CFD Modeling of Crossflow Membrane Filtration- Integration of Filtration Model and Fluid Transport Model

Cross-flow membrane filtration has become a promising technique for waste-water treatment as compared to conventional treatment methods. One of the reasons is that the membrane techniques offer separation that can be achieved at ambient temperature with minimum energy. It is also an innovation for the application of cross-flow filtration in oil and gas industry especially as an integral part for the oil-in-water analysis of produced water prior to offshore disposal. However, good fouling control is essential for the efficiency of the cross-flow filtration unit. With the fact that membrane is not a passive entity, the understanding of particle deposition phenomena is vital for reducing fouling. In this paper, filtration will be modeled through the relationship between hydrodynamics of the cross-flows and the transfer of flows across the membrane. The results of FLUENT simulated model are in good agreement with experimental results. Simulation results of the model are presented and then validated using experimental data for distilled (DI) water. From the model, some connecting variables are identified and established in this modeling work. By attaining these connections, optimization of membrane filtration can be achieved by adjusting the operating parameters

The Study of Mass Transfer Coefficient in Membrane Separation for Produced Water

In this paper, membrane filtration of produced water is studied in terms of its mass transfer coefficient. This filtration process is incorporated to improve the existing OSPAR method in removing dissolved oil. During membrane filtration, concentration nearer to the membrane is higher than the concentration of bulk solution and thus a concentration profile develops. Studying the mass transfer coefficient (MTC) which drives the concentration difference can help us in understanding the phenomena of fouling in membrane. Two models i.e. combined solution diffusion/film theory model (Murthy and Gupta, 1997) and film theory model are compared and the most suitable model to predict the MTC is selected. From the experimental results, it was found that film theory (FT) model is suitable to calculate MTC for produced water samples in our experimental set-up. The models are found to be suitable only at a certain range of differential pressure

Effect of Mixing on a Lab-Scale Bioreactor Productivity

In this paper, we study the impact of variable mixing conditions arising from the different sets of aeration rate and stirrer speed on the ethanolic fermentation process, which utilizes the hydrolyzed cassava starch as carbon source. Interestingly, over the ranges of aeration rate and stirrer speed used in the study, the ethanol yield varied from 10% to 85% of theoretical maximum yield. Additionally over these experimental conditions, the selectivity of ethanol over glycerol varied from 3.6 to 12.3. One conclusion that can be drawn from this experimental study is that, the large variations in yield, selectivity and ethanol formation rate were more likely due to the different mixing conditions resulting from different values of aeration rate and stirrer speed, and less likely due to glucose and growth rates as previously reported

PCA-based Method of Identification of Dominant Variables for Partial Control

Since the early use of automatic control, the Partial Control strategy has frequently been adopted in complex chemical processes having more process variables than manipulated variables. The key idea of Partial Control is to find the dominant variables which can be controlled to constant setpoints and in turn leads to acceptable variations in the operating objectives in the face of external disturbances occurrence. Although the idea seems simple to understand, the identification of the dominant variables can be a daunting task where presently this is largely done based on extensive process knowledge and experience. In this paper, we present a novel methodology to identify the dominant variables based on Principal Component Analysis. The method can greatly facilitate the implementation of Partial Control strategy because it does not require extensive process experience and knowledge. The effectiveness of the methodology is demonstrated based on its application to a complex extractive fermentation process

CFD Approach for Non-Ideally Mixed Bioreactor Modeling

In this paper, we address the progress, challenges and prospect of modeling mixing in bioreactor by the utilization of Computational Fluid Dynamics (CFD). Efficient operation of bioreactor is essential in the biotechnological process, not only to ensure good yield but also to maintain consistent product quality. Process modeling technique has frequently been adopted in the bioreactor design, optimization and control as well as in scale-up process. One of the critical issues in bioreactor modeling is the need to overcome the mass and heat transfer limitations imposed on the bioreactor performance, particularly the close interaction between fluid flow and the biological reactions. CFD can be applied to overcome this obstacles by integrating the flow rates between adjacent zones, and fluid mechanical quantities, as the integration of mixing phenomena into the bioreactor modeling is considered a vital aspect in the efficient design and scale-up of bioreactor system

Multi-scale models for the optimization of batch bioreactors

Process models play an important role in the bioreactor design, optimisation and control. In previous work, the bioreactor models have mainly been developed by considering the microbial kinetics and the reactor environmental conditions with the assumption that the ideal mixing occurs inside the reactor. This assumption is relatively difficult to meet in the practical applications. In this paper, we propose a new approach to the bioreactor modelling by expanding the so-called Herbert’s Microbial Kinetics (HMK) model so that the developed models are able to incorporate the mixing effects via the inclusion of the aeration rate and stirrer speed into the microbial kinetics. The expanded models of Herbert’s microbial kinetics allow us to optimize the bioreactor’s performances with respects to the aeration rate and stirrer speed as the decision variables, where this optimisation is not possible using the original HMK model of microbial kinetics. Simulation and experimental studies on a batch ethanolic fermentation demonstrates the use of the expanded HMK models for the optimisation of bioreactor’s performances. It is shown that the integration of the expanded HMK model with the Computational Fluid Dynamics (CFD) model of mixing, which we call it as a Kinetics Multi-Scale (KMS) model, is able to predict the experimental values of yield and productivity of the batch fermentation process accurately (with less than 5% errors)

Hydrodynamics modeling and analysis of rapid expansion systems of supercritical solutions (RESS)

In this paper, we study the hydrodynamics aspects of the RESS (e.g. rapid expansion of supercritical solutions) process to produce fine particles for heat-sensitive organic compounds. The Computational Fluid Dynamic (CFD) modeling and analysis of the supercritical solutions passing through a capillary nozzle were studied. The CFD simulation is focused on the pre-expansion chamber of the RESS process consisting of three successive steps that are at the stagnation chamber (i.e. the reservoir), nozzle inlet and along the nozzle itself to the outlet. The solute considered is benzoic acid and the supercritical solvents are CO2 and CHF3 respectively. The aim of this study is to examinethe effect and sensitivity of the design parameters (i.e. temperature, pressure and density) on the formation of particulates in the chamber. The study reveals that at lower preexpansion temperature with constant pre-expansion pressure the solute nucleation seems to start inside the nozzle. Moreover, it is also found that pre-expansion pressure has insignificant effect on the nucleation process, i.e. the nucleation rate slightly increases when the pressure is set higher. Furthermore, the study also reveals that high preexpansion pressures and low pre-expansion temperature favors small particles. The results demonstrate that the variation of thee parameters in the ranges studied may lead to the increased super-saturation and simultaneously increase in nucleation rate

CFD Simulation on Supercritical Fluid Extraction of Black Pepper's Bioactive Compounds: Single Particle Study

To gain a better understanding on the application of computational fluid dynamics (CFD) towards extraction using supercritical fluid, a single particle study was carried out. The flow behaviour of an ambient supercritical carbon dioxide flowing through a heated black pepper particle in vertical direction was studied. The transfer of heat from the heated particle to supercritical fluid was examined. Various groups of parameters in the following ranges were carried out for the simulations: pressure 3000 psi, 4000 psi and 5000 psi; temperature 4°C, 50°C and 55°C; and solvent flow rate 5 ml min–1, 7.5 ml min–1 and 10 ml min–1. The contour of velocity magnitude and streamline of the flow along the particle were presented. Temperature profile and the local heat flux value on the heated particle surface were captured. The drag coefficients and average Nusselt numbers obtained from the simulations had shown a good agreement with the numerical correlations from literature

Intelligent monitoring interfaces for coal fired power plant boiler trips: A review

A major source of contemporary power is a Coal-fired Power Plant. These power plants have the capacity to continuously supply electricity to almost 500,000 residential and business units. An essential component of a Coal-fired Power plant is automation. A feature of this automation is an Intelligent System developed for the Power Plant. These Intelligent Systems have different configurations and design. This research studies the various Intelligent Monitoring Interfaces developed for Coal-fired Power Plant Trips, their advantages, disadvantages and proposes a new Intelligent Monitoring Interface that would alleviate the disadvantages of the existing systems. Current systems that use Neural Network models are investigated. The improved Intelligent Monitoring Interface as proposed in this paper is a modification of the existing monitoring system for the Coal-fired Power Plant Boiler Trips. It is expected to improve the overall system by implementing remote accessibility and interactability between the plant operator and the control system interface. The interface will also assist the operator by providing guidelines to troubleshoot the identified trips and the remote server application will allow data collected to be viewed anytime, anywhere