The present work extends non-extensive statistical formulation to the inter-event time dis- tribution of acoustic emission (AE) events generated by the fracture process in plain concrete. The timeinterval between two consecutive events can be defined as inter-event time and the…
The present work extends non-extensive statistical formulation to the inter-event time dis- tribution of acoustic emission (AE) events generated by the fracture process in plain concrete. The timeinterval between two consecutive events can be defined as inter-event time and the distribution of inter-event time is pivotal for understanding the underlying event-generating process. The magnitude and inter-event time of AE events may be correlated, resulting in repeated intervals of clustered AE activity and quiescence often observed in the concrete fracture process. The crack size is considered to be correlated with AE wave magnitude (amplitude) therefore, the long-tailed magnitude distribu- tion is usually used to infer the extent of cracking. Similarly, the inter-event time distribution can be used as an indicator of the frequency or rate of occurring events. The AE phenomena resulting from the fracture process exhibit non-Poissonian behavior, meaning that the time intervals between AEevents are not independent and identically distributed. AE inter-event time distribution in con- crete has not been explored as much as magnitude distribution however, few studies including rock fracture, concrete under compression, and seismology reported long-tailed behavior of the inter-event time distribution often modeled by power-law, log-normal, Weibull, Gamma as well as q-statistical exponential distributions. Recently, Burud and Chandra Kishen proposed two q-statistical distribu- tion functions based on exponential and power law ansatzes. The power law ansatz-based distribution function is shown to better represent AE magnitude distribution in concrete. We explore the expo- nential ansatz-based distribution function to inspect AE inter-event time distribution. The variation of q-statistical parameters for AE inter-event time distribution with respect to specimen size is discussed in detail.