This presentation details the use of fibre reinforced polymer matrix (FRP) composites in maritime applications as part of the Strength in Places project, ‘Decarbonisation of Maritime Transportation’. Three research areas are considered: (i) modelling and assessing impact damage in composites marine structures, (ii) hybrid composite-metal laminates for bolted joints, and (iii) application of artificial intelligence in the failure prediction of composite materials. In the first study, an in-house intralaminar damage model, capturing both fibre-dominated and matrix-dominated damage, along with an available interlaminar cohesive model are used within an explicit dynamic finite element formulation for modelling low velocity impact (LVI) damage and compression-after-impact (CAI) performance of composite maritime structures [1]. In the second study, a modified transverse crack tensile (mTCT) test method is extended for the calculation of mode II fracture toughness [2]. A parametric study is conducted using finite element analysis to determine the design parameters. Mechanical tests and digital image correlation (DIC) technique are then used to show that the proposed test setup can be extended to composite-metal laminates. In the third study, a data-driven probability embedded failure criterion is used for the failure prediction of unidirectional FRP composite materials under biaxial stress states based on micromechanical modelling and artificial neural networks (ANNs) [3]. High-fidelity 3D representative volume element (RVE) models are used for the generation of failure data sets. REFERENCES [1] S. L. J. Millen, Z. Ullah, and B. G. Falzon. "On the importance of finite element mesh alignment along the fibre direction for modelling damage in fibre-reinforced polymer composite laminates." Composite Structures 278 (2021). [2] T. Scalici , Z. Ullah, B. Falzon, G. Catalanotti, A novel experimental method for the assessment of the mode II fracture behaviour of metal-polymer composites interfaces, International Symposium on Dynamic Response and Failure of Composite Materials, Island of Ischia, 21 - 24 June 2022. [3] L. Wan, Z. Ullah, D. Yang, B. G. Falzon “Probability embedded failure prediction of unidirectional composites under biaxial loadings combining machine learning and micromechanical modelling”, Composite Structures (Accepted). This presentation details the use of fibre reinforced polymer matrix (FRP) composites in maritime applications as part of the Str