Structural Adhesives: Fatigue Life
Predicting the fatigue life of adhesively bonded structures is an important aspect of the design and process optimisation in many industrial applications, including aircraft, railway and other engineering sectors. The main goal of this use case is to facilitate the fatigue life prediction of adhesively bonded structures using data-driven models in a way that maximises the accuracy while minimising the number of required experiments and therefore the design and go-to-market time. To this end, a workflow will be created ensuring the interoperability of data related to material properties and fatigue life and a sequential learning framework. In particular, the following data currently available will be made interoperable with the DOME 4.0: static tensile properties of adhesives, fatigue lifetime curves of adhesives and damage evolution curves. The sequential learning software tools focus the optimisation search both on high uncertainty candidate materials and high-performing regions of the parameter space, thus enabling novel material exploration in a seamless manner.
Examples of companies profiting from this work are small, medium and largescale companies during product development, as well as engineering consulting companies providing design, modelling and simulation that do not have access to experimental facilities would benefit by buying data required for fatigue assessments.