engleski

Manganese waste mud immobilization in cement – natural zeolite – lime blend: Process optimization using artificial neural networks and multi-criteria functions

In this study, stabilization/solidification process of manganese contaminated mud using portland cement was optimized. For that purpose, immobilization process was modeled applying artificial neural networks with radial basis activation function. The optimal model presented satisfactory prediction characteristics (R2 value for manganese leaching was 0.9615 while and for concrete flexural strength 0.8748). Therefore, it was used in combination with seven inhouse developed multi-criteria optimization functions, separately, in order to optimize concrete formulation. The used approach proved itself as efficient and cost effective alternative in ecological material formulation process. The best properties (i. e. high flexural strength and lowest manganese leaching) manifested stabilization/solidification matrix consisted of 350 g of portland cement, 20 g of lime, 70 g of natural zeolite, 10 g of manganese waste mud and 180 g of water.

manganese mud ; stabilization/solidification ; artificial neural networks ; multi-criteria functions

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