Session: Research Posters

Paper Number: 166131

Computational Modeling of Grain Structures With Boundary Serrations 

The advancement of computational modeling techniques has significantly improved the ability to predict and analyze material behavior under various conditions. In this study, we investigate the impact of grain boundary modifications,specifically boundary serrations,on the mechanical properties of materials. The motivation for this research stems from the need to understand how controlled microstructural variations influence stress distribution and failure mechanisms, which has direct applications in materials engineering, aerospace, and structural integrity assessments.

Our study employs a Voronoi-based computational model to generate grain structures with controlled boundary modifications. A MATLAB algorithm was developed to create non-overlapping grains, incorporating serrated boundaries using sinusoidal functions with adjustable amplitude and frequency. These structures were analyzed in COMSOL, a finite element analysis (FEA) tool, to evaluate stress concentrations and mechanical responses under simulated loading. By systematically varying grain size, serration parameters, and boundary randomness, we explored the correlation between microstructural modifications and material strength.

Preliminary results indicate that serrated grain boundaries introduce localized stress variations, which can either enhance or weaken structural integrity depending on the amplitude and distribution of the serrations. We observed that certain serration patterns reduce crack propagation by altering stress pathways, while others increase stress concentration at critical points, leading to premature failure. The study also highlights the role of grain size distribution and edge characteristics in influencing material performance. The findings contribute to the broader understanding of how microstructural engineering can optimize material properties for specific applications.

This research provides a scalable and computationally efficient approach for analyzing grain structure behavior, offering insights into material design optimization. Additionally, our methodology enables high-resolution analysis of microstructural influences on mechanical performance, which is crucial for tailoring materials to specific engineering needs. Our findings suggest that material engineers can strategically modify grain boundaries to develop tougher and more resilient materials suitable for applications requiring enhanced durability and resistance to fracture.

Future work includes incorporating anisotropic material properties into the model, expanding the study to include real-world experimental validation, and refining serration algorithms to better mimic naturally occurring grain boundary variations. Further improvements will focus on integrating machine learning techniques to enhance predictive modeling capabilities. Additionally, we aim to explore the impact of temperature and environmental conditions on serrated grain boundaries to assess their long-term stability in extreme conditions. By improving the predictive capabilities of computational material models, this work aims to bridge the gap between theoretical simulations and practical engineering applications while advancing the field of computational materials science.

Presenting Author: James Burns San Diego State University

Presenting Author Biography: James Burns is a senior mechanical engineering student at San Diego State University with a strong interest in computational modeling, and materials science. His academic experience includes research on microstructural engineering and computational simulations for material behavior analysis.

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