no code implementations • 8 Dec 2021 • Naresh S. Iyer, Amir M. Mirzendehdel, Sathyanarayanan Raghavan, Yang Jiao, Erva Ulu, Morad Behandish, Saigopal Nelaturi, Dean M. Robinson
In this paper, we propose PATO-a producibility-aware topology optimization (TO) framework to help efficiently explore the design space of components fabricated using metal additive manufacturing (AM), while ensuring manufacturability with respect to cracking.
no code implementations • 18 May 2018 • Morad Behandish, Saigopal Nelaturi, Johan de Kleer
A multimodal HM process plan is represented by a finite Boolean expression of AM and SM manufacturing primitives, such that the expression evaluates to an 'as-manufactured' artifact.
no code implementations • 14 Jul 2017 • Jonathan Rubin, Rui Abreu, Anurag Ganguli, Saigopal Nelaturi, Ion Matei, Kumar Sricharan
The work presented here applies deep learning to the task of automated cardiac auscultation, i. e. recognizing abnormalities in heart sounds.