8 papers
First Contact: Data-driven Friction-Stir Process Control
James Koch, Ethan King, WoongJo Choi +4
This study validates the use of Neural Lumped Parameter Differential Equations for open-loop setpoint control of the plunge sequence in Friction Stir Processing (FSP). The approach…
Automated Grain Boundary (GB) Segmentation and Microstructural Analysis in 347H Stainless Steel Using Deep Learning and Multimodal Microscopy
Shoieb Ahmed Chowdhury, M. F. N. Taufique, Jing Wang +5
Austenitic 347H stainless steel offers superior mechanical properties and corrosion resistance required for extreme operating conditions such as high temperature. The change in mic…
Neural Lumped Parameter Differential Equations with Application in Friction-Stir Processing
James Koch, WoongJo Choi, Ethan King +5
Lumped parameter methods aim to simplify the evolution of spatially-extended or continuous physical systems to that of a "lumped" element representative of the physical scales of t…
Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing
Scott Howland, Lara Kassab, Keerti Kappagantula +2
The research and development cycle of advanced manufacturing processes traditionally requires a large investment of time and resources. Experiments can be expensive and are hence c…
TopTemp: Parsing Precipitate Structure from Temper Topology
Lara Kassab, Scott Howland, Henry Kvinge +2
Technological advances are in part enabled by the development of novel manufacturing processes that give rise to new materials or material property improvements. Development and ev…
Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps
Elizabeth Coda, Nico Courts, Colby Wight +6
While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as ma…
Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing
Loc Truong, WoongJo Choi, Colby Wight +4
Advanced manufacturing techniques have enabled the production of materials with state-of-the-art properties. In many cases however, the development of physics-based models of these…
A Topological-Framework to Improve Analysis of Machine Learning Model Performance
Henry Kvinge, Colby Wight, Sarah Akers +7
As both machine learning models and the datasets on which they are evaluated have grown in size and complexity, the practice of using a few summary statistics to understand model p…