The Chemical Engineering Journal and the Biochemical Engineering Journal最新文献

Different methods of analysis of chaotic time series of the wall pressure fluctuations were applied to characterize the intermittent flow patterns in a horizontal pipe. A weak sign of deterministic chaos was diagnosed within a transition from plug flow to slug flow. At higher superficial gas velocities, the amplitude modulation of the pressure pulses in the slug flow regime indicated a significant degree of correlation between the subsequent slugs. The transition to annular flow was found to occur via the gas blow through the shortest and most aerated slugs. The resulting transition patterns displayed the intermittency route to chaos.

Fractal geometry can be used in the development of porous catalysts with higher conversions and selectivities for desirable products. The fractal surface morphology, which can be tuned by changing the preparation conditions, has an influence on the Knudsen diffusivities and on the intrinsic reaction rates per unit catalyst mass. Depending on the catalyst and the operating conditions, the effective reaction rate of a first-order reaction can either increase or decrease with the fractal dimension of the surface. The simulation of an industrial unit for the catalytic reforming of naphtha is used as an example of how the design of the fractal catalyst surface can influence iso-paraffins, aromatics and hydrogen yields. The hydrogen yields exhibit a maximum of around 3.6 wt.% for an intermediate fractal surface dimension, D^s_ads = 2.6. The highest isoparaffins yield is obtained for a smooth surface (23 wt.%), while surfaces with a high D^x_ads lead to the highest aromatics yields (up to 76 wt.% for D^s_ads = 3).

Recent developments in non-linear dynamics and complex phenomena have resulted in mathematical tools which are potentially useful in the control and design of bubble column reactors. It is conjectured that analysis of conductivity time series, measured in a bubble column, indicated a low-dimensional chaotic attractor. The cross-sectional average correlation dimension varied with the liquid and the gas flow rate. The cross-sectional average correlation dimension characterized the global bubble column hydrodynamics and, more specifically, the average bubble size.

We investigate the yield of bimolecular chemical reaction between two initially separated reactants in a tubular reactor of different coiling geometries. Laminar and steady flow with high mass Peclet number, Pe, are assumed. Asymptotic approximations for slow reactions are obtained by studying the reaction at a thin interfacial boundary layer. For a straight tube it is found that the area-averaged product mass fraction at a given axial position z goes z^{$\text{3}\text{2}$} Λ(z) Pe^{−$\text{1}\text{2}$}, where Λ(z) is the length of the interface separating the two reactants. Coiling and flow kinematics have a strong effect on Λ(z). Regular mixing produced by secondary transverse flow in a helical coil stretches the interface linearly with z, yielding a z^{$\text{5}\text{2}$} dependence for hte product mass fraction. Further enhancement derived from chaotic mixing and stretching is possible in a coil with a coiling axis that is periodically changed in the flow direction. If the switching length exceeds a critical value, the folding and stretching of the chaotic action leads to an exponentially growing length that can be related to a positive Lyapunov exponent. Numerical solutions show that this enhancement by chaotic mixing also exists for fast reactions, and that the stretching effect can be overwhelmed by tight and uneven interfacial separation in a long, high-yield reactor when the reaction boundary layers begin to overlap or interact with the wall.

The development of a rheological model for aggregated suspensions is necessarily based upon a suitable characterization of the structure of the disperse phase and of the structural modifications produced by a deformation or a velocity field. The disperse phases of real aggregate particle suspensions, both dilute and concentrated, may present a wide variety of structures, which can be conveniently characterized by using the concepts of fractal geometry. In the present paper we formulate a rheological model able to correlate the structural processes induced by shear sflow conditions and the consequent shear dependence of viscosity with the shear stress changes experienced by the suspension. The flow curves calculated from the model, both for dense and fractal aggregates, closely resemble those observed for real colloidal and non-colloidal suspensions. The model appears particularly advantageous in describing the transition from shear thinning to plastic behavior, which usually occurs with increasing volume fraction or aggregation of the disperse phase. The role played by the aggregation state of the disperse phase become predominant in the low shear stress range, where aggregates may be composed of many particles, and, consequently, where the fractal dimensionality D becomes an important parameter in determining the compactness of the aggregate structure and the rheological behavior of concentrated suspensions. The validity of the proposed model is checked further through an analysis of experimental viscosity data relative to two series of epoxy-acrylic systems, containing titanium dioxide and aluminum silicate at different disperse phase concentrations.

The performance of multiphase reactors is greatly affected by their flow regime. The box-counting dimension of a probe signal characterizes its intrinsic, dimensionless structure and is not significantly affected by moderate changes in probe calibration constants. Using the box-counting dimension to characterize the flow regime can, thus, eliminate problems associated with changes in probe, liquid or solid characteristics. This study uses an approximate box-counting dimension which is so rapidly calculated that it could be used for on-line control. The box-counting dimension of the raw signal from a bubble probe allows the accurate detection of gas maldistribution in bubble columns and gas-liquid-solid fluidized beds. The box-counting dimension of the raw signal from a local conductivity probe allows the accurate detection of liquid maldistribution in bubble columns and gas-liquid-solid fluidized beds. The fluidization regime of liquid-solid and gas-liquid-solid beds can be accurately identified from the box-counting dimension of the signal recorded with either local probes or cross-sectional probes. The complete fluidization of a liquid-solid bed of splinter-like particles can be determined from the box-counting dimension of the signals from either a local probe or trace rinjection experiments.

The time evolution of fractal objects is ivestigated. A mechanism of iterative development is suggested based on the partial scaling of the initiator-generator fractals. The approach enables us to estimate the Hausdorff dimension of the resulting objects. An example is given from the modeling of catalytic gas-solid reactions.

The intermittent flow in a circulating fluidized bed is shown to possess a multifractal character. The voidage signals at different solids concentrations and radial positions are characterized by defining an intermittency measure selected from a hierarchy of multifractal exponents. The intermittency profiles based on the raw measured data are consistent with the bindings of Brereton and Grace (Chem. Eng. Sci., 48 (14) (1993) 2565–2572), while the results obtained after removing the contribution from clusters match those of Jiang et al. (Circulating Fluidized Bed Technology IV, AIChE Publications, 1994, pp. 111–117). The success of multifractal characterization of CFB flow suggests that the cluster motion may behave as a multiplicative cascade process.

Chaos has been found in a number of nonlinear chemical processes including electrochemical reactions, fluidized beds, pulsed combustors, and polymerization reactions. While the control of chaos has recently a received a great deal of attention, the performance of traditional control schemes is poorly understood. Rather than implement a specific chaos control scheme, such as the well-known OGY method, we examine the feedback control of a chaotic polymerization reaction to a steady state using conventional linear and nonlinear control techniques. We show that it is possible to control a chaotic reaction system using a simple proportional controller, a discrete controller, a nonlinear model predictive controller which includes process-model mismatch. The performance of each control scheme is evaluated from the basin of successful control. While model predictive control yields a the most extensive basin and thus the best performance, in all cases the basin has a fractal structure for some values of the control parameter. The implications of a fractal basin to the robustness of the controller and the likelihood of successful control are discussed.