Work

scientific AI for real-time engineering design under uncertainty

Year: 2024

Type: conference-paper

Abstract: Mike McKerns2 11/21/24 can ML enable in-situ manufacturing with verified reliability estimates? • …-…• … -… Testing requires > 18 months and > $1.5 M per part, per material, per machine.The standard approach does not scale for distributed additive manufacturing requirements / success criteria

DOI: 10.2172/2496647

Author: Michael McKerns

Institution: Los Alamos National Laboratory

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funders: U.S. Department of Energy, National Nuclear Security Administration, Los Alamos National Laboratory

Awards: G1017065088, G1279347439, G6410514744