The hydrolytic depolymerization of poly(ethylene terephthalate) (PET) was carried out in a stirred batch reactor at 235, 250, and 265 °C above its melting point and under autogenous pressure. The solid products which were mainly composed of terephthalic acid were analyzed by potentiometric titration and elemental analysis. The liquid products which were mainly composed of ethylene glycol and a small amount of its dimer were analyzed by gas chromatrography. A kinetic model consisting of forward and backward reactions for the PET hydrolysis fitted well with the experimental data. Moreover, an autocatalytic mechanism was suggested, which indicates that some of the hydrolytic depolymerization of PET was catalyzed by the carboxyl groups produced during the reaction. The dependence of the rate constant on the reaction temperature was correlated by the Arrhenius plot giving the activation energy of 123 kJ/mol for the PET hydrolysis.

The depolymerization of poly(ethylene terephthalate) (PET) flakes in a potassium hydroxide solution was carried out in a stirred batch reactor at 120, 140, and 160 °C, below its melting point and under pressures of about 1.7, 2.9, and 4.6 atm, respectively. After the reactions, the residual solids almost remained in flake shape and their molecular weights were close to that of PET before the reaction. The products composed of ethylene glycol and terephthalic potassium salt were in the liquid phase. They were separated by acidification (to obtain solid terephthalic acid) and filtration processes and subsequently were analyzed quantitatively by potentiometric titration, elementary analysis, and gas chromatography. The results of kinetic analysis showed that the depolymerization reaction rate was first order to potassium hydroxide and first order to the PET concentration. This indicates that the ester linkages on the surface of the solid PET flakes sequentially reacted with potassium hydroxide in the solution to produce ethylene glycol and terephthalic potassium salt. A mechanism for the major reaction occurring on the polymer chain end section on the solid PET surface was proposed in this research. The dependence of the rate constant on the reaction temperature was correlated by the Arrhenius plot, which shows an activation energy of 69 kJ/mol and an Arrhenius constant of 419 L/min/cm 2 .

SUMMARY The objective of this paper is to develop methods for extracting trends from long‐term static deformation data of a dam and try to set an early warning threshold level on the basis of the results of analyses. The static deformation of a dam is mainly influenced by the water pressure (or water level) of the dam and the temperature distribution of the dam body. The relationship among the static deformation, the water level, and the temperature distribution of the dam body is complex and unknown; therefore, it can be approximated by static neural networks. Although the static deformation almost has no change during a very short time, it changes with time for long‐term continuous observation. Therefore, long‐term static deformation can be approximated dynamically using dynamic neural networks. Moreover, static deformation data is rich, but information is poor. Linear and nonlinear principal component analyses are particularly well suited to deal with this kind of problem. With these reasons, different approaches are applied to extract features of the long‐term daily based static deformations of the Fei‐Tsui arch dam (Taiwan). The methods include the static neural network, the dynamic neural network, principal component analysis, and nonlinear principal component analysis. Discussion of these methods is made. By using these methods, the residual deformation between the estimated and the recorded data are generated, and through statistical analysis, the threshold level of the static deformation of a dam can be determined on the basis of the normality assumption of the residual deformation. Copyright © 2011 John Wiley & Sons, Ltd.