Parameter study and optimization design of a hat oblique tunnel portal

2021 ◽  
pp. 095440972110140
Author(s):  
Zijian Guo ◽  
Tanghong Liu ◽  
Wenhui Li ◽  
Yutao Xia
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Pareto Front ◽  
Optimization Problem ◽  
Optimization Method ◽  
Design Parameters ◽  
Parameter Study ◽  
Buffer Structure ◽  
Tunnel Entrance ◽  
The Ideal

The present work focuses on the aerodynamic problems resulting from a high-speed train (HST) passing through a tunnel. Numerical simulations were employed to obtain the numerical results, and they were verified by a moving-model test. Two responses, [Formula: see text] (coefficient of the peak-to-peak pressure of a single fluctuation) and[Formula: see text] (pressure value of micro-pressure wave), were studied with regard to the three building parameters of the portal-hat buffer structure of the tunnel entrance and exit. The MOPSO (multi-objective particle swarm optimization) method was employed to solve the optimization problem in order to find the minimum [Formula: see text] and[Formula: see text]. Results showed that the effects of the three design parameters on [Formula: see text] were not monotonous, and the influences of[Formula: see text] (the oblique angle of the portal) and [Formula: see text] (the height of the hat structure) were more significant than that of[Formula: see text] (the angle between the vertical line of the portal and the hat). Monotonically decreasing responses were found in [Formula: see text] for [Formula: see text] and[Formula: see text]. The Pareto front of [Formula: see text] and[Formula: see text]was obtained. The ideal single-objective optimums for each response located at the ends of the Pareto front had values of 1.0560 for [Formula: see text] and 101.8 Pa for[Formula: see text].

An Optimization Design Platform for Fir-Tree Root and Groove for Steam Turbine

2018 ◽  
Author(s):  
Deqi Yu ◽  
Xiaojun Zhang ◽  
Jiandao Yang ◽  
Kai Cheng ◽  
Weilin Shu ◽  
...  
Keyword(s):  
Stress Concentration ◽  
Steam Turbine ◽  
Gas Turbines ◽  
High Speed ◽  
Optimization Design ◽  
Turbine Blades ◽  
Local Stress ◽  
Optimization Method ◽  
Steam Turbines ◽  
Geometry Configuration

Fir-tree root and groove profiles are widely used in gas turbine and steam turbine. Normally, the fir-tree root and groove are characterized with straight line, arc or even elliptic fillet and splines, then the parameters of these features were defined as design variables to perform root profile optimization. In ultra-long blades of CCPP and nuclear steam turbines and high-speed blades of industrial steam turbine blades, both the root and groove strength are the key challenges during the design process. Especially, in industrial steam turbines, the geometry of blade is very small but the operation velocity is very high and the blade suffers stress concentration severely. In this paper, two methods for geometry configuration and relevant optimization programs are described. The first one is feature-based using straight lines and arcs to configure the fir-tree root and groove geometry and genetic algorithm for optimization. This method is quite fit for wholly new root and groove design. And the second local optimization method is based on B-splines to configure the geometry where the local stress concentration occurs and the relevant optimization algorithm is used for optimization. Also, several cases are studied as comparison by using the optimization design platform. It can be used not only in steam turbines but also in gas turbines.

The Effect of Different Optimization Methods on Robustness for Robust Optimization Design

2014 ◽  
Vol 721 ◽  
pp. 464-467
Author(s):  
Tao Fu ◽  
Qin Zhong Gong ◽  
Da Zhen Wang
Keyword(s):  
Robust Optimization ◽  
Objective Function ◽  
Robust Design ◽  
Optimization Design ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Parameters ◽  
Hybrid Particle Swarm Optimization ◽  
Design Variables ◽  
Robust Optimization Design

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.

Research on Optimization of Ground-Coupled Heat Pump Systems under Specific Constraint Conditions

2014 ◽  
Vol 953-954 ◽  
pp. 673-679
Author(s):  
Yang Yang Wang ◽  
Ping Fang Hu ◽  
Fei Lei ◽  
Na Zhu ◽  
Tian Hua Wu ◽  
...  
Keyword(s):  
Heat Pump ◽  
Optimization Problem ◽  
Design Method ◽  
Optimization Method ◽  
Simulation Software ◽  
Design Parameters ◽  
Decision Variable ◽  
Economic Optimization ◽  
Ground Coupled Heat Pump

A design method for ground-coupled heat pump (GCHP) systems with specific constraint conditions is proposed. The total borehole number, borehole depth, borehole space and average velocity of fluid in the U-tube are considered as variables in the optimization problem. The optimization problem of four variables is transformed into that of single decision variable. A case study, which includes different schemes for designing GCHP systems of an office building and the corresponding economic analysis, is performed with the aid of simulation software. The result shows that optimal design parameters could be found in an economic optimization problem with specific constraint conditions. Additionally, design parameters may have a notable influence on the energy consumption of circulating pumps. The optimization method in this paper could be utilized by engineering designers for reference.

The Optimal Research of Force Increasing Mechanism of Injection Machine based on Genetic Simulated Annealing Algorithms

2011 ◽  
Vol 338 ◽  
pp. 505-512
Author(s):  
Tie Jun Li ◽  
Xin Li ◽  
Li Qun Yan ◽  
Cheng Shi Zhu ◽  
Yong Ying Du
Keyword(s):  
Simulated Annealing ◽  
Performance Measures ◽  
Optimization Design ◽  
Optimization Problem ◽  
Design Parameters ◽  
Performance Parameters ◽  
Total Length ◽  
Complete Procedure ◽  
Annealing Algorithms ◽  
Analysis Of Motion

The analysis of motion and mechanics property has been studied on the five hinged incline arranged and double elbowed force increasing mechanism of injection machine in this paper. An optimization design is proposed on the force increasing mechanism by use of genetic simulated annealing algorithms. A complete procedure of optimal design is introduced so as to increase the stroke ratio and the amplification of the force, and to decrease the total length of mechanism, which belongs to multi-object optimization problem. Compared with the traditional methods, the result shows that the stroke ratio is increased, the amplification of the force is increased and the total length of mechanism is decreased. Moreover a sensitivity analysis of design parameters has been performed to see changes in injection performance parameters, and results show that the length of back elbowed bar and the length of connected bar have a significant impact on the performance measures. And the results recommend that the close clearance of the length of back elbowed bar and the length of connected bar must be maintained.

Improving the Robustness of Adjoint-Based Airfoil Drag Reduction Design

2013 ◽  
Vol 444-445 ◽  
pp. 259-263
Author(s):  
Yan Hong Fan
Keyword(s):  
Drag Reduction ◽  
Optimization Design ◽  
Line Search ◽  
Optimization Problem ◽  
Design Method ◽  
Optimization Method ◽  
Search Method ◽  
Linear Search

The effect of steps in the line search on the consistence of adjoint-based drag reduction of airfoil is investigated in this paper. Constant step adopted in drag reduction design usually gives different optimization results and choice of constant step often depends on designers experience and optimization problem. Bracket method is applied to automatically give the optimal step in performing drag reduction design of airfoils RAE2822 and S73613 and the consistent optimal results are obtained. The results illustrate that the linear search method can automatically find the optimal step, and overcome the restriction on choice of user-defined constant step which is used in the traditional adjoint-based optimization method. That is, it reduces the dependence of step in the drag reduction design, and improves the robustness of the adjoint-based airfoil drag reduction optimization design method.

scholarly journals Thermal performance analysis and optimization design of dry type air core reactor with the double rain cover

2021 ◽  
pp. 67-67
Author(s):  
FaTing Yuan ◽  
Shouwei Yang ◽  
Shihong Qin ◽  
Kai Lv ◽  
Bo Tang ◽  
...  
Keyword(s):  
Finite Element ◽  
Temperature Distribution ◽  
Temperature Rise ◽  
Optimization Design ◽  
Orthogonal Experiment ◽  
Structural Parameters ◽  
Fluid Velocity ◽  
Optimization Method ◽  
Design Parameters ◽  
Air Core

In this paper, a fluid-thermal coupled finite element model is established according to the design parameters of dry type air core reactor. The detailed temperature distribution can be achieved, the maximum error coefficient of temperature rise is only 6% compared with the test results of prototype, and the accuracy of finite element calculate method is verified. Taking the equal height and heat flux design parameters of reactor as research object, the natural convection cooling performance of reactor with and without the rain cover is investigated. It can be found that the temperature rise of reactor is significantly increased when adding the rain cover, and the reasons are given by analyzing the fluid velocity distribution of air dcuts between the encapsulation coils. In order to reduce the temperature rise of the reactor with the rain cover, the optimization method based on the orthogonal experiment design and finite element method is proposed. The six factors of the double rain cover are given, which mainly affect the temperature rise of reactor, and the five levels are selected, the influence curve and contribution rate of each factor on the temperature rise of reactor are analyzed. The results show that the contribution ratio of the parameter H1, L1 and L2, are obviously higher than the parameter H2, L3 and ?, so the more attention should be paid in the design of double rain cover. Meanwhile, the optimal structural parameters of rain cover are given based on the influence curves, and the temperature rise is only 43.25?C. The results show that the optimization method can reduce the temperature rise of reactor significantly. In addition, the temperature distribution of inner encapsulations coils of reactor are basically the same, the current carrying capacity of coils can be fully utilized, which provides an important guidance for the optimization design of reactor.

Optimization Design and Experimental Study of a Two-disk Rotor System Based on Multi-Island Genetic Algorithm

2019 ◽  
Vol 36 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Jingjing Huang ◽  
Longxi Zheng ◽  
Chris K Mechefske ◽  
Bingbing Han
Keyword(s):  
Genetic Algorithm ◽  
Vibration Amplitude ◽  
High Speed ◽  
Optimization Design ◽  
Critical Speed ◽  
Optimization Method ◽  
Rotor System ◽  
Flexible Rotor ◽  
Optimum Position ◽  
Transient Experiments

Abstract Based on rotor dynamics theory, a two-disk flexible rotor system representing an aero-engine with freely supported structure was established with commercial software ANSYS. The physical model of the two-disk rotor system was then integrated to the multidisciplinary design optimization software ISIGHT and the maximum vibration amplitudes experienced by the two disks when crossing the first critical speed were optimized using a multi-island genetic algorithm (MIGA). The optimization objective was to minimize the vibration amplitudes of the two disks when crossing the first critical speed. The position of disk 1 was selected as the optimization variable. The optimum position of disk 1 was obtained at the specified constraint that the variation of the first critical speed could not exceed the range of ±10 %. In order to validate the performance of the optimization design, the proof-of-transient experiments were conducted based on a high-speed flexible two-disk rotor system. Experimental results indicated that the maximum vibration amplitude of disk 1 when crossing the first critical speed declined by 60.9 % and the maximum vibration amplitude of disk 2 fell by 63.48 % after optimization. The optimization method found the optimum rotor positions of the flexible rotor system which resulted in minimum vibration amplitudes.

scholarly journals Sensor Networks Hierarchical Optimization Model for Security Monitoring in High-Speed Railway Transport Hub

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Zhengyu Xie ◽  
Yong Qin
Keyword(s):  
Sensor Networks ◽  
Optimization Model ◽  
High Speed ◽  
Optimization Problem ◽  
Optimization Method ◽  
Hierarchical Optimization ◽  
Railway Transport ◽  
High Speed Railway ◽  
Security Monitoring

We consider the sensor networks hierarchical optimization problem in high-speed railway transport hub (HRTH). The sensor networks are optimized from three hierarchies which are key area sensors optimization, passenger line sensors optimization, and whole area sensors optimization. Case study on a specific HRTH in China showed that the hierarchical optimization method is effective to optimize the sensor networks for security monitoring in HRTH.

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.

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.

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