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

Abstract

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 degrees 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 (sic)/m(3), 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.