The Flexural Strength Prediction of Porous Cu-Sn-Ti Composites via Artificial Neural Networks
Porous alloy-composites have demonstrated excellent qualities with regards to grinding superalloys. Flexural strength is an important mechanical property associated with the porosity level as well as inhomogeneity in porous composites. Owing to the non-linear characteristics of the constituents of t...
Main Authors: | , , , , , |
---|---|
Format: | Book Chapter |
Language: | English English English |
Published: |
Universiti Malaysia Pahang
2018
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/24528/1/62.%20The%20flexural%20strength%20prediction%20of%20porous%20cu-sn-ti.pdf http://umpir.ump.edu.my/id/eprint/24528/8/8.%20The%20flexural%20strength%20prediction%20of%20porous%20Cu-Sn-Ti%20composites%20via%20artificial%20neural%20networks.pdf http://umpir.ump.edu.my/id/eprint/24528/9/8.1%20The%20flexural%20strength%20prediction%20of%20porous%20Cu-Sn-Ti%20composites%20via%20artificial%20neural%20networks.pdf |
Internet
http://umpir.ump.edu.my/id/eprint/24528/1/62.%20The%20flexural%20strength%20prediction%20of%20porous%20cu-sn-ti.pdfhttp://umpir.ump.edu.my/id/eprint/24528/8/8.%20The%20flexural%20strength%20prediction%20of%20porous%20Cu-Sn-Ti%20composites%20via%20artificial%20neural%20networks.pdf
http://umpir.ump.edu.my/id/eprint/24528/9/8.1%20The%20flexural%20strength%20prediction%20of%20porous%20Cu-Sn-Ti%20composites%20via%20artificial%20neural%20networks.pdf