Prediction of leachate pH for cement paste containing pure metal compounds.
Neural network models, to predict the leachate pH for single batch extraction leaching tests conducted on Portland cement pastes containing pure compounds, were constructed using existing data from the literature. The models were able to represent the known non-linear dependency of pH on acid addition, and were used to show that Cu increases, and Zn and NO3- decrease, the leachate pH for addition of 8 meq acid/g dry cement (to achieve a mid-alkaline pH). Ba, Cd, Cr(III), Ni, Pb, Cl- and OH- had no detectable effect on the acid neutralisation capacity (ANC) of the cement pastes in the concentration ranges investigated. The laboratory where testing was conducted was found to be an important predictive variable, which acted as a surrogate variable for laboratory specific variables that were not adequately reported in the literature, such as cement characteristics, sample preparation details, and leaching test and pH measurement details. This work has shown that development of good empirical predictive models for solidified product leachate pH is feasible, and is limited only by the availability of data.
Stegemann
J A
JA
Concrete Durability Group, Department of Civil and Environmental Engineering, Imperial College of Science, Technology and Medicine, Imperial College Road, London SW7 2BU, UK. j.stegemann@ic.ac.uk
Buenfeld
N R
NR
D004787:Environmental Pollution; D005544:Forecasting; D006863:Hydrogen-Ion Concentration; D008420:Manufactured Materials; D008422:Materials Testing; D019216:Metals, Heavy / Q000737:chemistry*; D016571:Neural Networks, Computer; D012037:Refuse Disposal / Q000379:methods*
D019216:Metals, Heavy