<i>FractalAnalyzer</i>: A MATLAB Application for Multifractal Seismicity Analysis

Roy, Prasanta; Gupta, Das

doi:10.1785/0220150013

Cited by 16 publications

(5 citation statements)

References 51 publications

(57 reference statements)

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“…Previously, the spatio-temporal approach of fractal correlation dimension has helped in finding out the stressed zones and also focusing of microseismic events for many strong earthquakes like the Bhuj earthquake, earthquakes occurring in the North Western Himalayas, the Bam region of South Eastern Iran etc. [15][16][17][18][19][20][21][22] . Following in the same way here, an attempt has been made to use the fractal correlation dimension values obtained from the correlation integral method as a possible spatio-temporal signature to monitor the stress level in the overlying strata in the underground mine, both before and after roof collapse takes place (naturally or by induced blasting method).…”

Section: Methodsmentioning

confidence: 99%

“…Further Here the total number of pairs of events w.r.t one another in a fractal set having 50 events is represented by 'N' which is equal to 50 C 2 (=1225) and 'q' is the space which is taken as 2 for representing the microseismic events on 2D surface. 50-70 events window is considered as the optimum window length, as exceeding the window length would led to missing of the shorter patterns and decreasing the event window would have created difficulty in obtaining linear relation in log 10 C(r) versus log 10 r curve 21,22 . The distance between the events in the fractal set has been calculated with the help of P-wave travel time equation and is given as Eq.…”

Section: Methodsmentioning

confidence: 99%

“…micro fracturing under continuously changing stress conditions), its time of occurrence and the velocity of the P-wave generated is represented by x, y, z, t and v respectively [21][22][23][24][25][26] . Proceeding further through Eq.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Use of Correlation Fractal Dimension signatures for understanding the Overlying Strata Dynamics in Longwall Coal Mines

Mondal

Roy

Behera

2017

International Journal of Rock Mechanics and Mining Sciences

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Use of Correlation Fractal Dimension signatures for understanding the Overlying Strata Dynamics in Longwall Coal Mines

Mondal

Roy

Behera

2017

International Journal of Rock Mechanics and Mining Sciences

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“…Later, the estimated values have been assigned to the mean of the corresponding time window. ZMAP software is employed for estimating the temporal variations of b-value [Wiemer 2001] whereas the temporal evolution of D C is calculated by using FactalAnalyzer software developed by Roy and Gupta [2015]. Mitra et al [2015] suggested that the second major earthquake (M W 7.2) is alleged to have occurred due to the propagation of stresses on the adjacent segment of the same fault of the first major earthquake (M W 7.8).…”

Section: Methodsmentioning

confidence: 99%

Statistical analysis of aftershock sequences related with two major Nepal earthquakes: April 25, 2015, MW 7.8, and May 12, 2015, MW 7.2

Chingtham

Sharma

Chopra

et al. 2016

Annals of Geophysics

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Present study describes the statistical properties of aftershock sequences related with two major Nepal earthquakes (April 25, 2015, MW 7.8, and May 12, 2015, MW 7.2) and their correlations with the tectonics of Nepal Himalaya. The established empirical scaling laws such as the Gutenberg–Richter (GR) relation, the modified Omori law, and the fractal dimension for both the aftershock sequences of Nepal earthquakes have been investigated to assess the spatio-temporal characteristics of these sequences. For this purpose, the homogenized earthquake catalog in moment magnitude, MW is compiled from International Seismological Center (ISC) and Global Centroid Moment Tensor (GCMT) databases during the period from April 25 to October 31, 2015. The magnitude of completeness, MC, a and b-values of Gutenberg–Richter relationship for the first aftershock sequence are found to be 3.0, 4.74, 0.75 (±0.03) respectively whereas the MC, a and b-values of the same relationship for the second aftershock sequence are calculated to be 3.3, 5.46, 0.90 (±0.04) respectively. The observed low b-values for both the sequences, as compared to the global mean of 1.0 indicate the presence of high differential stress accumulations within the fractured rock mass of Nepal Himalaya. The calculated p-values of 1.01 ± 0.05 and 0.95 ± 0.04 respectively for both the aftershock sequences also imply that the aftershock sequence of first main-shock exhibits relatively faster temporal decay pattern than the aftershock sequence of second main-shock. The fractal dimensions, DC values of 1.84 ± 0.05 and 1.91 ± 0.05 respectively for both the aftershock sequences of Nepal earthquakes also reveal the clustering pattern of earthquakes and signifies that the aftershocks are scattered all around the two dimensional space of fractured fault systems of the Nepal region. The low b-value and low DC observed in the temporal variations of b-value and DC before the investigated earthquake (MW 7.2) suggest the presence of high-stress concentrations in the thrusting regimes of the Nepal region before the failure of faults. Moreover, the decrease of b-value with the corresponding decrease of DC observed in their temporal variations can primarily act as an indicator for possible prediction of major earthquakes in the study region.

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“…erefore, laboratoryscale AE experiments of coal samples being loaded to failure can be con dently utilised to demonstrate seismic hazard assessment associated with rock failures, which is hopefully to be applied in the eld-scale MS monitoring. Since rst introduced by Mandelbrot [8] to describe geometric patterns in nature, fractals or fractal dimensions have been widely applied in crustal seismology and earthquake engineering (e.g., [9] and references therein), MS in underground mining and tunnelling [10][11][12][13], and AE in the laboratory [14][15][16][17], towards quanti cation of their clustering properties. However, most of the current studies tended to focus on only one of the attributes (i.e., time, space, or energy) of AE/ MS information based on fractal capacity dimension.…”

Section: Introductionmentioning

confidence: 99%

Laboratory-Scale Insight into Fractal Dimension Indicators for Seismic Hazard Assessment Associated with Rock Failures

Cai

2022

Shock and Vibration

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Investigation of acoustic emission (AE) characteristics during laboratory tests of coal samples can provide useful guidance on the recognition of microseismicity (MS) precursors for seismic hazards in underground coal mining. In this study, a methodology, involving fractal dimension indices and a fuzzy comprehensive evaluation model, was developed and demonstrated using AE monitoring data in a uniaxial loading test of coal samples, which allows for a better and quantitative recognition of AE/MS precursors to seismic hazards associated with rock failures. In this methodology, the fractal dimension indices include six information dimension indices as well as three previously used capacity dimension indices. The assessment results were initially characterised as probabilities belonging to each of four risk levels (none, weak, moderate, and strong), and then output as a comprehensive result corresponding to one of these four risk levels. The results indicated that this developed methodology was able to recognise the AE precursors for rock failures.

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FractalAnalyzer: A MATLAB Application for Multifractal Seismicity Analysis

Cited by 16 publications

References 51 publications

Use of Correlation Fractal Dimension signatures for understanding the Overlying Strata Dynamics in Longwall Coal Mines

Use of Correlation Fractal Dimension signatures for understanding the Overlying Strata Dynamics in Longwall Coal Mines

Statistical analysis of aftershock sequences related with two major Nepal earthquakes: April 25, 2015, MW 7.8, and May 12, 2015, MW 7.2

Laboratory-Scale Insight into Fractal Dimension Indicators for Seismic Hazard Assessment Associated with Rock Failures

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