Predicton of interface level height of stratified liquid-liquid flow using artficial neural network

In this study, artificial neural network (ANN) was used to predict the interface level height (ILH) of two immiscible liquids flowing in a horizontal pipe. A three-layer feed-forward back-propagation (FFBP) neural network was constructed and trained with experimental data of two different liquid-liquid flow systems reported in the literature. The all studied flow patterns were stratified flow (stratified smooth and stratified wavy with or without droplets at interface ). The input parameters of the ANN model were superficial velocity of phases, pipe diameter, the ratio of the lighter phase density to the heavier phase density (ρlp/ρhp) and the ratio of the lighter phase viscosity to the heavier phase viscosity (μlp/μhp), while the interface level height (ILH) of phases was its output. The Levenberg–Marquardt (LM) algorithm, the hyperbolic tangent sigmoid and the linear activation functions were used for training and developing the ANN. Optimal configuration of the ANN model was determined using minimizing the mean absolute percent error (MAPE) and mean square errors (MSE) between experimental and predicted ILH data by the ANN model. The results showed that the optimal configuration was a network with five neurons in hidden layer that was highly accurate in predicting the interface level. MAPE and correlation coefficient (R) between the experimental and predicted values were determined as 1.8% and 0.9962 for training, and 1.52% and 0.9996 for testing date sets, respectively

Experimental investigations of two-phase liquid-liquid horizontal flows through orifice plates

Paper presented at the 9th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Malta, 16-18 July, 2012.This paper is concerned with two-phase liquid-liquid flows through orifice plates in horizontal pipes, and in particular with a phenomenon known as “phase inversion” that can occur in dispersed flow. Experimental investigations were carried out in which two-phase flows comprising oil and water were pumped via an inlet section into a horizontal pipe of diameter 25.4 mm and length 7 m. In one series of experiments the light phase (oil) was introduced into the inlet section above the heavier one (water), in a “stable” inlet configuration. This was followed by a set of experiments in which the water was introduced above the oil, in an “unstable” inlet configuration. Furthermore, tests were performed with and without the insertion of a static mixer just downstream of the inlet. The orifice plate was placed in two alternate positions with respect to the inlet: one near (1.30 m) the inlet, and one far (5.20 m) downstream, i.e., in both developing and fully developed flows. The pressure drop across the orifice plate was measured with a differential pressure transducer in a series of independent experimental runs in which the two liquid flow-rates were varied independently in order to span a range of superficial mixture velocities and inlet phase fractions (water-cuts). From the data generated in the present experimental campaign, the pressure drop measured across the orifice plate showed a gradual increase as the mixture velocities were increased, as expected. However, for a given mixture velocity, a decrease in the pressure drop across the orifice plate was observed as the water-cut was varied. This decrease was observed at water-cut values that were close to those for which phase inversion was expected in our flows (~0.2-0.3). It is inferred that the phase inversion point may be associated with this decrease in pressure drop. This interesting finding is contrary to the increase in pressure drop demonstrated in previous studies involving two-phase pipe flow and has important implications for the design of pipeline systems that incorporate orifice plates for flow measurement. In addition, the inlet orientation appeared to have little effect on the phase inversion point.dc201

Harnessing the potential of ligninolytic enzymes for lignocellulosic biomass pretreatment

Abundant lignocellulosic biomass from various industries provides a great potential feedstock for the production of value-added products such as biofuel, animal feed, and paper pulping. However, low yield of sugar obtained from lignocellulosic hydrolysate is usually due to the presence of lignin that acts as a protective barrier for cellulose and thus restricts the accessibility of the enzyme to work on the cellulosic component. This review focuses on the significance of biological pretreatment specifically using ligninolytic enzymes as an alternative method apart from the conventional physical and chemical pretreatment. Different modes of biological pretreatment are discussed in this paper which is based on (i) fungal pretreatment where fungi mycelia colonise and directly attack the substrate by releasing ligninolytic enzymes and (ii) enzymatic pretreatment using ligninolytic enzymes to counter the drawbacks of fungal pretreatment. This review also discusses the important factors of biological pretreatment using ligninolytic enzymes such as nature of the lignocellulosic biomass, pH, temperature, presence of mediator, oxygen, and surfactant during the biodelignification process