9 citations · 11 across the 4 of their papers we have counts for
4 papers
A Cutting Mechanics-based Machine Learning Modeling Method to Discover Governing Equations of Machining Dynamics
Alisa Ren, Mason Ma, Jiajie Wu +4
This paper proposes a cutting mechanics-based machine learning (CMML) modeling method to discover governing equations of machining dynamics. The main idea of CMML design is to inte…
AFSD-Physics: Exploring the governing equations of temperature evolution during additive friction stir deposition by a human-AI teaming approach
Tony Shi, Mason Ma, Jiajie Wu +3
This paper presents a modeling effort to explore the underlying physics of temperature evolution during additive friction stir deposition (AFSD) by a human-AI teaming approach. AFS…
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements
Mason Ma, Jiajie Wu, Chase Post +4
This study presents a physics-informed machine learning-based control method for nonlinear dynamic systems with highly noisy measurements. Existing data-driven control methods that…
Integration of discrete-event dynamics and machining dynamics for machine tool: modeling, analysis and algorithms
Mason Ma, Alisa Ren, Christopher Tyler +4
Machining dynamics research lays a solid foundation for machining operations by providing stable combinations of spindle speed and depth of cut. Furthermore, machine learning has b…