Determination and Evaluation of the Pyrolysis Temperature for the Cogeneration Process in Downdraft Gasification with the Use of Artificial Neural Networks (ANN).

Abstract

In the present study, the control of the pyrolysis temperature was carried out in a gasification process of eucalyptus wood, its prediction is made based on the operating parameters of the reactor to ensure the obtaining of a synthesis gas with the required quality. The results obtained from the mathematical modeling for the prediction of the pyrolysis temperature with the use of artificial intelligence techniques and the development of artificial neural networks are shown, with experimental data of the process. For this reason, an experimental statistical design of type 3ⁿ was implemented, with two additional replications, by means of which the training of an artificial neural network capable of predicting the pyrolysis temperature in a downdraft type gasifier with cogeneration was carried out. The prediction of the pyrolysis temperature has an error of 4.6 ^oC and an adjustment of 93.71%, adequate values ​​for this working parameter.