Advances in Delamination Analysis and Damage Prediction: A Comprehensive Review on Polymer Composite Materials

ABSTRACT The study simulation of delamination and damage prediction in composite materials is an important area of research that impacts various engineering applications, such as aerospace structures, significantly influencing their static, dynamic, buckling, fatigue, and crack resistance. To this end, this review presents a comprehensive analysis of modern approaches to predicting delamination and damage in polymer composites. In this regard, the review summarizes the views of 200 published studies and examines various computational methods, including finite element formulations, adaptive hierarchical kinematics, extended finite element methods (xFEM), cohesive zone models (CZM), and experimental methods, to evaluate their performance in damage prediction and delamination analysis. This review examines the strengths and weaknesses of each approach and highlights the need for further improvement in delamination analysis and damage prediction in the static, dynamic, buckling, and fatigue response and fracture behavior of composite structures. Dynamic analysis reveals that delamination substantially alters natural frequencies, damping characteristics, and vibration modes while influencing aeroelastic stability and impact resistance. Fatigue and fracture analyses demonstrate the critical roles of residual stress, fiber bridging, and material architecture in governing delamination propagation behavior. Experimental validation techniques, ranging from piezoelectric sensors to laser vibrometry and Lamb wave‐based structural health monitoring, are increasingly integrated with machine learning algorithms to enable real‐time damage detection and localization. Through systematic synthesis of these multidisciplinary advancements, this review identifies emerging trends including transitions toward higher‐order theories, physics‐informed machine learning approaches, and experiment‐numerical hybrid paradigms, collectively offering promising directions for enhancing advanced composite reliability and structural integrity.

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Publication Details

Journal
Engineering Reports
Published
2026-02-01
DOI
https://doi.org/10.1002/eng2.70620
Primary Topic
Mechanical Behavior of Composites
Type
article
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article

Advances in Delamination Analysis and Damage Prediction: A Comprehensive Review on Polymer Composite Materials

Mesfin Kebede Kassa, Ananda Babu Arumugam, Dhivya Elumalai, Yitbarek Gashaw Tadesse et al.
Engineering Reports
Mechanical Behavior of Composites
article

Advances in Delamination Analysis and Damage Prediction: A Comprehensive Review on Polymer Composite Materials

Mesfin Kebede Kassa, Ananda Babu Arumugam, Dhivya Elumalai, Yitbarek Gashaw Tadesse, Mohit Gupta
article en

Abstract

ABSTRACT The study simulation of delamination and damage prediction in composite materials is an important area of research that impacts various engineering applications, such as aerospace structures, significantly influencing their static, dynamic, buckling, fatigue, and crack resistance. To this end, this review presents a comprehensive analysis of modern approaches to predicting delamination and damage in polymer composites. In this regard, the review summarizes the views of 200 published studies and examines various computational methods, including finite element formulations, adaptive hierarchical kinematics, extended finite element methods (xFEM), cohesive zone models (CZM), and experimental methods, to evaluate their performance in damage prediction and delamination analysis. This review examines the strengths and weaknesses of each approach and highlights the need for further improvement in delamination analysis and damage prediction in the static, dynamic, buckling, and fatigue response and fracture behavior of composite structures. Dynamic analysis reveals that delamination substantially alters natural frequencies, damping characteristics, and vibration modes while influencing aeroelastic stability and impact resistance. Fatigue and fracture analyses demonstrate the critical roles of residual stress, fiber bridging, and material architecture in governing delamination propagation behavior. Experimental validation techniques, ranging from piezoelectric sensors to laser vibrometry and Lamb wave‐based structural health monitoring, are increasingly integrated with machine learning algorithms to enable real‐time damage detection and localization. Through systematic synthesis of these multidisciplinary advancements, this review identifies emerging trends including transitions toward higher‐order theories, physics‐informed machine learning approaches, and experiment‐numerical hybrid paradigms, collectively offering promising directions for enhancing advanced composite reliability and structural integrity.

Engineering ReportsVol. 8(2)
Jain University (IN), Noida International University (IN), Wollo University (ET), Addis Ababa Science and Technology University (ET), Dehradun Institute of Technology University (IN)
Openalex Percentile: Top 70%
Mechanical Behavior of Composites
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