A stochastic model for soft tissue failure using acoustic emission data

Sánchez-Molina, David; Martínez-González, Eva; Velázquez-Ameijide, Juan; Llumà, Jordi; Soria, M.C. Rebollo; Arregui‐Dalmases, Carlos

doi:10.1016/j.jmbbm.2015.07.002

Cited by 14 publications

(26 citation statements)

References 26 publications

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“…This model was verified to be able to capture the major microscopic mechanisms of the deterioration behaviors against the experimental results [41]. Recently, Sa'nchez-Molina et al [42] proposed a stochastic model for modelling the soft tissue failure under monotonic loading by combining the FBM and AE. The relationship between fiber failure number and AE counts and the relationship between damage variable and AE cumulative energy were both examined.…”

Section: Introductionmentioning

confidence: 85%

“…Although several researchers regarded the AE counts as an unreliable indicator of damage, it is considered the most direct response to the microstructural variation in materials [46]. A number of works on studying the relationship between fatigue behaviors and AE responses of materials have been conducted by using AE counts [15,17,42,[46][47][48][49][50][51][52][53][54][55]. Based on AE counts, the literature [56,57] defined a new AE parameter, average frequency (AF), for fracture mode classification.…”

Section: Acoustic Emission Quantification Of Fatigue Damagementioning

confidence: 99%

“…It is also noted that the decline of an application of AE counts [15,42,[46][47][48][49][50][51][52][53][54][55], even those with certain modifications [17,18], will result in a subsequent decline of the application of average frequency (AF) and others [56,57]. The reason is concluded that, if a large variation of AE counts could be caused by changing a threshold by only a small proportion as one who claims, while only a relatively small variation of AE duration could be generated by the mentioned changing, the average frequency (AF) could obtain a larger variation subsequently.…”

Section: Acoustic Emission Quantification Of Fatigue Damagementioning

confidence: 99%

“…Precisely, the amounts of the energy dissipation resulted from those types of microscopic events are usually different from each other. Moreover, it is found that there are significant variations in energy dissipation resulted from a single mode-I crack initiation/growth event (modeled by fiber failures and named microfailures in the literature [42]) in different time.…”

Section: Acoustic Emission Quantification Of Fatigue Damagementioning

confidence: 99%

“…Note that this work only focuses on the damage and AE responses of the concrete materials (i.e., the representative volume elements (RVEs)) due to the sophisticated behaviors under fatigue loading, although a number of works have been contributed by researchers concerning that of reinforced concrete structures. Considering that the materials' behaviors are essential for further analysis of the mechanical behaviors of structures, a great number of studies have been already conducted in the literature [14,15,17,19,28,29,31,42,43]. In addition, the damages of concrete structures subjected to mode-I, mode-II, and mixing mode loading were classified by using AE [3].…”

Section: Introductionmentioning

confidence: 99%

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Damage Quantification in Concrete under Fatigue Loading Using Acoustic Emission

Shan

Xiao

et al. 2019

Journal of Sensors

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Acoustic emission (AE) is an effective nondestructive evaluation method for assessing damage in materials; however, few works in the literature have focused on one quantification method of damage in concrete under fatigue loading by using AE for characterizing the entire three main deterioration behaviors simultaneously. These deterioration behaviors include Young’s modulus degradation, fatigue total strain, and residual strain development. In this work, an AE quantification method of fatigue damage in concrete was developed, by combining AE and a fiber bundle-based statistical damage model (fiber bundle-irreversible chain model). By establishing a relationship between normalized AE counts and the damage variable based on the fiber bundle-irreversible chain model, the method was proposed. Additionally, this method was verified against the experimental results. It is able to capture the mechanisms of damage accumulation and characterize the three deterioration behaviors simultaneously.

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Section: Introductionmentioning

confidence: 85%

Section: Acoustic Emission Quantification Of Fatigue Damagementioning

confidence: 99%

Section: Acoustic Emission Quantification Of Fatigue Damagementioning

confidence: 99%

Section: Acoustic Emission Quantification Of Fatigue Damagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Damage Quantification in Concrete under Fatigue Loading Using Acoustic Emission

Shan

Xiao

et al. 2019

Journal of Sensors

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

García-Vilana¹,

Sánchez-Molina²,

Llumà³

et al. 2021

Medical Physics

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Purpose The aim of this paper is to propose a fracture model for human ribs based on acoustic emission (AE) data. The accumulation of microcracking until a macroscopic crack is produced can be monitored by AE. The macrocrack 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 microfailures 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 Body Mass Index. The proposed model could be used to predict the structural failure of ribs subjected to bending.

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A probabilistic model for murder weapon identification using stab-marks in human ribs

Sánchez-Molina¹,

Galtés

García-Vilana³

et al. 2023

Int J Legal Med

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The aim of this article is to provide a scientific and statistical basis to identify the murder weapon in stabbing cases from the geometric characteristics of the stab-marks left on human ribs. For this purpose, a quantitative predictive model is developed, based on geometric measurements of the stab-mark and its location along the rib. A general method based on Bayesian inference and probabilities is used for the model development, rather than a deterministic model given its inability in certain occasions to identify the murder weapon. Following the process explained in this article to collect the stab-mark information required, the complete probabilistic model exposed attained a high accuracy in the identification of the murder weapon between two macroscopically identical blades with a microscopic alteration in one of them (more than 90% of correct identification is achieved).

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A stochastic model for soft tissue failure using acoustic emission data

Cited by 14 publications

References 26 publications

Damage Quantification in Concrete under Fatigue Loading Using Acoustic Emission

Damage Quantification in Concrete under Fatigue Loading Using Acoustic Emission

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

A probabilistic model for murder weapon identification using stab-marks in human ribs

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