A comprehensive review of fiber-reinforced polymer-matrix composites under low-velocity impact

Composite materials have drawn significant attention across diverse disciplines owing to their excellent performance in loading bearing, corrosion resistance, deformation control, and thermal stability. The concept of composite materials can be traced back to ancient civilizations, where wooden strips, straws or wheat straws were ingeniously employed to reinforce clay structures and plywood. In the 1940s, due to the needs of the aviation industry, glass Fiber-Reinforced plastic (commonly known as fiberglass) was developed, giving rise to the name of composite materials. The laminated panels in composite materials have unique characteristics, such as the designability and the optimization of overall structural performance by adjusting geometric parameters. In consideration of composite materials mainly applied in the aerospace industry, the impact-induced damage during operation is one of the major concerns. Furthermore, the impact resistance performance heavily affects the applicable scope of laminated materials in various fields. This article presents a comprehensive review of the primary parameters influencing the impact resistance of Fiber-Reinforced Polymer-Matrix Composites (FRPMCs). Initially, the most influential parameters and the typical failure modes of FRPMCs under impact effects are introduced. Subsequently, this article outlines existing approaches to reduce the impact-induced damage of FRPMCs. Lastly, conclusive studies are conducted to elaborate on various parameters' influence on composite materials' impact resistance. After a detailed review of hundreds of research, this article aims at the recent achievements in composite materials against impact effects and the progress in mechanism analysis and material design. In the future, researchers need to focus on multi-scale, multi-physics field studies and model optimization. For example, more effort should be paid to explore the complex relationship between material parameters and impact performance, improve the accuracy of machine learning in prediction, and promote the application of composite materials.