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Reactor Operation (reactor + operation)
Selected AbstractsBonding Form Analysis of Metals and Sulfur Fractionation in Methanol-Grown Anaerobic Granular SludgeENGINEERING IN LIFE SCIENCES (ELECTRONIC), Issue 5 2007A. van der Veen Abstract This study investigates the metal and sulfur bonding form distribution in mesophilic (30,°C, pH 7) methanol-grown anaerobic granular sludge from upflow anaerobic sludge bed reactors operating at an organic loading rate of 3.8,g CH3OH-COD/L d. This was achieved by applying a modified Tessier sequential extraction scheme to investigate the metal bonding forms and a sequential extraction scheme for sulfur and simultaneously extracted metals to granular sludge samples of the reactors after 0, 22, 35 and 43 days of operation. Metals were also determined in the sulfur extracts. Co and Ni predominated in their oxidizable bonding forms, which increased together with the pseudo-total content during reactor operation. An omission of Co and Ni from the influent led to only a minor decline of the pseudo-total content in the sludge, mainly from the acid-soluble fraction. The ratio of simultaneously extracted metals (Co, Fe, Mn, Ni) to acid-volatile sulfides was lower than 1, indicating that the sludge contained sufficient sulfide to bind the metals as metal monosulfides. The bioavailability of metals in the methanol-grown anaerobic granular sludge investigated is therefore mainly controlled by sulfide formation/dissolution. [source] Optimization of Operating Temperature for Continuous Immobilized Glucose Isomerase Reactor with Pseudo Linear KineticsENGINEERING IN LIFE SCIENCES (ELECTRONIC), Issue 5 2004N.M. Faqir Abstract In this work, the optimal operating temperature for the enzymatic isomerization of glucose to fructose using a continuous immobilized glucose isomerase packed bed reactor is studied. This optimization problem describing the performance of such reactor is based on reversible pseudo linear kinetics and is expressed in terms of a recycle ratio. The thermal deactivation of the enzyme as well as the substrate protection during the reactor operation is considered. The formulation of the problem is expressed in terms of maximization of the productivity of fructose. This constrained nonlinear optimization problem is solved using the disjoint policy of the calculus of variations. Accordingly, this method of solution transforms the nonlinear optimization problem into a system of two coupled nonlinear ordinary differential equations (ODEs) of the initial value type, one equation for the operating temperature profile and the other one for the enzyme activity. The ODE for the operating temperature profile is dependent on the recycle ratio, operating time period, and the reactor residence time as well as the kinetics of the reaction and enzyme deactivation. The optimal initial operating temperature is selected by solving the ODEs system by maximizing the fructose productivity. This results into an unconstrained one-dimensional optimization problem with simple bounds on the operating temperature. Depending on the limits of the recycle ratio, which represents either a plug flow or a mixed flow reactor, it is found that the optimal temperature of operation is characterized by an increasing temperature profile. For higher residence time and low operating periods the residual enzyme activity in the mixed flow reactor is higher than that for the plug flow reactor, which in turn allows the mixed flow reactor to operate at lower temperature than that of the plug flow reactor. At long operating times and short residence time, the operating temperature profiles are almost the same for both reactors. This could be attributed to the effect of substrate protection on the enzyme stability, which is almost the same for both reactors. Improvement in the fructose productivity for both types of reactors is achieved when compared to the constant optimum temperature of operation. The improvement in the fructose productivity for the plug flow reactor is significant in comparison with the mixed flow reactor. [source] Hydrogen generation in a reverse-flow microreactor: 1.AICHE JOURNAL, Issue 8 2005Model formulation, scaling Abstract A 1-D model for methane partial oxidation in a tubular microreactor is considered. This work is motivated by a recent report by Kikas et al. that experimentally demonstrated the possibility of autothermal generation of hydrogen by partial oxidation of methane in a tubular microreactor. The reactor consists of four cylindrical channels, each 500 microns in diameter, containing Pt/13%,Rh catalyst. Autothermal generation of hydrogen was possible in both unidirectional (UD) and reverse-flow (RF) operations of the reactor, with the RF operation providing better hydrogen yield and lower temperatures than those of the UD operation. Critical comparison of methane oxidation and reforming kinetics from the literature is performed. An analysis of the timescales of individual processes within the reactor is presented to gain fundamental insight into the reactor operation. Finally, the effect of radiation heat transfer is also considered, and it is found to play an important role for a shorter-size reactor. © 2005 American Institute of Chemical Engineers AIChE J, 2005 [source] Simulating cyclohexane millisecond oxidation: Coupled chemistry and fluid dynamicsAICHE JOURNAL, Issue 6 2002R. P. O'Connor Cyclohexane partial oxidation over a 40-mesh Pt,10% Rh single-gauze catalyst can produce ,85% selectivity to oxygenates and olefins at 25% cyclohexane conversion and 100% oxygen conversion, with cyclohexene and 5-hexenal as the dominant products. A detailed 2-D model of the reactor is solved using density-functional theory (with 35 reactions among 25 species) and computational fluid dynamics. Rapid quenching in the wake of the wires allows highly nonequilibrium species to be preserved. The simulations show that the competition between cyclohexyl and cyclohexylperoxy radicals is crucial in determining product selectivities. At high temperatures and low pressures, the cyclohexyl radical is favored, leading to high selectivities to cyclohexene. At lower temperatures or high pressures, cyclohexylperoxy radicals are favored, allowing the formation of parent oxygenates to dominate. Numerical simulations suggest ways to tune reactor operation for desired product distributions and allow the investigation of dangerous or costly operating conditions, such as high pressure. [source] Prediction of Polymer Properties in LDPE ReactorsMACROMOLECULAR MATERIALS & ENGINEERING, Issue 4 2005Gary J. Wells Abstract Summary: A new analysis tool is presented that uses the governing kinetic scheme to predict properties of low-density polyethylene (LDPE) such as the detailed shape of the molecular weight distribution (MWD). A model that captures mixing details of autoclave reactor operation is used to provide a new criterion for the onset of MWD shouldering. Kinetic effects are shown to govern the existence of MWD shoulders in LDPE reactors, even when operation is far from perfectly-mixed. MWD shoulders occur when the mean reaction environment has a relatively high radical concentration and has a high polymer content, and is at a low temperature. Such conditions maximize long chain formation by polymer transfer and combination-termination, while limiting chain scission. For imperfectly-mixed reactors, the blending of polymer-distributions produced in different spatial locations has a small effect on the composite MWD. However, for adiabatic LDPE autoclaves, imperfect mixing broadens the stable range of mean reactor conditions, and thereby increases the possibility for MWD shouldering. Polymer MWD produced in an LDPE autoclave reactor by various kinetic mechanisms. [source] Gel point prediction of metal-filled castor oil-based polyurethanes system,POLYMERS FOR ADVANCED TECHNOLOGIES, Issue 10-12 2002Anil Srivastava Abstract Prediction of gel point conversion and network formation is of great importance in polycondensation during synthesis as well as processing. It enables one to estimate the safe conversions for reactor operation without gelation and the cycle time during processing, and plays an important role in controlling the molding parameters used for reinforced reaction injection molding (RRIM), reaction injection molding (RIM) and compression molding. Theories of gelation have been extensively published in the literature and supported by experimental data for various polycondensation systems. However, most such studies relate to unfilled systems. In this work, metal-filled polyurethanes have been synthesized in bulk by reacting toluene di-isocyanate with castor oil and its polyols possessing different hydroxyl values. Metallic aluminum powder (10,40% by weight) was dispersed thoroughly in castor oil and its polyols before reacting at different temperatures (30,60,°C) in a moisture-free, inert environment. The gel point conversions were measured experimentally and an empirical model from the experimental data has been developed to predict the gelation behavior. The proposed model could be of immense importance in the paints, adhesives and lacquers industries, which use castor oil in bulk. From these experiments it was concluded that: (i) fine metal powder gives a rise in viscosity; (ii) metal fillers not only restrict the molecular motion due to the increase in viscosity, but also lower the conversion; (iii) the vegetable oil and its polyols have a number of bulky groups, which also impart the delay tendency in gel time; (iv) there is a change in gelation dynamics at 50,°C , this is due to the change in reactivity of di-isocyanates; (v) the presence of metal filler does not initiate the intermolecular condensation; (vi) there is a gap between theoretical and experimental gel point owing to the unequal reactivity of the secondary alcohol position; (vii) there is an inverse relationship of gel time with the reaction temperature and hydroxyl value of polyols. An empirical model based on process parameters, i.e., hydroxyl value, temperature, shape factor and filler concentration, has been derived and found to be adequate for the metal-filled system. The correlation coefficient on the data is on the lower side in some cases because the following were not taken into account: (i) the first-order kinetics followed by the reaction in the second half while it is tending towards gelation; (ii) the error in observing the gel point viscosity; (iii) errors in assuming the spherical shape of aluminum metal powder; (iv) errors due to failure to maintain the constant speed in agitation. Copyright © 2003 John Wiley & Sons, Ltd. [source] Carrier effects on oxygen mass transfer behavior in a moving-bed biofilm reactorASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 5 2009Jie Ying Jing Abstract This study investigates the carrier effects on the oxygen mass transfer behavior of a gas,liquid biofilm surface, and aims to provide evidence for parameter optimization in the practical operation of a moving-bed biofilm reactor (MBBR) during the coking-plant wastewater process. By using the dynamic oxygen dissolution method, the volumetric oxygen mass transfer coefficient KLa was measured by varying the suspended carrier stuffing rate and the intensity of aeration. Within the range of fluidizable flow rate, the efficiency of oxygen mass transfer increased with suspended carrier stuffing rate, and KLa reached its peak value when the stuffing rate was 40%. KLa has an increasing trend with an increase of the aeration intensity, but high aeration intensity was not favorable for reactor operation. Better oxygen mass transfer effect and higher oxygen transfer efficiency could be achieved when the aeration intensity was 0.3 m3 h,1 and the suspended carrier stuffing rate was 30,50%. The possible mechanisms that can account for carrier effects on oxygen mass transfer are the changes in the gas,liquid interfacial area. The ammonia nitrogen removal performance of the coking-plant wastewater in MBBR was satisfied by using the above-suggested conditions. Copyright © 2009 Curtin University of Technology and John Wiley & Sons, Ltd. [source] Design of Metabolic Engineering Strategies for Maximizing l -(,)-Carnitine Production by Escherichia coli.BIOTECHNOLOGY PROGRESS, Issue 2 2005Bioreactor Levels, Integration of the Metabolic In this work metabolic engineering strategies for maximizing l -(,)-carnitine production by Escherichia coli based on the Biochemical System Theory (1,3) and the Indirect Optimization Method are presented (4). The model integrates the metabolic and the bioreactor levels using power-law formalism. Based on the S-system model, the Indirect Optimization Method was applied, leading to profiles of parameter values that are compatible with both the physiology of the cells and the bioreactor system operating conditions. This guarantees their viability and fitness and yields higher rates of l -(,)-carnitine production. Experimental results using a high cell density reactor were compared with optimized predictions from the Indirect Optimization Method. When two parameters (the dilution rate and the initial crotonobetaine concentration) were directly changed in the real experimental system to the prescribed optimum values, the system showed better performance in l -(,)-carnitine production (74% increase in production rate), in close agreement with the modelapos;s predictions. The model shows control points at macroscopic (reactor operation) and microscopic (molecular) levels where conversion and productivity can be increased. In accordance with the optimized solution, the next logical step to improve the l -(,)-carnitine production rate will involve metabolic engineering of the E. coli strain by overexpressing the carnitine transferase, CaiB, activity and the protein carrier, CaiT, responsible for substrate and product transport in and out of the cell. By this means it is predicted production may be enhanced by up to three times the original value. [source] Dynamic On-Line Reoptimization Control of a Batch MMA Polymerization Reactor Using Hybrid Neural Network ModelsCHEMICAL ENGINEERING & TECHNOLOGY (CET), Issue 9 2004Y. Tian Abstract A hybrid neural network model based on-line reoptimization control strategy is developed for a batch polymerization reactor. To address the difficulties in batch polymerization reactor modeling, the hybrid neural network model contains a simplified mechanistic model covering material balance assuming perfect temperature control, and recurrent neural networks modeling the residuals of the simplified mechanistic model due to imperfect temperature control. This hybrid neural network model is used to calculate the optimal control policy. A difficulty in the optimal control of batch polymerization reactors is that the optimization effort can be seriously hampered by unknown disturbances such as reactive impurities and reactor fouling. With the presence of an unknown amount of reactive impurities, the off-line calculated optimal control profile will be no longer optimal. To address this issue, a strategy combining on-line reactive impurity estimation and on-line reoptimization is proposed in this paper. The amount of reactive impurities is estimated on-line during the early stage of a batch by using a neural network based inverse model. Based on the estimated amount of reactive impurities, on-line reoptimization is then applied to calculate the optimal reactor temperature profile for the remaining time period of the batch reactor operation. This approach is illustrated on the optimization control of a simulated batch methyl methacrylate polymerization process. [source] | ||||||||||||||||