Título: Aplicando Redes Neurais no Processo de Hidrorrefino
Autores: Silva, Raissa Maria Cotta Ferreira; Aires, Joyce Stone de Souza; Oliveira, Luciano Villanova
Resumo: The use of neural network for modeling process is increasing in several kinds of chemical industries. This paper presents a brief review of applications in petroleum refining industry. Moreover, it presents some applications in Hydrotreating process of diesel oil. In this refining process, the knowledge about specific characteristics of process is very important to unit design, process optimization, product quality control and environment protection. The Neural Network technique has been used to model the behavior of the hydrogen chemical consumption, generation of light gas, the conversions of the hydrogenation of aromatic hydrocarbons (HDA), hydrodesulfurization (HDS) and hydrodenitrogenation (HDN) reactions and product physical properties. Operation conditions and some relevant feedstock properties were selected as input variables. The models were developed with experimental data, which were obtained in hydrogenation pilot plants from Brazilian Petroleum Company (PETROBRAS).
Código DOI: 10.21528/CBRN2003-006
Artigo em PDF: 6CBRN_006.PDF
Arquivo BibTex: 6CBRN_006.bib