Artificial Neural Networks-Based Creep Reliability Analysis Method of Turbine Disk

LI Quan-tong; JING Xiao-ning; L Wen-lin

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Artificial Neural Networks-Based Creep Reliability Analysis Method of Turbine Disk

更新时间：2026-07-07

- Artificial Neural Networks-Based Creep Reliability Analysis Method of Turbine Disk
- Vol. 18, Issue 2, (2003)
- 作者机构：
  
  1. 西北工业大学航空动力与热力工程系,陕西,西安,710072
  2. 空军工程大学工程学院,陕西,西安,710038
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2003
- 稿件说明：
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LI Quan-tong, JING Xiao-ning, L Wen-lin. Artificial Neural Networks-Based Creep Reliability Analysis Method of Turbine Disk[J]. 2003, 18(2).
DOI：

LI Quan-tong, JING Xiao-ning, L Wen-lin. Artificial Neural Networks-Based Creep Reliability Analysis Method of Turbine Disk[J]. 2003, 18(2). DOI：

摘要

用ADINA程序计算的涡轮盘盘缘蠕变位移量的有限个结果对人工神经网络进行训练。利用Monte-Carlo法对基本随机变量进行随机抽样

并基于随机有限元方法思想用人工神经网络代替有限元程序计算涡轮盘盘缘蠕变位移量

进而分析涡轮盘蠕变可靠性。

Abstract

The basic variables are sampled by Monte Carlo method. Instead of complicate finite element analysis

a Neural Network

which was well trained by the results of ADINA program

is used to calculate the displacement at the rim of turbine disc.As a result

this paper shows how to use Neural Network method to calculate the creep reliability of an aero engine turbine disc.

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Application of θ projection method in analysis of creep deformation of turbine disc

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Life Prediction Considering Creep and Stress Relaxation for Gas Turbine Engine Hot Section

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Research Center of Small Sample Technology, Beijing University of Aeronautics and Astronautics

School of Mechanical Engineering and Automation, Northeastern University

Department of Mathematics, Daqing Petroleum Institute

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