Qualidade de efluente – garantia probabilística, Fuzzy e avaliação de capabilidade do sistema de tratamento

Abstract

Mathematical modeling is a tool used to predict the occurrence and intensity of relevant phenomena. In this way provide tools for the responsible by a given process to prevent adverse situations or to take full advantage of favorable situations. The performance of Sewage Treatment Stations (ETE) is likely to lead to a high degree of randomness of the data. Due mainly to the fluctuation in flow values, organic load, operational parameters, inclement weather climate change, etc. Therefore, to use mathematical modeling to predict the performance of removal of pollutants by TEE is a work that brings an intrinsic error of nature of the data. For this, we use Confidence Interval (CI) that delimits a range of values ​​in which the expected value is likely to be found. The construction of IC by Conventional method is time-consuming and costly since it requires the withdrawal of many samples from the study population. It is necessary to adopt robust tools to predict satisfactorily the occurrence of the phenomena of pollutant removal in TEE. In order to overcome this difficulty, the Boostrap Methodology is used to construct IC, with this tool are raised antagonistic scenarios (IC trust bands). The risk of non-compliance of sewage treatment is commonly Fuzzy Risk associated with a Triangular Fuzzy Number (NFT) which is a simple methodology and easy to interpret. The effort to integrate the probabilistic risk obtained through of the Boostrap methodology with the Fuzzy risk associated to NFT. Raised the picture of reliability related to the treatment of effluents through the probabilistic methodology and Fuzzy has the need to gauge if the process is able to satisfy a given objective. In this context, the tools described in the Statistical Process Control (CEP) emerge. Through this methodology IC was established for the effluent quality parameters against environmental standards.