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A study of creep rupture life prediction for P91 steel with machine learning method: model selection and sensitivity analysis

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Journal:International Journal of Pressure Vessels and Piping

Indexed by:Journal paper

Document Code:105494

Discipline:Engineering

Document Type:J

Volume:216

Translation or Not:yes

Date of Publication:2025-03-21

Included Journals:SCI

Next One : Long-term creep life prediction of P91 steel using domain knowledge and back propagation artificial neural network

Personal information

Supervisor of Master's Candidates

Name (Pinyin):zhulin

Date of Birth:1993-01-16

Date of Employment:2019-12-30

School/Department:化工学院

Education Level:With Certificate of Graduation for Doctorate Study

Gender:Male

Degree:Doctoral Degree in Engineering

Status:Employed

Alma Mater:西北大学

Discipline:Other specialties in Chemical Engineering and Technology
Chemical Process Machinery

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