Brown University

Massachusetts Institute of Technology

Nanyang Technological University

George E Karniadakis

Subra Suresh

Ming Dao

Paris Perdikaris

Lu Lu

Maziar Raissi

Methods and apparatus for extracting one or more mechanical properties for a material based on one or more indentation parameters for the material. The method comprises receiving load-displacement data from one or more instrumented indentation tests on the material, determining, by at least one computer processor, the indentation parameters for the material based, at least in part, on the received load-displacement data, providing as input to a trained neural network, the indentation parameters for the material, determining, based on an output of the trained neural network, the one or more mechanical properties of the material, and displaying an indication of the determined one or more mechanical properties of the material to a user of the computer system.

Machine learning techniques for estimating mechanical properties of materials

A method for analyzing an object includes modeling the object with a differential equation, such as a linear partial differential equation (PDE), and sampling data associated with the differential equation. The method uses a probability distribution device to obtain the solution to the differential equation. The method eliminates use of discretization of the differential equation.

Physics informed learning machine

Growing community of inventors

Newton, MA, United States of America

George E Karniadakis