A high frequency electronic transducer for multiphase flow measurements

This paper describes an electronic transducer for multiphase flow measurement. Its high sensitivity, good signal to noise ratio and accuracy are achieved through an electrical impedance sensor with a special guard technique. The transducer consists of a wide bandwidth and high slew rate differentiator where the lead inductance and stray capacitance effects are compensated. The sensor edge effect is eliminated by using a guard electrode based on the virtual ground potential of the operational amplifier. A theoretical modeling and a calibration method are also presented. The results obtained seem to confirm the validity of the proposed technique.

Estudo por espectroscopia micro-Raman dos mecanismos de separação de fase em vidros fosfatos de metais de transição

Glass-ceramics are prepared by controlled separation of crystal phases in glasses, leading to uniform and dense grain structures. On the other hand, chemical leaching of soluble crystal phases yields porous glass-ceramics with important applications. Here, glass/ceramic interfaces of niobo-, vanado- and titano-phosphate glasses were studied by micro-Raman spectroscopy, whose spatial resolution revealed the multiphase structures. Phase-separation mechanisms were also determined by this technique, revealing that interface composition remained unchanged as the crystallization front advanced for niobo- and vanadophosphate glasses (interface-controlled crystallization). For titanophosphate glasses, phase composition changed continuously with time up to the equilibrium composition, indicating a spinodal-type phase separation.

Detection of Horizontal Two-Phase Flow Patterns Through a Neural Network Model

One of the main problems related to the transport and manipulation of multiphase fluids concerns the existence of characteristic flow patterns and its strong influence on important operation parameters. A good example of this occurs in gas-liquid chemical reactors in which maximum efficiencies can be achieved by maintaining a finely dispersed bubbly flow to maximize the total interfacial area. Thus, the ability to automatically detect flow patterns is of crucial importance, especially for the adequate operation of multiphase systems. This work describes the application of a neural model to process the signals delivered by a direct imaging probe to produce a diagnostic of the corresponding flow pattern. The neural model is constituted of six independent neural modules, each of which trained to detect one of the main horizontal flow patterns, and a last winner-take-all layer responsible for resolving when two or more patterns are simultaneously detected. Experimental signals representing different bubbly, intermittent, annular and stratified flow patterns were used to validate the neural model.

On-site calibration of a phase fraction meter by an inverse technique

The formal calibration procedure of a phase fraction meter is based on registering the outputs resulting from imposed phase fractions at known flow regimes. This can be straightforwardly done in laboratory conditions, but is rarely the case in industrial conditions, and particularly for on-site applications. Thus, there is a clear need for less restrictive calibration methods regarding to the prior knowledge of the complete set of inlet conditions. A new procedure is proposed in this work for the on-site construction of the calibration curve from total flown mass values of the homogeneous dispersed phase. The solution is obtained by minimizing a convenient error functional, assembled with data from redundant tests to handle the intrinsic ill-conditioned nature of the problem. Numerical simulations performed for increasing error levels demonstrate that acceptable calibration curves can be reconstructed, even from total mass measured within a precision of up to 2%. Consequently, the method can readily be applied, especially in on-site calibration problems in which classical procedures fail due to the impossibility of having a strict control of all the input/output parameters.