MULTIOBJECTIVE OPTIMIZATION OF AN UPFLOW ANAEROBIC SLUDGE BLANKET REACTOR
The purpose of this paper is to optimiza the operation of an upflow anaerobic sludge blanket (UASB) reactor. In this kind of processes, besides to maximiza organic matter removal, it is attractive to capture the biogas and to use it to provide energy services. For this purpose, the biogas has to be...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2007 |
| País: | Perú |
| Institución: | Universidad Nacional Mayor de San Marcos |
| Repositorio: | Revistas - Universidad Nacional Mayor de San Marcos |
| Idioma: | español |
| OAI Identifier: | oai:revistasinvestigacion.unmsm.edu.pe:article/4096 |
| Acceso en línea: | https://revistasinvestigacion.unmsm.edu.pe/index.php/quim/article/view/4096 |
| Access Level: | acceso abierto |
| Palabra clave: | Reactor UASB Tratamiento de aguas residuales optimización multiobjetivo Multiplex métodos lnterior puntos algoritmos genéticos modelos multivariados UASB reactor Wastewater treatment Multiobjective optimization lnterior-point methods Genetic algorithms Multivariate modelling. |
| Sumario: | The purpose of this paper is to optimiza the operation of an upflow anaerobic sludge blanket (UASB) reactor. In this kind of processes, besides to maximiza organic matter removal, it is attractive to capture the biogas and to use it to provide energy services. For this purpose, the biogas has to be produced in large quantities. Thus, we have two clear objectives to be achieved: to maximiza both the organic matter removal and the biogas production. Three multiobjective optimization techniques are used to solve this problem. The first optimization approach is multiplex, which is based on the simplex method for single objective optimization. Other used approach is an interior point method, which is proved to be an efficient linear programming technique. Finally, it is applied an evolutionary algorithm, namely the elitist non-dominated sorting genetic algorithm (NSGA 11), which is considerad a very attractive heuristic method. Formulation of the multiobjective optimization problem is based on a multivariate regression model, which is built using experimental data from a full-scale UASB reactor, at CETESB, in Sao Paulo City, Brazil. Obtained optimization solutions are comparad and discussed. |
|---|