Art Modeling Liliana Model

Art Modeling Liliana Model

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The modelling and experimental results show the ability of the predictive analytical model to provide the required information, which is important to carry out control actions in order to achieve the best performance of the process. As a result, the predictive model is also useful for the management of the process and the adjustment of the operating conditions of the process.

The values of the parameters of the model are within the range of those reported in the literature, which is reasonable because the experiment was carried out at the same temperature (31.5°C), pH (7.5) and organic loading rate (1.5 g/L reactor day), to that found by Sendjaja [32].

The obtained results are presented in Table 3 and the statistics of the parameters of the model are as follows: R2 = 0.98, adjusted R2 = 0.96, Q2 = 0.90 and RMSE = 0.52 which show a good match between the experimental data and the predicted data. The estimated parameters are: maximum velocity (Vmax) = 8.51 g/L reactor day, half saturation constant (Ks) = 5.57 g/L reactor day, minimum concentration (Km) = 1.30 g/L reactor day and maximum concentration (b) = 2.70 g/L reactor day.

This work has been performed in the framework of the Research Project “Computational Modeling of Biological Processes” Project ID RG/CMP/SR/0170/2013, financed by the Portuguese Science Foundation, FCT. The authors also acknowledge the support of the FCT/MCTES (Portuguese Ministry of Science, Technology and Higher Education) through project ID/EMS/0004/2013 and CICECO-Aveiro Institute of Materials, UID/CTM/50011/2013. The authors also acknowledge the support of the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement #241575 (AEROWORKS).

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