Semi‐adiabatic temperature measurements are recorded and used to define semi‐empirical equations for the simulation and prediction of the anionic polyamide‐6 (APA‐6) reaction kinetics. The resin mixture used has a long infusion window before the reaction starts. The prediction of the induction time and its corresponding initial temperature of reaction is explored. By means of this semi‐empirical approach and an optimised fitting procedure, the reaction kinetics of APA‐6 can successfully be described. The adiabatic polymerisation can be predicted on the basis of an autocatalytic Kamal‐Sourour model for thermoset resins, and the crystallisation can be described using the isothermal crystallisation model.
A 1‐D through‐the‐thickness transient heat transfer model is built to simulate the curing process of thick‐walled glass‐fibre‐reinforced anionic polyamide‐6 (APA‐6) composites. The temperature and the degree of polymerisation through the thickness of the composite are calculated and compared to the experimentally obtained results. The kinetic models describing the polymerisation behaviour of APA‐6 are implemented in the model. The kinetic model not taking into account the convection in the polymerisation process shows the best results. It is found that the predicted temperature profiles agree well with the experimental data. magnified image
The potential of Real Time Control (RTC) to reduce the overflow volume from a combined sewer system has been investigated for a catchment in Copenhagen, named Strandvaenget. The results have been compared with the alternative of increasing the storage volume of the system. The RTC strategy has been derived using a mathematical optimization and a rule based method. As the only objective is to reduce the Combined Sewer Overflow (CSO), the developed rule based control algorithm can achieve almost the same results as the optimization method.
From the results of time series calculations, it can be concluded that the introduction of RTC appears very promising when the mean yearly CSO volume has to be reduced. In this research, the potential of RTC is investigated for an increasing amount of storage volume and for an increasing demand for reduction of CSO volume.
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