scholarly journals Load Sharing Multiobjective Optimization Design of a Split Torque Helicopter Transmission

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Chenxi Fu ◽  
Ning Zhao ◽  
Yongzhi Zhao
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Design ◽  
Optimal Solution ◽  
Load Sharing ◽  
Operating Conditions ◽  
Design Parameters ◽  
Nonlinear Dynamic Model ◽  
Nsga Ii ◽  
Reference Design ◽  
Split Torque

Split torque designs can offer significant advantages over the traditional planetary designs for helicopter transmissions. However, it has two unique properties, gap and phase differences, which result in the risk of unequal load sharing. Various methods have been proposed to eliminate the effect of gap and promote load sharing to a certain extent. In this paper, system design parameters will be optimized to change the phase difference, thereby further improving load sharing. A nonlinear dynamic model is established to measure the load sharing with dynamic mesh forces quantitatively. Afterwards, a multiobjective optimization of a reference split torque design is conducted with the promoting of load sharing property, lightweight, and safety considered as the objectives. The load sharing property, which is measured by load sharing coefficient, is evaluated under multiple operating conditions with dynamic analysis method. To solve the multiobjective model with NSGA-II, an improvement is done to overcome the problem of time consuming. Finally, a satisfied optimal solution is picked up as the final design from the Pareto optimal front, which achieves improvements in all the three objectives compared with the reference design.

Multi-Objective Shape Optimization Design for LNG Cryogenic Helical Corrugated Steel Pipe

2016 ◽  
Author(s):  
Zhixun Yang ◽  
Jun Yan ◽  
Qingzhen Lu ◽  
Jinlong Chen ◽  
Shanghua Wu ◽  
...  
Keyword(s):  
Shape Optimization ◽  
Optimization Design ◽  
Rbf Neural Network ◽  
Optimal Solution ◽  
Steel Pipe ◽  
Structural Deformation ◽  
Design Parameters ◽  
Operation Condition ◽  
Nsga Ii ◽  
Multi Objective

The flexible cryogenic hose has been a favored alternative for offshore liquefied natural gas (LNG) exploitation recently, of which helical corrugated steel pipe is the crucial component with C shaped corrugation. Parametric finite-element models of LNG cryogenic helical corrugated pipe are presented based on 3D shell element in this paper. Taking account of nonlinearity such as cryogenic material and large geometric structural deformation, mechanical behavior characteristics results are obtained under axial tensional, bending and inner pressure loads. Meanwhile, the design parameters are determined for the shape optimization of structures of the flexible cryogenic hose through sectional dimension analysis, and sensitivity analysis is performed with changing geometric parameters. A multi-objective optimization with the object of minimizing stiffness and strength stress is formulated based on operation condition. Full factorial experiment and radial basis function (RBF) neural network are applied to establish the approximated model for the analysis of the structure. The Pareto optimal solution set and value range of parameters are obtained through NSGA-II GA algorithm under manufacturing and stiffness constraints. It provides a feasible optimal approach for the structural design of LNG cryogenic corrugated hose.

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 Control Devices to Suppress Tall Buildings Vibrations against Earthquake Excitations Using Fuzzy Logic and Genetic Algorithms

2015 ◽  
pp. 787-817
Author(s):  
Saeid Pourzeynali ◽  
Shide Salimi
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Optimization Design ◽  
Base Isolation ◽  
Control Strategies ◽  
Optimal Solution ◽  
Base Shear ◽  
Viscous Dampers ◽  
Nsga Ii ◽  
Isolation Systems

The main objective of this chapter is to find the optimal values of the parameters of the base isolation systems and that of the semi-active viscous dampers using genetic algorithms (GAs) and fuzzy logic in order to simultaneously minimize the buildings' selected responses such as displacement of the top story, base shear, and so on. In this study, performance of base isolation systems, and semi-active viscous dampers are studied separately as different vibration control strategies. In order to simultaneously minimize the objective functions, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solution. To study the performance of semi-active viscous dampers, the torsional effects exist in the building due to irregularities, and unsymmetrical placement of the dampers is taken into account through 3D modeling of the building.

Structure Optimization Design for the Bed of Gear Hobbing Machine

2013 ◽  
Vol 765-767 ◽  
pp. 176-180
Author(s):  
Rong Chuang Zhang ◽  
Ao Xiang Liu ◽  
Jun Wang ◽  
Wan Shan Wang
Keyword(s):  
Optimization Design ◽  
Optimal Solution ◽  
Element Model ◽  
Weighting Coefficient ◽  
Design Parameters ◽  
Analytic Hierarchy ◽  
Design Variables ◽  
Gear Hobbing ◽  
Vibration Modal ◽  
Hierarchy Process

In the optimization design of the gear hobbing machine bed, the finite element model is build and the static analysis and vibration modal analysis are performed. Then sensitivity analysis is used to gain the main design parameters which influence the bed property most. Furthermore, the multi-objective optimization design of the bed is performed in ANSYS Workbench with these design parameters as the design variables. At last, after all optimum proposals are showed up, Analytic Hierarchy Process is used to determine the weighting coefficient, and the most optimal solution is found out. As a result, the dynamic and static performances of the machine bed are improved under control of the machine bed mass.

scholarly journals Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Qiang Gao ◽  
Jilin Chen ◽  
Li Wang ◽  
Shiqing Xu ◽  
Yuanlong Hou
Keyword(s):  
Control System ◽  
Multiobjective Optimization ◽  
Fractional Order ◽  
Optimization Design ◽  
Differential Evolution Algorithm ◽  
Optimal Solution ◽  
Parameter Tuning ◽  
Gun Control ◽  
Tuning Method ◽  
Fractional Order Pid

Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. With assistance of the evolutionary algorithm, the optimal solution for the specified problem is selected. The numerical simulation results show that the control system can rapidly follow the demand signal with high accuracy and high robustness, demonstrating the efficiency of the proposed controller parameter tuning method.

Optimal Design Parameters of Cab’s Isolation System for Vibratory Roller Using a Multi-Objective Genetic Algorithm

2018 ◽  
Vol 875 ◽  
pp. 105-112 ◽  
Author(s):  
Van Quynh Le ◽  
Khac Tuan Nguyen
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Dynamic Model ◽  
Nonlinear Dynamic ◽  
Ride Comfort ◽  
Design Parameters ◽  
Nonlinear Dynamic Model ◽  
Nsga Ii ◽  
Isolation System ◽  
Multi Objective

In order to improve the vibratory roller ride comfort, a multi-objective optimization method based on the improved genetic algorithm NSGA-II is proposed to optimize the design parameters of cab’s isolation system when vehicle operates under the different conditions. To achieve this goal, 3D nonlinear dynamic model of a single drum vibratory roller was developed based on the analysis of the interaction between vibratory roller and soil. The weighted r.m.s acceleration responses of the vertical driver’s seat, pitch and roll angle of the cab are chosen as the objective functions. The optimal design parameters of cab’s isolation system are indentified based on a combination of the vehicle nonlinear dynamic model of Matlab/Simulink and the NSGA - II genetic algorithm method. The results indicate that three objective function values are reduced significantly to improve vehicle ride comfort.

scholarly journals Optimization Design of Actuator Parameters in Multistage Reciprocating Compressor Stepless Capacity Control System Based on NSGA-II

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhinong Jiang ◽  
Chao Zhou ◽  
Yao Wang ◽  
Jinjie Zhang ◽  
Wenhua Liu ◽  
...  
Keyword(s):  
Control System ◽  
Multiobjective Optimization ◽  
Impact Velocity ◽  
Hydraulic System ◽  
Optimization Design ◽  
Reciprocating Compressor ◽  
Spring Stiffness ◽  
Capacity Control ◽  
Nsga Ii ◽  
The Impact

The capacity control system of reciprocating compressor has great significance for the contribution of energy conservation and emission reduction. The parameters of the actuator and hydraulic system within a reciprocating compressor stepless capacity control system play a decisive role in its control accuracy, mechanical reliability, and mechanical security. The actuators and hydraulic system parameters of the same stage are in conflict with each other. Therefore, the actuator and the multistage reciprocating compressor are studied here, specifically through multiobjective optimization using the Nondominated Sorting Genetic Algorithm (NSGA)-II. The multiobjective optimization design was performed on a two-dimensional (2D) reciprocating compressor test bench. When the spring stiffness of the first stage spring was 27358 N m−1, the spring stiffness of the second stage spring was 23315 N m−1, the inlet oil pressure was 296.62 N, the impact velocity of ejection was 0.4215 m s−1, and the total indicated power deviation was 12.05 kW; the objective functions were optimized. Compared with traditional parameters, the inlet oil pressure, spring stiffness, and impact velocity were all reduced. This parameter optimization design lays the foundations for global optimization designs for stepless capacity control systems.

scholarly journals Optimization Design on Functionally Graded Cem for Trains Based on LPM Model with Calibrated Parameters

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ruixian Qin ◽  
Bingzhi Chen
Keyword(s):  
Optimization Design ◽  
Optimization Method ◽  
Functionally Graded ◽  
Optimization Techniques ◽  
Design Parameters ◽  
Nsga Ii ◽  
Longitudinal Response ◽  
Lumped Parameter ◽  
1D Model ◽  
Crash Model

Lumped parameter modeling (LPM) combined with optimization techniques is an efficient approach for parametric configuration design of energy absorption to improve crashworthiness performance during train collision. This work proposed a simplified model by introducing a bar element to consider the influence of the carbody in a collision process. The optimization method is applied to calibrate the equivalent parameters of the bar element. Bar elements with calibrated parameters are adopted in establishing a one-dimensional (1D) model for the train crash. Subsequently, a novel crash energy management (CEM) mode with functionally graded energy (FGE) configuration is introduced to the train crash model for improving crashworthiness performance. The influence of parameters in graded function on interfacial force and peak acceleration is investigated and optimal design parameters are obtained by Nondominated Sorting Genetic Algorithm (NSGA-II). It is concluded that considering the behavior of the carbody can improve the accuracy of LPM in predicting the longitudinal response, and the gradient CEM is a potential energy configuration mode to improve the crashworthiness of the train in a collision.

Multi-Objective Shape Optimization Design for Liquefied Natural Gas Cryogenic Helical Corrugated Steel Pipe

2017 ◽  
Vol 139 (5) ◽  
Author(s):  
Zhixun Yang ◽  
Jun Yan ◽  
Jinlong Chen ◽  
Qingzhen Lu ◽  
Qianjin Yue
Keyword(s):  
Natural Gas ◽  
Optimization Design ◽  
Rbf Neural Network ◽  
Liquefied Natural Gas ◽  
Steel Pipe ◽  
Structural Deformation ◽  
Design Parameters ◽  
Nsga Ii ◽  
Multi Objective ◽  
Operation Conditions

Recently, the flexible cryogenic hose has been preferred as an alternative to exploit offshore liquefied natural gas (LNG), in which helical corrugated steel pipe is the crucial component with C-shaped corrugation. Parametric finite element models of the LNG cryogenic helical corrugated pipe are established using a three-dimensional shell element in this paper. Considering the nonlinearity of cryogenic material and large geometric structural deformation, mechanical behaviors are simulated under axial tension, bending, and internal pressure loads. In addition, design parameters are determined to optimize the shape of flexible cryogenic hose structures through sectional dimension analysis, and sensitivity analysis is performed with changing geometric parameters. A multi-objective optimization to minimize stiffness and stress is formulated under operation conditions. Full factorial experiment and radial basis function (RBF) neural network are applied to establish the approximated model for structure analysis. The set of Pareto optimal solutions and value range of parameters are obtained through nondominated sorting genetic algorithm II (NSGA-II) under manufacturing and stiffness constraints, thereby providing a feasible optimal approach for the structural design of LNG cryogenic corrugated hose.

Multi-Objective Optimization Design of Control Devices to Suppress Tall Buildings Vibrations against Earthquake Excitations Using Fuzzy Logic and Genetic Algorithms

2013 ◽  
pp. 180-215
Author(s):  
Saeid Pourzeynali ◽  
Shide Salimi
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Optimization Design ◽  
Base Isolation ◽  
Control Strategies ◽  
Optimal Solution ◽  
Base Shear ◽  
Viscous Dampers ◽  
Nsga Ii ◽  
Isolation Systems

The main objective of this chapter is to find the optimal values of the parameters of the base isolation systems and that of the semi-active viscous dampers using genetic algorithms (GAs) and fuzzy logic in order to simultaneously minimize the buildings’ selected responses such as displacement of the top story, base shear, and so on. In this study, performance of base isolation systems, and semi-active viscous dampers are studied separately as different vibration control strategies. In order to simultaneously minimize the objective functions, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solution. To study the performance of semi-active viscous dampers, the torsional effects exist in the building due to irregularities, and unsymmetrical placement of the dampers is taken into account through 3D modeling of the building.

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