Prodip K. Kundu

Simulation and sensitivity analysis of transport in asymmetric hollow fiber membrane permeators for air separation

Development of high performance membranes requires deep insights about the various design, fabrication and operational parameters involved in the process. In the present study, the influence of input parameters such as active fiber length, feed temperature, feed composition and feed pressure is investigated to analyze the efficiency of the mathematical models developed for the separation of O2/N2 mixtures in an asymmetric hollow fiber membrane permeator. In addition, the effect of various non-idealities on the membrane performance are studied, individually. Results reveal that in contrast to pressure, temperature changes have no influential effects on the concentrations of O2 and N2 at permeate and retentate streams. The influence of feed composition on the product purities is more significant compared to active fiber length. Moreover, analysis of non-ideal effects indicates that pressure changes and concentration polarization are the most significant non-idealities among the effects. Results of this investigation can effectively be used for having a comprehensive overview about the impact of influential parameters and non-ideal effects on the membrane performance for O2/N2 separation application.

Gas permeation and separation in asymmetric hollow fiber membrane permeators: Mathematical modeling, sensitivity analysis and optimization

Mathematical modeling is useful for analysis of process design and performance and is widely used for membrane separation and other important technologies in the energy sector. This study presents the results of our investigations on the mathematical modeling and optimization of hollow fiber membrane permeators specifically used for air separation as well as natural gas purification. The governing equations and mathematical models are developed based on the consideration of ideal and non-ideal conditions often involved in the separation of gas mixtures using membrane permeators. The influence and consequences of adoption of two distinct numerical methods for solving governing equations are investigated in details. The results obtained by using the models as well as the effect of numerical method type are examined and compared to the experimental data. The findings highlight the important role of the solution method on the validity and accuracy of the models. Moreover, the effect of variations in the operating conditions and physical geometries of the membrane are investigated through comprehensive sensitivity analysis. Accordingly, a set of optimal input parameters is determined using an appropriate statistical method. The findings provide useful information for the design and development of high performance membrane permeators and processes particularly in the case of binary gas mixtures for energy applications.

Mathematical Modeling of Natural Gas Separation Using Hollow Fiber Membrane Modules by Application of Finite Element Method through Statistical Analysis

Abstract Hollow fiber membrane permeators used in the separation industry are proven as preferred modules representing various benefits and advantages to gas separation processes. In the present study, a mathematical model is proposed to predict the separation performance of natural gas using hollow fiber membrane modules. The model is used to perform sensitivity analysis to distinguish which process parameters influence the most and are necessary to be assessed appropriately. In this model, SRK equation was used to justify the nonideal behavior of gas mixtures and Joule-Thomson equation was employed to take into account the changes in the temperature due to permeation. Also, the changes in temperature along shell side was calculated via thermodynamic principles. In the proposed mathematical model, the temperature dependence of membrane permeance is justified by the Arrhenius-type equation. Furthermore, a surface mole fraction parameter is introduced to consider the effect of accumulation of less permeable component adjacent to the membrane surface in the feed side. The model is validated using experimental data. Central Composite Designs are used to gain response surface model. For this, fiber inner diameter, active fiber length, module diameter and number of fibers in the module are taken as the input variables related to the physical geometries. Results show that the number as well as the length of the fibers have the most influence on the membrane performance. The maximum mole fraction of CO2 in the permeate stream is observed for low number of fibers and fibers having smaller active lengths. Also results indicate that at constant active fiber length, increasing the number of fibers decreases the permeate mole fraction of CO2. The findings demonstrate the importance of considering appropriate physical geometries for designing hollow fiber membrane permeators for practical gas separation applications.

Mathematical Modeling and Investigation on the Temperature and Pressure Dependency of Permeation and Membrane Separation Performance for Natural gas Treatment

Abstract Due to special features, modules comprising asymmetric hollow fiber membranes are widely used in various industrial gas separation processes. Accordingly, numerous mathematical models have been proposed for predicting and analyzing the performance. However, majority of the proposed models for this purpose assume that membrane permeance remains constant upon changes in temperature and pressure. In this study, a mathematical model is proposed by taking into account non-ideal effects including changes in pressure and temperature in both sides of hollow fibers, concentration polarization and Joule-Thomson effects. Finite element method is employed to solve the governing equations and model is validated using experimental data. The effect of temperature and pressure dependency of permeance and separation performance of hollow fiber membrane modules is investigated in the case of CO2/CH4. The effect of temperature and pressure dependence of membrane permeance is studied by using type Arrhenius type and partial immobilization equations to understand which form of the equations fits experimental data best. Findings reveal that the prediction of membrane performance for CO2/CH4 separation is highly related to pressure and temperature; the models considering temperature and pressure dependence of membrane permeance match experimental data with higher accuracy. Also, results suggest that partial immobilization model represents a better prediction to the experimental data than Arrhenius type equation.

Genetic algorithm for multi-parameter estimation in sorption and phase equilibria problems

ABSTRACT The techniques of applying single and multi-objective optimization (MOO) for single/multiple parameters estimation in sorption and phase equilibria calculations were demonstrated, and it was shown that non-dominated sorting genetic algorithm with jumping genes adaptation is a useful tool for standard nonlinear regressions. Simultaneous description of vapor liquid equilibrium (VLE) and the heat of mixing (excess enthalpy) are considered a complex task in applied thermodynamics. MOO problem for simultaneous VLE and excess enthalpy prediction was formulated by (1) transforming multi-objectives into an aggregated/single scalar objective function, and (2) formulating independent objectives and solving simultaneously. It was shown that GA leads to an entire set of equally good optimal solutions known as Pareto-optimal fronts. However, simultaneous solution of MOO problem produced a wide range Pareto-optimal solution than that of the weighted sum approach. Pareto-optimal solutions are important process knowledge from which a decision-maker can opt for any set based on the applications/requirements.