• The mechanics of diamond core drilling of rocks

      Wang, Zhengwen W. (1995)
      In an attempt to study the mechanics of diamond core drilling in rocks, an investigation on rock drillability was conducted at the University of Alaska Fairbanks. A series of drilling and coring tests was conducted on six types of rock using several different diamond bits. Factors involved in a diamond coring and drilling process such as weight-on-bit, rotational speed, and rock type were identified and the effects of those parameters were experimentally evaluated based on the penetration rate, applied torque, and specific energy. Statistical techniques were used to design the drilling tests and to develop drilling models. Fundamentals of rock failure mechanics in relation to rock drilling were reviewed. Several existing rock drilling models were also examined with the data from this study. Results indicated that all of the three drilling parameters, i.e., the penetration rate, applied torque, and specific energy, were significantly affected by the weight-on-bit and rock type. The penetration rate of a bit was also affected by the rotational speed. The effects of the rotational speed on the applied torque and specific energy, however, were found to be insignificant. It was also found that the theoretical models can be used to predict the maximum effective weight-on-bit and penetration rate. Among the four theoretical models examined, the elastic model predicted the most accurate penetration rate. The maximum effective weights-on-bit predicted by the plastic model and the two fracture models, however, were close to each other and in agreement with the experimental observation. Statistical models developed in this study were used to predict the penetration rate in the Rock Drilling under the Greenland Ice Sheet project. The variation between the predicted value and the actual value was less than 10%.
    • Neural-Network Modeling Of Placer Ore Grade Spatial Variability

      Ke, Jinchuan; Bandopadhyay, Sukumar (2002)
      Traditional geostatistical methods have been used in ore reserve estimation for decades. Research in the last two decades or so has added a number of other statistical methodologies for ore reserve estimation procedures. Recent advances in neural networks have provided a new approach to solve this problem. This thesis is focused on the Neural-network modeling for the estimation of placer ore reserve. Due to the spatial variability, multiple dimensional inputs and very noisy drill hole sample data from the selected region, it requires that the neural-network be organized in a multiple-layers to handle the non-linearity and hidden slabs for smoothing the predicted results. Various neural-network architectures are investigated and the Back-propagation is selected for modeling the ore reserve estimation problem. Sensitivity analysis is performed for the following parameters: the type of neural-network architecture, number of hidden layers and hidden neurons, type of activation functions, learning rate and momentum factors, input pattern schedule, weight updated, and so on. The influences of these parameters on the predicted output are analyzed in details and the optimal parameters are determined. To investigate the accuracy and promise of neural network modeling as a tool for ore reserve estimation, the ore grade and tonnage of Neural-network output is compared with those estimated by geostatistical methods under various cut-off grades. In addition, the overall performance is also validated by the analysis of R-squared (R2), Root-Mean-Squared (RMS), and the comparison between predicted values and 'actual' values. As the final part of this study, the optimized Neural Network was used to estimate the distribution of placer gold grade and volume of gold resource in offshore Nome. The predicted results for all the mining blocks in the lease area are validated by checking the values of RMS, R2, and Scatter plots. The estimated gold grades are also presented as contour maps for visualization.
    • Calibration of an on-line analyzer using neural network modeling

      Yu, Shaohai (2003-08)
      The goal of the project was to predict the ash content of raw coal in real time using the Americium-137 and Cesium-241 scintillation counts from an on-line analyzer. Rather than regression methods (that are current industrial practice), neural networks were used to map the scintillation counts to percentage ash. Quick stop training was used to prevent overfitting The noise and sparseness of the data required that the training, calibration and prediction subsets are statistically similar to each other. Therefore, Kohonen networks were first used to detect the features present in the data set. Three subsets were then built such that they had representative members from each feature. Neural network models were developed for the screened coal, the unscreened coal and the combined data respectively. The results show that the performance of the combined model was comparable to the performance with two different models for the screened and unscreened data. Due to the variance in the sample data, the neural networks (screened, unscreened and combined) did not predict individual samples well. The network predictions were, however, accurate on the average. Compared to the common regression approach, neural network modeling demonstrated much better performance in ash prediction based on certain criteria.
    • Investigation and development of a mathematical model for the oxidation of cyanide in the INCO SO₂/O₂ process

      Oleson, James L. (2003-12)
      The purpose of this study was to develop a mathematical model to describe the oxidation of cyanide with SO₂ as proposed in the INCO process. This research employed a direct method for measuring the change in cyanide concentration with respect to time as affected by varying concentrations of SO₂ and copper and pH. This model may be applicable in determining optimum conditions in a process well known and used in the mining industry.
    • Resource estimation and analysis for offshore placer deposit using GIS technology

      Li, Hui (2004-12)
      In this thesis, an advanced GIS system is developed to manage, analyze and distribute Alaskan near-shore marine mineral deposition data. The developed GIS system is applied in a case study of the marine gold deposits in the offshore area of Nome, Alaska. The data collected during the previous phases of the research project are compiled using several computer application softwares such as ArcGIS8.3, Microsoft Access 2000 and others. Two improved relational geodatabases are created, in which various maps integrated with digital data sets are stored. The first database is known as the 'Integrated Geodatabase', which stores all the relative data collected in the Nome area, such as borehole data, bedrock geology, surficial geology, and geochemical data. database, a 'Regularized 2.5D Geodatabase', is generated based on the Geodatabase to store the layered orebody parameter for each regularized cell. The other Integrated With these GIS geodatabases, many important applications of data management and analysis, such as information query, data visualization, geostatistical analysis, gold distribution analysis, sediment distribution analysis, and resources estimation, are carried out readily for better understanding of Nome offshore mineral resources. Based on the enhanced GIS structure, a GIS-based website is developed using ArcIMS. Users can integrate local data sources with Internet data sources for display, query, and analysis in an easy-to-use web browser.
    • An experimental investigation of natural freezing and biopolymers for permeability modification to reduce the volume of dense non-aqueous phase liquids in groundwater

      D'Cunha, Neil John (2004-12)
      Dense Non-Aqueous Phase Liquid (DNAPL) contamination is one of the major environmental concerns today. DNAPL can remain in significant quantities as residual contaminants in the low permeability zones even after the bulk phase has been removed. As the drive fluid sweeps through the aquifer it follows the path of least resistance, which is the high permeability zone. Thus the contaminants trapped in the low permeability zones remain as residuals and serve as a source for prolonged contamination. Conventional remediation techniques are ill-equipped to deal with the heterogeneities of the aquifers. Various techniques to enhance the efficiency of the conventional methods are tried without significant success. Reducing the temperature of soil formations can modify aquifer flow paths. The natural freezing of soils in winter may be used effectively to modify the flow paths. In summer, permeability modification can be accomplished by emplacement of microbial polymer gels. In this thesis, we have investigated using a laboratory scale one dimensional column experiment, a novel technique to reduce the volume of residual DNAPL using a combination of natural freezing in winter and biopolymer in summer.
    • Low-rank high-volatile matter sub-bituminous coal grinding versus power plant performance

      Malav, Dinesh Kumar; Bandopadhyay, Sukumar; Wilson, Terril (Ted); Ganguli, Rajive (2005-08)
      The objective of this project was to determine if the power plant performance, characterized by megawatt and steam generation, is reduced when particle size distribution (PSD) of pulverized-coal fed into the burners is made slightly coarser. Tests were conducted in two phases at a Golden Valley Electric Association power plant. During the first phase, two tests were conducted at significantly different PSDs. Results indicated that coarser distribution did not hurt plant performance. Later, the second phase was carried out to test the repeatability of the observed combustion behavior as well as to test hypotheses on mill power consumption, emissions and unburned carbon. Unfortunately, the three tests in this phase did not result in statistically different PSD's, precluding any conclusions on the main objective. Therefore, further tests are needed to establish the effect of coarser PSD on power plant performance, emissions, unburned carbon and mill power consumption.
    • Pretreatment of aqueous phase of mine plant tailings for submarine disposal

      Choudhury, Abhishek; Bandopadhyay, Sukumar; Lin, Steve; Schiewer, Silke; Ganguli, Rajive; Wilson, Terril E. (2005-12)
      Submarine disposal of mine tailings is a relatively recent technology that holds the promise of solving the recurring problems that the mining industry has had with tailings disposal. The system has been successfully implemented in many mines around the world. Before implementation, however, a decision needs to be made whether the biogeochemical characteristics of the area selected for submarine disposal and characteristics of the tailings are conducive to implement submarine disposal of tailings. While an expert system can decide the feasibility of submarine tailings disposal (STD) based on its database of information and decision loops for the critical factors, tailings cannot be disposed of under water without pretreatment, which is the focus of this thesis. Bioremediation, freeze concentration and reverse osmosis were examined as possible alternatives for treatment. Laboratory tests were performed for all the methods, and in the case of bioremediation, pilot scale tests were also performed. It was concluded that all the three methods remove dissolved metals from mine water to varying degrees. Reverse osmosis was found to be the most efficient method, while freeze concentration was the least efficient method.
    • Exploration and estimation of gravel resource potential in southeast Chukchi Sea continental shelf off Kivalina, Alaska

      D'Souza, Abhijith T. (2005-12)
      Frequent storm surges in the Alaskan arctic result in washovers and high erosion of barrier islands. The village council of Kivalina has resolved to relocate from its present location on a barrier island in Northwest arctic Alaska to an adjacent onshore site. The relocation plan envisages excavation of upper 4 meter of the 25 km² onshore permafrost ground and construction of a foundation pad. The objective of this research is to estimate the gravel resource potential in the continental shelf off Kivalina. In this context seismic surveys and sediment sampling were conducted. The seismic surveys were of limited use as they failed to resolve the upper 1-2 m of the seafloor. The lithostratigraphy indicated dominance of the 2.4-3.4 mm size fraction in the region north of Kivalina. The geostatistical analysis indicated an omnidirectional variogram fit to the data with ordinary kriging producing the best kriging estimate of the gravel resource potential. At least 20 x 10⁶ m³ of gravel above the 90 % cut-off is present in the upper 0.5 m of the seafloor. The regional Pleistocene glaciation has affected the lateral variations in gravel abundance in the nearshore southeast Chukchi Sea.
    • An Evalulation Of Variables Affecting Gold Extraction At A Mineral Processing Plant Operated In A Sub-Arctic Environment

      Hollow, John T.; Lin, Hsing Kuang (2006)
      The Fort Knox Mine, located 25 miles northeast of Fairbanks, Alaska, is operated in a sub-Antic environment. Since process slurry temperatures cycle seasonally with air temperature, the mine presents a unique opportunity to measure the impact of slurry temperature on process performance under full scale plant, conditions. This thesis analyzes an energy balance approach to model the seasonal variations in slurry temperature throughout the Fort Knox mill. The mill utilizes both gravity concentration and cyanidation for gold recovery. Models were developed to accurately predict the impact of slurry temperature on cyanide leach, carbon adsorption and cyanide destruction kinetics. The energy balance model, combined with the kinetics models, was used to accurately predict the gold recovery and subsequently to justify the installation of a tailings wash thickener to recovery heat from the mill tailings. A substantial portion of this thesis is dedicated to the development of these models, analysis of the post expansion plant performance, and summarizing project economics. Gold in the Fort Knox deposit is generally less than 100 microns in size and contained in quartz veins and along shears within the host granite, at an average gold grade of 0.8 g/metric ton. In April 2001, the mill began processing ore from a satellite ore deposit, the True North Mine, as a blend with Fort Knox ore. The gold grade in the True North deposit averages 1.5 g/metric ton and can be associated with pyrite, arsenopyrite and stibnite. An unexpected drop in gold recovery resulted from processing the blended ore and was the subject of an extensive laboratory evaluation. Laboratory results suggested that the leach kinetics of the coarse gold particles were significantly impacted, when the blended ore was processed, and that the impact could be reduced, or eliminated, with the addition of lead nitrate. Subsequently, a lead nitrate addition scheme was implemented at the Fort Knox mill. A portion of this thesis is dedicated to a review of the laboratory program, an evaluation of the environmental impacts and a summary of plant performance, when utilizing lead nitrate at the Fort Knox Mine.
    • Predictive Performance Of Machine Learning Algorithms For Ore Reserve Estimation In Sparse And Imprecise Data

      Dutta, Sridhar; Bandopadhyay, Sukumar (2006)
      Traditional geostatistical estimation techniques have been used predominantly in the mining industry for the purpose of ore reserve estimation. Determination of mineral reserve has always posed considerable challenge to mining engineers due to geological complexities that are generally associated with the phenomenon of ore body formation. Considerable research over the years has resulted in the development of a number of state-of-the-art methods for the task of predictive spatial mapping such as ore reserve estimation. Recent advances in the use of the machine learning algorithms (MLA) have provided a new approach to solve the age-old problem. Therefore, this thesis is focused on the use of two MLA, viz. the neural network (NN) and support vector machine (SVM), for the purpose of ore reserve estimation. Application of the MLA have been elaborated with two complex drill hole datasets. The first dataset is a placer gold drill hole data characterized by high degree of spatial variability, sparseness and noise while the second dataset is obtained from a continuous lode deposit. The application and success of the models developed using these MLA for the purpose of ore reserve estimation depends to a large extent on the data subsets on which they are trained and subsequently on the selection of the appropriate model parameters. The model data subsets obtained by random data division are not desirable in sparse data conditions as it usually results in statistically dissimilar subsets, thereby reducing their applicability. Therefore, an ideal technique for data subdivision has been suggested in the thesis. Additionally, issues pertaining to the optimum model development have also been discussed. To investigate the accuracy and the applicability of the MLA for ore reserve estimation, their generalization ability was compared with the geostatistical ordinary kriging (OK) method. The analysis of Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Error (ME) and the coefficient of determination (R2) as the indices of the model performance indicated that they may significantly improve the predictive ability and thereby reduce the inherent risk in ore reserve estimation.
    • Gis-Based Approaches To Slope Stability Analysis And Earthquake -Induced Landslide Hazard Zonation

      Luo, Huayang; Zhou, Wendy (2006)
      This dissertation presents newly developed GIS-based deterministic and probabilistic approaches for slope stability analysis and earthquake-induced landslide hazard zonation. The described approaches combine numerical slope stability analysis with GIS spatial analysis to evaluate earthquake-induced slope failures, both shallow and deep-seated. The study has four major research components. The first component is a GIS-based procedure which was developed based on one-, two-, and three-dimensional (1D, 2D, and 3D) deterministic approaches to slope stability analysis and landslide hazard zonation. Slope stability methods in the GIS-based procedure included the infinite slope model, the block sliding model, the ordinary method of slices, the Bishop simplified method, and the Hovland's column method. The second component focuses on causative factors analysis of earthquake-induced landslide hazards. This component also discusses the determination of peak ground acceleration for slope stability analysis. The third component consists of an evaluation of the topographic effect of ground motion and the seismic response in the Balsamo Ridge area in Nueva San Salvador. The fourth component is concerned with the regional and site-specific landslide hazard zonation, using newly developed models for landslide hazard assessment in Nueva San Salvador. The slope stability and landslide susceptibility were mapped in terms of slope stability index (factor of safety, critical acceleration, Newmark displacement, failure probability, and reliability index). The landslides triggered by an earthquake on January 13, 2001 in El Salvador provide a setting for the calibration of results from GIS-based approaches. The procedures developed in this research proved to be feasible and cost-effective for slope stability analysis and earthquake-induced landslide hazard zonation.
    • Resource estimation for platinum at Goodnews Bay, Alaska

      Tenorio, Victor Octavio (2006-08)
      Ore grade estimation is one of the most difficult problems when mining offshore deposits. In this research, a platinum deposit near Goodnews Bay, South-West of Alaska, was estimated with emerging techniques such as conditional simulation and support vector machines (SVM). Results of the estimation are presented and compared with a traditional estimation technique, such as the Inverse Distance Squared method. The area was divided in three clusters, based on the K-means method and geographical features. Also, Genetic Algorithm was used for appropriate data division. SVM parameters were optimized prior to the ore grade calculations. All estimations produced similar results for various cut-off grades, being the highest tonnages of platinum between 400 and 200 mg/m3. Reliability for conditional simulation was measured selecting blocks over 90% of probability for each cut-off value. SVM performance was evaluated using the Mean Square Error (MSE), the Mean Absolute Error (MAE) and the Correlation Coefficient Squared (R2). Using Pearson's correlation coefficient, SVM results presented a confidence of 95% in cluster 01, and 99% in clusters 02 and 03. Support vector machines seem to be an adequate tool for ore grade prediction, and it has a potential for its use in more complex geological and mining problems.
    • Geodatabase development and GIS based analysis for resource assessment of placer platinum in the offshore region of Goodnews Bay, Alaska

      Oommen, Thomas (2006-12)
      Goodnews Bay, southwest Alaska, is known for extensive Pt reserves that have their source in the neighboring Red Mountain. The reserves potentially extend offshore into the Bering Sea. This study aims at developing a geodatabase to integrate all offshore platinum related data collected by researchers and agencies in the past, with the intent to identify data gaps. Based on these data gaps 49 new areas were sampled for Pt and geophysical data were collected in summer 2005. Spatial distribution map for offshore Pt was created using a new Multiple Regression Pattern Recognition Technique (MRPRT) that gave an R²=0.76, a significant improvement from standard GIS based geospatial techniques. Four potential Pt exploration areas were delineated, including one area where drowned ultramafics and buried alluvial channels co-occur. Coastal currents influenced the surficial platinum accumulations, and no clear relation between Pt distribution and sand bars in the far offshore could be established.
    • Modeling Of Depressurization And Thermal Reservoir Simulation To Predict Gas Production From Methane -Hydrate Formations

      Patil, Shirish L.; Chen, Gang; Huang, Scott L.; Sonwalkar, Vikas S.; Reynolds, Douglas B. (2007)
      Gas hydrates represent a huge potential future resource of natural gas. However, significant technical issues need to be resolved before this enormous resource can be considered to be an economically producible reserve. Developments in numerical reservoir simulations give useful information in predicting the technical and economic analysis of the hydrate-dissociation process. For this reason, a commercial reservoir simulator, CMG (Computer Modeling Group) STARS (Steam, Thermal, and Advanced Processes Reservoir Simulator) has been adapted in this study to model gas hydrate dissociation caused by several production mechanisms (depressurization, hot water injection and steam injection). Even though CMG is a commercially available simulator capable of handling thermal oil recovery processes, the novel approach of this work is the way by which the simulator was modified by formulating a kinetic and thermodynamic model to describe the hydrate decomposition. The simulator can calculate gas and water production rates from a well, and the profiles of pressure, temperature and saturation distributions in the formation for various operating conditions. Results indicate that a significant amount of gas can be produced from a hypothetical hydrate formation overlying a free gas accumulation by several different production scenarios. However, steam injection remarkably improves gas production over depressurization and hot water injection. A revised axisymmetric model for simulating gas production from hydrate decomposition in porous media by a depressurization method is also presented. Self-similar solutions are obtained for constant well pressure and fixed natural gas output. A comparison of these two boundary conditions at the well showed that a higher gas flow rate can be achieved in the long run in the case of constant well pressure over that of fixed gas output in spite of slower movement of the dissociation front. For different reservoir temperatures and various well boundary conditions, distributions of temperature and pressure profiles, as well as the gas flow rate in the hydrate zone and the gas zone, are evaluated.
    • Froth flotation characterization and processing plant design for the platiniferous and auriferous marine sediments of Southwestern Alaska

      Bissue, Charles (2007-12)
      The purpose of this study was to characterize, and investigate the beneficiation of, the platiniferous and auriferous marine sediments of Southwestern Alaska, located near Platinum, Alaska. The majority of placer gold particles are contained in the 50 x 150 mesh size fraction, while the platinum is finer, residing in the 100 x 200 mesh size fraction. Liberated placer gold and placer platinum group metals (PGM) particles are visible to the naked eye and readily observed under a binocular microscope. Preliminary, qualitative microprobe analysis of PGM grains from the flotation concentrate showed grains of nearly pure iridium, isoferroplatinum and Pt-Rh-Ir-Fe-S-As mineralogy. Froth flotation showed that placer gold responded very well to all the collectors used, with gold recoveries of 82.7-99.8%. Flotation of platinum responded well to only potassium amyl xanthate, with a recovery of 80.4%. Results of low intensity magnetic separation showed that virtually all the liberated gold and platinum reported to the non magnetic product. A flowsheet, with estimated capital and operating costs, was developed to process 1500 tph of marine placer feed. Annualized costs per ton to process marine sediments were estimated to be $2.40 to $3.72 depending upon plant availability, 90% to 50%, respectively.
    • Experimental And Numerical Study Of Sonic Wave Propagation In Freezing Sand And Silt

      Li, Hui (2009)
      A numerical model for delineating the temperature-velocity relationship of freezing porous media and soil is developed in Matlab based on Leclaire's Biot-type three-phase theory. Leclaire's theory gives lower sonic velocities than the experimental results because it does not take into consideration the effect of the solid-ice frame when water is freezing. To take the solid-ice effective frame into account, the average bulk and shear moduli estimation are modified with a proposed procedure. The modification gives higher P-wave and S-wave velocities that fit experimental data well. A comprehensive suite of physical and acoustic laboratory experiments are conducted on artificial sands, sand-clay mixtures and Fairbanks silts to investigate the temperature-velocity relationship during the freezing process and the effects of grain size and fine clay content. A Multi-channel ultrasonic scanning system (MUSS) is designed, installed and programmed for the experimental computerized ultrasonic tomography (CUST) study. The inward and outward freezing process and freezing front development in Fairbanks silt samples are observed using computerized ultrasonic tomography (CUST) in the laboratory. The experiments generate sonic wave velocity and temperature distribution during the freezing process. The freezing front is clearly identified in the CUST as a function of time and temperature. Comprehensive numerical finite element method (FEM) simulations, which account for the conduction in porous media, the latent heat effect and the nonlinear thermal properties of soil, are performed on the inward and outward freezing process of Fairbanks silt based on the experimental conditions. In conjunction with the temperature-velocity model developed in the study, sonic wave velocity tomograms are generated. The results are comparable with those obtained by CUST. The study indicates that CUST is an effective method for studying freezing processes and has potential for indirect measurement of unfrozen water content variations in the soil without interfering with the freezing process.
    • Multiphysics Modeling Of Gaseous Contaminant Transport In Deep Open Pit Mines Under Arctic Air Inversions

      Choudhury, Abhishek; Bandopadhyay, Sukumar (2011)
      Entrapment of pollutants in a deep open pit operating in a cold climate could occur due to atmospheric inversion. The process of air inversion is complex and requires thorough understanding in order to design a mine ventilation plan to remove trapped pollutants in open-pit mines operating in the arctic/sub-arctic regions. The objective of this dissertation is to develop a model using Computational Fluid Dynamics (CFD) tools for analysis of gaseous pollutant transport in deep, open pit mines under air inversion in arctic or subarctic regions. An Eulerian 3-D model was used for the development and validation of the CFD model of pollutant transport in an idealized open pit mine. No prior assumptions, turbulent or laminar, were considered for the nature of the flow. The 2-D model results indicated that air velocity, air temperature, diffusivity coefficient and slope angle were important controlling parameters in the inversion process. The flow regime was laminar at the origin, but as the flow progressed toward the center of the pit it changed to quasi-laminar and generated local eddies towards the pit bottom. The total energy of the quasi-laminar flow as well as the small local eddies was not enough to lift the inversion cap. However, a combination of quasi-turbulent flow and the local eddy transport resulted in removal of some of the pollutant mass from the pit bottom, either due to turbulent mixing, or due to advection. Presence of backflow may appear to be a logical mode of flow in deep open-pit mines in arctic regions. Next, the 3D model was validated using data from a selected open-pit mine. Influent air velocity, diffusivity coefficient, larger pit geometry were found to influence the retention and transport of pollutant out of the pit. The most important conclusion that was drawn from this research is that natural ventilation alone cannot remove the pollutants from an open pit or lift the inversion cap.
    • Comprehensive Investigation Into Historical Pipeline Construction Costs And Engineering Economic Analysis Of Alaska In-State Gas Pipeline

      Rui, Zhenhua; Metz, Paul; Chen, Gang; Zhou, Xiyu; Reynolds, Douglas (2011)
      This study analyzes historical cost data of 412 pipelines and 220 compressor stations. On the basis of this analysis, the study also evaluates the feasibility of an Alaska in-state gas pipeline using Monte Carlo simulation techniques. Analysis of pipeline construction costs shows that component costs, shares of cost components, and learning rates for material and labor costs vary by diameter, length, volume, year, and location. Overall average learning rates for pipeline material and labor costs are 6.1% and 12.4%, respectively. Overall average cost shares for pipeline material, labor, miscellaneous, and right of way (ROW) are 31%, 40%, 23%, and 7%, respectively. Regression models are developed to estimate pipeline component costs for different lengths, cross-sectional areas, and locations. An analysis of inaccuracy in pipeline cost estimation demonstrates that the cost estimation of pipeline cost components is biased except for in the case of total costs. Overall overrun rates for pipeline material, labor, miscellaneous, ROW, and total costs are 4.9%, 22.4%, -0.9%, 9.1%, and 6.5%, respectively, and project size, capacity, diameter, location, and year of completion have different degrees of impacts on cost overruns of pipeline cost components. Analysis of compressor station costs shows that component costs, shares of cost components, and learning rates for material and labor costs vary in terms of capacity, year, and location. Average learning rates for compressor station material and labor costs are 12.1% and 7.48%, respectively. Overall average cost shares of material, labor, miscellaneous, and ROW are 50.6%, 27.2%, 21.5%, and 0.8%, respectively. Regression models are developed to estimate compressor station component costs in different capacities and locations. An investigation into inaccuracies in compressor station cost estimation demonstrates that the cost estimation for compressor stations is biased except for in the case of material costs. Overall average overrun rates for compressor station material, labor, miscellaneous, land, and total costs are 3%, 60%, 2%, -14%, and 11%, respectively, and cost overruns for cost components are influenced by location and year of completion to different degrees. Monte Carlo models are developed and simulated to evaluate the feasibility of an Alaska in-state gas pipeline by assigning triangular distribution of the values of economic parameters. Simulated results show that the construction of an Alaska in-state natural gas pipeline is feasible at three scenarios: 500 million cubic feet per day (mmcfd), 750 mmcfd, and 1000 mmcfd.
    • Engineering economic analysis of a rail extension from Dunbar siding to Livengood, Alaska

      Bohart, Charles W.; Metz, Paul A.; Huang, Scott L.; Misra, Debasmita (2011-12)
      The Dunbar Siding to Livengood rail extension study is an economic prefeasibility investigation, and is conducted from two perspectives as a cost benefit analysis. The first perspective is, that of the Alaska Railroad Corporation (ARRC) in which the capital and operating costs of the proposed extension are recovered through the revenue stream resulting from the out-bound mineral freight loads, the in-bound re-supply freight loads, and the potential commuter passenger service to mining projects and communities in the Livengood area. The second perspective is that of the private sector in which a shipping sensitivity and employee transport analysis with respect to mining project developments. The large mineral resource base within the Dunbar-Livengood Corridor indicates an excellent freight potential with generous benefits for Alaska's economy of greater than $2 billion annually in gross revenues; whereas, resource and rail development are synergistic.