Joseph Zeaiter

Operation of semi-batch emulsion polymerisation reactors: Modelling, validation and effect of operating conditions

A detailed dynamic model was developed for a styrene emulsion polymerisation semi-batch reactor to predict the evolution of the product particle size distribution (PSD) and molecular weight distribution (MWD) over the entire range of monomer conversion. A system exhibiting zero-one kinetics was employed, with the model comprising a set of rigorously developed population balance equations to predict monomer conversion, PSD and MWD. The modelling equations included diffusion-controlled kinetics at high monomer conversion where the transition from the zero-one regime to a pseudo-bulk regime occurs. The model predictions were found to be in good agreement with experimental results. Both particle growth and the PSD were found to be strongly affected by the monomer feedrate. Reactor temperature had a major influence on the MWD which was, however, insensitive to changes in the monomer feedrate. These findings were confirmed experimentally. As a result, it seems reasonable to propose that the use of the monomer feedrate to control the PSD and the reactor temperature to control the MWD are appropriate in practical situations. Consequently, an optimal monomer feed trajectory was developed off-line (using the validated reactor simulation) and verified experimentally by producing a polymer with specific PSD characteristics.

Inferential conversion monitoring and control in emulsion polymerisation through calorimetric measurements

Abstract A dynamic model has been developed describing the emulsion polymerisation of styrene within a batch/semi-batch stirred tank reactor (BSTR). This model includes the initiation, propagation and termination steps for styrene polymerisation, along with the relevant mass balance equations (including those for polymeric radicals) and energy balance equations—the latter covering heat of reaction, internal and external heat transfer effects, as well as external heat losses. The resulting set of (differential/algebraic) equations was solved for both species concentrations and temperature profiles as functions of time. Experiments were conducted in a laboratory BSTR instrumented with platinum resistance thermal transducers and gravimetric conversion measurement devices. The model predictions compared well with inferential calorimetric measurements which were validated using experimental gravimetric data. Subsequent implementation of a model-based optimal control strategy resulted in a 13% relative increase in monomer conversion, together with a 28% reduction in batch time.

Pyrolysis of waste tires: A modeling and parameter estimation study using Aspen Plus®

This paper presents a simulation flowsheet model of a waste tire pyrolysis process with feed capacity of 150kg/h. A kinetic rate-based reaction model is formulated in a form implementable in the simulation package Aspen Plus, giving the flowsheet model the capability to predict more than 110 tire pyrolysis products as reported in experiments by Laresgoiti et al. (2004) and Williams (2013) for the oil and gas products respectively. The simulation model is successfully validated in two stages: firstly against experimental data from Olazar et al. (2008) by comparing the mass fractions for the oil products (gas, liquids (non-aromatics), aromatics, and tar) at temperatures of 425, 500, 550 and 610°C, and secondly against experimental results of main hydrocarbon products (C7 to C15) obtained by Laresgoiti et al. (2004) at temperatures of 400, 500, 600, and 700°C. The model was then used to analyze the effect of pyrolysis process temperature and showed that increased temperatures led to chain fractions from C10 and higher to decrease while smaller chains increased; this is attributed to the extensive cracking of the larger hydrocarbon chains at higher temperatures. The utility of the flowsheet model was highlighted through an energy analysis that targeted power efficiency of the process determined through production profiles of gasoline and diesel at various temperatures. This shows, through the summation of the net power gain from the plant for gasoline plus diesel that the maximum net power lies at the lower temperatures corresponding to minimum production of gasoline and maximum production of diesel. This simulation model can thus serve as a robust tool to respond to market conditions that dictate fuel demand and prices while at the same time identifying optimum process conditions (e.g. temperature) driven by process economics.

Dynamic modeling and path planning of a hybrid autonomous underwater vehicle

In this paper, we present a mechanical design of a conceptual hybrid autonomous underwater vehicle (H-AUV) which combines the features of both a propelled underwater vehicle and those of an underwater glider. We develop its dynamic model and perform several simulations to showcase its locomotive capabilities. The main contribution of the paper is in the proposed motion planning technique to solve for trajectories from a start to a goal configuration. Our method generates feasible trajectories by integrating two Dubins curves. In fact, the motion planning technique is devised to not only generate feasible trajectories but also to assess the optimality of the proposed trajectories.

Bio-Oil Upgrading by Catalytic Cracking Over Different Solid Catalysts

Fossil fuel crises along with global environmental issues, due to combustion of fossil fuel, lead to focus on biomass derived fuels. Bio-oil nowadays is seriously considered to be one of the favorable, renewable and alternative energy sources to replace fossil fuel and has become a significant energy carrier for transportation, industrial and commercial applications. In this study, bio-oil was upgraded by catalytic cracking in a fixed bed reactor in the presence of three different catalysts HY, H-mordenite and HZSM-5.All of the experimental runs were carried out at 500 °C, 0.3MPa and 15:1 oil to catalyst ratio. Catalysts characterization revealed that HZSM-5 with uniform pore and TPD analysis shows the presence of large number of acidic sites as compared to HY and H-mordenite. HZSM-5 proved its effectiveness in terms of deoxygenation and converting oxygenating compounds to hydrocarbons. The amount of hydrocarbons formed was 16.27 wt % OLP for HZSM-5, 15.16 wt% for HY and 14.954 wt % for H-mordenite. HZSM-5 possessed a strong acidity, uniform pore size and high activities which tended to permit the transformation of the oxygenated compounds present in the bio-oil to hydrocarbons. The upgraded bio-oil obtained posses improved physiochemical properties such pH which was increased from 2.21 to 3.56 while density was decreased upto 0.82 kg/m. The calorific value also increased upto 31.65 kJ/kg. The improved bio-oil by HZSM-5 catalyst can be considered as a potential for to be used as direct fuel.

The role of wave-net models in emulsion polymerisation

Abstract As the first step in a study to assess the impact of modern control techniques on the performance of polymerisation reactors, an existing kinetic model (written in Fortran) was used to predict the particle size distribution (PSD), particle number and amount of secondary nucleation in an emulsion polymerisation system. However, this model proved far too slow for studying the dynamic behaviour (and advanced control) of such reactors. To circumvent this problem, two approaches were taken. Firstly, the relevant population balance and kinetic equations were solved using the commercial gPROMS package—this gave a very significant reduction in model solution time. Secondly, two input–output wave-net models were developed—the first to estimate an “averaged” particle size distribution, the second to estimate the full particle size distribution. These wave-net models used simulation data obtained from the gPROMS model for the case of styrene polymerisation, and covered a range of initiator and surfactant concentrations, as well as different reaction temperatures. The wave-net models were acceptably accurate (relative to the full kinetic model), although the study showed that extrapolation beyond the available training data can yield poor results.

Reactor Operating Strategy and Secondary Nucleation in Emulsion Polymerization

Particle formation is a key step in emulsion polymerization reactions and has been the subject of extensive investigations in the past few decades. The main aim of this work was to investigate, both theoretically and experimentally, the conditions for secondary nucleation and particle evolution in batch and semi-batch emulsion polymerization. The effects of variation in monomer and emulsifier concentration in the feed, the distribution between the charge and the feed, temperature and the emulsion feed rate on polystyrene particle size distribution were investigated both theoretically and experimentally. The population balance and kinetic models developed were employed for predicting the product attributes for a range of reactor operating conditions. The sets of nonlinear algebraic and integro-differential evolution equations were solved efficiently for this work.Monomer and surfactant feed rates were found to have significant effects on the growth of polymer particles and consequently on the particle size. Different particle sizes and distributions were obtained using the same procedure with variable operating mode. A semi-batch reactor with variable monomer emulsion feed can produce latexes with variable polydispersity. A high initial rate of particle formation could lead to reduction in secondary nucleation and hence to the formation of a mono-modal PSD. This can be achieved by using high initiator and emulsifier concentrations in the feed, a high temperature, or a low monomer concentration in the charge. A low initial rate of nucleation increases the possibility of secondary nucleation and the formation of a bimodal PSD. The evolution of a bimodal PSD requires secondary nucleation after primary nucleation occurs.

On-Line Optimal Control of Particle Size Distribution in Emulsion Polymerisation

Abstract This paper concerns itself with the question of the on-line optimal control of the particle size distribution (PSD) from an emulsion polymerisation reactor, using the monomer feed rate as a manipulated variable. A recently developed (and validated) reactor model was employed in the formulation of this control strategy. The model was implemented within the gPROMS software package and used as a “soft sensor” for the on-line estimation of the PSD within a model-based predictive control (MPC) formulation, so as to determine on-line the optimal trajectory for the monomer feed rate. For control purposes, the distributed nature of the PSD was represented by the leading moments, with the control objective being formulated as a function of both the breadth of the distribution and the average particle diameter. Off-line sample analysis, carried out using capillary hydrodynamic fractionation, was also incorporated into the control strategy (as irregular measurements), so as to update the on-line model predictions. Experimental studies on a laboratory scale styrene polymerisation reactor showed that such an approach was able to accurately predict the behaviour of the reactor, as well as improving its performance.

Strategies for optimisation and control of molecular weight and particle size distributions in emulsion polymerisation

Publisher Summary Emulsion polymerization is widely used in industries to produce products ranging from adhesives to surfboards. The process is preferred because the reaction medium (usually water) facilitates agitation, heat and mass transfer, and provides an inherently safe process. Emulsion polymerization reactor dynamics were modeled with a focus on the computation of molecular-weight distributions (MWD) and particle-size distributions (PSD). The evolution model equations included the detailed kinetics of styrene polymerization in a semibatch reactor through free-radical mechanism. The effects of variations in temperature, feed-rate, and monomer and surfactant concentrations on the molecular weight, particle size, and polydispersity indices are investigated. The operating temperature and monomer and surfactant feed rates are found to have significant effects on the MWD and PSD. Based on findings, strategies for controlling the MWD and PSD are formulated.

Solar pyrolysis of waste rubber tires using photoactive catalysts

The solar pyrolysis of waste tire rubber was investigated with the application of heterogeneous photocatalysts including TiO2, Pd/TiO2, Pt/TiO2, Pd-Pt/TiO2, and Bi2O3/SiO2/TiO2. Experiments were performed at temperatures ranging between 550 and 570 °C under solar irradiations of 950-1050 W/m2. The gas yield from non-catalytic solar pyrolysis was at 20% while the use of TiO2 catalyst increased the gas yield to 27%. Doping of TiO2 with noble metals and Bi2O3/SiO2 metal oxides enhanced further the cracking ability of the catalyst. Bi2O3/SiO2/TiO2 gave a 32% gas yield. The highest gas yields of 40% and 41% were achieved over Pd-Pt/TiO2 and Pd/TiO2 catalysts, respectively. Catalyst characterization by BET, SEM, EDX and XRD showed the role of metal doping in altering the morphology of TiO2, resulting in nanocrystallites, larger pore volume and higher surface area. Both, Pd and Bi influenced the photocatalytic properties of TiO2 improving cracking activity during pyrolysis of waste rubber.