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Research On The Efficient Optimization Of The Fir-tree Attachment Based On The Spline Curve

Posted on:2017-05-22Degree:MasterType:Thesis
Country:ChinaCandidate:H M ZongFull Text:PDF
GTID:2272330488953059Subject:Power Machinery and Engineering
Abstract/Summary:PDF Full Text Request
Fir-tree attachment is liable to fracture failure and fatigue crack. Thus, based on the three teeth fir-tree attachment used by a MW grade gas turbine, shape optimization has been carried out to reduce the stress level. The main contents are as follows:1. Based on the feature-based modelling method, the 2-D and 3-D parametric models with geometric constraints considered are built by APDL. Then, the model is meshed, the contact pairs are set up and the boundary conditions are imposed. After FEM calculation, the stress is extracted. By programing all the process in the macro file, automatically analysis and modification are achieved.2. In order to improve the optimization potential, the transition area in the third tooth is redesigned with double-arc, arc-line-arc, single-section spline curve, double-section spline curve and multi-section spline curve. Based on the redesigns, Genetic Algorithm is adopted for optimization. As a result, multi-section spline curve achieves the maximum equivalent stress decrease by 37.32% and most uniform stress distribution between the three teeth. The analysis to the curvature radiuses shows the spline curve is more flexible in modeling and insensitive to the geometric constraints. Besides, enlarging the transition region is helpful to smooth the stress distribution.3. Since FEM analysis is time-consuming, it is replaced with the Kriging surrogate model. Besides, the sequential sampling technique based on the LOLA-Voronoi algorithm is adopted to generate the samples. Thus, by comprehensive application of multiple technologies including parametric modeling, surrogate model, sequential sampling and Genetic Algorithm, an efficient optimization flow is built. Based on the optimization flow, the multi-section spline curve redesign is optimized. Compared with the direct optimization method, the Kriging-based method improves the efficiency by 39.10%. Meanwhile, the optimization result is better and the maximum stress in the third tooth decreases by 42.54%.
Keywords/Search Tags:fir-tree attachment, parametric modeling, Kriging model, LOLA-Voronoi algorithm, genetic algorithm
PDF Full Text Request
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