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Effects of squeeze casting parameters on solidification time based on neural network

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成果类型:
期刊论文
作者:
Wang, Rong Ji*;Tan, Wen Fang;Zhou, Dian-Wu
通讯作者:
Wang, Rong Ji
作者机构:
[Wang, Rong Ji; Tan, Wen Fang] Cent South Univ Forestry & Technol, Coll Mech & Elect Engn, Changsha 410004, Hunan, Peoples R China.
[Zhou, Dian-Wu] Hunan Univ, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China.
通讯机构:
[Wang, Rong Ji] C
Cent South Univ Forestry & Technol, Coll Mech & Elect Engn, Changsha 410004, Hunan, Peoples R China.
语种:
英文
关键词:
Dies;Heat transfer coefficients;Neural networks;Pressure pouring;Squeeze casting;Applied pressure;Casting parameters;Critical value;Influence of process parameters;Interfacial heat transfer coefficients;Pouring temperatures;Process parameters;Solidification time;Solidification
期刊:
INTERNATIONAL JOURNAL OF MATERIALS & PRODUCT TECHNOLOGY
ISSN:
0268-1900
年:
2013
卷:
46
期:
2-3
页码:
124-140
基金类别:
Science Fund of State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body [30815004]
机构署名:
本校为第一且通讯机构
院系归属:
机电工程学院
摘要:
Based on artificial neural network (ANN) and ProCast software, the effects of different process parameter on the solidification time of squeeze casting hot die steel were investigated, such as interfacial heat transfer coefficient of metal/cavity die (h1), applied pressure (Pa), interfacial heat transfer coefficient of metal/male die (h2), die pre-heat temperature (Td) and pouring temperature (Tp). An ANN model on the relationship between process parameters and solidification time was constructed. The test results show that the ANN model is rea...

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