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Statistical techniques for the treatment and analysis of experimental data from laboratory reactors were considered, as applied to a CREC Riser Simulator reactor for the example of FCC catalyst evaluation. Deviations in mass balances were reconciliated considering the variance in each product mass. After reconciliations, simple OPE curves were used to fit the data due to their simplicity and proper representation of the yield curves. In the data fitting step, errors in both dependent and independent variables were considered by using information obtained in the reconciliation procedure. The impact of different levels of confidence bands in the models on the discrimination of experimental results was discussed. Significant improvements in catalyst evaluation could be achieved either in the CREC Riser Simulator or other types of laboratory reactors with the help of the statistical procedures described here without increasing substantially the number of experiments.

Despite existing several techniques for distributed sensing (temperature and strain) using standard Single Mode optical Fiber (SMF), compensating or decoupling both effects is mandatory for many applications. Currently, most of the decoupling techniques require special optical fibers and are difficult to implement with high spatial resolution distributed techniques, such as ϕ-PA-OFDR. So, this work’s objective is to study the feasibility of decoupling temperature and strain out of a ϕ-PA-OFDR readouts taken over an SMF. For this purpose, the readouts will be subjected to a study using several Machine Learning algorithms, among them, Deep Neural Networks. The motivation which underlies this target is the current blockage in the widespread use of Fiber Optic Sensors in situations where both strain and temperature change, due to the coupled dependence of currently developed sensing methods. Instead of using other types of sensors or even other interrogation methods, the objective of this work is to analyze the available information in order to develop a sensing method capable of providing information about strain and temperature simultaneously.