scholarly journals Mechanical properties optimization of the steering column based on multi-objective optimization design

2016 ◽  
Vol 8 (12) ◽  
pp. 168781401668294 ◽  
Author(s):  
Si Chen ◽  
Zhaohui Wang ◽  
Mi Lv
Keyword(s):  
Mechanical Properties ◽  
Process Parameters ◽  
Optimization Design ◽  
Strain Difference ◽  
Optimization Method ◽  
Equivalent Strain ◽  
Multi Objective Optimization ◽  
Optimal Process ◽  
Multi Objective ◽  
Initial Results

The mechanical properties of the steering column have a significant influence on the comfort and stability of a vehicle. In order for the mechanical properties to be improved, the rotary swaging process of the steering column is studied in this article. The process parameters, including axial feed rate, hammerhead speed, and hammerhead radial reduction, are systematically analyzed and optimized based on a multi-objective optimization design. The response surface methodology and the genetic algorithm are employed for optimal process parameters to be obtained. The maximum damage value, the maximum forming load, and the equivalent strain difference obtained with the optimal process parameters are, respectively, decreased by 30.09%, 7.44%, and 57.29% compared to the initial results. The comparative results present that the quality of the steering column is improved. The torque experiments and fatigue experiments are conducted with the optimal steering column. The maximum torque is measured to be 260 NM, and the service life is measured to be 2 weeks (40 NM, 2500 times), which are, respectively, increased by 8.3% and 8.69% compared to the initial results. The above results display that the mechanical properties of the steering column are optimized to verify the feasibility of the multi-objective optimization method.

scholarly journals Multi-Objective Optimization of Process Parameters of Longitudinal Axial Threshing Cylinder for Frozen Corn Using RSM and NSGA-II

2020 ◽  
Vol 10 (5) ◽  
pp. 1646 ◽  
Author(s):  
Jun Fu ◽  
Haikuo Yuan ◽  
Depeng Zhang ◽  
Zhi Chen ◽  
Luquan Ren
Keyword(s):  
Process Parameters ◽  
Feed Rate ◽  
Loss Rate ◽  
Optimization Method ◽  
Operational Performance ◽  
Multi Objective Optimization ◽  
Optimal Process ◽  
Nsga Ii ◽  
Multi Objective ◽  
Damage Rate

Corn was frozen at harvest time in high-latitude areas, when corn kernel is wetter and more easily broken. When frozen corn was threshed and separated by the longitudinal axial threshing cylinder of a combine harvester, it caused a significantly high kernel damage rate and loss rate. The process parameters of threshing cylinder were optimized using RSM (response surface method) and NSGA-II (Non-Dominated Sorted Genetic Algorithm-II). The drum speed (Ds), feed rate (Fr) and concave clearance (Cc) were determined as the optimized process parameters. The loss rate (Lr) and damage rate (Dr) were indicators of operational performance. The RSM was used to establish a mathematical model between process parameters and indicators. With an elite strategy, NSGA-II was used for multi-objective optimization to obtain the optimal operational performance of the threshing cylinder. Overall, when the drum speed was selected as 384.1 rpm, the feed rate as 8.6 kg/s and the concave clearance as 40.5 mm, according to the requirement of corn harvest, the best operational performance of the longitudinal axial threshing cylinder on frozen corn was obtained. The Lr was 1.98% and the Dr was 3.49%. This result indicated that the applicability of the optimal process parameters and the optimization method of combining NSGA-II and RSM was effective for determining the optimal process parameters. This will provide an optimization method for synchronously reducing the loss rate and damage rate of grain harvesters.

scholarly journals Multi-Objective Optimization Design and Multi-Physics Analysis a Double-Stator Permanent-Magnet Doubly Salient Machine

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2130 ◽  
Author(s):  
Yunyun Chen ◽  
Yu Ding ◽  
Jiahong Zhuang ◽  
Xiaoyong Zhu
Keyword(s):  
Permanent Magnet ◽  
Optimization Design ◽  
Optimization Method ◽  
Torque Ripple ◽  
Field Analysis ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Doubly Salient ◽  
Interesting Candidate ◽  
Material Utilization

The double-stator permanent-magnet doubly salient (DS-PMDS) machine is an interesting candidate motor for electric vehicle (EV) applications because of its high torque output and flexible working modes. Due to the complexity of the motor structure, optimization of the DS-PMDS for EVs requires more research efforts to meet multiple specifications. Effective multi-objective optimization to increase torque output, reduce torque ripple, and improve PM material utilization and motor efficiency is implemented in this paper. In the design process, a multi-objective comprehensive function is established. By using parametric sensitivity analysis (PSA) and the sequential quadratic programming (NLPQL) method, the influence extent of each size parameter for different performance is effectively evaluated and optimal results are determined. By adopting the finite element method (FEM), the electromagnetic performances of the optimal DS-PMDS motor is investigated. Moreover, a multi-physical field analysis is included to describe stress, deformation of the rotor, and temperature distribution of the proposed motor. The theoretical analysis verified the rationality of the motor investigated and the effectiveness of the proposed optimization method.

Multi-Objective Optimization Method for Borehole Trajectory Design of Directional Well

2012 ◽  
Vol 152-154 ◽  
pp. 816-819
Author(s):  
Jian Bing Zhang ◽  
Xin Liu ◽  
Xiang Hong Lv
Keyword(s):  
Optimization Design ◽  
Ideal Point ◽  
Optimization Theory ◽  
Mathematic Model ◽  
Optimization Method ◽  
Drill String ◽  
Trajectory Design ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Multi Objective Programming

To offer those who are engaged in oil development a multi-objective design method of borehole trajectory for a directional well, the author adopted optimization theory to build a multi-objective optimization mathematic model with the shortest trajectory, the lowest drill string torque and the minimum rig hook load as final objectives, and put forward an approach to seek effective solutions to these multi-objective programming problems with ideal point method. The approach proposed in the paper can help satisfy concurrently multiple objectives of drilling design for an oilfield to implement the multi-objective optimization design schemes of borehole trajectory for a directional well, and to reduce the oilfield development costs accordingly.

Application of Particle Swarm Optimization in Cylinder Helical HGearH Multi-Objective Design

2011 ◽  
Vol 474-476 ◽  
pp. 2229-2233
Author(s):  
Yuan Bin Mo ◽  
Ji Zhong Liu ◽  
Bao Lei Wang ◽  
Wei Min Wan
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Design ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective

Cylinder helical gGear is widely used in industry. Multi-objective optimization design of the component is often met in its different application sSituation. In this paper a novel multi-objective optimization method based on Particle Swarm Optimization (PSO) algorithm is designed for applying to solve this kind of problem. A paradigm depicted in the paper shows the algorithm is practical.

scholarly journals Optimization of process parameters for surface roughness and tool wear in milling TC17 alloy using Taguchi with grey relational analysis

2021 ◽  
Vol 13 (2) ◽  
pp. 168781402199653
Author(s):  
Zhe Wang ◽  
Lei Li
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Process Parameters ◽  
Critical Role ◽  
Optimization Method ◽  
Ratio Method ◽  
Multi Objective Optimization ◽  
Processing Efficiency ◽  
Multi Objective ◽  
Process Guidance

To improve machining quality and processing efficiency, the Taguchi analysis method is employed to design the milling tests of titanium alloy TC17. According to results based on the signal-to-noise ratio method, the cutting depth plays a critical role in improving the surface roughness and tool wear. The grey correlation analysis is a multi-objective optimization method that can help to acquire process parameters combination of the optimal surface roughness and the optimal tool wear. Finally, the correctness of multi-objective optimization results is verified through comparison experiments. The research results can provide process guidance and data reference for the actual production processing.

scholarly journals Multi-Objective Optimization of Variable-Stiffness Composites Fabricated by Tailored Fiber Placement Machine

2019 ◽  
Vol 2 (1) ◽  
pp. 14-18
Author(s):  
Shinya Honda
Keyword(s):  
Mechanical Properties ◽  
Volume Fraction ◽  
Variable Stiffness ◽  
Optimization Method ◽  
Pareto Optimum ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Fiber Placement ◽  
Curvilinear Fibers ◽  
Placement Machine

A multi-objective optimization method for the laminated composite fabricated by a tailored fiber placement machine that is an application of embroidering machine is presented. The mechanical properties of composite with curvilinear fibers including stiffness, volume fraction, and density are variable depending on curvatures of fibers. The present study first measures the relation between curvatures and mechanical properties. The measured results indicate that the stiffness of composite decreases linearly as the curvature increases. Then, the obtained relation is applied to the multi-objective optimization where the maximum principal strain and magnitude of curvature are employed as objective functions. Obtained Pareto optimum solutions are widely distributed ranging from the solutions with curvilinear fibers to those with straight fibers, and the curvilinear fiber has still advantages over straight fiber even its weakened stiffness.

Machining Process Parameters Optimization Based on Grid Optimization Algorithm

2012 ◽  
Vol 562-564 ◽  
pp. 2021-2025 ◽  
Author(s):  
Chao Deng ◽  
Yao Xiong ◽  
Yuan Hang Wang ◽  
Jun Wu
Keyword(s):  
Process Parameters ◽  
Optimization Algorithm ◽  
Optimization Method ◽  
Parameters Optimization ◽  
Machining Process ◽  
Cnc Machine Tools ◽  
Multi Objective Optimization ◽  
Cnc Machine ◽  
Multi Objective ◽  
Grid Optimization

Machining process parameters directly affect the machining quality and efficiency of heavy-duty CNC machine tools, selecting correctly machining process parameters can improve the machine’s machining performance effectively. This paper presents a machining process parameters optimization method based on grid optimization algorithm for heavy-duty CNC machine tools. In this method, a multi-objective optimization model will be established, which considers not only the linear constrains of machining process parameters, such as machining time and machining cost, but also the non-linear constrain, such as chatter in machining process. Grid optimization algorithm will be adapted to search the optimal combination of machining process parameters from the multi-objective optimization model. In the end, this paper will present an example to verify superiority of the multi-objective optimization method by comparing with single-objective optimization method.

The Optimization Design about Flat Tail of Small Drones

2014 ◽  
Vol 1030-1032 ◽  
pp. 1260-1263
Author(s):  
Min Ji ◽  
Jing Feng He ◽  
Wei Ming Zhang
Keyword(s):  
Optimization Design ◽  
Optimization Method ◽  
Control Performance ◽  
Multi Objective Optimization ◽  
Longitudinal Stability ◽  
Longitudinal Control ◽  
Multi Objective ◽  
Flying Qualities

A multi-objective optimization method was advanced to make the drag and structure mass minimum of horizontal stabilizer based the precondition of meeting flying qualities. After the optimization, the longitudinal stability reduced, the longitudinal control performance increase. This method has referential meaning for the design of horizontal stabilizer for Mini-UVA.

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