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Author: Admin | 2025-04-28
Scholar] [CrossRef]Silva, F.M.P. Da Aperfeiçoando Decisões de Investimento em Condições de Risco com uso de Método de Monte Carlo: Análise da Infraestrutura Urbana. Master’s Thesis, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brasil, 2017. [Google Scholar] Figure 1. Algorithm for choosing access and transport. Figure 1. Algorithm for choosing access and transport. Figure 2. Multicriteria Analysis Model for Mine Access/Transportation Selection. Figure 2. Multicriteria Analysis Model for Mine Access/Transportation Selection. Figure 3. Distributions of priorities presented in the Monte Carlo simulation by normal distribution. Figure 3. Distributions of priorities presented in the Monte Carlo simulation by normal distribution. Figure 4. Distributions of priorities presented in the Monte Carlo simulation by triangular distribution. Figure 4. Distributions of priorities presented in the Monte Carlo simulation by triangular distribution. Figure 5. Distributions of priorities presented in the Monte Carlo simulation by triangular distribution on weights. Figure 5. Distributions of priorities presented in the Monte Carlo simulation by triangular distribution on weights. Table 1. Papers with cost approach in mine access and transportation. Table 1. Papers with cost approach in mine access and transportation. AuthorFocusKey PointsElevli et al. [17]Evaluation of shaft or ramp for an underground chromite mine.Evaluation of the alternative based on the Net Present Value (NPV) of the options. Lower CAPEX for Shaft to depth of 370 m. Higher OPEX for Ramp from 390 m.Rupprecht [16]Evaluation of inflection depth in the choice between shaft and ramp for the South African case.Evaluation of the alternative based on operating cost. Cost
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