Feasibility study on manganese nodules recovery in the Clarion-Clipperton Zone

The sea occupies three quarters of the area on the earth and provides various kinds of resources to mankind in the form of minerals, food, medicines and even energy. “Seabed exploitation” specifically deals with recovery of the resources that are found on the seabed, in the form of solids, liquids and gasses (methane hydrates, oil and natural gas). The resources are abundant; nevertheless the recovery process from the seabed, poses various challenges to mankind. This study starts with a review on three types of resources: polymetallic manganese nodules, polymetallic manganese crusts and massive sulphides deposits. Each of them are rich in minerals, such as manganese, cobalt, nickel, copper and some rare earth elements. They are found at many locations in the deep seas and are potentially a big source of minerals. No commercial seabed mining activity has been accomplished to date due to the great complexities in recovery. This book describes the various challenges associated with a potential underwater mineral recovery operation, reviews and analyses the existing recovery techniques, and provides an innovative engineering system. It further identifies the associated risks and a suitable business model.Chapter 1 presents a brief background about the past and present industrial trends of seabed mining. A description of the sea, seabed and the three types of seabed mineral resources are also included. A section on motivations for deep sea mining follows which also compares the latter with terrestrial mining.Chapter 2 deals with the decision making process, including a market analysis, for selecting manganese nodules as the resource of interest. This is followed by a case study specific to the location of interest: West COMRA in the Clarion-Clipperton Zone. Specific site location is determined in order to estimate commercial risk, environmental impact assessment and logistic challenge.Chapter 3 lists the existing techniques for nodule recovery operation. The study identifies the main components of a nodules recovery system, and organizes them into: collector, propulsion and vertical transport systems.Chapter 4 discusses various challenges posed by manganese nodules recovery, in terms of the engineering and environment. The geo-political and legal-social issues have also been considered. This chapter plays an important role in defining the proposed engineering system, as addressing the identified challenges will better shape the proposed solution.Chapter 5 proposes an engineering system, by considering the key components in greater details. An innovative component, the black box is introduced, which is intended to be an environmentally-friendly solution for manganese nodules recovery. Other auxiliary components, such as the mother ship and metallurgical processing, are briefly included. A brief power supply analysis is also provided.Chapter 6 assesses the associated risks, which are divided into sections namely commercial viability, logistic challenges, environmental impact assessment and safety assessment. The feasibility of the proposed solution is also dealt with.Chapter 7 provides a business model for the proposed engineering system. Potential customers are identified, value proposition is determined, costumer relation is also suggested. Public awareness is then discussed and finally a SWOT analysis is presented. This business model serves as an important bridge to reach both industry and research institutes.Finally, Chapter 8 provides some conclusions and recommendation for future work

The hydraulic impact and alleviation phenomena numeric modeling in the industrial pumped pipelines

The issues of the hydropercussion phenomena mathematical modeling in the industrial pumped piping systems, with the pumps and dampeners included, to determine the impact absorbers effectiveness on the amplitude-frequency charac- teristics of these hydro-mechanical systems are considered. It’s still actual and many authors are still looking for the systems CFD issues research and resolution, see [6, 7]. Method of calculating the transient and frequency characteristics of the pipeline that contains a pump and a dampener, is based on nonlinear mathematical model. Simulation of overlapping stream with using industrial valves is provided by introducing the exponential law of diminishing cross-sectional area of the pipeline. The basis of calculation is the method of characteristics applied to the simplified Navier- Stokes equations

Sustainable seabed mining: guidelines and a new concept for Atlantis II Deep

The feasibility of exploiting seabed resources is subject to the engineering solutions, and economic prospects. Due to rising metal prices, predicted mineral scarcities and unequal allocations of resources in the world, vast research programmes on the exploration and exploitation of seabed minerals are presented in 1970s. Very few studies have been published after the 1980s, when predictions were not fulfilled. The attention grew back in the last decade with marine mineral mining being in research and commercial focus again and the first seabed mining license for massive sulphides being granted in Papua New Guinea’s Exclusive Economic Zone.Research on seabed exploitation and seabed mining is a complex transdisciplinary field that demands for further attention and development. Since the field links engineering, economics, environmental, legal and supply chain research, it demands for research from a systems point of view. This implies the application of a holistic sustainability framework of to analyse the feasibility of engineering systems. The research at hand aims to close this gap by developing such a framework and providing a review of seabed resources. Based on this review it identifies a significant potential for massive sulphides in inactive hydrothermal vents and sediments to solve global resource scarcities. The research aims to provide background on seabed exploitation and to apply a holistic systems engineering approach to develop general guidelines for sustainable seabed mining of polymetallic sulphides and a new concept and solutions for the Atlantis II Deep deposit in the Red Sea.The research methodology will start with acquiring a broader academic and industrial view on sustainable seabed mining through an online survey and expert interviews on seabed mining. In addition, the Nautilus Minerals case is reviewed for lessons learned and identification of challenges. Thereafter, a new concept for Atlantis II Deep is developed that based on a site specific assessment.The research undertaken in this study provides a new perspective regarding sustainable seabed mining. The main contributions of this research are the development of extensive guidelines for key issues in sustainable seabed mining as well as a new concept for seabed mining involving engineering systems, environmental risk mitigation, economic feasibility, logistics and legal aspects

Improving single classifiers prediction accuracy for underground water pump station in a gold mine using ensemble techniques

Abstract: In this paper six single classifiers (support vector machine, artificial neural network, naïve Bayesian classifier, decision trees, radial basis function and k nearest neighbors) were utilized to predict water dam levels in a deep gold mine underground pump station. Also, Bagging and Boosting ensemble techniques were used to increase the prediction accuracy of the single classifiers. In order to enhance the prediction accuracy even more a mutual information ensemble approach is introduced to improve the single classifiers and the Bagging and Boosting prediction results. This ensemble is used to classify, thus monitoring and predicting the underground water dam levels on a single-pump station deep gold mine in South Africa, Mutual information theory is used in order to determine the classifiers optimum number to build the most accurate ensemble. In terms of prediction accuracy, the results show that the mutual information ensemble over performed the other used ensembles and single classifiers and is more efficient for classification of underground water dam levels. However the ensemble construction is more complicated than the Bagging and Boosting techniques

UNDERSTANDING LARGE-SCALE NATURAL MINE WATER-GEOLOGIC FORMATION SYSTEMS FOR GEOTHERMAL APPLICATIONS

Geothermal energy recovery from flooded mines has been gaining momentum worldwide. Numerous mines are flooded after their closure, either naturally or artificially, in which the water in the mines can be heated by the surrounding geologic formations due to geothermal gradients, leading to sizeable man-made reservoirs of warm water. Such mine water, therefore, can be treated as a renewable geothermal resource for heating/cooling buildings, which has the potential to benefit over millions of people in the United States and much more around the world. Though some real projects and/or installations launched worldwide for the use of flooded mines for geothermal applications, there are many uncertainties in the theoretical aspect of this application, in particular, the scientific understanding of the large-scale natural mine water-geologic formation system is still in a preliminary stage and thus far lags behind its application. Motived by this missing scientific linkage, the current dissertation presents an investigation with multiphysics analyses to understand the large-scale natural mine water-geologic formation system. The main objective is to provide an in-depth understanding of this system for guiding and optimizing this large-scale geothermal application from a scientific perspective. For the purpose, this dissertation presents four specific investigations. The first investigation explores a specific site with comprehensive information relevant to the natural mine water-geologic formation system for recovering geothermal energy from deep abandoned mines for heating and cooling buildings. The second investigation presents the results of field tests and multiphysics analysis of a flooded shaft for understanding the transport of heat and mass in the natural mine water-geologic formation system. The third investigation addresses a key scientific issue regarding the layering phenomenon observed in large bodies of mine water, which controls the temperature distribution and heat energy storage in the deep geothermal field for the proposed energy renovation. The fourth investigation aims to provide insights into the dominant heat and mass transport mechanisms underlying thermohaline stratifications and investigate the factors influencing thermohaline stratifications. The above four investigations presented in this dissertation provide the urgently needed scientific understanding of the natural mine water-geologic formation system for this large-scale geothermal application, which eventually offers scientific bases for the future optimal design of this unique large-scale application of recovering geothermal energy from flooded mines

Pump It Up: Predict Water Pump Status using Attentive Tabular Learning

Water crisis is a crucial concern around the globe. Appropriate and timely maintenance of water pumps in drought-hit countries is vital for communities relying on the well. In this paper, we analyze and apply a sequential attentive deep neural architecture, TabNet, for predicting water pump repair status in Tanzania. The model combines the valuable benefits of tree-based algorithms and neural networks, enabling end-to-end training, model interpretability, sparse feature selection, and efficient learning on tabular data. Finally, we compare the performance of TabNet with popular gradient tree-boosting algorithms like XGBoost, LightGBM,CatBoost, and demonstrate how we can further uplift the performance by choosing focal loss as the objective function while training on imbalanced data.Comment: 9 pages, 5 figures, 2 table

A Study on Comparison of Classification Algorithms for Pump Failure Prediction

The reliability of pumps can be compromised by faults, impacting their functionality. Detecting these faults is crucial, and many studies have utilized motor current signals for this purpose. However, as pumps are rotational equipped, vibrations also play a vital role in fault identification. Rising pump failures have led to increased maintenance costs and unavailability, emphasizing the need for cost-effective and dependable machinery operation. This study addresses the imperative challenge of defect classification through the lens of predictive modeling. With a problem statement centered on achieving accurate and efficient identification of defects, this study’s objective is to evaluate the performance of five distinct algorithms: Fine Decision Tree, Medium Decision Tree, Bagged Trees (Ensemble), RUS-Boosted Trees, and Boosted Trees. Leveraging a comprehensive dataset, the study meticulously trained and tested each model, analyzing training accuracy, test accuracy, and Area Under the Curve (AUC) metrics. The results showcase the supremacy of the Fine Decision Tree (91.2% training accuracy, 74% test accuracy, AUC 0.80), the robustness of the Ensemble approach (Bagged Trees with 94.9% training accuracy, 99.9% test accuracy, and AUC 1.00), and the competitiveness of Boosted Trees (89.4% training accuracy, 72.2% test accuracy, AUC 0.79) in defect classification. Notably, Support Vector Machines (SVM), Artificial Neural Networks (ANN), and k-Nearest Neighbors (KNN) exhibited comparatively lower performance. Our study contributes valuable insights into the efficacy of these algorithms, guiding practitioners toward optimal model selection for defect classification scenarios. This research lays a foundation for enhanced decision-making in quality control and predictive maintenance, fostering advancements in the realm of defect prediction and classification

A Feasibility Study for the Automated Monitoring and Control of Mine Water Discharges

The chemical treatment of mine-influenced waters is a longstanding environmental challenge for many coal operators, particularly in Central Appalachia. Mining conditions in this region present several unique obstacles to meeting NPDES effluent limits. Outlets that discharge effluent are often located in remote areas with challenging terrain where conditions do not facilitate the implementation of large-scale commercial treatment systems. Furthermore, maintenance of these systems is often laborious, expensive, and time consuming. Many large mining complexes discharge water from numerous outlets, while using environmental technicians to assess the water quality and treatment process multiple times per day. Unfortunately, this treatment method when combined with the lower limits associated with increased regulatory scrutiny can lead to the discharge of non-compliant water off of the mine permit. As an alternative solution, this thesis describes the ongoing research and development of automated protocols for the treatment and monitoring of mine water discharges. In particular, the current work highlights machine learning algorithms as a potential solution for pH control.;In this research, a bench-scale treatment system was constructed. This system simulates a series of ponds such as those found in use by Central Appalachian coal companies to treat acid mine drainage. The bench-scale system was first characterized to determine the volumetric flow rates and resident time distributions at varying flow rates and reactor configurations. Next, data collection was conducted using the bench scale system to generate training data by introducing multilevel random perturbations to the alkaline and acidic water flow rates. A fuzzy controller was then implemented in this system to administer alkaline material with the goal of automating the chemical treatment process. Finally, the performance of machine learning algorithms in predicting future water quality was evaluated to identify the critical input variables required to build these algorithms. Results indicate the machine learning controllers are viable alternatives to the manual control used by many Appalachian coal producers

Flooding and reequilibration of a series of Pittsburgh bed underground coal mines, 1980 to 2015

This study examines the water-level elevation history of selected flooding and flooded underground mines in the Pittsburgh coal basin of SW Pennsylvania from the time of closure until post-flooding pool-level reequilibration. Mines within this mining district developed pools with nearly steady-state groundwater flow within 10 to 50 years after closure. Equilibrated pool levels within each of the mines were controlled by various combinations of spillage to the surface or other mines, pumpage, and barrier leakage. In a study of flooding in the Clarksville, PA area, field water-level observations, mine geometry, barrier hydraulic conductivity, recharge rates, and late-stage storage gains were parameterized to match known pumping rates and develop a fluid mass balance. Vertical infiltration (recharge and leakage) estimates were developed using a depth-dependent model based on the assumption that most vertical infiltration is focused in areas with \u3c75 m of overburden. A MODFLOW simulation of the nearly steady-state flow conditions was calibrated to hydraulic heads in observation wells and to known pumping rates by varying barrier hydraulic conductivity. The calibrated model suggests significant head-driven leakage between adjacent mines, both horizontally through coal barriers and vertically through interburden into an overlying mine. Calibrated barrier hydraulic conductivities were significantly greater than literature values for other mines at similar depths in the region. This suggests that some barriers may be hydraulically compromised by un-mapped entries, horizontal boreholes, or similar features that act to interconnect mines. These model results suggest that post-mining inter-annual equilibrium conditions are amenable to quantitative description using mine maps, sparse observation-well data, accurately-estimated pumping rates, and depth-dependent vertical infiltration estimates. Results are applicable to planning for post-flooding water control schemes, although hydraulic testing may be required to verify model results.;In a second study of a nearby area, three mines were mapped to determine mining type distribution (longwall, etc.) and these mining-type areas assigned typical porosity values based on industry-standard extraction ratios. The porosity estimates were plotted against coal-base elevation contours to model the hypsometric distribution of porosity. Using pumping rates from active operations and these hypsometric porosities, the approximate duration of flooding was estimated for two of the mines; these overestimate the actual (observed) flooding time by 200-275%. On the other hand, mine inflow rates estimated using observed water levels and the porosity model indicate temporal changes in the fluid mass balance for each mine that are consistent with spillage and/or barrier leakage between mines interpreted from water-level hydrographs. Results indicate that accurate prediction of the duration of mine flooding requires explicit consideration of groundwater conditions in adjacent mines and the potential for barrier leakage