Abordagem fuzzy quanto ao desempenho e estabilidade operacional de reatores UASB

Detalhes bibliográficos
Ano de defesa: 2020
Autor(a) principal: Lima, Dayane de Andrade
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/56682
Resumo: Anaerobic sewage treatment using UASB reactors has expanded over the past few decades and consists of a consolidated technology in hot climate regions. Several advantages of the anaerobic process make it a more sustainable option for the treatment of sewage. However, a huge variety of operational problems resulting from inefficient operation and monitoring can hinder process performance. Other restrictions are related to design and construction. Although the UASB reactors are considered robust, the same monitoring mechanisms obtained, control or systematic of effective operational diagnosis, under penalty of becoming unstable or inefficient. The performance of UASB reactors is commonly susceptible to a large randomness of interferents, mainly related to fluctuation in flow values, clandestine connections, organic load, operational parameters and weather conditions. This work aims to develop and demonstrate a mathematical structure based on Fuzzy Logic to evaluate performance and detect instability and operational failure in anaerobic reactors. The concept of the Fuzzy Agreement Index -ICF(an application of the concepts of fuzzy logic through the method of Fuzzy Triangular Numbers) was used with a focus on the idea of guarantee from the marginal performance function and the Fuzzy Risk -RF. The fuzzy performance of UASB reactors measured from the removal of pollutants, effluent quality, stability indicators and compliance with the environmental standard was evaluated. A fuzzy performance ofUASB reactors was also analyzed, with measurement of fuzzy potential for biosolids and biogas and the fuzzy stability of UASB reactors was verified. The study was divided into two parts, working with monitoring data and compiled data. For the monitoring, data were used from nineteen UASBs reactors operating in full scale treating domestic sewage, were treated with data, average (most likely) and maximum parameters: pH, COD, SSed, SST, temperature, O&G, AMT and E. coli. In the second part of the work, compiled data were used, published in studies using UASBs reactors treating sanitary effluents at different scales (bench, pilot and real) the worked parameters form the BOD / COD ratio, the AGV / alkalinity ratio and dissolved inorganic carbon. The results obtained show that the UASBs aggregated better ICF for the parameters of pH and O&G, dissipated ICFfor the parameters of COD and SST, not meeting the environmental requirements for this criterion. The ICF values for the quality of the treated effluent were higher in UASB9UASB17, with greater fuzzy agreement with environmental standards. And the greatest fuzzy risk in the UASB4and UASB12reactors. The variations in the TDH and the VASCfor the measurement of the fuzzy guarantee and the fuzzy risk considering the variations in flows, in the scenario where the flow is four times greater than the average flow is more susceptible to not meeting the launching standards in addition to the dragging of sludge and failures in the process as a whole. The fuzzy logic, through the ICFand of the RF, proves to be an efficient tool in the evaluation of the performance of ETEs providing a better understanding of the operational functioning of UASB reactors and on the fulfillment of its environmental criteria. Due to its simplicity, the study revealed that the fuzzy approach enables the development of computational tools for the evaluation and control of UASB reactor systems, in addition to seeking a better understanding of operational functioning.