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Heat capacities of aqueous NaOH/NaAl(OH)4 solutions at total stoichiometric ionic strengths of up to 6 mol kg^-1 and with up to 60 mol % substitution of OH^- by Al(OH)4^- have been measured at 25 °C using a Picker flow calorimeter. The mean apparent molar heat capacities (Cpφ) of the NaOH/NaAl(OH)4 mixtures were linear with respect to Al(OH)4^- substitution, consistent with Young's rule. This enabled Cpφ values to be derived for the hypothetical pure NaAl(OH)4(aq) solutions. The results so obtained are well described by a Pitzer model adapted from the literature, even up to high concentrations.

Heat capacities of aqueous solutions of Na2SO4 and Na2CO3 up to near saturation (1.9 and 2.5 mol·kg^-1, respectively) and of NaOH (to 7 mol·kg^-1) have been measured at 25 °C with a Picker flow calorimeter. The calorimeter performance was checked using concentrated NaCl(aq) solutions. On the basis of these measurements, an experimental protocol suitable for the reliable determination of the heat capacities of concentrated electrolyte solutions by Picker calorimetry was established. The heat capacities for Na2SO4(aq), Na2CO3(aq), and NaOH(aq) and literature data for the apparent molar volumes of NaOH(aq) at 25 °C were correlated using the Pitzer formalism. A number of inadequacies in previous models at high concentrations and for extrapolation to infinite dilution are discussed. In particular, it has been confirmed that the heat capacity data for Na2CO3(aq) at low concentrations must be corrected for the hydrolysis of the carbonate ion. Standard partial molar heat capacities for the three salts and the standard partial molar volume of NaOH(aq) have been derived at 25 °C.

A multivariable control methodology using several models representing a physical system in different operating points is presented. The algorithmic structure can be expressed by a division into two parts; firstly, the location of the different models using a linear filter theory and, secondly, the tracking control. This algorithm is characterized by a parallel structure, and its implementation is carried out in parallel multimicroprocessor systems developed in our laboratory. Using this system, an application exempIe is presented.

The paper expose briefly the aims of process control and propose its realization through a tracking approach. Therefore a linear quadratic input-output tracking algorithm is presented and completed with the constraints satisfaction. To overcome the modelling errors and the linear model limitations, two approachs are proposed. First, the output feed back integral correction. Second, multimodel te chnique with two parts : location and control synthesis. The linear optimal filtering is used for the process models location. Based on the quality of models a global control synthesis is realized from weighted combination of the individual models control values. The experimental results on a binary distillation column are discussed. The output feedback corrector is applied for the control around one operating point and the multimodel control in the case of transition from one operating point to another.