Advances in the analysis of honeycomb structures: A comprehensive review

Abstract

Honeycomb structures are widely used in engineering due to their excellent mechanical properties and lightweight design. However, their discrete heterogeneity creates significant challenges in mechanical analysis and design. Over recent decades, substantial advancements have been made in predicting honeycomb performance. This review systematically explores these developments, emphasizing the theoretical analysis of their linear, nonlinear, and non-uniform properties. It provides a detailed review of analytical models, numerical simulation methods, and experimental validations, emphasizing the critical importance of comprehensive and high-quality datasets in enhancing the understanding and prediction of honeycomb behavior under varied conditions.

Despite these advancements, challenges persist. Current models often lack generality, require extensive high-quality datasets, and face high computational costs in complex engineering applications. Accurate modeling of material heterogeneity and integrating multi-scale effects remain unresolved, limiting the broader application of honeycomb structures.

Looking forward, integration of machine learning with artificial intelligence is anticipated to enhance model accuracy and computational efficiency. Developing universal datasets for diverse honeycomb materials and adopting hybrid simulation-experiment approaches will help address complex engineering challenges.

This review emphasizes the need for adaptable models, data-driven techniques, and efficient computational frameworks. It provides a comprehensive overview of recent progress, persistent challenges, and emerging trends, offering valuable insights to guide future research and engineering applications.