Comparative Assessment of Chang–Chang and Tsai–Wu Failure Criteria for Predicting Low-Velocity Impact Damage in CFRP Laminates using LS-DYNA

Modern aircraft and high-performance cars increasingly rely on materials that are lighter and stronger than steel, yet they face a persistent vulnerability: the hidden bruise. Engineers build structures from layers of carbon-fiber-reinforced polymer, a composite material where incredibly strong fibers are bound together by a resin matrix. These laminates are designed to be tough, but they have a specific weakness when struck by a dropped tool, a piece of runway debris, or a bird. A low-velocity impact can occur at speeds slow enough that the surface of the material looks perfectly fine to the naked eye. However, beneath that smooth exterior, a complex network of internal cracks, delaminations, and broken fibers can form. This condition, known as barely visible impact damage, is dangerous because it silently robs the structure of its strength and stiffness, potentially leading to failure long after the initial strike. Because inspecting every square inch of a plane or car for these hidden defects is slow and expensive, engineers turn to computer simulations to predict exactly how and where this damage happens before a physical part is ever built.

A team of researchers from several institutions in India set out to test the reliability of two different mathematical rules used inside these computer simulations to predict how the carbon-fiber layers fail. They used a powerful software tool called LS-DYNA to create a virtual model of a carbon-fiber plate and simulate a heavy steel ball dropping onto it. The researchers wanted to know if the choice of failure rule mattered for the overall result. One rule, known as the Chang–Chang criterion, treats the breaking of the fibers and the cracking of the resin matrix as separate events, checking each one individually. The other, the Tsai–Wu criterion, combines all the stresses into a single, unified calculation to decide if the material has failed. The team built a virtual plate made of twenty-four layers of carbon fiber, arranged in a specific pattern, and dropped a rigid steel hemisphere weighing 1.85 kilograms onto it. They first calibrated their model against real-world experimental data from a previous study, ensuring their virtual setup matched reality with near-perfect accuracy in terms of the force measured during impact and the energy absorbed by the plate.

Once the model was validated, the researchers ran a series of controlled experiments in the computer to see how changing the thickness of the plate or the speed of the impact affected the outcome. They tested plates that were 5 millimeters and 7 millimeters thick, and they varied the impact energy from 10 joules up to 20 joules. The results showed that making the plate thicker significantly increased the force required to dent it, nearly doubling the peak force when the thickness increased from 5 to 7 millimeters. Thicker plates also absorbed slightly more energy, but the most striking finding was that the two different failure rules produced almost identical results for the overall behavior of the structure. Whether the software used the Chang–Chang rule or the Tsai–Wu rule, the predicted force on the impactor, the speed at which it bounced back, and the total energy absorbed by the plate were virtually the same.

This suggests that for engineers trying to predict the global response of a structure—how much it bends, how much force it feels, and how much energy it soaks up—the choice between these two specific mathematical rules does not change the answer. The difference between the two methods appears to lie only in the microscopic details of exactly which type of damage occurs at a specific point, such as whether a fiber breaks or a resin crack forms, rather than in the big-picture performance of the part. The study confirms that a single, well-validated computer model can reliably predict the impact response of carbon-fiber laminates across a range of thicknesses and energies. This provides a computationally efficient way for designers to estimate the extent of hidden damage and to build safer, more impact-resistant structures for aerospace and automotive applications, knowing that the fundamental physics of the impact are captured accurately regardless of which of these two common failure rules is selected.