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Liquid Equilibrium Data (liquid + equilibrium_data)

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Chemistry	100%

Selected Abstracts

Modeling solubilities of sugars in alcohols based on original experimental data

AICHE JOURNAL, Issue 9 2007
Fernando Montañés
Abstract Solubility of six different carbohydrates in methanol, ethanol, 1-propanol, and 2-propanol were measured at 22, 30, and 40°C. Ketose sugars (fructose, tagatose, and lactulose) show higher solubilities than aldoses (glucose, galactose, and lactose). The binary solid,liquid equilibrium data obtained was satisfactory represented by using the A-UNIFAC model. Additionally, the capability of the model to predict the carbohydrate solubility in alcohol,alcohol and alcohol,water mixed solvents was explored. © 2007 American Institute of Chemical Engineers AIChE J, 2007 [source]

Generalized least-squares parameter estimation from multiequation implicit models

AICHE JOURNAL, Issue 10 2003
Simon L. Marshall
Maximum likelihood fit of nonlinear, implicit, multiple-response models to data containing normally distributed random errors can be carried out by a combination of the Gauss-Newton generalized nonlinear least-square algorithm first described by Britt and Luecke in 1973, with a Fletcher-Reeves conjugate gradient search for initial parameter estimates. The convergence of the algorithm is further improved by adding a step-limiting procedure that ensures a reduction in the objective function for each iteration. Multiple-equation regression methods appropriate to the solution of explicit fixed-regressor models are derived from this general treatment as special cases. These include weighted nonlinear least squares (where the covariance matrix of the response is known), and uniformly weighted nonlinear least squares (where the responses are uncorrelated and characterized by a single common variance). Alternative methods for fixed-regressor fits of explicit multiequation models with an unknown covariance matrix of the responses are also considered. The moment-matrix determinant criterion appropriate in such situations is also efficiently minimized by use of the conjugate-gradient algorithm, which is considerably less sensitive to the accuracy of the initial parameter estimate than the more usual Gauss-Newton methods. The performance of the new algorithm for models defined by one, two, and three implicit functional constraints per point is illustrated by random-regressor fits of isothermal p,X and p,X,Y vapor,liquid equilibrium data, and ternary liquid,liquid equilibrium data, respectively. [source]

Effect of number of fractionating trays on reactive distillation performance

AICHE JOURNAL, Issue 12 2000
Muhammad A. Al-Arfaj
Sneesby et al. recently suggested that adding trays in the stripping and rectifying sections of a reactive distillation column can degrade performance. This effect, if true, is not only counterintuitive, but very disturbing because it suggests that the design of reactive distillation columns cannot use conservative estimates of tray numbers, that is, we cannot simply add excess trays, as in conventional distillation. The problem is compounded by the uncertainty in vapor,liquid equilibrium data and tray efficiencies. This implies that developing reactive distillation columns would require extensive experimental work at the pilot-plant and plant stages to find the numbers of stages offering the best performance. Such a scenario would mean long and expensive development programs. This article explores the effect of the number of trays in the rectifying and/or stripping sections of reactive (catalytic) distillation columns. Three reactive distillation systems are used: an ideal hypothetical system, the ETBE system, and the methyl acetate system. Contrary to the published results, it is demonstrated that additional trays do not degrade performance. Two degrees of freedom available in all cases must be carefully chosen for fair comparisons. [source]

Estimation of vapour,liquid equilibrium data for binary refrigerant systems containing 1,1,1,2,3,3,3-heptafluoropropane (R227ea) by using artificial neural networks

THE CANADIAN JOURNAL OF CHEMICAL ENGINEERING, Issue 2 2010
M. R. Nikkholgh
Abstract In this research, the ability of multilayer perceptron neural networks to estimate vapour,liquid equilibrium data have been studied. Four typical binary refrigerant systems containing R227ea have been investigated in a large range of temperatures and pressures. The systems are categorised into four groups, based on their different deviations from the Raoult's law. The networks with one hidden layer consisted of five neurons are developed as the optimal structure. For these binary systems, uncertainties in the artificial neural networks (ANNs) estimations were not more than 1.03%. In addition, the abilities of ANNs are shown by comparisons with Margules, van Laar, and some other correlations. Dans ce travail de recherche, nous avons étudié la capacité de réseaux neuraux de perceptron multicouche à estimer les données d'équilibre vapeur-liquide. Quatre systèmes typiques de réfrigérants binaires contenant du R227ea ont été étudiés sur de grands intervalles de température et de pression. Les systèmes étaient classés en quatre groupes, en fonction de leurs déviations différentes par rapport à la Loi de Raoult. Les réseaux ayant une couche cachée composée de cinq neurones sont développés comme la structure optimale. Pour ces systèmes binaires, les incertitudes dans les estimations ANN ne dépassaient pas 1,029 %. De plus, les capacités des ANN sont données en comparaison avec Margules, van Laar et certaines autres corrélations. [source]