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Modeling and analysis of compressive properties of porous NiTi shape memory alloy using artificial neural network

หน่วยงาน Central Queensland University, Australia

รายละเอียด

ชื่อเรื่อง : Modeling and analysis of compressive properties of porous NiTi shape memory alloy using artificial neural network
นักวิจัย : Li, Qiang. , Sun, Xudong. , Yu, Jingyuan. , Liu, Zhigang. , Duan, Kai.
คำค้น : Applied research. , 861199 Basic Metal Products (incl. Smelting, Rolling, Drawing and Extruding) not elsewhere classified. , 091207 Metals and Alloy Materials. , Neural networks (Computer science) , Shape memory alloys. , Porous NiTi SMA -- BP neural network -- Process parameters -- Compressive properties
หน่วยงาน : Central Queensland University, Australia
ผู้ร่วมงาน : -
ปีพิมพ์ : 2551
อ้างอิง : http://hdl.cqu.edu.au/10018/28231 , cqu:4325
ที่มา : Li, Q Sun, X Yu, J Liu, Z & Duan, K 2008, "Modeling and analysis of compressive properties of porous NiTi shape memory alloy using artificial neural network", Advanced Materials Research , vol.41-42, pp.135-140.
ความเชี่ยวชาญ : -
ความสัมพันธ์ : Advanced materials research. Switzerland. : Trans Tech Publications, 2008. Vol. 41-42, (2008), p. 135-140 6 pages Refereed 1022-6680 , ACQUIRE [electronic resource] : Central Queensland University Institutional Repository.
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

Artificial neural network (ANN) is an intriguing data processing technique. Over the last decade, it was applied widely in the chemistry field, but there were few applications in the porous NiTi shape memory alloy (SMA). In this paper, 32 sets of samples from thermal explosion experiments were used to build a three-layer BP (back propagation) neural network model. According to the registered BP model, the effect of process parameters including heating rate (v), green density(D) and particle size of Ti ( d ) on compressive properties of reacted products including ultimate compressive strength (σ ) and ultimate compressive strain (ε ) was analyzed. The predicted results agree with the actual data within reasonable experimental error, which shows that the BP model is a practically very useful tool in the properties analysis and process parameters design of the porous NiTi SMA prepared by thermal explosion method.

บรรณานุกรม :
Li, Qiang. , Sun, Xudong. , Yu, Jingyuan. , Liu, Zhigang. , Duan, Kai. . (2551). Modeling and analysis of compressive properties of porous NiTi shape memory alloy using artificial neural network.
    กรุงเทพมหานคร : Central Queensland University, Australia.
Li, Qiang. , Sun, Xudong. , Yu, Jingyuan. , Liu, Zhigang. , Duan, Kai. . 2551. "Modeling and analysis of compressive properties of porous NiTi shape memory alloy using artificial neural network".
    กรุงเทพมหานคร : Central Queensland University, Australia.
Li, Qiang. , Sun, Xudong. , Yu, Jingyuan. , Liu, Zhigang. , Duan, Kai. . "Modeling and analysis of compressive properties of porous NiTi shape memory alloy using artificial neural network."
    กรุงเทพมหานคร : Central Queensland University, Australia, 2551. Print.
Li, Qiang. , Sun, Xudong. , Yu, Jingyuan. , Liu, Zhigang. , Duan, Kai. . Modeling and analysis of compressive properties of porous NiTi shape memory alloy using artificial neural network. กรุงเทพมหานคร : Central Queensland University, Australia; 2551.