CompSTLar project turns TPC materials into their own SHM systems

Editor’s note: CW aims to move beyond the algorithm with this new content format. The “snapshot” delivers brief, focused insights designed to quickly inform readers on key composite developments shared by industry players without sacrificing relevance or clarity. 

The EU project CompSTLar is focused on advancing the design, manufacturing, maintenance and recycling of high-performance composite aerostructures for next-generation aircraft. This includes topics like zero-defect manufacturing, digital twins and a modular digital pipeline to improve data flow throughout the supply chain as well as structural health monitoring (SHM) and more.

One key topic is exploring how laser-induced graphene (LIG) patterned directly on and within the layers of thermoplastic composite (TPC) parts can provide aircraft structures with their inherent structural health monitoring (SHM) system, tightly connected to simulations and digital twins.

Seamless sensors within structural parts = live data

Writing LIG-based sensors directly onto layers of the TPC (embedded) creates a very sensitive and seamless conductive nervous system on the part itself with no extra sensors or heavy wiring. This system is also conformal, lightweight and compatible with aeronautic composites, enabling continuous monitoring of strain, damage growth and local hot spots. Thus, the physical part stops being “just hardware” and becomes a data source for its own digital twin.

Virtual stress tests = predictive insight

Once the part is sensorized, CompSTLar combines structural simulations with real sensor data that can explore thousands of virtual load cases and “what-if” scenarios. They also use LIG-based measurements to validate and update the model. Differences between the model and reality reveal hidden weak spots long before there is visible damage on the part.

Instead of asking, “Did something break?” it’s now possible to ask, “Where is this part most likely to fail next?”

Closing the loop: from monitoring to prediction

For TPC aerostructures, this enables:

• Condition-based maintenance instead of fixed inspection intervals.
• Design feedback with in-service data feeding future simulations and layouts.
• Digital records over the full life of the part, from first load to end-of-life decisions.

In short: Laser-induced graphene turns TPC into self-reporting structures, and simulation turns that data into reliable predictions.

Read more about this work in LinkedIn at on CompSTLar’s LinkedIn page. Also read more about sensors in CW’s Sensors knowledge center and article archive, as well as articles on digital twins, zero-defect manufacturing and SHM.