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Abstract:The heap leaching of minerals is one of the more commonly used processes in the mining industry. This process has been modeled by many authors. However, the validation, verification, and implementation of these models are difficult since there is uncertainty about the operating conditions and the leaching model parameters. This work uses the uncertainty quantification, based on uncertainty and sensitivity analysis, for studying the model strength against uncertainties in heap leaching. The uncertainty analysis (UA) is used to quantify the effect of the magnitude of the uncertainties of the input variables on the recovery of heap leaching. Global sensitivity analysis (GSA) is used to study the nature of connections between the recovery and input variables of the leaching model. In addition, GSA facilitates the detection of whether a leaching model is over-parameterized. The information obtained allows studying some applications of the kinetic model. The Mellado et al. kinetic model is used as an example. The UA results indicate that the kinetic model can estimate the recovery behavior considering the full range of uncertainties of input variables. The GSA indicates that the kinetic model is over-parameterized on the uncertainties range considered; this conclusion contradicts the results when the local sensitivity analysis is used. However, the model shows a good correlation between the results of GSA and the kinetic behavior of heap leaching. In addition, the kinetic model presents versatility because it allows the determination of operating regions for heap leaching.

SUMMARYWe propose a p-adaptive algorithm for the Galerkin method solving the hypersingular integral operator of the Laplacian on the plane screen. The error indicators=estimators are based on projections of the actual error onto local subspaces. These subspaces are deÿned by decompositions of specially designed enriched ansatz spaces. Our algorithm uses di erent strategies for the reÿnement and the stopping criterion. The error estimator that stops the algorithm is based on an overlapping decomposition of an ansatz space that is deÿned by mesh reÿnement. The error indicators that steer the p-reÿnement are computed via an almost direct decomposition of an enriched ansatz space that uses the same mesh but higher polynomial degrees. Numerical results support the e ciency of our algorithm.