Roussos Dimitrakopoulos

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Spatially distributed natural phenomena represent complex non-linear and non-Gaussian systems. Currently, their spatial distributions are typically studied using second-order spatial statistical models, which are limiting considering the spatial complexity of natural phenomena such as geological applications. High-order geostatistics is a new area of(More)
Conventional open pit mine optimization models for designing mining phases and ultimate pit limit do not consider expected variations and uncertainty in metal content available in a mineral deposit (supply) and commodity prices (market demand). Unlike the conventional approach, a stochastic framework relies on multiple realizations of the input data so as(More)
We generalize the well-known Laguerre series approach to approximate multivariate probability density functions (PDFs) using multidimensional Laguerre polynomials. The generalized Laguerre series, which is defined around a Gamma PDF, is suited for simulating high complex natural phenomena that deviate from Gaussianity. Combining the multivariate Laguerre(More)
Conditional simulation of ergodic and stationary Gaussian random fields using successive residuals is a new approach used to overcome the size limitations of the LU decomposition algorithm as well as provide fast updating of existing simulated realizations with new data. This paper discusses two different implementations of this approach. The(More)
The three-dimensional high-order simulation algorithm HOSIM is developed to simulate complex non-linear and non-Gaussian systems. HOSIM is an alternative to the current MP approaches and it is based upon new high-order spatial connectivity measures, termed high-order spatial cumulants. The HOSIM algorithm implements a sequential simulation process, where(More)