From criticality to final collapse: Evolution of the “b-value” from 1.5 to 1.0

Carpinteri, Alberto; Lacidogna, Giuseppe; Puzzi, Simone

doi:10.1016/j.chaos.2008.04.010

Cited by 176 publications

(104 citation statements)

References 21 publications

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“…Now, let us see the result of fractal dimension. Some researches show the decrease of the fractal dimensions before a great rupture (Carpinteri et al, 2009;Goltz, 1997;Kiyashchenko et al, 2004;Lee et al, 2008;Matcharashvili et al, 2000;Radulian and Trifu, 1991). Because the correlation dimension D 2 is the most typical in the fractal dimensions, we only research D 2 in this paper.…”

Section: Local Scaling Propertymentioning

confidence: 98%

“…Li (lqdzjybzx@126.com) has also been shown in multifractal research on seismic activity that the spectrum of generalised dimensions and the singularity spectrum display characteristic changes before large earthquakes (Caruso et al, 2006;Dimitriu et al, 2000;Nakaya, 2005;Roy and Padhi, 2007). Some results have confirmed that the decrease in fractal dimension, the steepening of curves in the generalised dimension spectrum and the broadening of the value range in the singularity spectrum, can be taken as indicators of an unstable state of an earthquake system before a large rupture (Carpinteri et al, 2009;Goltz, 1997;Kiyashchenko et al, 2004;Lee et al, 2008;Matcharashvili et al, 2000;Radulian and Trifu, 1991;Telesca et al, 2005;Telesca and Lapenna, 2006). However, there are some shortcomings in the research: the mono-fractal dimension is not sufficient to characterise heterogeneous fractals (Grassberger and Procaccia, 1984;Kentz and Schreiber, 1997), while the generalised dimension spectrum and singularity spectrum can only represent a global description of the scaling properties (Chhabra and Jensen, 1989;Grassberger, 1983).…”

Section: Introductionmentioning

confidence: 95%

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Local scaling property of seismicity: an example of getting valuable information from complex hierarchical system

2010

Nonlin. Processes Geophys.

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Abstract. In order to get valuable information about the scale invariance in the process of seismogeny of Lijiang M 7.0 earthquake, the scaling property of the interevent time series of the seismic sequences for Lijiang area in China were studied by using the method of the local scaling property, the generalised dimension spectrum, and the correlation dimension. It is found that there is a clear characteristic variation of local scaling property prior to Lijiang M 7.0 earthquake while there is no characteristic variation of the generalised dimension spectrum and the correlation dimension. The reason for producing this phenomenon is that the fractal seismic system is a complex hierarchical system. For such a system, searching for a relevant choice in application of the three methodologies is needed. Compared with the generalised dimension spectrum and mono-fractal dimension which focus on the global description of the scaling properties of fractal objects, the local scaling property emphasizes the local features, and can give the local information of the singularity of the fractal system, therefore, it is easier for us to get valuable information from complex hierarchical structure with this method.

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Section: Local Scaling Propertymentioning

confidence: 98%

Section: Introductionmentioning

confidence: 95%

Local scaling property of seismicity: an example of getting valuable information from complex hierarchical system

2010

Nonlin. Processes Geophys.

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“…In analogy with seismology, this statement is expressed by the Gutenberg-Richter relationship [13] [16]:…”

Section: History Parameters and B-valuementioning

confidence: 99%

“…Some authors [16] suggest that, based on the fractal geometry approach in the mechanics of damage and fracture of heterogeneous materials, b-value should approach 1.0 with the evolution of damage. However, this conclusion is only partly supported by experimental observations [13,[24][25][26][27] (Fig.…”

Section: History Parameters and B-valuementioning

confidence: 99%

“…This has been codified by the Japanese standard [10]; 2. The use of b-value [11][12][13][14], and, more recently, by Carpinteri et al [15], which proposed analytical correlation with theory of fracture [16] and numerical models [17] [18]. The approach of linking AE experimental data to numerical simulations seems interesting, and quite unexplored at this stage; 3.…”

Section: Introductionmentioning

confidence: 99%

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Acoustic Emissions analysis of a four-point bending test on a Reinforced Concrete beam

et al. 2017

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Abstract. Assessment of existing structures by means of non-destructive techniques is an important research topic in modern engineering, because of its potential in estimating structural health status without introducing undesired damage. Among several recognized techniques, Acoustic Emission (AE) analysis is growing interest in the scientific community, since it can be used to detect the initiation of cracking processes, to determine cracking typology and to extract other information from the specimen. In this paper, the authors present the results of a four-point bending test on a Reinforce Concrete (RC) beam, performed at the University of Salerno. The test has been conducted according to a loading protocol characterised by several loading-unloading cycles, and both mechanical and acoustic data have been recorded. The results will be presented in terms of standard AE parameters, commonly adopted in literature, such as Felicity ratio, signal strength and cumulative signal strength, historic index and b value. It will be underlined that these parameters allow to detect interesting moments of the phenomenon (cracking onset and development) and to assess the damage of the structure.

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Damage detection of SFRC concrete beams subjected to pure torsion by integrating acoustic emission and Weibull damage function

Behnia

Chai

Ranjbar

et al. 2015

Struct. Control Health Monit.

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Summary In some cases, torsion is the dominant or critical factor contributing to the failure of a concrete member. This research proposes a novel damage detection method for fiber‐reinforced concrete beams subjected to pure torsion loading by statistical analysis of acoustic emission (AE) data. Concrete beams with varying water/cement ratios and different fiber volume fractions were subjected to pure torsion during AE monitoring. It was found that the cumulative AE event with respect to the twist angle correlated well to the mechanical loading. A Weibull rupture probability distribution is introduced to quantitatively predict the mechanical damage behavior under pure torsion. A bi‐logarithmic regression analysis is carried out to calibrate the Weibull damage distribution function with the detected AE data in order to characterize the torsion fracture process. Moreover, a quantitative approach by means of b‐value results is presented in this article to further analyze damage and fracture process. Torsion fracture properties were correlated to the AE parameters, and it was shown that the magnitudes of AE parameters were influenced significantly by mechanical properties of specimens. Therefore, AE would be suitable to describe the fracture of concrete specimens subjected to torsion. Copyright © 2015 John Wiley & Sons, Ltd.

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From criticality to final collapse: Evolution of the “b-value” from 1.5 to 1.0

Cited by 176 publications

References 21 publications

Local scaling property of seismicity: an example of getting valuable information from complex hierarchical system

Local scaling property of seismicity: an example of getting valuable information from complex hierarchical system

Acoustic Emissions analysis of a four-point bending test on a Reinforced Concrete beam

Damage detection of SFRC concrete beams subjected to pure torsion by integrating acoustic emission and Weibull damage function

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