Eric Asa

Intelligent Modeling: Advances in Open Pit Mine Design and Optimization Research

Design and optimization of pit layouts yield the mineable ore reserves and minimum waste to maximize the net pit value and to ensure optimum location of surface facilities. Many algorithms and their modifications, derived from stripping ratio concepts, displacement of conic volumes, dynamic programming and graph theory, have been developed to design and optimize pit layouts. These algorithms have assisted engineers in making design decisions but they are limited in dealing with pit design stochastic processes. Large information and database and the requirement for complete rerun of these algorithms with information and data changes result in long computations and CPU times. Current algorithms do not provide analysts with intelligent design options to deal with structural, hydrological and tectonics problems of mine design. In this paper, the authors discuss current state-of-the-art technology and research in intelligent modeling. Current and future research frontiers in intelligent modeling are also addressed with emphasis on developing efficient and user-friendly technology for pit design and optimization.

Comparison of Linear and Nonlinear Kriging Methods for Characterization and Interpolation of Soil Data

Characterization and analysis of large quantities of existing soil data represent highly complicated tasks because of the spatial correlation, uncertainty, and complexity of the processes underlying soil formation. In this work, three linear kriging (simple kriging, ordinary kriging, and universal kriging) and three nonlinear kriging (indicator kriging, probability kriging, and disjunctive kriging) algorithms are compared to determine which is best suited for the characterization and interpolation of soil data for applications in transportation projects. A spherical model is employed as the experimental variogram to aid the spatial interpolation and cross-validation. The kriged data are subjected to leave-one-out cross-validation. The data used are in both vector and raster format. Statistical measures of correctness (mean prediction error, root-mean-square error, standardized root-mean-square error, average standard error) from the cross-validation are used to compare the kriging algorithms. Using indica...

Linear Spatial Interpolation and Analysis of Annual Average Daily Traffic Data

AbstractTransportation planning requires the use of accurate traffic data to produce estimates of traffic volume predictions over time and space. The annual average daily traffic (AADT) data is an important component of transportation design, operation, policy analysis, and planning. The use of traffic volume forecasting models for the characterization, analysis, and estimation of transportation data has proven to be a useful method for reducing high costs, overcoming spatial constraints, and limiting the errors associated with data collection and analysis in transportation planning. The geostatistical kriging technique is a viable method for modeling and forecasting AADT. The degree to which the technique of kriging can be useful in forecasting AADT depends highly on an understanding of the decision-making variables, the relationship between the variables, and the practical limitations of the various kriging techniques and variogram models. This paper applied three different linear kriging techniques [si...

Mechanics of Oil Sands Slurry Flow in a Flexible Pipeline System

Slurry transportation is an economic haulage system in oil sands and coal-mining operations characterized by long haulage distances and rugged terrain. In such conditions, the ton-km-hr limits are exceeded creating extreme tire wear and high maintenance costs. Steep haul grades and rugged terrain also cause mechanical wear and tear, which decrease haulage equipment economic life. Hydraulic transportation is a proven and viable technology for slurry transportation in such conditions. Currently, stationary pipeline transportation is being used in transporting minerals in many mines. There is an increasing demand to create slurrified minerals at the mining faces to be transported to the processing plant. However, stationary pipelines are not capable for dealing with the rapidly changing configuration of the mining faces. In this paper, the authors develop the ground articulating pipeline (GAP) technology to address this problem. The GAP system consists of pipelines connected together with flexible joints in each pipe section, which allows deflection to avoid torsional stresses from the adjoining frames. This flexible arrangement accommodates the horizontal and vertical displacements of the mobile system as it follows the hydraulic shovels in the excavation process. The mechanics of the GAP system, as well as the production–economic function, are formulated and simulated over an extended period using data and information from Syncrude’s North Mine. The results show that the GAP system is technically and economically viable for productivity between 6,300 and 6,500 tons per hour. The simulated head loss for the GAP system is 15.66 m per 400 m, which compares with 20 m per 400 m for the existing stationary system at Syncrude. The pressure gradient-radius curves are asymptotic to the pipe boundaries, which indicates steep axial pressure gradient in these areas.

Extending the Service Life of Electric Distribution and Transmission Wooden Poles Using a Wet Layup FRP Composite Strengthening System

This paper investigates the feasibility of using an in situ wet layup fiber-reinforced polymer (FRP) repairing system to extend the service life of electric distribution and transmission wooden poles. The effectiveness of the FRP strengthening method was evaluated through field tests performed on Class-4 deteriorated wooden poles and a step-by-step rapid installation procedure was developed. Results indicated that the application of the in situ wet layup FRP system increased the load capacity of the poles where more than 85% of their original capacity was restored. In addition, the repaired poles exceeded the minimum lateral load required by the NESC and ANSI 05.1 codes indicating that it would be more cost-effective repairing the poles than replacing them. Moreover, in addition to the cost savings, the FRP system extended the service life of the deteriorated poles up to 30 years.

NUMERICAL SIMULATION OF SURFACE MINE PRODUCTION SYSTEM USING PIT SHELL SIMULATOR

Surface mine production systems involve complex, multi-faceted and costly sequence of processes that must be planned, designed and evaluated to promote well-conditioned decision processes. Strategic and tactical mine plans are used to provide a long-term production vision and the resource requirements for meeting specific periodic mine and plant capacities. The schedule and sequence of material movement must respond quickly to changing technical, safety and economic constraints within the surface mining environment. Many production planning, scheduling and resource allocation methods are based on simplistic methodologies without rigorous technical and economic basis. These methods fail to consider the random processes governing critical production variables. With increasing demand for efficient schedules for low-cost bulk production requirements, the need for efficient tools is critical. In this study, the authors develop an innovative pit shell simulator to address these problems. Rigorous geometric formulations of the ellipsoidal approximations of the pit shells geometry, their planar expansions and vertical interactions are modeled to mimic material displacement dynamics in an open pit operation. Numerical simulation techniques are used to provide solutions to the time-dependent geometric models in random multivariate states. The pit shell simulator is used to solve the Pine Valley open pit mine production schedule for the first three years of production. The simulator provides the schedule and sequence of all the cuts from various quadrants in the four pit shells within the optimised pit layout. The simulator results show that, in order to maximize the mine value, the mine must produce 304,000, 180,000 and 140,000 tonnes of ore respectively for years 1, 2 and 3. The total materials within this period also include 72,000, 80,000 and 190,000 tonnes of stockpiles and 30,000, 80,000 and 30,000 tonnes of waste materials respectively for years 1, 2 and 3. This results in a maximum NPV of

Estimating cost for transportation tunnel projects: a systematic literature review

27,000 at a discount rate of 12 percent over the 3-year duration.

MULSOPS: Multivariate Optimized Pit Shells Simulator for tactical mine planning

Estimating the cost of transportation tunnel projects during the feasibility stage is highly complex and challenging for state/federal agencies. The use of traditional methods to estimate tunnel project costs has led to significant cost underestimation because of limited information/data to compare different alternatives. To address cost underestimation, 40 cost estimating factors were identified by conducting a systematic literature review. Seven electronic databases were searched and articles were screened based on pre-established criteria. Of the 788 articles retrieved, 39 articles published from 1988 to 2013 met the inclusion criteria and were included in the review. The resulting data was analysed using descriptive and Anderson–Darling statistical methods. The results of the analysis showed that the top five factors contributing to cost underestimation were engineering and construction complexities, geological conditions, cost estimation, market conditions, and environmental requirements. The findings from the review showed the importance of incorporating the effect of each determined estimating factor by state/federal agencies or metropolitan planning organizations when preparing initial estimates to avoid cost underestimation and/or to reduce the errors associated with such estimates. Future research may be warranted to explore the possibility of weighting the factors.

Nonlinear Spatial Characterization and Interpolation of Wind Data

Abstract Production planning, scheduling and allocation of resources in large-scale surface mining operations present a great challenge to mine planning engineers. Ore and waste extraction plans must be executed to achieve tactical objectives using appropriate tools. Many production planning and scheduling and resource allocation methods are based on trial and error, crisis management or subjective judgements with no detailed economic basis or mathematical rigour. In addition, these methods do not consider the random processes governing critical development and production variables. In this study, the authors develop a multivariate pit shell simulator, MULSOPS, which addresses these problems. Rigorous geometric formulations of the ellipsoidal approximations of the pit shells geometry, their expansions and sequential interactions are modeled to mimic material displacement dynamics in an open pit operation. Stochastic and numerical modeling techniques are used to provide solutions to the time-dependent geom...

Machine learning characterization of a two-seam coal deposit

High fossil fuel (oil and gas) prices; concerns about the stability of the Arabian oil supply; and the adverse effects of externalities generated by fossil fuel production, distribution, and consumption are fueling the move towards sustainable energy sources like wind generated electricity. Wind energy is becoming one of the preferred substitutes to fossil fuels because of the widespread availability, sustainability, and renewability of wind resources. However, the economic viability of a wind energy generation project is strongly dependent on the accurate characterization and estimation of the wind resource (wind speed) and its associated uncertainty. Analyzing wind resources is a complicated process due to the spatial variability, uncertainty and the complexity of the meteorological processes underlying the formation and behavior of wind. The objective of this work is to employ the two most common nonlinear kriging algorithms (indicator kriging and probability kriging) and five variogram models (spherical, exponential, circular, Gaussian, and hole effect) to characterize and interpolate wind data (in both vector and raster format). The ten sets of variograms and nonlinear kriging algorithms were compared to discover which set is best suited for the characterization and interpolation of each type of wind data used in wind power generation projects. The kriged data was subjected to leave-one-out cross-validation and the resulting statistics were employed in the ranking and comparison of the ten sets of algortihms. The research used ten combinations of nonlinear interpolation methods and variograms and determined that the best nonlinear kriging algorithm for characterizing and interpolating the vector wind data was indicator kriging and exponential variogram. Using indicator kriging with either the spherical or the exponential variogram would result in the same estimates for the raster data.