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International Journal for Multiscale Computational Engineering
Factor de Impacto: 1.016 Factor de Impacto de 5 años: 1.194 SJR: 0.554 SNIP: 0.68 CiteScore™: 1.18

ISSN Imprimir: 1543-1649
ISSN En Línea: 1940-4352

International Journal for Multiscale Computational Engineering

DOI: 10.1615/IntJMultCompEng.2017021137
pages 477-504

A BENCHMARKING OF COMPETING BIO-OBJECTIVE FUNCTIONS FOR MULTIRESPONSE OPTIMIZATION OF UASB SYSTEM IN PRETREATMENT OF POULTRY MANURE SLURRY

Kaan Yetilmezsoy
Department of Environmental Engineering, Faculty of Civil Engineering, Yildiz Technical University, 34220, Davutpasa, Esenler, Istanbul, Turkey

SINOPSIS

A novel hybrid mathematical programming model was described for multicriteria optimization of an up-flow anaerobic sludge blanket (UASB) reactor in pretreatment of poultry manure slurry. Three-variable bio-objective functions (five popular kinetic models and two newly derived multiple regression–based equations) with various multiple constraints and process-related parameters were derived, and more than 200 benchmarking simulations were performed within the framework of desirability function methodology. The maximum composite desirability was estimated as 0.9959 at an influent substrate concentration of 13.98 g COD/L, a hydraulic retention time of 12.93 days, and an operating temperature of 30.81°C. Correspondingly, the effluent substrate concentration, the biogas yield, and the net operating cost were obtained to be 2.25 g COD/L, 7.30 L/day, and 11.18 €/m3, respectively. According to verification tests, mean deviations were less than 3% at global optima, suggesting that the proposed approach was a well-suited technique for multiresponse optimization of a highly nonlinear biosystem.


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