Solution of Lubrication Problems with Deep Neural Network
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-4208-2_34
Reference8 articles.
1. Yadav SK, Sharma SC (2016) Performance of hydrostatic textured thrust bearing with supply holes operating with non-Newtonian lubricant. Tribol Trans 59(3):408–420
2. Kumar V, Sharma SC (2018) Influence of dimple geometry and micro-roughness orientation on performance of textured hybrid thrust pad bearing. Meccanica 53(14):3579–3606
3. Yadav SK, Thakre GD, Khatri CB (2021) Improvement in textured hole-entry hybrid journal bearing system by using multi-objective genetic algorithm. J Braz Soc Mech Sci Eng 44(1):32
4. Khatri CB, Sharma SC (2017) Influence of couple stress lubricant on the performance of textured two-lobe slot-entry hybrid journal bearing system. Proc Inst Mech Eng, Part J: J Eng Tribol 231(3):366–384
5. Samaniego E et al (2020) An energy approach to the solution of partial differential equations in computational mechanics via machine learning: concepts, implementation and applications. Comput Methods Appl Mech Eng 362:112790
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