Investigation of process dynamics and control of polystyrene batch reactor using hybrid model

The effects of operating conditions such as initiator and monomer concentration as well as reactor temperature of polymerization reactors are studied in this work. A recently developed hybrid model for polystyrene batch reactor is utilized in simulation study. The simulation results reveal the sensitivity of polymer properties and monomer conversion to variation of process operating conditions. In the second phase of this study, the optimization problem involving minimum time optimal temperature policy is considered for control study. An advanced neural network-based model predictive controller (NN-MPC) is designed and tested online. The experimental studies reveal that the developed controller is able to track the optimal setpoint with a minor oscillation and overshoot.

Performance analysis of two advanced controllers for polystyrene polymerization in batch reactor

The performance of two advanced model based non-linear controllers is analyzed for the optimal setpoint tracking of free radical polymerization of styrene in batch reactors. Artificial neural network-based model predictive controller (NN-MPC) and generic model controller (GMC) are both applied for controlling the system. The recently developed hybrid model [1] as well as available literature models are utilized in the control study. The optimal minimum temperature profiles are determined based on Hamiltonian maximum principle. Different types of disturbances are artificially generated to examine the stability and robustness of the controllers. The experimental studies reveal that the performance of NN-MPC is superior over that of GMC.

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.

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.

Evaluation of the microbial diversity of denitrifying bacteria in batch reactor

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Chemical Reactors. Problem 2: Constant pressure adiabatic stirred batch reactor with variable heat capacities (2011-2012 Course)

Wording of problem 2 (week 3, 17/10/11).

Chemical Reactors. Problem 2: Constant pressure adiabatic stirred batch reactor with variable heat capacities. Solution (2011-2012 Course)

Chemical Reaction Engineering. Course 2011-12. Solution of problem 2: constant pressure adiabatic stirred batch reactor with variable heat capacities.

Enhanced biological phosphorus removal in a sequencing batch reactor using propionate as the sole carbon source

An enhanced biological phosphorus removal (EBPR) system was developed in a sequencing batch reactor (SBR) using propionate as the sole carbon source. The microbial community was followed using fluorescence in situ hybridization (FISH) techniques and Candidatus 'Accumulibacter phosphatis' were quantified from the start up of the reactor until steady state. A series of SBR cycle studies was performed when 55% of the SBR biomass was Accumulibacter, a confirmed polyphosphate accumulating organism (PAO) and when Candidatus 'Competibacter phosphatis,' a confirmed glycogen-accumulating organism (GAO), was essentially undetectable. These experiments evaluated two different carbon sources (propionate and acetate), and in every case, two different P-release rates were detected. The highest rate took place while there was volatile fatty acid (VFA) in the mixed liquor, and after the VFA was depleted a second P-release rate was observed. This second rate was very similar to the one detected in experiments performed without added VFA. A kinetic and stoichiometric model developed as a modification of Activated Sludge Model 2 (ASM2) including glycogen economy, was fitted to the experimental profiles. The validation and calibration of this model was carried out with the cycle study experiments performed using both VFAs. The effect of pH from 6.5 to 8.0 on anaerobic P-release and VFA-uptake and aerobic P-uptake was also studied using propionate. The optimal overall working pH was around 7.5. This is the first study of the microbial community involved in EBPR developed with propionate as a sole carbon source along with detailed process performance investigations of the propionate-utilizing PAOs. (C) 2004 Wiley Periodicals, Inc.

Differential distribution of ammonia- and nitrite-oxidising bacteria in flocs and granules from a nitrifying/denitrifying sequencing batch reactor

A lab-scale sequencing batch reactor was operated with alternating anoxic/aerobic conditions for nitrogen removal. Flocs and granules co-existed in the same reactor, with distinct aggregate structure and size, for over 180 days of reactor operation' Process data showed complete nitrogen removal, with temporary nitrite accumulation before full depletion of ammonia in the aerobic phase. Microbial quantification of the biomass by fluorescence in situ hybridisation showed that granules contained most of the nitrite-oxidising bacteria (NOB) whereas the ammonium-oxidising bacteria (AOB) seemed to be more abundant in the flocs. This was supported by microsensor measurements, which showed a higher potential of NO2- uptake than NH4 uptake in the granules. The segregation is possibly linked to the different growth rates of the two types of nitrifiers and the reactor operational conditions, which produced different sludge retention time for flocs and granules. The apparent physical separation of AOB and NOB in two growth forms could potentially affect mass transfer of NO2- from AOB to NOB, but the data presented here shows that it did not impact negatively on the overall nitrogen removal. (c) 2006 Elsevier Inc. All rights reserved.

Identifying causes for N2O accumulation in a lab-scale sequencing batch reactor performing simultaneous nitrification, denitrification and phosphorus removal

The recently described process of simultaneous nitrification, denitrification and phosphorus removal (SNDPR) has a great potential to save capital and operating costs for wastewater treatment plants. However, the presence of glycogen-accumulating organisms (GAOs) and the accumulation of nitrous oxide (N2O) can severely compromise the advantages of this process. In this study, these two issues were investigated using a lab-scale sequencing batch reactor performing SNDPR over a 5-month period. The reactor was highly enriched in polyphosphate-accumulating organisms (PAOs) and GAOs representing around 70% of the total microbial community. PAOs were the dominant population at all times and their abundance increased, while GAOs population decreased over the study period. Anoxic batch tests demonstrated that GAOs rather than denitrifying PAOs were responsible for denitrification. NO accumulated from denitrification and more than half of the nitrogen supplied in a reactor cycle was released into the atmosphere as NO. After mixing SNDPR sludge with other denitrifying sludge, N2O present in the bulk liquid was reduced immediately if external carbon was added. We therefore suggest that the N2O accumulation observed in the SNDPR reactor is an artefact of the low microbial diversity facilitated by the use of synthetic wastewater with only a single carbon source. (C) 2005 Elsevier B.V. All rights reserved.