Experimental Study of Void Fraction Measurement Using a Capacitance-Based Sensor and ANN in Two-Phase Annular Regimes for Different Fluids
نویسندگان
چکیده
One of the most severe problems in power plants, petroleum and petrochemical industries is accurate determination phase fractions two-phase flows. In this paper, we carried out experimental investigations to validate simulations for water–air, flow an annular pattern. To end, performed finite element with COMSOL Multiphysics, conducted concave electrode shape and, finally, compared both results. Our set-up was constructed a vertical tube. Afterwards, simulated models water–air condition were validated against measurements. results show relatively low relative error between simulation experiment indicating validation our simulations. Finally, designed Artificial Neural Network (ANN) model order predict void any consisting products as liquid pipelines. regard, range various liquid–gas, flows including crude oil, diesel fuel, gasoline water using simulation. We developed ANN by multi-layer perceptron (MLP) neural network MATLAB 9.12.0.188 software. The input parameters MLP set capacitance sensor material, whereas output parameter fraction. fraction predicted less than 2% different liquids via proposed methodology. Using presented novel metering system, can be precisely measured.
منابع مشابه
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ژورنال
عنوان ژورنال: Axioms
سال: 2023
ISSN: ['2075-1680']
DOI: https://doi.org/10.3390/axioms12010066