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A system based on Artificial Neural Networks (ANN ) is proposed to detect and diagnose multiple leaks in a pipeline leaks by recognizing the pattern of the flow using only two measurements. A nonlinear mathematical model of the pipeline is exploited for training, testing and validating the ANN -based system. This system was trained with tapped delays in order to include the system dynamics. Early results demonstrate the effectiveness of the approach in the detection and diagnosis of simultaneous multiple faults.

Analyses and experimental comparisons are given for liquid sloshing in a rigid cylindrical tank under conditions of moderately small axial accelerations; in particular, the theory is valid for Bond numbers larger than 10. The analytical results are put in the form of an equivalent mechanical model, and it is shown that the sloshing mass and the natural frequency of the first mode, for a liquid having a 0 deg contact angle at the tank walls, are smaller than for high-g conditions. The experimental data, obtained by using several small-diameter tanks and three different liquids, are compared to the predictions of the mechanical model; good correlation is found in most cases for the sloshing forces and natural frequency as a function of Bond number.

Abstract.In this manuscript we analyze some linear spectral transformations of a Hermitian linear functional using the multiplication by some class of Laurent polynomials. We focus our attention in the behavior of the Verblunsky parameters of the perturbed linear functional. Some illustrative examples are pointed out. Mathematics Subject Classification (2000). Primary 42C05; Secondary 15A23.

In this paper we analyze the behavior of Verblunsky parameters for hermitian linear functionals deduced from canonical linear spectral transformations of a quasi-definite hermitian linear functional. Some illustrative examples are studied.

In this paper we analyze spectral transformations of measures supported on the unit circle with real moments. The connection with spectral transformations of measures supported on the interval [−1, 1] using the Szegő transformation is presented. Some numerical examples are studied.

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