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The reaction process occurring on a solid surface where active sites are present is investigated. The phenomenon is described by a linear kinetic equation capable of accounting for memory effects in the adsorption-desorption and a first order reaction process. In order to broaden the formulation of the problem, the surface is in contact with a system defined in a half space where the dynamics is governed by a fractional diffusion equation, meaning, in principle, that the approach can be applied to complex systems such as biological fluids. Our results prove that the anomalous behavior has great importance on the reaction and, consequently, on the densities rates of particles at the surface and on the distribution of particles in the bulk. The results are particularly relevant for heterogeneous catalysis. [ABSTRACT FROM AUTHOR]

A closed-loop identification technique was applied to the pH control loop of the headbox of an industrial paperboard machine. A first-order-plus-time-delay process model was inserted into the closed-loop transfer function. The ISE index and its uncertainty were determined, leading the Kahn and Lehman rule to present the best performance and to the lowest ISE uncertainty. A novel index, IEP (integral of the error propagation), was also proposed to investigate the accuracy of the controlled variable predictions. The IEP index also led to the choice of the Brambilla et al tuning rule as the best choice, as it presented the lowest value. [ABSTRACT FROM AUTHOR]

The intensive necessity of hydrotreatment units for diesel production is pushing petroleum companies to seek alternatives to frame the produced streams into ultra low sulphur diesel (ULSD) specifications. One of the main difficulties in ULSD production is the presence of compounds from dibenzothiophenes (DBT), which are of difficult hy-drotreatment. The LCO cutpoint control represents an interesting alternative to overcome this situation. Thus, the objective of this work was to develop a soft sensor using linear models and neural networks considering a set of historical data of temperature, pressure and flow obtained from industrial plant information. Lab and process data concerning a period of 18 months was successfully used to infer 10%, 30%, 50%, 70% and 90% ASTM D-86 recovery temperature. Based on correlation matrix plots, using lab data as the dependent variable and plant data as independent variable, different models were developed for LCO cutpoint prediction. For all models, correlation coefficient between model predictions and experimental data were above 0.95. [ABSTRACT FROM AUTHOR]