Performance of reverse osmosis (RO) for water recovery from permeates of membrane bio-reactor (MBR)

In this study, permeate from a hollow fiber polyethylene (PE) membrane bio-reactor (MBR) system treating synthetic agricultural wastewater was fed into a cellulose acetate brackish water reverse osmosis (BWRO30 2540) membrane system; three different trans-membranes pressures (TMPs) of 1000, 2500, and 4000 kPa were selected to evaluate the system performance in terms of general operating parameters as well as the removal of chosen important potential fouling water quality parameters. The results showed that highest corrected permeate flux rate was at a TMP of 2500 kPa, whereas lowest recorded at a TMP of 4000 kPa. Similar situation prevailed in water recovery rate. But temperature corrected specific fluxes decreased as the applied TMPs increased. In all selected TMPs, more than 96% of salinity was removed. Permeate from MBR as feed to reverse osmosis required frequent chemical cleaning than the microfiltration/ultrafiltration (MF/UF) permeates and granular media filter (GMF) filtered in order to maintain the required rate of product water. One of the reasons for this frequent chemical cleaning is due to higher total organic carbon as well as total nitrogen (TN) in the MBR permeate. This result needs to be further evaluated through field trials.

Control of polystyrene batch reactor using fuzzy logic controller

Control of polymerization reactors is a challenging issue for researchers due to the complex reaction mechanisms. A lot of reactions occur simultaneously during polymerization. This leads to a polymerization system that is highly nonlinear in nature. In this work, a nonlinear advanced controller, named fuzzy logic controller (FLC), is developed for monitoring the batch free radical polymerization of polystyrene (PS) reactor. Temperature is used as an intermediate control variable to control polymer quality, because the products quality and quantity of polymer are directly depends on temperature. Different FLCs are developed through changing the number of fuzzy membership functions (MFs) for inputs and output. The final tuned FLC results are compared with the results of another advanced controller, named neural network based model predictive controller (NN-MPC). The simulation results reveal that the FLC performance is better than NN-MPC in terms of quantitative and qualitative performance criterion.

Report on research literature related to moving bed biofilm reactor wastewater treatment

 This report is an investigation of the research literature on Moving Bed Biofilm Reactor (MBBR) wastewater treatment, in particular examining the available literature relating to retrofitting MBBR technology to existing treatment plants and the operating costs of MBBR plants. A primary literature review was conducted using relevant online research databases, and the references listed in the first round of discovered documents were also examined to identify any other useful literature.

This report presents:
• a literature review based on the discovered relevant documents;
• a summary of the main findings; and
• a list of references.

Highly stable external short-circuit-assisted oxygen ionic transport membrane reactor for carbon dioxide reduction coupled with methane partial oxidation

A membrane reactor allows for simultaneous separation and reaction, and thus, can play a good role to produce value-added chemicals. In this work, we demonstrated such a membrane reactor based on fluorite oxide samarium-doped ceria (SDC) using an external short-circuit concept for oxygen permeation. The fluorite phase was employed to impart its high structural stability, while its limited electronic conductivity was overcome by the application of an external short circuit to function the SDC membrane for oxygen transport. On one side of the membrane, i.e., feed side, carbon dioxide decomposition into carbon monoxide and oxygen was carried out with the aid of a Pt or Ag catalyst. The resultant oxygen was concurrently depleted on the membrane surface and transported to the other side of the membrane, favorably shifting this equilibrium-limited reaction to the product side. The transported oxygen on the permeate side with the aid of a GdNi/Al2O3 catalyst was then consumed by the reaction with methane to form syngas, i.e., carbon monoxide and hydrogen. As such, the required driving force for gas transport through the membrane can be sustained by coupling two different reactions in one membrane reactor, whose stability to withstand these different gases at high temperatures is attained in this paper. We also examined the effect of the membrane thickness, oxygen ionic transport rate, and CO2 and CH4 flow rates to the membrane reactor performance. More importantly, here, we proved the feasibility of a highly stable membrane reactor based on an external short circuit as evidenced by achieving the constant performance in CO selectivity, CH4 conversion, CO2 conversion, and O2 flux during 100 h of operation and unaltered membrane structure after this operation together with the coking resistance.

Prediction interval-based neural network modelling of polystyrene polymerization reactor - a new perspective of data-based modelling

In this paper, prediction interval (PI)-based modelling techniques are introduced and applied to capture the nonlinear dynamics of a polystyrene batch reactor system. Traditional NN models are developed using experimental datasets with and without disturbances. Simulation results indicate that traditional NNs cannot properly handle disturbances in reactor data and demonstrate a poor forecasting performance, with an average MAPE of 22% in the presence of disturbances. The lower upper bound estimation (LUBE) method is applied for the construction of PIs to quantify uncertainties associated with forecasts. The simulated annealing optimization technique is employed to adjust NN parameters for minimization of an innovative PI-based cost function. The simulation results reveal that the LUBE method generates quality PIs without requiring prohibitive computations. As both calibration and sharpness of PIs are practically and theoretically satisfactory, the constructed PIs can be used as part of the decision-making and control process of polymerization reactors. © 2014 The Institution of Chemical Engineers.

Development and characterization of the 2,4,6-trichlorophenol (2,4,6-TCP) aerobic degrading granules in sequencing batch airlift reactor

2,4,6-trichlorophenol (2,4,6-TCP) aerobic degrading granules were successfully developed in the sequencing batch airlift reactor. The key strategy used in cultivation of the granules was dosing glucose and acetate as co-substrates. After granulation, average concentrations of 2,4,6-TCP and COD in the effluent were less than 8mgL-1 and 59mgL-1, respectively. The removal efficiencies of 2,4,6-TCP and COD were above 93% and 90%, respectively. The specific degradation rate of 2,4,6-TCP peaked at 61mg 2,4,6-TCP gVSS-1h-1 when inoculated at the concentration of 400mgL-1. The extracellular polymeric substance (EPS) contents of the 2,4,6-TCP aerobic degrading granules were decreased compared with the contents in seed sludge. Two peaks attributed to the protein-like fluorophores were identified by three-dimensional excitation emission matrix (EEM) fluorescence spectra. The decrease of fluorescence parameters, e.g., peak locations, intensities, indicated quenching effect of 2,4,6-TCP on the EPS fluorescence. Meanwhile, the shift of peak position indicated chemical changes of the EPS.

Enhancement of aerobic granulation by zero-valent iron in sequencing batch airlift reactor

This study elucidates the enhancement of aerobic granulation by zero-valent iron (ZVI). A reactor augmented with ZVI had a start-up time of aerobic granulation (43 days) that was notably less than that for a reactor without augmentation (64 days). The former reactor also had better removal efficiencies for chemical oxygen demand and ammonium. Moreover, the mature granules augmented with ZVI had better physical characteristics and produced more extracellular polymeric substances (especially of protein). Three-dimensional-excitation emission matrix fluorescence showed that ZVI enhanced organic material diversity. Additionally, ZVI enhanced the diversity of the microbial community. Fe(2+) dissolution from ZVI helped reduce the start-up time of aerobic granulation and increased the extracellular polymeric substance content. Conclusively, the use of ZVI effectively enhanced aerobic granulation.

Prediction interval-based modelling of polymerization reactor: a new modelling strategy for chemical reactors

Precise and reliable modelling of polymerization reactor is challenging due to its complex reaction mechanism and non-linear nature. Researchers often make several assumptions when deriving theories and developing models for polymerization reactor. Therefore, traditional available models suffer from high prediction error. In contrast, data-driven modelling techniques provide a powerful framework to describe the dynamic behaviour of polymerization reactor. However, the traditional NN prediction performance is significantly dropped in the presence of polymerization process disturbances. Besides, uncertainty effects caused by disturbances present in reactor operation can be properly quantified through construction of prediction intervals (PIs) for model outputs. In this study, we propose and apply a PI-based neural network (PI-NN) model for the free radical polymerization system. This strategy avoids assumptions made in traditional modelling techniques for polymerization reactor system. Lower upper bound estimation (LUBE) method is used to develop PI-NN model for uncertainty quantification. To further improve the quality of model, a new method is proposed for aggregation of upper and lower bounds of PIs obtained from individual PI-NN models. Simulation results reveal that combined PI-NN performance is superior to those individual PI-NN models in terms of PI quality. Besides, constructed PIs are able to properly quantify effects of uncertainties in reactor operation, where these can be later used as part of the control process. © 2014 Taiwan Institute of Chemical Engineers.

Performance analysis of three advanced controllers for polymerization batch reactor: an experimental investigation

The performances of three advanced non-linear controllers are analyzed for the optimal set point tracking of styrene free radical polymerization (FRP) in batch reactors. The three controllers are the artificial neural network-based MPC (NN-MPC), the artificial fuzzy logic controller (FLC) as well as the generic model controller (GMC). A recently developed hybrid model (Hosen et al., 2011a. Asia-Pac. J. Chem. Eng. 6(2), 274) is utilized in the control study to design and tune the proposed controllers. The optimal minimum temperature profiles are determined using the Hamiltonian maximum principle. Different types of disturbances are introduced and applied to examine the stability of controller performance. The experimental studies revealed that the performance of the NN-MPC is superior to that of FLC and GMC. © 2013 The Institution of Chemical Engineers.