Hybrid neural network-based prediction model for tribological properties of polyamide6-based friction materials-Reference-Cited by-同舟云学术

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Hybrid neural network-based prediction model for tribological properties of polyamide6-based friction materials

Published:2015-11-18 Issue:8 Volume:38 Page:1705-1711
ISSN:0272-8397
Container-title:Polymer Composites
language:en
Short-container-title:Polym. Compos.

Author:

Li Duxin¹,Lv Ruoyun¹,Si Gaojie¹,You Yilan¹

Affiliation:

1. State Key Laboratory of Powder Metallurgy; Central South University; Changsha People's Republic of China

Funder

Foundation of State Key Laboratory for Powder Metallurgy of Central South University

State Key Laboratory for Powder Metallurgy of Central South University

National Natural Science Foundation of China

Publisher

Wiley

Subject

Materials Chemistry,Polymers and Plastics,General Chemistry,Ceramics and Composites

Reference23 articles.

1. Friction and wear performance of polyamide 6 and graphite and wax polyamide 6 composites under dry sliding conditions

2. Friction and multiple scratch behavior of polymer+monomer liquid crystal systems

3. Effect of solid lubricants on tribological behavior of glass fiber reinforced polyamide 6

4. Tribological studies of polyamide 6 and high-density polyethylene blends filled with PTFE and copper oxide and reinforced with short glass fibers

5. Statistical wear analysis of PA-6/UHMWPE alloy, UHMWPE and PA-6

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