Identification of failure type in corroded pipelines: a bayesian probabilistic approach

Spillover of hazardous materials from transport pipelines can lead to catastrophic events with serious and dangerous environmental impact, potential fire events and human fatalities. The problem is more serious for large pipelines when the construction material is under environmental corrosion conditions, as in the petroleum and gas industries. In this way, predictive models can provide a suitable framework for risk evaluation, maintenance policies and substitution procedure design that should be oriented to reduce increased hazards. This work proposes a bayesian probabilistic approach to identify and predict the type of failure (leakage or rupture) for steel pipelines under realistic corroding conditions. In the first step of the modeling process, the mechanical performance of the pipe is considered for establishing conditions under which either leakage or rupture failure can occur. In the second step, experimental burst tests are used to introduce a mean probabilistic boundary defining a region where the type of failure is uncertain. In the boundary vicinity, the failure discrimination is carried out with a probabilistic model where the events are considered as random variables. In turn, the model parameters are estimated with available experimental data and contrasted with a real catastrophic event, showing good discrimination capacity. The results are discussed in terms of policies oriented to inspection and maintenance of large-size pipelines in the oil and gas industry.

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).

Prenatal RR fluctuations dynamics: detecting fetal short-range fractal correlations

OBJECTIVE

Several studies have suggested that the analysis of heart rate variability (HRV) during gestation provides indications of the development or maturation of fetal cardiovascular regulatory mechanisms. In this study, we evaluate the existence of short-range fractal-like correlations in fetal RR fluctuations data from the second half of human gestation.

METHODS

Fifty-six short-term abdominal ECG recordings were obtained from low-middle-risk pregnant women. Gestational age varied from estimated 21 weeks to term. For comparison, RR-interval data of 51 healthy adults were also analysed.

RESULTS

Principal findings along the gestational period explored were the existence of fractal RR dynamics in prenatal fetal data as revealed by the short-range scaling exponent alpha(1). No significant differences of alpha(1) (p = 0.4770) were found between fetal (median 1.2879) and adult data (median 1.3214), either between the fetal cases before or after 24 weeks (p = 0.6116) despite observing more variation at early stages. However, fetal RR data did involve lower magnitude in comparison with adults as we found significant differences in pNN20 and SDNN values.

CONCLUSION

The fetal short-range fractal behaviour of RR data could then be linked to the functional development of the parasympathetic activity, which appears to become manifested before 21 weeks of gestation.

Comparison of RR-interval scaling exponents derived from long and short segments at different wake periods

Heartbeat fluctuations show fractal-like correlations that are associated with highly adaptive cardiovascular regulatory systems. Moreover, the short-range fractal or scaling exponent alpha(1) extracted from these correlations has been found to be a predictor of mortality for subjects with an impaired left ventricular function. In general, the RR-interval data required for this analysis are derived from long-term ECG recordings during free-running conditions. Yet short-term recordings are more likely to be obtained in some practical circumstances, so becoming relevant to assess the possibility of obtaining representative alpha(1) exponents from these recordings. Here, we compare the alpha(1) exponents extracted from the RR-interval series (9:00 AM-6:00 PM) of 51 healthy adults in normal sinus rhythm and the alpha(1) calculated from three shorted segments of only 700 beats obtained from the same series at 9:00 AM, 1:30 PM and 5:00 PM. We found no significant differences between the scaling exponents derived from the whole 9 h series and the short segments at 9:00 AM and 5:00 PM, but did find significant differences when comparing the whole series with the short segment at 1:30 PM. Thus, only if the time of day is taken into consideration can short segments of heartbeat fluctuation data be used to obtain representative alpha(1) exponents.

Separation kinetics of karnal bunt (Tilletia indica) infected wheat (Triticum aestivum) grains in a fluidized bed / Cinética de separación de granos de trigo (Triticum aestivum) infectados con carbon parcial (Tilletia indica) en un lecho fluidificado

Infection of breadmaking wheat grains by karnal bunt ( Tilletia indica) is a common disease in north- western Mexican states, causing major economic losses. In this work, the feasibility of separating infected from wholesome wheat grains by using fluidized bed technologies was evaluated. The pro posed separation equipment was of the batch type and fluidization was attained via direct air injec tion into the grain bed. Minimum fluidization rates were determined and effects of infected grain composition in the bed were studied. The experimental results showed that the separation of infected grains was quite possible with small losses of wholesome wheat grains. A quantitative characteriza tion of the separation process was made by determining the separation kinetics from the available experimental data. Separation kinetics were shown to be useful for estimating the equipment operat ing time to attain an allowed level of grain infection, as established by the Mexican government for the commercialization of wheat.