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Engineering  |  FURI

Dylan Thomas Quarenghi

Hometown: Walnut Creek, California, United States | Graduation Date: Fall 2020
Aerospace engineering

A Novel Use of GAN’s to Efficiently Simulate Fracture in Polymer Composites

Mentor:
Research Theme: Data
FURI: Fall 2020

Can a neural network be used to speed up finite element analysis in certain material simulations? The researchers built a pipeline to generate thousands of finite element analysis maps and preprocess the data to be used by machine learning algorithms. Multiple architectures have been trained on the data and their effectiveness was measured. Preliminary data demonstrate that simple machine learning models can quickly and accurately estimate the output of finite element analysis in certain situations. These estimates can be refined with traditional analysis which results in a marked speedup. Future work involves expanding these models to handle more complex data.

Other Projects

A Novel Use of GAN’s to Efficiently Simulate Fracture in Polymer Composites

Mentor:
Research Theme: Data
FURI: Needs Review, Summer 2020

Can a neural network be used to speed up finite element analysis in certain material simulations? The researchers have built a pipeline to generate thousands of finite element analysis maps and preprocess the data to be used by machine learning algorithms. Multiple architectures have been trained on the data and their effectiveness was measured. Preliminary data demonstrate that simple machine learning models can quickly estimate the output of finite element analysis. Research is ongoing, however, small models can produce the first estimates of finite element output which can be refined with traditional analysis. This results in a marked speedup.

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