Research on formation mechanism and optimization method of surface waviness of TC4 blisk blade

2019 ◽  
Vol 39 ◽  
pp. 305-326 ◽  
Author(s):  
Dongbo Wu ◽  
Hui Wang ◽  
Kaiyao Zhang ◽  
Xiaojun Lin
Keyword(s):  
Formation Mechanism ◽  
Optimization Method ◽  
Surface Waviness ◽  
Blisk Blade

scholarly journals An optimization study of polishing efficiency of blisk and its technological parameters

2020 ◽  
Vol 103 (3) ◽  
pp. 003685042095785
Author(s):  
Wenbo Huai ◽  
Xiaojun Lin
Keyword(s):  
Surface Roughness ◽  
Optimization Method ◽  
Test Results ◽  
Technological Parameters ◽  
Optimization Study ◽  
Blisk Blade ◽  
Aero Engines ◽  
Five Axis ◽  
The Relationship ◽  
Polishing Efficiency

When applied to blisk blade profile polishing of aero-engines, “five-axis NC + flexible grinding head + elastic grindstone” polishing technological equipment has advantages of high precision, minor interference, favorable adaptivity, etc. In order to improve the polishing quality and polishing efficiency, a mathematical calculation formula of polishing efficiency was established according to the polishing principles of elastic grindstone (sanding wheel). The optimized combination of technological parameters ( ω = 6000 r/min, ap = 0.9 mm, vf = 320 mm/min) was obtained through the range method of orthogonal test results with double optimization objectives—surface roughness and polishing efficiency. Based on the relationship between number of polishing times and surface roughness, a technological program was put forward, that is, polishing is firstly conducted using 320# sanding wheel for 6 times and then 400# sanding wheel for 9 times (totally 15 times) under the optimized combination of technological parameters, then surface roughness less 0.4 μm can be achieved. Blade polishing test results indicate that: efficiency-optimized technological parameters can not only significantly shorten polishing time but also acquire qualified blade surface roughness less 0.4 μm, thus verifying reliability of the optimization method and results.

Optimization Method of Superelevation Transition for Oval Racing Tracks

CICTP 2019 ◽  
2019 ◽  
Author(s):  
Yuchen Wang ◽  
Tao Lu ◽  
Hongxing Zhao ◽  
Zhiying Bao
Keyword(s):  
Optimization Method

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

Dimensioning a recovery boiler furnace using mathematical optimization

TAPPI Journal ◽  
2015 ◽  
Vol 14 (2) ◽  
pp. 119-129 ◽  
Author(s):  
VILJAMI MAAKALA ◽  
PASI MIIKKULAINEN
Keyword(s):  
Radial Basis Function Network ◽  
High Capacity ◽  
Mathematical Optimization ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Performance Criteria ◽  
Boiler Furnace ◽  
Starting Point ◽  
Recovery Boiler ◽  
Base Design

Capacities of the largest new recovery boilers are steadily rising, and there is every reason to expect this trend to continue. However, the furnace designs for these large boilers have not been optimized and, in general, are based on semiheuristic rules and experience with smaller boilers. We present a multiobjective optimization code suitable for diverse optimization tasks and use it to dimension a high-capacity recovery boiler furnace. The objective was to find the furnace dimensions (width, depth, and height) that optimize eight performance criteria while satisfying additional inequality constraints. The optimization procedure was carried out in a fully automatic manner by means of the code, which is based on a genetic algorithm optimization method and a radial basis function network surrogate model. The code was coupled with a recovery boiler furnace computational fluid dynamics model that was used to obtain performance information on the individual furnace designs considered. The optimization code found numerous furnace geometries that deliver better performance than the base design, which was taken as a starting point. We propose one of these as a better design for the high-capacity recovery boiler. In particular, the proposed design reduces the number of liquor particles landing on the walls by 37%, the average carbon monoxide (CO) content at nose level by 81%, and the regions of high CO content at nose level by 78% from the values obtained with the base design. We show that optimizing the furnace design can significantly improve recovery boiler performance.

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