The Flexural Strength Prediction of Porous Cu-Sn-Ti Composites via Artificial Neural Networks

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...

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Bibliographic Details
Main Authors: El Sawy, Abdelrahman, Anwar, P. P. Abdul Majeed, Musa, Rabiu Muazu, Mohd Azraai, M. Razman, Mohd Hasnun Ariff, Hassan, Abdul Aziz, Jaafar
Format: Book Section
Language:English
English
English
Published: Universiti Malaysia Pahang 2018
Subjects:
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/24528/
http://umpir.ump.edu.my/id/eprint/24528/
http://umpir.ump.edu.my/id/eprint/24528/
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

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