Session: 16-01-01: Government Agency Student Poster Competition

Paper Number: 149953

149953 - Uncertainty Quantification in Architected Materials: Effects of Imperfections on Buckling Response 

Architected materials exhibit specific mechanical behaviors by leveraging the relationship between material properties and geometric configurations often not found in nature. Architected materials have been widely studied for different uses and applications including aerospace, biomedical, control systems, and soft robotics systems. Recent technological advances in additive manufacturing have simplified process such as prototyping, manufacturing of small and large-scale components, and the fabrication of medical devices. The recent rise of additive manufacturing has also facilitated the fabrication and exploration of architected materials. However, architected materials produced through additive manufacturing are highly susceptible to imperfections such as warping, waviness, layer inconsistencies, and precision /consistency issues. These imperfections impact the overall quality and mechanical behavior of the fabricated architected material. Understanding these imperfections and their influence on the mechanical response of architected materials is crucial for maximizing their potential and recognizing their current limitations.

The primary goal of our research is to perform uncertainty quantification (UQ) of the mechanical response and to understand the relationship between these imperfections and the mechanical behavior of architected materials. Specifically, through additive manufacturing, experimental testing, and finite element simulations, we aim to quantify the uncertainty associated with the effects of imperfections on the mechanical behavior of the architected material. Within this context, our research focuses on the role of imperfections in the buckling and post-buckling response of architected materials.

We have chosen to study hexagonal architected materials with embedded joint imperfections, which may be classified as "precision/consistency imperfections," subjected to compressive loading to induce buckling. Our methodology includes performing finite element simulations using Abaqus and conducting compressive testing with a Universal Testing Machine. We analyze the stress-strain response from both simulations and experiments to perform Verification and Validation (V&V) of our results. Joint distortions are introduced into our nominal "pristine" hexagonal architected materials as a normal distribution, altering joint positions to create the imperfect architected materials. These imperfect hexagonal architected materials are the central focus of our research. For the experiments, we additively manufacture these imperfect hexagonal architected materials using a hyperelastic resin and subject them to compressive loading. For simulations, we utilize Abaqus' built-in Plane Strain (CPE8H) elements, applying vertical displacement equal to approximately 20% strain to ensure buckling.

Preliminary results indicate the development of a streamlined simulation pipeline. A Monte-Carlo analysis of our imperfect lattices allowed us to retrieve statistical moments with confidence bounds of the mechanical response of hexagonal architected materials with embedded imperfections. This analysis provides a foundation for understanding and quantifying the uncertainties associated with imperfections in architected materials.

Presenting Author: Melvin Hernandez University of Texas at San Antonio

Presenting Author Biography: Melvin Hernandez is currently a M.S. student in Mechanical Engineering at the University of Texas at San Antonio (UTSA). He currently performs research at the Advanced Materials and Mechanical Systems Laboratory under PI Dr. David Restrepo. Prior to pursuing his master's degree, Hernandez did his undergraduate studies in Mechanical Engineering at UTSA. Hernandez' work focuses on studying uncertainty in the mechanical response of architected materials undergoing compressive forces. He works with Finite Element simulation software, experimental testing, programming with MATLAB and Python, and performs verification and validation.

Authors:

Melvin Hernandez University of Texas at San Antonio
David Risk University of Texas at San Antonio
Juan Navarro University of Texas at San Antonio
Mauricio Aristizabal University of Texas at San Antonio
Harry Millwater University of Texas at San Antonio
David Restrepo University of Texas at San Antonio