Sensitivity Analysis and Interval Multi-Objective Optimization for an Occupant Restraint System Considering Craniocerebral Injury

2019 ◽  
Vol 142 (2) ◽  
Author(s):  
Qiming Liu ◽  
Xingfu Wu ◽  
Xu Han ◽  
Jie Liu ◽  
Zheyi Zhang ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Optimization Design ◽  
Element Model ◽  
Design Parameters ◽  
Craniocerebral Injury ◽  
Restraint System ◽  
Multi Objective Optimization ◽  
Occupant Restraint System ◽  
Multi Objective ◽  
Vehicle Collision

Abstract In vehicle collision accidents, an occupant restraint system (ORS) is crucial to protect the human body from injury, and it commonly involves a large number of design parameters. However, it is very difficult to quantify the importance of design parameters and determine them in the ORS design process. Therefore, an approach of the combination of the proposed approximate sensitivity analysis (SA) method and the interval multi-objective optimization design is presented to reduce craniocerebral injury and improve ORS protection performance. First, to simulate the vehicle collision process and obtain the craniocerebral injury responses, the integrated finite element model of vehicle-occupant (IFEM-VO) is established by integrating the vehicle, dummy, seatbelt, airbag, etc. Then, the proposed approximate SA method is used to quantify the importance ranking of design parameters and ignore the effects of some nonessential parameters. In the SA process, the Kriging metamodel characterizing the relationships between design parameters and injury responses is fitted to overcome the time-consuming disadvantage of IFEM-VO. Finally, according to the results of SA, considering the influence of uncertainty, an interval multi-objective optimization design is implemented by treating the brain injury criteria (BRIC, BrIC) as the objectives and regarding the head injury criterion (HIC) and the rotational injury criterion (RIC) as the constraints. Comparison of the results before and after optimization indicates that the maximum values of the translational and rotational accelerations are greatly reduced, and the ORS protection performance is significantly improved. This study provides an effective way to improve the protection performance of vehicle ORS under uncertainty.

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.

Multi-Objective Optimization Design of Tanker Ships via a Genetic Algorithm

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Marcelo Ramos Martins ◽  
Diego F. Sarzosa Burgos
Keyword(s):  
Genetic Algorithm ◽  
Optimization Design ◽  
Optimization Problem ◽  
Pareto Frontier ◽  
Ship Design ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Total Cost ◽  
Multi Objective ◽  
The Cost

The cost of a new ship design heavily depends on the principal dimensions of the ship; however, dimensions minimization often conflicts with the minimum oil outflow (in the event of an accidental spill). This study demonstrates one rational methodology for selecting the optimal dimensions and coefficients of form of tankers via the use of a genetic algorithm. Therein, a multi-objective optimization problem was formulated by using two objective attributes in the evaluation of each design, specifically, total cost and mean oil outflow. In addition, a procedure that can be used to balance the designs in terms of weight and useful space is proposed. A genetic algorithm was implemented to search for optimal design parameters and to identify the nondominated Pareto frontier. At the end of this study, three real ships are used as case studies.

Parametric Optimal Design of Robot End-Effector Tool for Robot-Assisted Automatic Polishing System

2010 ◽  
Vol 450 ◽  
pp. 333-336
Author(s):  
Wei Yang Lin ◽  
Yue Du ◽  
Xiao Jun Yang ◽  
Bing Li
Keyword(s):  
Optimization Design ◽  
Model Updating ◽  
Optimization Methods ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Robot Assisted ◽  
End Effector ◽  
Multi Objective ◽  
Automatic Polishing ◽  
Parametric Optimal Design

In this paper the multi-objective optimization design of a preliminarily designed end-effector tool for robot-assisted automatic polishing system is presented. ADAMS and iSIGHT are integrated for the multi-objective optimization design, the overall procedure of which is shown in this paper. Design of Experiment is arranged before optimization. The global optimization methods provided by iSIGHT software- Exterior Penalty and Multi-Island Genetic are utilized to perform optimizing process. Simulation executed in ADAMS with model updating with optimized structural design parameters verifies the significance of the multi-objective optimization in improving the performance of preliminarily designed end-effector tool.

Parameter design of biped robot motion system based on multi-objective optimization

2021 ◽  
pp. 1-12
Author(s):  
Xiaokun Leng ◽  
Songhao Piao ◽  
Lin Chang ◽  
Zhicheng He ◽  
Zheng Zhu
Keyword(s):  
Design Process ◽  
Optimization Design ◽  
Physical Simulation ◽  
Biped Robot ◽  
Service Industries ◽  
Parameter Design ◽  
Design Parameters ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Simulation Engine

In recent years humanoid robots have been widely used in toy, performance, education and other service industries, but most biped robots walk slowly and have poor stability. The reason is that the driver parameters of the robot cannot properly match the walking gait algorithm, and the insufficient performance of the robot driver leads to the poor motion capability of the robot. In this paper, the optimization design process of biped robot parameters is studied and expounded, and its motion capability is improved by optimizing the driving parameters of the robot. Firstly, the contradiction between walking speed, stability and driver performance of biped robot is analysed. The performance evaluation functions of the three are further established, and the optimal parameter design to a certain extent is realized based on the multi-objective optimization method. Finally, combining with the physical simulation engine, the design parameters are simulated and checked, and the robot design process is completed through the guidance of simulation results.

scholarly journals Multi-objective optimization of flexure hinge mechanism considering thermal–mechanical coupling deformation and natural frequency

2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668791 ◽  
Author(s):  
Lufan Zhang ◽  
Xueli Li ◽  
Jiwen Fang ◽  
Zhili Long
Keyword(s):  
Finite Element ◽  
Natural Frequency ◽  
Element Model ◽  
Optimization Method ◽  
Design Parameters ◽  
Flexure Hinge ◽  
Multi Objective Optimization ◽  
Motion Platform ◽  
Mechanical Coupling ◽  
Multi Objective

Flexure hinge mechanism plays a key part in realization of terminal nano-positioning. The performance of flexure hinge mechanism is determined by its positioning design. Based on the actual working conditions, its finite element model is built and calculated in ANSYS. Moreover, change trends of deformation and natural frequency with positioning design parameters are revealed. And sensitivity analysis is performed for exploration response to these parameters. These parameters are used to build four objective functions. To solve it conveniently, the multi-objective optimization problem is transferred to the form of single-objective function with constraints. An optimal mechanism is obtained by an optimization method combining ANSYS with MATLAB. Finite element numerical simulation has been carried out to demonstrate the superiority of the optimal flexure hinge mechanism, and the superiority can be further verified by experiment. Measurements and tests have been conducted at varying accelerations, velocities, and displacements, to quantify and characterize the amount of acceleration responses obtained from flexure hinge mechanism before and after optimization. Both time- and frequency-domain analyses of experimental data show that the optimal flexure hinge mechanism has superior effectiveness. It will provide a basic for realizing high acceleration and high precision positioning of macro–micro motion platform.

Multi-objective optimization design of cement grate cooler control system based on improved long short-term memory network

2021 ◽  
pp. 014233122110230
Author(s):  
Wang Hongyi ◽  
Zhang Kun ◽  
Zhu Xinjun ◽  
Song Limei ◽  
Dong Feng
Keyword(s):  
Optimization Design ◽  
Short Term Memory ◽  
Design Parameters ◽  
Outlet Temperature ◽  
Multi Objective Optimization ◽  
Short Term ◽  
Term Memory ◽  
Multi Objective ◽  
Grate Cooler ◽  
Long Short Term Memory

For the cement production process, the optimization method of the grate cooler is important in reducing energy consumption and ensuring product quality. As a complicated and slow control process, there are several control objectives of the grate cooler, which are determined by design parameters. To compute the time delay of the design parameters automatically, we propose an improved long short-term memory with adaptive computation time (ACT-LSTM) model for objective prediction. An improved multi-objective optimization algorithm named bounded stable non-dominated sorting genetic algorithm II (BS-NSGA-II) is proposed to solve the optimal solutions. With the proposed methods, the average electricity consumption is reduced by 13.2%, the secondary air temperature is increased, the clinker outlet temperature is stabilized in a reasonable range, and the design parameters change smoothly. The experiment results have indicated that the proposed method is effective in the optimization of objectives and the stability operation of the equipment.

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