24 citations · 24 across the 4 of their papers we have counts for
4 papers
Machine learning enables roughness-driven inverse design of milling processes
Hadi Bakhshan, Sima Farshbaf, Fernando Rastellini +1
Interest in applying data-driven approaches in manufacturing has grown significantly, particularly for mapping complex, high-dimensional relationships. The milling process is one a…
An efficient open-source framework for high-fidelity 3D surface topography and roughness prediction in milling
Hadi Bakhshan, Sima Farshbaf, Adrián Travieso-Disotuar +3
With the emergence of data-driven approaches in science, there is growing interest in their application to manufacturing, particularly in surface precision engineering. However, ge…
AI Meets Plasticity: A Comprehensive Survey
Hadi Bakhshan, Sima Farshbaf, Junior Ramirez Machado +2
Artificial intelligence (AI) is rapidly emerging as a new paradigm of scientific discovery, namely data-driven science, across nearly all scientific disciplines. In materials scien…
Large deformation and collapse analysis of re-entrant auxetic and hexagonal honeycomb lattice structures subjected to tension and compression
Sima Farshbaf, Narges Dialami, Miguel Cervera
Additively manufactured auxetic structures offer desirable qualities like lightweight, good energy absorption, excellent indentation resistance, high shear stiffness and fracture t…