Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30135
Evaluating Hurst Parameters and Fractal Dimensions of Surveyed Dataset of Tailings Dam Embankment

Authors: I. Yakubu, Y. Y. Ziggah, C. Yeboah

Abstract:

In the mining environment, tailings dam embankment is among the hazards and risk areas. The tailings dam embankment could fail and result to damages to facilities, human injuries or even fatalities. Periodic monitoring of the dam embankment is needed to help assess the safety of the tailings dam embankment. Artificial intelligence techniques such as fractals can be used to analyse the stability of the monitored dataset from survey measurement techniques. In this paper, the fractal dimension (D) was determined using D = 2-H. The Hurst parameters (H) of each monitored prism were determined by using a time domain of rescaled range programming in MATLAB software. The fractal dimensions of each monitored prism were determined based on the values of H. The results reveal that the values of the determined H were all within the threshold of 0 ≤ H ≤ 1 m. The smaller the H, the bigger the fractal dimension is. Fractal dimension values ranging from 1.359 x 10-4 m to 1.8843 x 10-3 m were obtained from the monitored prisms on the based on the tailing dam embankment dataset used. The ranges of values obtained indicate that the tailings dam embankment is stable.

Keywords: Hurst parameter, fractal dimension, tailings dam embankment, surveyed dataset.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.2643906

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 212

References:


[1] Garland, R. (2011), “Acid mine drainage” the chemistry. pp. 50-52.
[2] Wehleekema, S. (2017), “Assessment of Iron Ore Mining Gangues in Itakpe for Secondary Recovery of Other Metal Values”, Published MSc Thesis work, African University of Science and Technology, Abuja, Nigeria, 59pp.
[3] Thomas, A. (2016), “Effect of oxidative weathering on in vitro bioaccessibility of toxic substances in contaminated, mine tailings-borne dust”, published MSc Thesis, The University of Arizona, Arizona, USA. pp.82.
[4] Davies, M. P. (2002), ‘Tailings impoundment failures: are geotechnical engineers listening’, Geotechnical News, vol. 20, no. 3, pp. 31–36.
[5] Wit T and Olivier G., (2018),” Imaging and monitoring tailings dam walls with ambient seismic noise” Paste 2018 – RJ Jewell and AB Fourie (eds) Australian Centre for Geomechanics, Perth, ISBN 978-0-9924810-8-7, pp. 455-463.
[6] Ganesh, M. (2006), “Monitoring of Tailings Dams with Geophysical Methods” (Unpublished) Thesis, Luleå University of Technology, pp. 93
[7] ICOLD, (1995), “Dam Failures Statistical” Bulletin 99, published by The International Commission on Large Dam together with UNEP, United Nations Environmental Program.
[8] Wei, L., and Chang, W. (2011), “GPS in the Tailings Dam Deformation Monitoring” Procedia Engineering, Vol. 26, pp.1648-1657.
[9] Flandrin, P, Rilling, G., and Goncalves, P. (2004), “Empirical Mode Decomposition as a Filter Bank”, IEEE Sig. Proc. Lett. Vol. 11, No. 2, pp.112-114.
[10] Mandelbrot, B. B. (1977), “Fractals Form, Chance, and Dimension”, W. H. Freeman and Company, San Francisco, USA, 1977. N-7491 Trodheim, Norway, pp.6; pp. 57-60.
[11] Mandelbrot, B.B, and Wallis, J. R. (1969), “Robustness of the rescaled range R/S in the measurements of noncyclic long-run statistical dependence, Water Resources, 5. pp. 967-988.
[12] Gui, L., Yin, K., and Glade, T. (2016), “Landslide displacement analysis based on fractal theory, in Wanzhou District, Three Gorges Reservoir”, Faculty of Engineering, China University of Geosciences, Wuhan, China; Department of Geography and Regional Research, University of Vienna, Vienna, Austria. pp. 1707-1725.
[13] Asklunel, R., and Eldvall, B. (2005), “Contamination of Water Resources in Tarkwa Mining Area of Ghana”, (Unpublished) MSc Thesis, Department of Engineering Geology, Royal Institute of Technology, LTh Ekosystemteknk, pp. 1-72.
[14] Boye, C. B., Peprah, M. S., and Kodie, N. K. (2018), “Geographic Assessment of Telecommunication Signals in a Mining Community: A Case Study of Tarkwa and Its Environs”, Ghana Journal of Technology, Vol. 2, No. 2, pp. 41-49.
[15] Kortatsi, B. K. (2004), “Hydrochemistry of Groundwater in the Mining Area of Tarkwa-Prestea, Ghana”, (Unpublished) PhD Thesis, University of Ghana, Legon-Accra, Ghana, pp. 1-45.
[16] Yakubu, I., Ziggah, Y. Y., and Peprah, M. S. (2018), “Adjustment of DGPS Data using Artificial Intelligence and Classical Least Square Techniques”, Journal of Geomatics, Vol. 12, No. 1, pp. 13-20.\
[17] Peprah, M. S., Ziggah, Y. Y., and Yakubu, I. (2017), “Performance Evaluation of the Earth Gravitational Model (EGM2008) – A Case Study”, South African Journal of Geomatics, Vol. 6, No. 1, pp. 47-72.
[18] Hurst, H. E. (1951), “Long term Storage of reservoirs: an Experimental study”, Transactions of the American Society of Civil Engineers, Vol. 116, pp. 770-799.
[19] Mandelbrot, B. and van Ness, J. (1968), “Fractional Brownian Motions, Fractional Noises and Applications” SIAM Review, Vol. 10, No. 4, pp. 422-437
[20] Mandelbrot, B. (1970), “Analysis of Long-Run Dependence in Economic: The R/S Technique” Econometrica, Vol. 39, pp. 107-108
[21] Hurst, H. E., R. P. Black, and Y. M. Simaika (1978), “The Nile Basin” Vol. 11. Nile Control Department, Ministry of Irrigation, Cairo, Egypt.
[22] Hamed, K. H. (2007), “Improved Finite-Sample Hurst Exponent Estimates Using Rescaled Range Analysis” Water Resour. Res., 43, W04413, doi: 10.1029/2006WR005111
[23] Mandelbrot, B. B., and J. R. Wallis(1969a), “Robustness of the Rescaled Range R/S in the Measurement of Noncyclic Long Run Statistical Dependence “, Water Resour: Res., Vol. 5, pp. 967-987
[24] Klemes, V., R. Srikanthan, and T. A. McMahon (1981), “Long-Memory Flow Models in Reservoir Analysis” What is their Practical Value?, Water Resour. Res., Vol. 17, pp.737-751
[25] Hosking, J. R. M. (1984), “Modeling Persistence in Hydrological Time Series Using Fractional Differencing” Water Resour. Res., Vol. 20, No. 12, pp. 1898-1908
[26] Mandelbrot, B. B., and J. R. Wallis (1969b), “Computer Experiments with Fractional Gaussian Noise” Part 1, 2, and 3, Water Resour. Res., Vol 5, No. 1, pp.228-267
[27] Karner, O. (2002), “On Nonstationary and Antipersistency in Global Temperature Series”, J. Geophys. Res., 107(D20), 4415, doi:10.1029/2001JD002024
[28] Lo, A. W. (1991), “Long–Term Memory in Stock Market Price”, Econometrica, Vol. 59, No. 5, pp.1279-1313.
[29] Barkoulas, J., W. Labys, and J. Onochie (1999), “Long Memory in Commodity Future Prices”, Financ. Rev., pp.117-132
[30] Giraitis, L., P. Kokoszka, R. Lepuis, and G. Teyssiere (2003), “Rescaled Variance and Related Tests for Long Memory in Volatility and Levels” J. Econom., Vol. 112, pp. 265-294.
[31] Kristoufek, L. (2010), “Rescaled Range Analysis and Detrended Fluctuation Analysis: Finite Sample Properties Confidence Intervals” AUCO Czech Economic, Review 4, pp.236-250
[32] Weron, R. (2002), “Estimating Long-Range Dependence: Finite Sample Properties and Confidence Intervals”, Physica A, Vol. 312, pp.285-299
[33] Taqqu, M., Teverosky, W. and Willinger , W. (1995), “Estimators for Long –Range Dependence: An Empirical Study” Fractals, Vol. 3, No. 4, pp.785-798
[34] Di Matteo, T. (2007), “Multi-Scaling in Finance “Quantitative Finance,Vol. 7, No. 1, pp.21-36
[35] Micallef A., Berndt C., Masson D. G., and Stow D. A.V. (2008), “Scale invariant characteristics of the Storegga Slide and implications for large-scale submarine mass movements”, Mar Geol. Vol. 247, pp. 46-60.
[36] Sezer, E. (2010), “A computer program for fractal dimension (FRACEK) with application on type of mass movement characterization”, Computer Geosciences, Vol.36, pp. 391-396.