Improved Methods of Creep-Fatigue Life Assessment of Components

被引:0
|
作者
Scholz, A. [1 ]
Berger, C. [1 ]
机构
[1] Tech Univ Darmstadt, Inst Mat Technol IfW, D-64283 Darmstadt, Germany
关键词
advanced 9-12% Cr-steels; 1%Cr-steel; creep fatigue; multiaxiality; fatigue scatter band assessment; stress relaxation; multi-stage loading; life time assessment; simulation;
D O I
10.1361/cp2007epri0748
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Improved life assessment methods contribute to an effective long term operation of high temperature components, reduces technical risk and increases high economical advantages. Creep-fatigue at multi-stage loading, covering cold start, warm start and hot start cycles in typical loading sequences e.g. for medium loaded power plants, was investigated here. At hold times creep and stress relaxation, respectively, lead to an acceleration of crack initiation. Creep fatigue life time can be calculated by a modified damage accumulation rule, which considers the fatigue fraction rule for fatigue damage and the life fraction rule for creep damage. Mean stress effects, internal stress and interaction effects of creep and fatigue are considered. Along with the generation of advanced creep data, fatigue data and creep fatigue data as well scatter band analyses are necessary in order to generate design curves and lower bound properties inclusive. Besides, in order to improve lifing methods the enhancement of modelling activities for deformation and life time are important. For verification purposes, complex experiments at variable creep conditions as well as at creep fatigue interaction under multi-stage loading are of interest. Generally, the development of methods to transfer uniaxial material properties to multiaxial loading situations is a current challenge. Further, a constitutive material model is introduced which is implemented as a user subroutine for Finite Element applications due to start-up and shut-down phases of components. Identification of material parameters have been achieved by Neural Networks.
引用
收藏
页码:748 / 761
页数:14
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