The research results are presented by the authors in the modeling of performance indicators of the operation of biomass gasification installations using artificial neural networks, starting by the classification of the information derived from the systemic analysis of its operation. A bibliographical study of previous related researches was developed. A 3N experimental plan with 3 replicas is made in order to generate four models according to their own performance indicators using neural networks. The quality indicators of the neural networks are compared with those obtained by nonlineal regression models. As biomass the Oryza sativa is used

The research results are presented by the authors in the modeling of performance indicators of the operation of biomass gasification installations using artificial neural networks, starting by the classification of the information derived from the systemic analysis of its operation. A bibliographical study of previous related researches was developed. A 3N experimental plan with 3 replicas is made in order to generate four models according to their own performance indicators using neural networks. The quality indicators of the neural networks are compared with those obtained by nonlineal regression models. As biomass the Oryza sativa is used

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...

The research results are presented by the authors in the modeling of performance indicators of the operation of biomass gasification installations using artificial neural networks, starting by the classification of the information derived from the systemic analysis of its operation. A bibliographical study of previous related researches was developed. A 3N experimental plan with 3 replicas is made in order to generate four models according to their own performance indicators using neural networks. The quality indicators of the neural networks are compared with those obtained by nonlineal regression models. As biomass the Oryza sativa is used

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...

The research results obtained on the effect that occurs on the properties of the synthesis gas obtained as a result of a biomass downdraft gasification process is presents in this paper, working with a cogeneration system internal to the reactor. A study of the previous related works was carried out, from which the dependent and independent variables necessary to evaluate the final quality of the process in the presence and absence of cogeneration were determined. For this, an experimental statistical design of four levels of type 4n was implemented, which allowed the performance of a comparative statistical analysis of the working states of the gasifier. On the other hand, an energy and exergy analysis of both states is presented where the potential of the gasification process to reuse thermal energy can be verified by incorporating a cogeneration system.

The research results obtained on the effect that occurs on the properties of the synthesis gas obtained as a result of a biomass downdraft gasification process is presents in this paper, working with a cogeneration system internal to the reactor. A study of the previous related works was carried out, from which the dependent and independent variables necessary to evaluate the final quality of the process in the presence and absence of cogeneration were determined. For this, an experimental statistical design of four levels of type 4n was implemented, which allowed the performance of a comparative statistical analysis of the working states of the gasifier. On the other hand, an energy and exergy analysis of both states is presented where the potential of the gasification process to reuse thermal energy can be verified by incorporating a cogeneration system.

A proposal is presented in which the respective energy analysis is carried out to characterize the calorific value of commercial gasolines in Ecuador as: Super, Extra and Ecopaís. This study is carried out in the laboratory of internal combustion engines of the University of the Armed Forces-ESPE, with the purpose of obtaining mathematical models that relate the energy and quality parameters of gasolines.Models that will be obtained through computational tools such as artificial neural network (ANN), which will use a set of historical data provided by the Agency for Regulation and Control of Hydrocarbons (ARCH) of Ecuador, for validation.

A proposal is presented in which the respective energy analysis is carried out to characterize the calorific value of commercial gasolines in Ecuador as: Super, Extra and Ecopaís. This study is carried out in the laboratory of internal combustion engines of the University of the Armed Forces-ESPE, with the purpose of obtaining mathematical models that relate the energy and quality parameters of gasolines.Models that will be obtained through computational tools such as artificial neural network (ANN), which will use a set of historical data provided by the Agency for Regulation and Control of Hydrocarbons (ARCH) of Ecuador, for validation.

A proposal is presented in which the respective energy analysis is carried out to characterize the calorific value of commercial gasolines in Ecuador as: Super, Extra and Ecopaís. This study is carried out in the laboratory of internal combustion engines of the University of the Armed Forces-ESPE, with the purpose of obtaining mathematical models that relate the energy and quality parameters of gasolines.Models that will be obtained through computational tools such as artificial neural network (ANN), which will use a set of historical data provided by the Agency for Regulation and Control of Hydrocarbons (ARCH) of Ecuador, for validation.