Date of Award

12-2025

Degree Name

Master of Science

Department

Mechanical and Aerospace Engineering

First Advisor

Peter A. Gustafson, Ph.D.

Second Advisor

Jinseok Kim, Ph.D.

Third Advisor

Yrithu T. Pillay, Ph.D.

Keywords

Composite materials, micromechanics, multi-scale modeling, nasmat, paraview, U-NET

Access Setting

Masters Thesis-Open Access

Abstract

This study addresses some of the primary deficits of a localization/homogenization workflow for composite materials by focusing on the visualization and enhancement of models based on GMC and HFGMC, with emphasis on their implementation within the NASMAT ecosystem.

This thesis details the development of two dynamic, ParaView-based plugins that convert large hierarchical simulation outputs into interactive insights. While NASMATDiscreteElement systematizes RUC creation with transparent parametrization in a reproducible GUI, NASMATExplorerRUC enables the inspection of deeply nested datasets through accurate cell picking and synchronizes comparisons between parent and child views. Additionally, a shallow U-Net neural network is optimized on HFGMC data to enhance the accuracy of field predictions for PMCs using GMC, namely considering its limitations in shear-normal coupling. The ML model achieved a very low validation error (MSE ≈ 5.11×10−5) and markedly improved the shear components, with reported gains of ∼ 52% (strain) and ∼ 170% (stress) on the measured linear regression slopes (R2 ≥ 0.965). The average simulation run-time remains lightweight (GMC+ML ≈ 0.1526s) relative to high-order baselines (HFGMC ≈ 0.19099s).

Additional Files
BritesRei_NASMATDiscreteElement_music.mp4 (82503 kB)
NASMATDiscreteElement Compilation Guidelines
BritesRei_NASMATExplorerRUC_music.mp4 (59137 kB)
BritesRei_NASMATExplorerRUC Compilation Guidelines
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