The objective of this study is to describe a suitable model of atrial fibrillation cryoablation thermodynamic properties. Three different thermal loads were applied to a cylindrical copper element simulating the cryoprobe, thermally coupled with a Peltier stack producing the freezing effect, and in contact with a bovine liver sample. Thermal events occurring inside the samples were measured using mirror image technique. Heat subtracted flux during ice formation and minimum temperature measured at probe–tissue interface were, respectively, 1.33 W cm
−2
and −27.8°C for Sample#0, 1.88 W cm
−2
and −35.6°C for Sample#1 and 1.82 W cm
−2
and 1.44 W cm
−2
before and after the ice trigger, respectively, and −29.3°C for Sample#2. Ice trigger temperature was around −8.5°C for Sample#0 and Sample#2, and −10.4°C for Sample#1. In all the investigated samples, ice front penetration was proportional to the square root of time and its velocity depended on the heat flux subtracted. The fraction of the useful energy spent for ice formation was less than 60% for Sample#0, and about 80% for Sample#1 and for Sample#2, before the reduction of the removed heat flux. Freezing time exceeding a cut-off, according to the heat subtracted flux, does not improve the procedure effectiveness and is detrimental to the surrounding tissues.
In the present work a Wire Mesh Sensor (WMS) has been adopted to characterize the air-water two-phase flow in a test section consisting of a horizontal Plexiglas pipe of internal diameter 19.5 mm and total length of about 6 m. The flow quality ranges from 0 to 0.73 and the superficial velocity ranges from 0.145 to 31.94 m/s for air and from 0.019 to 2.62 m/s for water. The observed flow patterns are stratified-bubble-slug/plugannular. The WMS consists of two planes of parallel wire grids (16x16) that are placed across the channel at 1.5 mm and span over the measuring cross section. The wires of both planes cross under an angle of 90°, with a diameter D wire of 70 μm and a pitch equal to 1.3 mm. The void fraction profiles are derived from the sensor data and their evolution in time and space is analyzed and discussed. The dependence of the signals on the measured fluid dynamic quantities is discussed too. The main task is to predict which flow pattern will exist under any set of operating conditions as well as to predict the value of characteristic flow parameters.
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