A predictive model for fracture in human ribs based on in vitro acoustic emission data

Abstract

Purpose The aim of this paper is to propose a fracture model for human ribs based on Acoustic Emission (AE) data. The accumulation of micro-cracking until a macroscopic crack is produced can be monitored by AE. This macro-crack propagation causes the loss of the structural integrity of the rib. Methods The AE technique was used in in-vitro bending tests of human ribs. The AE data obtained were used to construct a quantitative model that allows an estimation of the failure stress from the signals detected. The model predicts the ultimate stress with an error of less than 3.5% (even at stresses 15% lower than failure stress), which makes it possible to safely anticipate the failure of the rib. Results The Percolation Theory was used to model crack propagation. Moreover, a quantitative probability-based model for the expected number of AE signals has been constructed, incorporating some ideas of percolation theory. The model predicts that AE signals associated with micro-failures should exhibit a vertical asymptote when stress increases. The occurrence of this vertical asymptote was attested in our experimental observations. The total number of micro-failures detected prior to the failure is N ≈ 100 and the ultimate stress is σ_∞ = 197 + 62 MPa. A significant correlation (p < 0.0001) between σ_∞ and the predicted value is found, using only the first N = 30 micro-failures (correlation improves for N higher). Conclusions The measurements and the shape of the curves predicted by the model fit well. In addition, the model parameters seem to explain quantitatively and qualitatively the distribution of the AE signals as the material approaches the macroscopic fracture. Moreover, some of these parameters correlate with anthropometric variables, such as age or BMI. The proposed model could be used to predict the structural failure of ribs subjected to bending.