biological treatment of slaughterhouse wastewater: kinetic modeling and prediction of effluent

In this study three modeling approaches consisting modified stover-kincannon, multilayer perceptron neural network (mlpann) and b-spline quasi interpolation were applied in order to predict effluent of up-flow anaerobic sludge blanket (uasb) reactor and also to find the reaction kinetics. at first run, the average total chemical oxygen demand (tcod) removal efficiency was 48.3% with hydraulic retention time (hrt) of 26 h and 63.8% with hrt of 37 h, at olr of 0.77–1.66 kg tcod/m3 d. at the second run, uasb reactor operated with olr of 1.94–3.1 kg tcod/m3 d and achieved the average tcod removal efficiency of 64.74 and 72.48% with hrt of 26 and 37 h, respectively. the modified stover-kincannon performed well in terms of kinetic determination with a high value of regression coefficient over 0.98. the b-spline quasi interpolation and mlpann indicated a great fit for effluent prediction with average r of 0.9984 and 0.9986, and mse of 157.6050 and 129.7796, respectively; however, they gave no information about reactions occurred in the system.