Abstract A Brazilian Tensile Strength (BTS) laboratory test for meta-andesite was modeled using a Finite/Discrete Element Method (FDEM or FEM-DEM). These hybrid methodologies allow modeling the transition from continuous to discontinuous that happens on mechanical tests of rock samples. This article presents the calibration and the simulation of BTS tests using some parameters previously calibrated on UCS modeling of the same material. Irazu, a two-dimensional software developed by Geomechanica, was used to simulate the tests based on the tensile strength and the fracture pattern. The model shows that, in BTS test simulation, the mode II (shear) happens mainly on the rock-platen contact. The mode I (traction) rules the fractures on the BTS test as observed in laboratory tests. The model represents, with great fidelity, the results obtained in the physical test.

Abstract Finite/discrete element methods (FDEM) are hybrid numerical models that use algorithms to analyze the transition from continuous to discontinuous. This type of formulation allows modeling physical laboratory tests with greater proximity to reality. This article proposes to simulate the average behavior of a uniaxial compression test campaign. The tests were modeled and calibrated based on the strength and the fracture pattern using Geomechanica Inc. Irazu two-dimensional software. The simulated results were analyzed by the mean standard deviation of approximately 3000 elements in the middle third of the model, the same region where the clip gages are located in the physical test. The obtained results show that FDEM can replicate the laboratory test with great similarity.

Abstract Mining projects are often budgeted in millions of dollars, making it of interest to the investor to measure a project’s uncertainties and risks, which include the changes in the commodity price. The simulation of asset prices is valid because it enables displaying, with a degree of certainty, the future behavior of a financial asset. One of the most commonly used mathematical forecast models is the Geometric Brownian Motion (GBM) model. This article aims at simulating the forecast price of an iron ore commodity with the GBM method based on the historical price series and comparing it to other forecast approaches used in the financial market. The results of this study indicate that the model has limitations, which should be considered. However, it is an overall good tool to support the economic evaluation of a project, if performed along with other approaches.