Experimental data on pressure drop for two-phase gas-non-Newtonian ps;udoplastic liquid vertical slug flow have been analysed. Correlation have been proposed for predicting the two-phase friction factor as a function of the physical and dynamic variables of the system. © 1995, Taylor & Francis Group, LLC. All rights reserved.

SUDIP DAS

Chemical Engineering

M N BISWAS

University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

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The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

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It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

Pressure losses in two-phase gas-non-newtonian liquid flow in a vertical tube

Chemical Engineering Communications

Experiments have been carried out to determine the minimum fluidization velocity for sand particles of irregular shape and size using pseudoplastic liquids in different Perspex columns. The effect of different operating parameters, like column diameter, particle size and shape, rheological properties of the liquid on minimum fluidization velocity has been investigated. It has been observed that as sphericity of the particle decreases, minimum fluidization also decreases. Empirical correlation has been developed to predict the minimum fluidization velocity as a function of physical and dynamic variable of the system. Statistical analysis of the correlation suggests that is of acceptable accuracy. Applicability of the artificial neural network modelling using gradient descent and Levenberg-Marquardt algorithm have also been successfully tested. © 2017 Elsevier Ltd

Chemical Engineering Science

Non-spherical solid-non-Newtonian liquid fluidization and ANN modelling: Minimum fluidization velocity

This paper is an attempt to compare the the performance of the three different Multilayer Perceptron training algorithms namely Backpropagation, Scaled Conjugate Gradient and Levenberg- Marquardt for the prediction of the gas hold up and frictional pressure drop across the vertical pipe for gas non-Newtonian liquid flow from our earlier experimental data. The Multilayer Perceptron consists of a single hidden layer. Four different transfer functions were used in the hidden layer. All three algorithms were useful to predict the gas holdup and frictional pressure drop across the vertical pipe. Statistical analysis using Chi-square test (χ2) confirms that the Backpropagation training algorithm gives the best predictability for both cases. © (2014) Trans Tech Publications, Switzerland.

Advanced Materials Research

Modeling of gas holdup and pressure drop using ANN for gas-non Newtonian liquid flow in vertical pipe

Experimental studies on the pressure drop in tapered bubble columns using non-Newtonian pseudoplastic liquid have been reported. The effects of different variables such as liquid flow rate, clear liquid height, hole diameter of sieve plate, pseudoplasticity of the liquid on the frictional pressure drop have been investigated. The ANN with multilayer perceptron (MPL) with one hidden layer and four different transfer functions with backpropagation algorithm were used to demonstrate its applicability in the prediction of the frictional pressure drop. © 2013 Canadian Society for Chemical Engineering.

Canadian Journal of Chemical Engineering

Pressure drop in tapered bubble columns using non-Newtonian pseudoplastic liquid-experimental and ANN prediction

The ANN approach proved its worth when rigorous fluid mechanics treatment based on the solution of first principle equations is not tractable. Evaluation and prediction of the frictional pressure drop across different piping components such as orifices, gate and globe valves, elbows, and horizontal pipe in 0.0127 m diameter for gas non-Newtonian liquid flow is manifested in this paper. In this paper, we have used the power-law-model (Oswaldâde Waele model) liquids only. The experimental data used for the prediction is taken from our earlier work, Bandyopadhyay (Bandyopadhyay, T. K. Studies on non-Newtonian and gas-non-Newtonian liquid flow through horizontal tube and piping components. Ph.D Thesis, University of Calcutta, Kolkata, India, 2002) and the subsequent publications (Banerjee T. K.; Das, S. K. Gas-non-Newtonian liquid flow through globe and gate valves. Chem. Eng. Commun. 1998, 167, 133-146. Samanta A. K.; Banerjee, T. K.; Das, S. K. Pressure loses in orifices for the flow of gas-non-Newtonian liquids. Can. J. Chem. Eng. 1999, 77, 579-583. Bandyopadhyay, T. K.; Banerjee, T. K.; Das, S. K. Gas-non-Newtonian liquid flow through elbows. Chem. Eng. Commun. 2000, 82, 21-33). The proposed approach toward the prediction is done using a multilayer perceptron (MLP with one hidden layer and four different transfer functions), which is trained with backpropagation algorithm. © 2010 American Chemical Society.

Industrial and Engineering Chemistry Research

Prediction of pressure drop using artificial neural network for gas non-newtonian liquid flow through piping components

Investigations have been carried out to evaluate the two-phase frictional pressure drop for gas-non-Newtonian liquid flow through helical coils in vertical orientation. The experiments performed using nine coils and four different non-Newtonian liquids. The effects of gas and liquid flow rate, coil diameter, and liquid properties on two-phase frictional pressure drop have been illustrated. An attempt has been made to fit the experimental two-phase frictional pressure drop data by the Lockhart and Martinelli [R.W. Lockhert, R.C. Martinelli, Proposed correlation of data for isothermal two-phase two components flow in pipes, Chem. Eng. Prog. 45 (1949) 39-48] correlation and the modified Lockhart-Martinelli correlation as presented by different authors. In another approach, friction factor method was adopted to correlate the experimental data by dimensional analysis. The correlation developed predicts the two-phase frictional pressure drop with acceptable statistical accuracy. © 2007 Elsevier B.V. All rights reserved.

Journal	Chemical Engineering Communications
Publisher	GORDON BREACH PUBLISHING, TAYLOR & FRANCIS GROUP
ISSN	0098-6445