Banca de DEFESA: ELINA WANESSA RIBEIRO LOPES

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : ELINA WANESSA RIBEIRO LOPES
DATE: 16/03/2022
TIME: 14:00
LOCAL: Videoconferência (Google Meet) (https://meet.google.com/xhr-rmgo-kwr)
TITLE:

Use of Python Language for Modeling and Simulation of the Silva and Cerqueira Model in Microalgae Effluent Treatment

KEY WORDS:

Algorithm. Nutrient removal. Modeling. Microalgal Growth.

PAGES: 86
BIG AREA: Engenharias
AREA: Engenharia Sanitária
SUBÁREA: Tratamento de Águas de Abastecimento e Residuárias
SPECIALTY: Técnicas Avançadas de Tratamento de Águas
SUMMARY:

The excessive presence of nutrients such as nitrogen and phosphorus in water bodies is a current target of environmental concern, using microalgae to remove these nutrients appears as a promising alternative. The application of computational tools allows the development of algorithms that evaluate the behavior and optimize the effectiveness of this removal. The present study carried out the kinetic modeling of microalgal growth through the classic Monod model and the Silva and Cerqueira model, finding the characteristic kinetic constants and allowing the modeling and simulation of bioprocesses of effluent treatment by microalgae. Literature data were used for two studies, in the first one the removal of nutrients (contaminants) by Chlorella sp. for effluent from a combined anaerobic digestion (CAD) and an anaerobic digestion effluent from a primary settling tank (PS). In the second study, the removal of nutrients from an urban effluent by a mix of microalgae (Chlorella vulgaris, Scenedesmus obliquus and Chlamydomonas reinhardtii) was evaluated. The adopted algorithm proved to be adequate in both studies. To solve the proposed problem, the PSO (Particle Swarm Optimization) algorithm was implemented in Spyder software (an open source integrated development environment for programming in Python), and the PYSWARMS research toolkit was used for optimization (library). The model parameters were estimated by minimizing the sum of the calculated square errors and to evaluate the deviation of the simulated curve and of the experimental points, the concept of model predictive error (MPE – Model Predictive Error) was used (%). For the removal of contaminants, the equation of order n proved to be more suitable with intermediate order between 1st and 2nd being used (ie, 1 < n < 2) and with constant 0 < k < 0.2, obtaining MPE between 15 -28% similar to that seen in literature. Using the Monod Model, the algorithm was able to determine μ_max and Ks that were shown in the intervals: 0 < μ_max < 4 day^-1 and 0 < Ks < 50 mg/L with MPE between 15-28%. These constants could be applied in the Silva and Cerqueira model and the delimitation of m and p, which are specific to this model, could be studied. In fact, the model proved to be very sensitive to these constants, managing to define an interval for convergence: 0 < p < 0.5 and 0 < m < 2, obtaining for the same data tested in Monod an MPE between 4 -15% for Silva and Cerqueira (significantly lower). m and p showed a significant influence on the magnitude and curvature of the microalgal growth curve. The results showed that there was a good adjustment of microalgae growth and that it is possible to associate several contaminants with the cellular growth of microalgae.

BANKING MEMBERS:
Interno - 3081569 - CARLOS EDUARDO DE FARIAS SILVA
Interna - 1272239 - DANIELE VITAL VICH
Externa ao Programa - 1456420 - RENATA MARIA ROSAS GARCIA ALMEIDA
Externa à Instituição - FLÁVIA BARTIRA PEDRO DA SILVA ALMEIDA - IFAL