vol 597 ◽  
pp. 535-539
Author(s):  
Yi Qing Wang ◽  
Xu Chen ◽  
Bin Wang ◽  
Xin Bin Kuang ◽  
Xiao Geng Tian
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Sandwich Plate ◽  
Side Wall ◽  
Response Surfaces ◽  
Solution Set ◽  
Multi Objective Optimization ◽  
High Speed Train ◽  
Pareto Solution ◽  
Multi Objective

In order to obtain the side walls section structures of high speed train applicable to different running speeds and conditions, a multi-objective optimization design is made based on the structure of topology optimization. In this optimization formulation, the weight of sandwich plate, static compliance and maximum deformation are used as the objective functions; the thickness of face panels and cores in five parts of the side wall are variables; and the air pressure gradient in compartments is the constraint function. Surrogate model techniques are adopted for constructing the response surfaces based on the optimization. Finally, a multi-objective optimization is performed using the NSGA-II algorithm and the optimization generates a Pareto solution set. The structure performance in Pareto set is greatly improved by 8.21% -33.58% than that of topology structure. In addition, the Pareto solution set provides engineers with many alternative Pareto-optimal solutions for optimization design of the sandwich plate section applied in the high-speed train.

MDO of Anti-Creeper on High Speed Train Using Optimus

2011 ◽  
Vol 130-134 ◽  
pp. 3128-3132
Author(s):  
Kai Jie Liu ◽  
Hong Lun Zhao ◽  
Chao Xu
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Feasible Solution ◽  
Minimum Mass ◽  
Multi Objective Optimization ◽  
High Speed Train ◽  
Optimization Analysis ◽  
Pareto Solution ◽  
Optimization Software ◽  
Multi Objective

How to find the solution of multi-objective optimization quickly and exactly is the challenge of multi-objective optimization design. This paper explores the feasibility of multi-objective optimization solution briefly in theory, and makes a high-speed train’s anti-creeper as an example which using multi-objective design optimization software to find the feasible solution. Nastran and LS-Dyna are respectively adopted to solve the linear static and collision study analysis of the anti-creeper. In this paper Nastran and LS-Dyna are integrated on Optimus which is MDO platform to make a MDO of anti-creeper. The anti-creeper optimization analysis is proceeded based on many indexes satisfied, and its multi-objective Pareto solution of its minimum mass and biggest internal energy comes out. The method of multi-objective optimization solution in this paper is solved well in MDO.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

Multi-Objective Optimal Design of a Double Circular Gear Based on the Differential Evolution Algorithm

2014 ◽  
Vol 977 ◽  
pp. 365-369
Author(s):  
Li Mei Zou ◽  
Bo Guo ◽  
Xue Yi Qian
Keyword(s):  
Differential Evolution ◽  
Optimization Design ◽  
Design Method ◽  
Optimization Technique ◽  
Differential Evolution Algorithm ◽  
Research Process ◽  
Multi Objective Optimization ◽  
Design Quality ◽  
Multi Objective ◽  
Technical And Economic Indicators

In order to improve the comprehensive technical and economic indicators of a double circular gear, based on the conjugate principle and design method of the double circular gear, by use of the modified differential evolution multi-objective optimization technique and MATLAB computer simulation technology, constrained multi-objective optimization design of a double circular gear was done. According to the research process and results, by use of the improved differential evolutionary multi-objective optimization technique, the design cycle of product can be shorten effectively, the design quality of product can be improved.

Multi-Objective Optimization Design Method for Tandem Compressor Cascade at Design and Off Design Conditions

2010 ◽  
Author(s):  
Yaping Ju ◽  
Chuhua Zhang
Keyword(s):  
Optimization Design ◽  
Design Method ◽  
Pressure Ratio ◽  
Aerodynamic Performance ◽  
Multi Objective Optimization ◽  
Ann Model ◽  
Compressor Cascade ◽  
Control Cost ◽  
Multi Objective ◽  
Operation Conditions

Recently, there has been a renewed interest in the research of tandem compressor cascades due to the high stage pressure ratio and low control cost. Firstly, the computational fluid dynamics (CFD) method is employed to examine the particular aerodynamic performance of the tandem cascade. Then we propose an automatic multi-objective optimization design method of the tandem cascade for the superior aerodynamic performance under the multiple operation conditions. Particular efforts have been devoted to the gap geometry optimization in terms of the front and aft airfoil relative position, camber turning ratio as well as chord ratio. The multi-objective optimization algorithm comprises a refined multi-objective genetic algorithm (MOGA) and a developed artificial neural network (ANN) model which is used to fast approximate the aerodynamic performance of the tandem cascade. The results show that the tandem cascade outperforms the single cascade in terms of producing higher pressure ratio and lower losses while the operation range is rather narrow. The optimized all-better-than (ABT) tandem cascade has its design point performance significantly improved while the operation range slightly widened. We also find that a slight axial proximity and separation of the tandem airfoils are beneficial to widening the positive and negative operation range, respectively. This research is useful to the tandem compressor cascade design in minimizing the stage number of the engine compressors.

Multi-point and multi-objective optimization design method for industrial axial compressor cascades

2011 ◽  
Vol 225 (6) ◽  
pp. 1481-1493 ◽  
Author(s):  
Y P Ju ◽  
C H Zhang
Keyword(s):  
Optimization Design ◽  
Design Method ◽  
Axial Compressor ◽  
Multi Objective Optimization ◽  
Original Design ◽  
Design Point ◽  
Operating Range ◽  
Multi Objective ◽  
Pressure Loss Coefficient ◽  
Total Pressure Loss Coefficient

Modern aerodynamic optimization design methods for the industrial axial compressor cascade mainly aim at improving both design point and off-design point performance. In this study, a multi-point and multi-objective optimization design method is established for the cascade, particularly aiming at widening the operating range while maintaining good performance at the acceptable expense of computational load. The design objectives are to maximize the static pressure ratio and minimize the total pressure loss coefficient at the design point, and to maximize the operating range for the positive and negative incidences. To alleviate the computational load, a design of experiment (DOE)-based GA–BP-ANN model is constructed to rapidly approximate the cascade aerodynamic performance in the optimization process. The artificial neural network (ANN) is trained by the genetic algorithm (GA) technique and back propagation (BP) algorithm, where the training cascades are sampled by the DOE method and analysed by the computational fluid dynamics method. The multi-objective genetic algorithm is used to search for a series of Pareto-optimum solutions, from which an optimal cascade is found out whose objectives are all better than (ABT) those of the original design. The ABT cascade is characterized by the lower camber and higher turning angle, leading to better aerodynamic performance in a widened operating range. Compared with the original design, the ABT cascade decreases the total pressure loss coefficient by 1.54 per cent, 23.4 per cent, and 7.87 per cent at the incidences of 5°, −9°, and 13°, respectively. The established optimization design method can be extended to the three-dimensional aerodynamic design of axial compressor blade.

Sign in / Sign up

Export Citation Format

Share Document