no / Batch and semi-batch reactors are widely used for fine chemical productions. The target in the fine chemical industry is to produce a high quality product and operational optimization is the key-element to match it. This work investigates how batch and semi-batch reactors can be optimized in order to increase the yield of a desired product. Optimization problem is formulated and applied to calculate the optimal operating parameters such as the reactor temperature and the feed flow rate. Comparison and considerations on the two reactor configurations are given.

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<p> The transient behaviour of a batch stirred-tank reactor (BSTR) for free radical polymerization of styrene in toluene has been studied experimentally and theoretically. A kinetic model applicable to high conversions was developed using data from measurements of monomer conversion and molecular weight distribution (MWD). Significant improvement over the conventional kinetic model is obtained when the viscosity or gel effect is accounted for. The termination rate constant and catalyst efficiency are allowed to vary with viscosity. The findings agree with the general theory of diffusion-controlled reaction which predicts that viscosity is the most important parameter.</p> / Thesis / Master of Engineering (MEngr)

<p> The free radical polymerization of styrene in benzene using azo-bisisobutyronitrile as a catalyst has been studied both theoretically and experimentally. The molecular-weight distribution and conversion are predicted on the basis of a simplified kinetic mechanism, neglecting a number of minor side reactions. The steady-state assumption is investigated and is shown to be applicable in the case of styrene polymerization, a pseudo-steady-state being reached in less than one second. Using the steady-state approach a relatively simple kinetic model is obtained, suitable for computer simulation. The prime variables consist of the ordinary reaction conditions such as monomer concentration, solvent concentration, catalyst concentration, reaction temperature and reaction time.</p> <p> The polymerization was carried out isothermally in a stirred batch reactor from which samples were abstracted at various time intervals. Conversion was determined by precipitating the polymer with methanol, filtering, and weighing, and the molecular-weight distribution has been obtained by gel-permeation chromatography. A computer program was written to interpret the variation of refractive index with respect to the elution volume trace from the chromatograph, giving a readout of molecular chain length in monomer units versus weight fraction.</p> <p> The experimentally obtained conversion and distribution curves are compared with those obtained from the mathematical model. Except for bulk polymerization agreement between the two is good. Good agreement for conversion is obtained for all cases if the catalyst initiation efficiency is adjusted according to the monomer or solvent concentration. However, the same considerations do not give good agreement for molecular-weight distribution. Rather it appears that the rate constants instead of the catalyst efficiency are monomer or solvent concentration dependent, which would explain the discrepancies.</p> / Thesis / Master of Engineering (MEngr)

Filamentous bulking is a problem that has long plagued activated sludge (AS) wastewater treatment plants (WWTPs). Much research has looked at its prevention and control but there is still no solution. The sludge microbiological community is very complex and there are many factors that can affect bulking. Clay addition in scaled-down activated sludge systems was investigated at concentrations of 0.4, 2.0 and 5.0 g/L along with sequencing batch reactor (SBR) parameters when run with a synthetic wastewater (SWW). The 5.0g/L concentration exhibited positive results on settling in the form of modified SVI but appeared to cause no reduction in filament length. These preliminary investigations indicate that clay may help improve sludge settling but make no difference in the abundance of filamentous microorganisms. The SBRs exhibited trends in regards to running systems with a synthetic wastewater. A loss of volatile suspended solids (VSS), coupled with increase in sludge volume index (SVI), suggested a link between lack of non-VSS and settling ability. This has implications in the importance of non-VSS such as grit or clay in research performed using SWWs.

This thesis is comprised of two phases; the first phase concerns the effect of arsenic on the denitrification process in the presence of naturally-produced volatile fatty acids (VFAs); while the second phase evaluates the arsenic removal efficiency of New Zealand Iron Sand (NZIS) by adsorption. To accomplish the first phase of the study, VFAs were first produced naturally in an acid-phase anaerobic digester by using commercially-available soy flour. Secondly, a denitrifying biomass was cultivated in a sequencing batch reactor (SBR) using domestic wastewater as a feed solution. Finally, a series of biological denitrification batch tests were conducted in the presence of different concentrations of arsenic and nitrate. As mentioned, the VFAs were generated from an anaerobic digester using 40 g/L soy solution as a synthetic feed. The digester was operated at a solids retention time (SRT) and hydraulic retention time (HRT) of 10 days. The pH of the digester was measured to be 4.7 to 4.9 while the mean temperature was 31 ± 4 °C; however, both these parameters were not controlled. In the effluent of the digester, a mean VFA concentration of 5,997 ± 538 mg/L as acetic acid was achieved with acid speciation results of acetic (33 %), propionic (29 %), butyric (21 %), iso-valeric (5%) and n-valeric acid (12 %). The specific VFA production rate was estimated to be 0.028 mg VFA as acetic acid/mg VSS per day. The effluent sCOD was measured to be 14,800 mg/L (27.9 % of the total COD), as compared to 9,450 mg/L (16.8 % of total COD) in the influent of the digester. Thus, the COD solubilization increased by 11.1 % during digestion yielding a specific COD solubilization rate of 0.025 mg sCOD/mg VSS per day. The extent of the digestion process converting the substrate from particulate to soluble form was also evaluated via the specific TOC solubilization rate (0.008 mg TOC/mg VSS per day), and VSS reduction percentage (17.7 ± 1.8 %). A denitrifying biomass was developed successfully in an SBR fed with domestic sewage (100 % denitrification was achieved for the influent concentration of sCOD = 285 ± 45 mg/L and NH₄⁺-N = 32.5 ± 3.5 mg/L). A mean mixed liquor suspended solids (MLSS) of 3,007 ± 724 mg/L and a mean SRT of 20.7 ± 4.4 days were measured during the period of the research. The settleability of the SBR sludge was excellent evidenced by a low sludge volume index (SVI) measured to be between 50-120 mL/g (with a mean value of 87 ± 33 mL/g) resulting in a very low effluent solids concentration (in many cases less than 20 mg/L). Several preliminary tests were conducted to estimate the right dosage of VFAs (digester effluent), nitrates and arsenic to be added and to confirm the occurrence of denitrification in an appropriate time frame of 4-6 h. From these tests, an optimum C/N ratio was observed to be somewhere between 2 to 4, somewhat higher than all the theoretical C/N ratios required for a complete denitrification using the four major VFAs identified in the digester effluent. During the denitrification batch tests, it was also observed that some NO₃⁻- N was removed instantaneously by reacting with As (III) (As₂O₃); while an increase in alkalinity of around 5.60 mg as CaCO₃ produced per mg NO₃⁻- N reduction was also observed. This latter number was very close to the theoretical value of alkalinity production (i.e. 5.41 mg as CaCO₃ per mg NO₃⁻- N). The effect of arsenic on the denitrification process was evaluated by observing the specific denitrification rate in series of denitrification batch tests (with different concentrations of arsenic). Results from the denitrification batch tests showed that there was a clear effect for both As (III) and As (V) on denitrification. In particular, the specific denitrification rate fell from 0.37 to 0.01 g NO₃⁻- N /g VSS per day as the concentration of As (III) increased from 0 to 50 mg/L. In contrast, there was comparatively less effect for As (V); i.e. only a 37 % decrease in the specific denitrification rate (from 0.34 g NO₃⁻- N /g VSS per day to 0.23 g NO₃⁻- N /g VSS per day) when the initial arsenic concentration increased from 0 to a very high level of 2,000 mg/L. The effects of both the As (III) and As (V) forms of inorganic arsenic on the denitrification rate were further quantified by constructing exponential equation models. It was suspected that the effect of As (III) on denitrification was more substantial than the effect of As (V) because of the former’s toxicity to microbes. Finally, the fate of arsenic was tracked by examining bacterial uptake. During the normal denitrification batch tests (i.e. designed for evaluation of the effect of arsenic on denitrification), no significant arsenic removal was observed. However, additional batch tests with a comparatively low concentration of biomass revealed that the denitrifying biomass removed 1.35 µg As (III) /g dry biomass and 2.10 µg As (V) /g dry biomass. In the second phase of this research, a series of arsenic adsorption batch tests as well as a column test were performed to examine the arsenic (As (III) and As (V)) removal efficiency of NZIS from an arsenic-contaminated water. The kinetics and isotherms for adsorption were analysed in addition to studying the effect of pH during the batch tests. Breakthrough characteristics for both As (III) and As (V) were studied to appraise the effectiveness of NZIS treating an arsenic contaminated water. Batch tests were performed with different concentrations of arsenic as well as at different pH conditions. A maximum adsorption of As (III) of approximately 90 % occurred at a pH of 7.5, while the As (V) adsorption reached its maximum value of 97.6 % at a very low pH value of 3. Both Langmuir and Freundlich Models were tested and found to fit with R² values of more than 0.92 in all cases. From the Langmuir adsorption model, the maximum adsorption capacity of NZIS for As (III) was estimated to be 1,250 µg/g, significantly higher (about three times) than for As (V) of 500 µg/g. In column tests, arsenic-contaminated water with total As concentration of 400 µg/L (in either form of As) were treated and a pore volume (PV) of 700 and 300 yielded a total arsenic level less than the WHO guideline value of 10 µg/L for As (III) and As (V) respectively; while, the breakthrough occurred after a throughput of approximately 3,000 PV of As (III) and 2,700 PV of As (V) with an average flow rate of approximately 1.0 mL/min.

Batch and semi-batch processes provide needed flexibility for multi-product plants, especially when products change frequently and production quantities are small. However, challenges occur when trying to implement reliable control systems in batch processes due to some unavoidable inherent characteristics such as the presence of time-varying and nonlinear batch process dynamics and a host of unmeasured disturbances. The most typical control strategy employed in batch process operations does not use utilise online measurements of variables directly related to the product quality and as such is bound to produce off specification products even when the specified control objective has been met. Work done in this thesis is concerned with the design of a supervisory control scheme that takes into consideration the online status of the quality variable of interest from the beginning to the end of the batch process. A novel control methodology is proposed which combines the speed and flexibility of Near-Infrared (NIR) spectroscopic measurements as quality feedback variables within a multiple model predictive control (MPC) framework. In particular the multivariate NIR spectral data is pre-processed for feedback using a statistical model based on Independent Component Analysis (ICA). The proposed controller is tested on a benchmark simulated batch reactor using several case studies and is demonstrated to bring significant improvement in control performance when contrasted with other inferential and direct quality controllers.

No / The use of neural networks (NNs) in all aspects of process engineering activities, such as modelling, design, optimization and control has considerably increased in recent years (Mujtaba and Hussain, 2001). In this work, three different types of nonlinear control strategies are developed and implemented in batch reactors using NN techniques. These are generic model control (GMC), direct inverse model control (DIC) and internal model control (IMC) strategies. Within the control strategies, NNs have been used as dynamic estimator, dynamic model (forward model) and control (inverse model). An exothermic complex reaction scheme in a batch reactor is considered to explain all these control strategies and their robustness. A dynamic optimization problem with a simple model is solved a priori to obtain optimal operation policy in terms of the reactor temperature with an objective to maximize the desired product in a given batch time. The resulting optimal temperature policy is used as set-point in the control study. All types of controllers performed well in tracking the optimal temperature profile and achieving target conversion to the desired product. However, the NNs used in DIC and IMC controllers need training beyond the nominal operating condition to cope with uncertainties better.

Yes / Due to the environmental legislations related to sulfur content and proceeding with the challenges to find an appropriate catalyst of such contamination producing clean fuel, a main thrust for improving of more efficient technologies on new oxidative catalyst is viewed a vital issue in fuel quality development. So, in this study, the sulfur compound (ethyl mercaptan) presents in light naphtha feedstock is removed by oxidative desulfurization (ODS) in a batch reactor using a new homemade nano-catalyst and air as oxidant under different reaction conditions (reaction temperatures, reaction time and the initial sulfur concentrations) that has not been studied in such field. The catalyst is zinc oxide supported on zeolite nanoparticles which is locally prepared by Incipient Wetness Impregnation (IWI) method. Mathematical model of the relevant reactions is also developed in this study to match the experimental results via obtaining the optimal kinetic parameters utilizing optimization techniques within gPROMS program. Such optimization is conducted using two approaches (linear and nonlinear regression) and the results showed that the nonlinear approach is more accurate than linear approach. The optimal kinetic parameters are then used to achieve a clean fuel via getting the optimal operation conditions based on the maximum conversion. Where, higher than 99% of the process conversion has obtained at temperature of 327.4 K, reaction time at163.6 min and initial concentration of 335.3 ppm.

The purpose of this research was to characterize a flushed dairy manure wastewater and to develop the kinetic and stoichiometric parameters associated with nitrogen removal from the wastewater, as well as to demonstrate experimental and simulated nitrogen removal from the wastewater. The characterization showed that all the wastewaters had carbon to nitrogen ratios large enough for biological nitrogen removal. Analysis of carbon to phosphorus ratios showed that enough carbon is available for phosphorus removal but enough may not be available for both nitrogen and phosphorous removal in anaerobically pretreated wastewater. In addition, kinetic and stoichiometric parameters were determined for the biological nitrogen removal in sequencing batch reactors for the dairy manure wastewater. Results showed that many parameters are similar to those of municipal wastewater treatment systems. This characterization and the derived kinetic and stoichiometric parameters provided some of the information necessary for development of a nitrogen removal process in a sequencing batch reactor. Lab scale treatment of a 1:2 dilution of the anaerobically pretreated wastewater was demonstrated. Treatment was able to achieve between 89 and 93% removal of soluble inorganic nitrogen as well as up to 98% removal of biodegradable soluble and colloidal COD. In addition, a solids removal efficiency of between 79 and 94% was achieved. The lab scale treatment study demonstrated that sequencing batch reactors are capable of achieving high nitrogen removal on wastewaters with the carbon to nitrogen ratios of the dairy manure wastewater. Model simulations of the treatment process were used to develop a sensitivity analysis of the reactor feed configuration as well as the kinetic and stoichiometric parameters. The analysis of the feed configuration demonstrated the advantage of decreasing the amount of feed that is fed in the last feed period so that the effluent nitrate will be minimized. The analysis indicated that the autotrophic growth rate is one of the most important parameters to measure while error in the heterotrophic decay or yield values can lead to miscalculations of oxygen required for treatment. / Master of Science