Development of Digital Twin Technology as a Demonstrator for Real-Time Integrity Assessment of Crack Growth in Composite Tensile Specimens
TWI Industrial Member Report 1217-2026
By Owen Rees-Lloyd and Sam Hurrell
Industrial Need
Digital twins with real-time decision support are increasingly required to manage the structural integrity of safety critical composite structures across industry. The primary industrial need addressed by this work is the ability to identify, assess and respond to damage at an early stage, while avoiding unnecessary downtime or overly conservative inspection regimes. These limitations can either lead to unplanned failures or excessive maintenance routines that reduce availability of an asset or increase operating costs.
Digital twins offer a potential solution by combining structural models with inspection and monitoring data to support informed, data driven risk-based decision making. If supported by accurate and timely condition data, digital twins can increase confidence in operations, reduced unplanned downtime, lower operating costs, optimise inspection planning, and enable proactive maintenance strategies. In addition, they offer the potential to optimise operating conditions, extend asset life and provide continuous assessment of failure risk.
A key barrier to the uptake of digital twins for asset integrity management is the availability of reliable condition monitoring data that can be used as meaningful model inputs. Structural health monitoring (SHM) techniques such as acoustic emission (AE) have the potential to detect damage as it occurs. However, the viability of AE as an input to digital twins, particularly for composite materials requires further investigation.
This project aims to demonstrate the feasibility of informing a digital twin capable of predicting failure loads by combining AE data with finite element analysis (FEA) and X-Ray Computed Tomography (XCT). By assessing the strengths and limitations of AE for damage detection, location and sizing, this work aims to identify the role of AE within digital twins for composite structures in order to support safer and more informed asset management.
Key Findings
- Acoustic emission data corresponded well with the findings of the X-Ray Computed Tomography, particularly in identifying the onset and location of cracking within composite specimens.
- Finite element analysis (FEA) models show good correlation with experimental testing including the specimen fracture force, regions of fracture and drops in load during testing associated with crack growth.
- AE datasets demonstrated the capability to differentiate the different types of damage mechanisms within composite specimens, such as matrix cracking and fibre matrix debonding.
- AE was highly effective as a damage detection and location tool but not for reliable crack sizing in composite specimens.
Impact
Although the digital twin developed in this work does not represent a complete integrated system, the combined AE and FEA results demonstrate the feasibility of a digital twin based approach for composite damage assessment. Progressive increases in cumulative AE energy during cyclic loading, together with high amplitude AE signals prior to final tensile failure, confirm that AE is capable of detecting damage before critical failure occurs.
These results support the use of AE as an effective early warning tool within a digital twin. Further development is required to overcome current hardware and integration limitations, particularly to enable live AE data to be fed directly into the digital twin model.