No abstract

Pasteurization is an important, if not the most important, process step in the packaging of milk. It is subject to alterations stemming from the variation in the temperature, pH and raw milk quality. The variability may manifest itself in changes in the formation of the deposit (fouling) in the pasteurization unit, such that there is a need for tools, both instrumentation and computational, to help in monitoring the process and keeping it on the desired course. In this paper we describe a practical procedure based on artificial neural networks (ANN) that allows prediction of the deposit thickness, the overall heat transfer coefficient and the critical time (the time that the unit has to be stopped for cleaning) for reducing the impact of fouling on such processes. The procedure determines when the cleaning operation is required once the system is under critical conditions of operations. A combination of fundamental studies and plant measurements were used for study of the operating conditions and thus evaluation of the trades-offs between operating conditions and longer operating life span. The results are encouraging, enough to validate current operating industrial techniques.

n the design of separation processes, it is of vital importance to know the solubility of reagents and products. If the solubility is wrongly I estimated it could cause undesirable fouling and crystallization in process equipment. Especially in the petroleum industry and similar industry with heavy feedstock it is necesary to avoid that the flow lines will be plugged.Polycyclic aromatic compounds (PAH) (such as anthracene, fluoranthene, and pyrene) are of great importance to the petroleum industry, and at the same time known to be carcinogenous. Therefore, crystallization of these compounds must be avoided in chemical processes. Data for the solubility of such compounds given in the literature are scarce, and normally only available a t 25°C. In order to estimate the solubility for these polycyclic aromatic compounds one can use predicting procedures. Due to the fact that ideal solubility only is reasonable to accept in systems with solutes of the same chemistry as the solvents, it is in most cases necessary to find methods to calculate the activity coefficient of the solute. To address this problem, researchers have turned to group contributions methods and semiempirical expressions to predict the activity coefficient. Even though the group contribution method of UNIFAC (Fredenslund et al., 1975(Fredenslund et al., , 1977 earlier has shown its potential for calculating solid-liquid equilibria (Cmehling et al., 1978), no thorough work using UNIFAC to estimate solubilities for PAHs has been published yet. This is interesting especially after that both the UNIFAC (Hansen et al., 1991) and the Modified UNIFAC (Dortmund) (Weidlich and Cmehling, 1987, Cmehling et al., 1998) have been revised recently, and are now covering a wide range of functional groups.The objective of this work is to analyze the predictability of UNIFAC and modified UNIFAC (Dortmund) models to calculate solubilities of anthracene, fluoranthene and pyrene in a series of organic solvents. A comparison between the computed solubilities obtained here and values calculated by the Mobile Order Theory (Acree, 1999; Roy et al., 1999; Hernandez and Acree, 1998; Powell et al., 1994) will be given. Thermodynamic BackgroundA pure solid solute (2) partly dissolves in a liquid solvent (1). The equation of solid-liquid phase equilibrium for the solute is given by: *Author to whom correspondence may be addressed. E-mail address: hkhansen@ kemi.dhr.dkThe solubility of anthracene in 43 organic solvents, fluoranthene (45 solvents) and pyrene (30 solvents) has been calculated using UNIFAC and Modified UNIFAC (Dortmund) models to estimate the activity coefficient of the solute. It was found that both UNIFAC and Modified UNIFAC described better the solubilities in polar solvents like alcohols, ketones, esters and ethers than in nonpolar solvents like alkanes and aromatic hydrocarbons. UNIFAC and the Mobile Order Theory supplement each other well in calculating the solubilities, which means that one can choose the right model depending on the solvent one is using.La...

We determined interfacial gas-liquid areas for the absorption of CO 2 or O 2 in a bubble column, with and without surfactants and/or sucrose in the absorbent liquid. All the experiments were carried out under batch processing conditions. The values obtained by the three chemical methods used have been compared, and the dependence of the operating conditions and physical properties on the interfacial area has also been analyzed. The results of experiments to determine the dependence of the area on the geometrical characteristics of the column and physical properties were fitted to within an 8% error by dimensionless modules.