Model correlation involves comparing two different models. When models exhibit closely spaced or repeated modes, small perturbations in mass or stiffness can cause significant rotations of the mode shapes within their local subspace. Consequently, when using the modal assurance criterion (MAC) to assess model correlation in such scenarios, low MAC values may be obtained in the case of significant angles of rotation, even when there is a strong correlation between the models in terms of mass and stiffness. To address this inconsistency, a variation of the MAC, termed ROTMAC, is proposed. The ROTMAC serves as an indicator of shear by computing the MAC after rotating the mode shapes of one of the systems. To obtain the rotation matrix R, the QR decomposition or the polar decompositions can be applied. In this study, the effectiveness of ROTMAC is demonstrated by analysing the correlation between different experimental structures with closely spaced modes and their corresponding numerical models. A square glass plate and two two-story lab-scale structures were considered in this study. The
results show that ROTMAC successfully mitigates the effects of local rotations, leading to higher correlation values.