Investigating the aging damage evolution characteristics of layered hard sandstone using digital image correlation

•Associative dimension of AE ring counts had a negative correlation with peak stress.•The peak correlative dimension implied a judgmental marker for damage aggravation.•The displacement field had a spatiotemporal dissimilation characteristics.•The damage constitutive model was established by introducing the influence factor. Layered sedimentary hard rock is an important inducing factor that deforms the tunnel structure. To explore the aging deformation and mechanical characteristics of damaged layered hard sandstone, the digital image correlation technique and acoustic emission (AE) was used to obtain the displacement and strain fields and AE signals under uniaxial compression. The results showed that mechanical parameters and failure models had significant heterogeneity. The more significant the layering effect, the less obvious the bearing capacity. The AE ringing count has fractal characteristics and associative dimensions of 0-90° samples were 1.2067, 1.3497, 1.6788, 1.7400 and 1.4799, respectively. The greater the bearing strength, the greater the associative dimension. The associative dimension had a phase response to the applied loading stress, and the rupture process had dimensionality reduction features. The peak information of correlative dimension during plastic deformation was used as an effective index for internal damage aggravation. The dissimilation phenomenon of displacement field caused synergistic features and resulted in spatiotemporal response characteristics. The displacement fields had an initial disordered distribution and evolved to an ordered structure, and then localized dissimilation occurred in banded dissociation zones. The dislocation performance of isodisplacement lines containing potential cracks and formation of band-like dissimilation zone indicated penetration of cracks. The influence factor was introduced to establish a segmental statistical damage model and the performed analyses revealed the model's accuracy. The more obvious the structural effect, the higher the influence factor.