Time-correlations in the dynamics of hazardous material pipelines incidents.

This paper addresses the following question: Are the hazardous materials pipeline incidents non-randomly time distributed? Our analysis suggests that they are correlated, which means that a hazardous materials pipeline incident is not independent from the time elapsed since the previous event. That is, our statistical tests suggest that previous accident counts correlate with future counts. But, if we consider incidents with a large severity index (spills and property damage), the phenomenon is unpredictable, since it approaches a Poissonian process (random, independent and uncorrelated).

[1]  Jose Alvarez-Ramirez,et al.  Time-correlations in marathon arrival sequences , 2007 .

[2]  W. Kent Muhlbauer,et al.  Pipeline Risk Management Manual , 1992 .

[3]  H E Stanley,et al.  Deviations from uniform power law scaling in nonstationary time series. , 1997, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[4]  Prasanta Kumar Dey,et al.  A risk‐based model for inspection and maintenance of cross‐country petroleum pipeline , 2001 .

[5]  R Cooke,et al.  A probabilistic model for the failure frequency of underground gas pipelines. , 1998, Risk analysis : an official publication of the Society for Risk Analysis.

[6]  Young-Do Jo,et al.  A method of quantitative risk assessment for transmission pipeline carrying natural gas. , 2005, Journal of hazardous materials.

[7]  D. Stoyan,et al.  Recent applications of point process methods in forestry statistics , 2000 .

[8]  Georgios A. Papadakis,et al.  Major Hazard Pipelines: A Comparative Study of Onshore Transmission Accidents. , 1999 .

[9]  Rosa Lasaponara,et al.  Time-scaling properties in forest-fire sequences observed in Gargano area (southern Italy) , 2005 .

[10]  D. S. Etkin,et al.  Estimation of potential impacts and natural resource damages of oil. , 2004, Journal of hazardous materials.

[11]  Maria Macchiato,et al.  Long-range time-correlation properties of seismic sequences , 2004 .

[12]  Richard L. O 'Driscoll Description of spatial pattern in seabird distributions along line transects using neighbour K statistics , 1998 .

[13]  G. Spadoni,et al.  Risk analysis of hazardous materials transportation: evaluating uncertainty by means of fuzzy logic , 1998 .