Search Documents

By Mark A. Rohrbach, Timothy R. Kovacs, PhD Saidin

"Crosshole Sonic Logging (CSL) testing is commonly used to verify the integrity, quality and ultimately the acceptability of the concrete in structural elements such as drilled shaft foundations, secant pile cutoff walls, and secant/tangent pile earth retention structures. Besides concrete quality, many factors can impact CSL test results (e.g. laitance, air temperature, access tube spacing, access tube debonding, etc.). Effective use of CSL testing requires fully informed qualified practitioners capable of distinguishing between abnormal readings unrelated to deficiencies in the drilled shaft concrete and similar readings indicating the presence or possible presence of drilled shaft defects. Based on data and experience gathered from CSL testing of thousands of drilled shafts across North America, this paper discusses such factors and other information useful when evaluating CSL test results, and provides practical recommendations intended to reduce the potential for incorrect test data interpretation. The CSL testing industry is lacking in a clear, universally accepted guideline for the interpretation of CSL data and acceptance criteria of these concrete elements. This paper proposes terminology and a streamlined process for use when atypical results are obtained. The proposed terminology and method are intended to simplify and expedite the submittal review and approval process. Because construction activities for these elements are often on the project’s critical path, the benefits obtained in terms of project savings and reducing costly delays areundoubtedly valuable.1. INTRODUCTIONCSL testing is used extensively throughout the world on many projects to verify the quality of concrete used for drilled shaft foundations, secant pile walls, diaphragm walls, etc. In this paper, these structural elements will be referred to as “drilled shafts,” as they are the most common subject of this test method. In the United States, CSL testing is frequently specified by state and regional transportation agencies, ports, design builders, and others. Although other methods are currently available such as Gamma-Gamma Logging and low-strain Impulse-Echo or Sonic-Echo testing, and new methods are under development such as the Thermal Integrity testing, CSL testing is likely to remain one of the most useful tools for evaluating the acceptability of constructed drilled shafts for quite some time. The popularity of CSL as a testing method can be attributed to two main factors: 1) there is no depth limitation to the method and 2) the apparent ease of interpreting the results. A third advantage of CSL testing is that, when correctly interpreted and with adequate test coverage, it is unlikely to misrepresent a defective profile resulting in acceptance of a defective or inadequate drilled shaft. In other words, CSL testing is very likely to underestimate concrete quality/drilled shaft acceptability within its area of coverage."

Jan 1, 2017

By S Watson, L Martinez

Mine projects are complex opportunities that demand a constant assessment of uncertainty, ie risk and upside potential. This is because the value of a mine project is typically influenced by many underlying economic and physical uncertainties, such as metal/mineral prices, metal/mineral grades, costs, schedules, quantities, and environmental issues, amongst others, which are not known with much certainty at the beginning of the project. But, is uncertainty an enemy or an ally of the mine planner/analyst? To answer this question, this paper first assesses and elaborates upon the general concept of uncertainty. It then looks at the different sources of uncertainty in a mining project, such as the orebody, costs and product price uncertainties, and their effect on the final project value. Next, a general?review?of current mine evaluation techniques highlighting their limitations when dealing with uncertainty is made. Finally, an extended evaluation and risk management framework that addresses the existing uncertainty in the (greenfield/brownfield) mine evaluation process is proposed. One important characteristic of this framework is that it uses and manages uncertainty in order to generate additional value to the project; this is done through operational and managerial flexibility, which allow mine planners to minimise/maximise project risk/upside-potential giving a more realistic estimate of the projectÆs market value - this is shown in practical and simple examples occurring at different stages of a mine project, such as exploration and operation. Final conclusions are provided at the end.CITATION:Martinez, L and Watson, S, 2012. Uncertainty - An important source of (additional) value for mine projects, in Proceedings Project Evaluation 2012 , pp 131-140 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

Material sampling theory is well established in mineral process monitoring, improvement and control. It has been much enhanced by fundamental contributions due to Gy. When GyÆs sampling theory is applied to sampling inspection and monitoring, it provides estimates of average quality or extent of contamination. It also provides estimates of uncertainty, but these often ignore uncertainty in estimated variograms or other measures of variability. Risk assessment is often an implied task in sampling inspection and quality monitoring. A valid technique of risk assessment needs to take into account the uncertainty in the variational measures themselves. Standard statistical tolerance limit calculations which do take such uncertainty into account can be adapted to develop a technique for handling uncertainty in variational measures such as the variogram. Data from a published example is used to illustrate the technique.

Jan 1, 2005

By James A. Schneider

Selection of resistance factors within Load and Resistance Factor Design (LRFD) requires accurate assessment of uncertainty and bias in load and resistance. To date, many studies have focused predominantly on the assessment of uncertainty, while the potential for bias appears to be the dominant factor in design for consistent levels of reliability under a variety of situations. Bias comes from factors which have been ignored in design method development but significantly influence resistance when extrapolating from conditions typical of databases to those at a given site. Uncertainty and bias can be quantified as the coefficient of variation and mean (or median) of a data set, respectively, for statistical assessment of load and resistance factors. This paper first presents an overview of statistical assessment of resistance factors, and then discusses factors that influence uncertainty and bias when extrapolating to situations outside of conventional databases of driven pile axial capacity.

Jan 1, 2009

By Abolfazl Eslami, Sara Heidarie Golafzani

CPT-based methods considered as complementary tools for static analyses outperform other axial pile bearing capacity predictive methods. Considering soil spatial variability and minor errors associated with procedure and operator, CPT-base methods mitigate the effect of latent uncertainties in pile design. These methods were developed based on different databases and purposes. Hence, several statistical and probabilistic attributes were defined and implemented to assess the predictive CPT-based methods’ performance via CPT and pile databases in terms of the model parameter. These features make a comparison among methods in terms of precision, accuracy, and efficiency. Furthermore, CPT-based methods can be subjected to scrutiny over their backgrounds and how they were developed via reliability analysis. In this regard, a database of sixty-two driven piles and their adjacent CPT soundings were gathered, and six commonly applied CPT-based methods were examined according to criteria other than prevailing statistical and probabilistic ones, including; (a) input variables, (b) soil behavior classification (SBC) (c) model assumption (d) Influence zone, and (e) axial loading direction. According to these introduced criteria, CPTbased methods were classified and appraised via efficiency ratio. Eventually, these reliability-based, statistical, and probabilistic criteria evaluate the understudied methods performance for the investigated compiled database and help designers select consciously appropriate predictive methods according to the site conditions.

Sep 8, 2021

The words ""Uncertainty"" and ""Risk"" pervade every discussion about mining exploration and investment. Perhaps these terms are subjectively understood by industry professionals, but objective portrayal of these concepts outside the industry is a woefully undeveloped science. This paper addresses current industry understanding and practice regarding quantitative risk assessment techniques, and provides examples of the application of three of these techniques. Probabilistic techniques for financial risk assessment are valuable adjuncts to conventional financial analysis, and address a range of issues not assessable by any other means. The value of whole-of-project probabilistic risk assessment is currently debatable for decision-making purposes, but is seen as important as a mechanism to focus attention to the critical issues that ultimately impact on project success. The dissection of project capital into risk and non-risk components provides valuable insights into risk characteristics not readily quantifiable in any other way. This technique also provides a framework for more objective ""what if?"" scenario evaluation and for the capital structure of resource projects. Finally, mechanisms for the valuation of undeveloped reserves are examined, and guidelines suggested. The importance of reliability in production cost estimates is highlighted and the impact of early development on reserve valuations is discussed. The importance of economics throughout all stages of the evaluation process is fundamental.

Jan 1, 1994

By Ö. Erdem

The investment decision making process in the insurance and finance industries is affected by new advances such as simulation techniques. These advances have improved the discounted cash flow method (DCF). In DCF, a dynamic and flexible model construction is not possible because it does not consider uncertain conditions. Each project should be evaluated taking into account the related uncertainties because the related uncertainties determine the characterization of the project. Related uncertainties can be processed in dynamic DCF, which is applicable to both financial and non-financial industries with different kind of uncertainties, such as power generation and petroleum projects. The dynamic DCF method can estimate net present value (NPV) while managing related project uncertainties with a simulation method like Monte Carlo Simulation. The simulation method is preferred because its output is unbiased. Therefore, a more realistic financial evaluation of the project can be concluded. In spite of the improvement of dynamic DCF, this project evaluation method is not used frequently in mining industry. However, the mining industry is ideally suited to this concept because it is highly dependent on estimations such as orebody size and ore grade. During the project evaluation stage, these uncertainties can be included with the dynamic DCF method. This study aims to contribute to increasing the usage of this method in mining projects. A copper reserve in Turkey is selected as a case study to apply uncertainty assessment for the evaluation of NPV.

Jan 1, 2012

By Ö. Erdem

The investment decision making process in the insurance and finance industries is affected by new advances such as simulation techniques. These advances have improved the discounted cash flow method (DCF). In DCF, a dynamic and flexible model construction is not possible because it does not consider uncertain conditions. Each project should be evaluated taking into account the related uncertainties because the related uncertainties determine the characterization of the project. Related uncertainties can be processed in dynamic DCF, which is applicable to both financial and non-financial industries with different kind of uncertainties, such as power generation and petroleum projects. The dynamic DCF method can estimate net present value (NPV) while managing related project uncertainties with a simulation method like Monte Carlo Simulation. The simulation method is preferred because its output is unbiased. Therefore, a more realistic financial evaluation of the project can be concluded. In spite of the improvement of dynamic DCF, this project evaluation method is not used frequently in mining industry. However, the mining industry is ideally suited to this concept because it is highly dependent on estimations such as orebody size and ore grade. During the project evaluation stage, these uncertainties can be included with the dynamic DCF method. This study aims to contribute to increasing the usage of this method in mining projects. A copper reserve in Turkey is selected as a case study to apply uncertainty assessment for the evaluation of NPV.

Jan 1, 2012

By J. Gholamnejad

In open pit mine planning and design, push back mine sequencing is widely used for long-term production planning. In push back design, a series of nested pits is generated and then considered as possible push backs with regard to the minimum push back width requirements. These nested pits are produced by parameterizing on one economic parameters like commodity price, mining or processing cost, stripping ratio etc. The most important characterization of these push backs is that the inner most push back has the highest value per ton, the second inner most push back has the second highest value per ton and so on. These nested pits are generated based on the best estimates of grade within a representation of the ore body in a three dimensional matrix form. Therefore, the inherent uncertainty associated with reserve estimation (for our discussion grade uncertainty) is not taken into account when push backs are designed. These methods do not attempt to establish which part of the deposit is likely to be worth most. This paper introduced a new algorithm that incorporates ore grade uncertainty during push back design process. The suggested strategy tries to seek to schedule risky blocks later in the extraction sequence.

Jan 1, 2007

By M. Rafie, M. Rinne, F. Samimi Namin

"SynopsisRock mass classification systems constitute an integral part of empirical underground excavation design. One system that is commonly used to classify rock mass is the Rock Mass Rating, or RMR, system. The RMR system has evolved over time to better reflect the perceived influence of various rock mass factors on excavation stability. While the introduced modifications have enhanced the applicability of this classification system, there are still areas that cause potential ambiguity. The RMR system cannot deal with input data ambiguities, uncertainties, and vagueness. To deal with the uncertainty, a Fuzzy Rock Mass Rating (FRMR) has been developed. This study aims to describe the main concept of the fuzzy approach, which is implemented in the FRMR to classify rock mass. The FRMR considers the uncertainty associated with the input data (uncertain variables) used in rock mass classification. The Gol-e-Gohar (GEG) area 3 iron ore deposits in the south of Iran were chosen as the case study for investigating the applicability of FRMR. The results of this study show that the FRMR software tool can easily be used for rock mass classification, even if uncertain input parameters have been used. FRMR consists of three parts, each of which is suitable for certain conditions.IntroductionNowadays, rock engineering classification systems, which constitute the backbone of the empirical design approach, are widely employed in both civil engineering and mining engineering. Rock mass classifications have recently been quite popular and are being used mostly for the preliminary design and planning purposes of projects. According to Bieniawski (1989), a rock mass classification scheme is intended to classify the rock masses, provide a basis for estimating deformation and strength properties, supply quantitative data for support estimation, and present a platform for communication between the exploration, design, and construction groups."

Jan 1, 2015

By Mario E. Rossi

Often geometallurgical models are prepared at various project stages from very few data and are assumed to be representative of very large tonnages. These may include recovery models; crushing and grinding parameters and models; models of concentrate grades; models of acid consumption; etc. These models commonly do not carry a measure of uncertainty or variability, and are taken at face value at the time of design and planning. This paper proposes a proactive approach to modelling variability, providing uncertainty estimates and thus allowing for risk analysis and mitigation of geometallurgical models. The variability model is built up by understanding the limitations of the pillars of a geometallurgical model: data uncertainty; geologic model uncertainty; domain definition uncertainty; and parameter estimation uncertainty. Of these factors, typically domain definition is the most significant contributor to geometallurgical model variability. First, the fundamental supports for these models are briefly discussed, with domain definition emphasized. Second, two methods for uncertainty modelling are proposed. The first, more applicable to conceptual or early-stage projects, is a simpler and more expedient alternative that provides initial assessments of variability. This is intended to aid management in decision-making related to budgeting, including further sampling and testing. The second, a block-by-block approach that allows a detailed assessment of risk for specific designs and mine plans, thus providing further opportunities for mitigation. In the example provided, emphasis is placed in communicating this variability to both management and technical personnel in the form of “measured-indicated-inferred” indicators and also block-by-block confidence intervals.

Jun 25, 2023

By S. Rukhaiyar, M. Ramulu, G. Pradeep, P. K. Singh, P. B. Choudhury

The drill and blast method is the most prominent rock excavation method used in mining and civil engineering projects. The ground vibration is the most undesirable effect of the blasting and needs to be controlled. The blasts are designed so that ground vibration at nearby structures must remain under the prescribed limit. Various empirical blast vibration attenuation models have been presented to estimate the ground vibration for designing purposes. These models assume ground vibration as a function of distance and maximum charge per delay. United States Bureau of Mines (USBM) model is most commonly used for the blast design. However, the uncertainty associated with these models is seldom characterized, thus diminishing its reliability. The probabilistic Bayesian approach associated with the Monte Carlo method can easily quantify uncertainties associated with the model and its parameters. Thirty-three blast vibration observation data from a granite quarry in Kerala, India, is used to estimate the probability distribution of model parameters. Markov Chain Monte Carlo (MCMC) approach is used for sampling 12,000 samples for obtaining the posterior distribution of parameters. The uncertainty associated with model parameters is quantified from the posterior distribution, and this is further used to estimate the credible and prediction limits of the model. The point estimate of the most optimum value of the parameter is estimated using maximum-aposteriori or MAP estimate. The model parameters are also obtained using the commonly used least-square error method, which is a maximum likelihood estimation or MLE approach. It has been observed that the accuracy of the model obtained using both MAP and MLE approach is almost equal. However, the MAP estimate as per Bayesian probabilistic analysis has the added advantage that it can estimate the uncertainty of parameters as well as the model, which is not possible using the MLE approach.

Sep 27, 2021

By M. E. Rossi

In mineral resources, geologic and mining data are acquired, processed, analysed, interpreted and modelled, eventually serving as basis to generate predictions and production plans. This is a complex process, and the resulting predictions are impacted by uncertainties related to the data itself and the processing methods and techniques used. They are also impacted by the subjective decisions made by the modeler(s) at each step of the way. Knowledge, biases, skills, and prior experience come into play in the long mineral resource evaluation development workflow. It is meaningless to discuss uncertainties without evaluating the associated risks that those uncertainties imply. It is important to quantify and assess uncertainty, and to evaluate and mitigate its consequences. This paper discusses (1) conceptual and practical sources of uncertainty; (2) the utopia of an “objective” uncertainty; and (3) the quantification and public reporting of uncertainty using geostatistical conditional simulations. The objective of this paper is to postulate that the industry is running out of reasons and excuses to ignore uncertainty and risk in project evaluation. This is done in two parts, with this, the first one, presenting a more conceptual discussion. Part 2 will present case studies from different types of mining projects and operations showcasing the impact that risk assessments can have in a mining project.

Feb 22, 2026

By Dr. George W. Annadale, Dr. Adrian G. Chantler

Materials which are likely to produce Acid Rock Drainage (ARV) can be identified with a reasonable degree of certainty. However, it is not currently possible to predict the concentrations of future contaminant discharges with similar confidence. One way of overcoming this problem is to model the uncertainty in knowledge related to estimates of future contaminant concentrations, and utilize this information in a decision model to decide on acceptable levels of expenditure on ARV control measures. The paper presents a risk modeling approach and proposes a decision model.

Jan 1, 1992

By H. H. Einstein

This paper reviews how uncertainty has been dealt with over the past 40 years using the decision making cycle as a frame of reference. The review of the phases of this cycle, as applied to rockmechanics and rock engineering, namely characterization, performance analysis, updating and decision making shows that in each, progress has been made over the past 40 years, although most of the basic concepts existed already in the 1960’s. Characterization is the area in which the greatest scientific steps were taken, this phase and performance analysis also gained from the tremendously expanded computational capabilities which allow one to use both more complex and more practically oriented models. The greatest practical advance is without using any doubt in risk based decision making although its acceptance shows interesting differences between different professions. Dans l’article suivant on utilise le cycle de décision pour illustrer le développement du traitement des incertitudes en mécanique des roches et en construction en roche dans les quarante années passées. La revue des phases du cycle de décision montre qu’on a fait du progrès dans chaque phase du cycle de décision, c’est à dire dans la caractérisation, dans l’analyse et la prédiction du comportement, dans l’actualisation et dans l’acte de décision, même si les concepts fondamentaux existaient déjà dans les années 1960. Les plus grands avancements scientifiques se trouvent dans le domaine de la caractérisation tandis que l’analyse prédictive profitait du développement de l’informatique qui a mené à des modèles plus complexes mais aussi plus pratiques. Le plus grand progrès est sans doute dans le domaine de l’acte de décision sur la base des risques. Ce procédé est devenu assez commun même s’il y a encore des différences d’acceptation entre différentes professions. Im vorliegenden Artikel wird der Entscheidungszyklus gebraucht, um darzustellen wie sich derUmgang mit Unsicherheiten im Felsbau während der letzen 40 Jahre entwickelt hat. DerÜberblick über die Phasen des Entscheidungsprozesses zeigt, dass bei der Anwendung in derFelsmechanik und im Felsbau, in allen Phasen d.h. bei der Charakterisierung, bei der analytischenVorhersage, beim Aktualisieren und bei der Entscheidungsfindung Fortschritte gemacht wurden,obwohl die grundlegenden Konzepte bereits in den 1960er Jahren existierten. Im Gebiet derCharakterisierung gab es wohl die grössten wissenschaftlichen Entwicklungen, während dieanalytische Vorhersage vor allem von den Fortschritten der Informatik profitierte, welchekomplexere wie auch praktischere Modelle möglich machte. Der grösste Fortschritt ist ganz sicherin der Entscheidungsfindung zu beobachten, wo Risikobetrachtungen gang und gäbe sind, obwohlhier noch einige Unterschiede zwischen verschiedenen Berufsgattungen zu finden sind.

Jan 1, 2003

By K Luthbom, A Lagerkvist

According to the Swedish Environmental Protection Agency, the number of potentially contaminated sites in Sweden is approximately 40 000. The funding for remediation from the Swedish Government alone amounts to $A 60 - 80 M (300 - 400 MSEK) annually for the period 2003 - 2006. Uncertainties will arise when obtaining samples in field, preparing them in laboratories and analysing them. Different procedures give rise to varying errors. Using data for decision-making that does not truly represent the site could be fatal. Misclassification of soil could lead to unnecessary costs or to risks to human health and the environment. The total uncertainty of an environmental sample can be split into analytical uncertainty and sampling uncertainty. The analytical uncertainty is usually known and reported from routine analysis. The size of the sampling uncertainty is less well known. Hence, the question is how big are the sampling uncertainties for contaminated soil and how big is the analytical error compared to the total sampling error? A scrap yard and two landfills within a workshop area were investigated. An excavator dug trial pits and samples were taken with a trowel from the walls of the trial pits. Samples were put into plastic bags and taken off site for preparation and analysis using XRF. Sample preparation included drying and sieving. The samples were homogenised by kneading the sample bags prior to analysis. The sampling and sample handling were performed in an intuitively way without knowledge of sampling theory. However, Pierre GyÆs sampling theory was used for subsequent evaluation of the data from the site investigation. The theory defines seven sampling errors, which can be applied to sampling of soil. Some errors have a variance that can be calculated or at least estimated, while other errors can give some idea whether the bias is positive or negative. The total sampling error varied over three orders of magnitudes from sample to sample. The single largest contributor to the large variation in error was the contaminant level. When comparing the analytical error and the total sampling error the ratio varies more than three orders of magnitude.

Jan 1, 2005

By B. Panton, J. Carvalho, E. T. Brown

High-capacity, post-tensioned anchors have found wide-spread use in initial dam design and construction, and in the strengthening and rehabilitation of concrete dams to meet modern design and safety standards. Despite the advances that have been made in rock mechanics and rock engineering during the almost 80 years in which post-tensioned anchors have been used in dam engineering, some aspects of the rock engineering design of high-capacity rock anchors for dams have changed relatively little over the last 30 or 40 years. This applies, in particular, to the calculations usually carried out to establish the grouted embedment lengths required for deep, post-tensioned anchors. These calculations which involve a number of aleatory and epistemic uncertainties, usually make simplified assumptions about the distribution and values of rock-grout interface shear strengths, the shape of the volume of rock likely to be involved in uplift failure under the influence of a system of post-tensioned anchors, and the mechanism of that failure. The resulting designs are generally conservative. These aspects of the rock engineering design of large, post-tensioned rock anchors for dams could be improved by making greater use of modern, comprehensive, numerical analyses in conjunction with 3D models of the rock mass structure, realistic rock and rock mass properties, and the results of prototype anchor tests in the rock mass concerned.

Jan 1, 2015

By Robert B. Parsons

"Income tax legislation is not keeping pace with federal and provincial environmental legislation. There is a vast array of new environmental regulations at various stages of implementation across the country. Unfortunately, there are serious concerns about the deductibility of significant payments which mining companies will be required to make under these new rules, and the Department of Finance seems to be reluctant to act on these concerns. IntroductionWhile the federal and provincial governments are racing ahead with obvious fervour to introduce new envirorunental laws, the tax rules relating to envirorunental costs are being allowed to lag far behind. In a nutshell, the tax treatment of envirorunental costs is not keeping pace with the new envirorunental legislation.One of the most serious concerns of the mining industry is the deductibility of mine reclamation or closing costs. The producing provinces are well advanced down the road toward mandating upfront deposits, bonds, or similar financial guarantees to protect the envirorunent from the operation and eventual closure of a mine. These requirements are not small. In some instances, they can amount to tens of millions of dollars. And, if there is no tax deduction for these sums when they are set aside by the mining company, then the costs have to be paid out of the company's after-tax earnings."

Jan 1, 1991

By B. Samanta

This paper highlights the use of an innovative mine production scheduling scheme for grade-control planning tasks that take into consideration grade-model uncertainty. The scheduling exercise has been carried out with the help of a multiobjective genetic algorithm (MOGa) for the production scheduling operations. The underlying motive behind the use of MOGa has been the generation of a set of pareto optimal solutions to meet the goals of the target-grade specifications for the considered multiple grade attributes. Several new concepts related to MOGa formulation, in particular the mutation operation and the convergence criteria of this algorithm, are proposed in this paper. The modeling of grade uncertainty into the scheduling outputs has also been incorporated through a set of conditional simulated grade maps. The proposed scheme of production scheduling operations has been applied for the grade-control planning operations in an iron ore mine to meet the targeted grade specifications of iron, silica and alumina, and a risk analysis has been performed to this end.

Jan 1, 2013

By M. Vasudevan

In sulfide mineral flotation, the efficiency of separation is severely affected by the presence of non-sulfide gangue minerals, such as altered silicates and serpentines. Although this is an acknowledged fact, most studies in mineral processing have focused on value minerals, and studies on gangue minerals affecting flotation performance are quite rare, and even those that do are limited in scope. This paper is an attempt to highlight the use of grade-recovery curves in studying the effects of gangue minerals. Specifically, we present the flotation response of problematic Ni and Cu ores which show highly uncharacteristic but similar grade-recovery characteristics despite the very different mineralogy and try to understand this behavior and the underlying mechanism. Finally, we propose chemical modifiers as solutions to overcome the detrimental effects of these gangue minerals and improve efficiency of flotation performance. Keywords: Non-sulfide gangue, grade-recovery, sulfide minerals, serpentines, talc, shale, slimes, spiking, modifiers

Sep 1, 2012