DOAJ Open Access 2023

Artificial intelligence-based model for physical-mechanical surface properties of nanostructured coatings

F.J. Sánchez-Ruiz M. Bedolla-Hernández G. Rosano-Ortega J. Bedolla-Hernández P.S. Schabes-Retchkiman +2 lainnya

Abstrak

This article presents a computational numerical model for the simulation and analysis of quantum chemistry and Gibbs free energy theory using static (ANNS), dynamic (DANN), and chaotic neural networks (CANN). The model calculates the physical-surface mechanics of hardness, adhesion, and strength. They resulted in nanostructured metal coatings with electrodeposited chromium nanoparticles on low-carbon steel. The ANNS, DANN, and CANN simulations showed that model-obtained values for analyzed properties presented an approximation of 99 % concerning theoretical matters taken as base. Likewise, model accuracy was verified by comparison with reference data (datasheet). The proposed model is not limited to the analyzed case and provides consistent results for predicting surface physical-mechanical properties of electrodeposited coating-substrate arrangements, with a minimum error percentage of 1–1.5 % over learning.

Topik & Kata Kunci

Materials of engineering and construction. Mechanics of materials

Penulis (7)

F.J. Sánchez-Ruiz

M. Bedolla-Hernández

G. Rosano-Ortega

J. Bedolla-Hernández

P.S. Schabes-Retchkiman

C.A. Vega-Lebrún

E. Vargas-Viveros

Format Sitasi

APA MLA BibTeX

Sánchez-Ruiz, F., Bedolla-Hernández, M., Rosano-Ortega, G., Bedolla-Hernández, J., Schabes-Retchkiman, P., Vega-Lebrún, C. et al. (2023). Artificial intelligence-based model for physical-mechanical surface properties of nanostructured coatings. https://doi.org/10.1016/j.rinma.2023.100494

Akses Cepat

PDF tidak tersedia langsung

Cek di sumber asli →

Lihat di Sumber doi.org/10.1016/j.rinma.2023.100494

Informasi Jurnal

Tahun Terbit: 2023
Sumber Database: DOAJ
DOI: 10.1016/j.rinma.2023.100494
Akses: Open Access ✓