Application of Neural Networks to Mechanical Property Determination of Ni-base Superalloys.

• Warde J.

  Department of Materials Science and Metallurgy, University of Cambridge

• Knowles D. M.

  Department of Materials Science and Metallurgy, University of Cambridge

抄録

In this work the application of a neural network, within a Bayesian framework, to the prediction of tensile properties has been critically assessed. Following optimisation of input parameters a series of neural networks were trained to predict tensile properties of a range of polycrystalline superalloys as a function of temperature. <br>Once trained the models have been subjected to several metallurgical tests in order to demonstrate that they predict the trends expected from experimental observations. Generally it is found that the models are in agreement with expected trends. In addition areas of uncertainty are highlighted through the production of large error bars, which act as warning signals.

収録刊行物

• ＩＳＩＪ　Ｉｎｔｅｒｎａｔｉｏｎａｌ

  ＩＳＩＪ　Ｉｎｔｅｒｎａｔｉｏｎａｌ 39 (10), 1006-1014, 1999

  一般社団法人 日本鉄鋼協会

キーワード

• Ni-base superalloys
• modelling
• neural networks
• yield strength
• tensile strength

詳細情報

• CRID: 1390282681429651200
• NII論文ID: 10002555722
• NII書誌ID: AA10680712
• DOI: 10.2355/isijinternational.39.1006
• ISSN: 13475460
• ISSN: 09151559
• Web Site: http://www.jstage.jst.go.jp/article/isijinternational1989/39/10/39_10_1006/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • Crossref
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可