Development Of Mineral Resources Research Articles

Comprehensive benefit evaluation of mineral resources development based on dual population constrained multi-objective evolutionary algorithm

With the increasing global demand for mineral resources, the comprehensive benefit evaluation of mineral resources development is playing an increasingly important role in the field of mineral resources development. However, there are few attempts to use multi-objective evolutionary algorithms (MOEAs) to study the comprehensive benefit evaluation problem of mineral resources development. To effectively solve this problem, this study established a multi-objective optimization model for comprehensive benefit evaluation of mineral resources development and proposed a dual-population constrained multi-objective evolutionary algorithm (CMOEA). The algorithm uses two populations to organically combine the efficient convergence of the non-dominated sorting genetic algorithm II (NSGA-II) with the advantage of the adaptive geometry estimation based multi-objective evolutionary algorithm (AGE-MOEA) in estimating the shape of the Pareto front, named co-evolution based on non-dominated sorting genetic algorithm and adaptive geometry estimation (C-NSGA-AGE). 3 test suites are used to verify the performance of the proposed algorithm. Experimental results show that compared with competing algorithms, C-NSGA-AGE has strong competitiveness in most test functions. The proposed method is used to solve the model, and five optimal comprehensive benefit evaluation schemes are given for different objectives. Among them, the maximum benefit is obtained when each objective is developed in a balanced way, which reaches 0.837181.

Демографические тенденции и парадоксы развития северных территорий Западной Сибири

This paper analyzes socio-demographic trends over the past sixty years in the northern territories of Western Siberia, specifically the Khanty-Mansiysk and Yamalo-Nenets Autonomous Okrugs. The study spans from the initial development of mineral resources in the 1950s–1960s to the present day. These regions are distinctive not only for their climatic and ethnocultural characteristics but also for their unique socio-economic models of regional development.The active phase of resource exploitation led to substantial population growth and rapid urbanization in the Khanty-Mansiysk and Yamalo-Nenets Autonomous Okrugs, resulting in the establishment of over 20 new cities. However, since the 2000s, a gradual decline in oil and gas production has reversed these trends, causing a persistent outflow of population and reduced economic activity in many municipalities. The study identifies both commonalities and divergences in socio-demographic trends across the two regions. For instance, the Khanty-Mansiysk Autonomous Okrug, unlike the Yamalo-Nenets Autonomous Okrug, has experienced a gradual population increase, primarily driven by natural population growth and positive net migration. Meanwhile, both regions exhibit similar changes in the age and gender structure of their populations and a shift in settlement patterns between urban and rural areas. The findings highlight the need for further comprehensive analysis of socio-demographic trends, with particular attention to permanent residents, indigenous small-numbered peoples of the North, and populations engaged in shift work. Additionally, the study underscores the importance of considering socio-cultural and climatic conditions in evaluating health indicators, as well as mortality and fertility rates.

The Measurement of Metal Mineral Particle Size Under the Microscope Based on Gaussian Pyramids and Directional Maximum Intercept

With the development of mineral resources, minerals are becoming increasingly difficult to process. In order to utilize these resources more effectively, in-depth research into process mineralogy has become increasingly important in the field of mineralogy, and particle size measurement under the microscope is one of the critical aspects of process mineralogy. At present, the use of scanning electron microscopes and other equipment for measurement is very expensive, and manual measurement has problems such as poor accuracy and low efficiency. In addition, there is a lack of reference materials for the segmentation algorithm of mineral light images. This article proposes a Gaussian pyramid based on bilateral filtering combined with directional maximum intercept to measure mineral particle size under the microscope. In the experiments, different segmentation algorithms were studied, including Gaussian pyramid segmentation based on bilateral filtering, segmentation based on Fuzzy C-Means, and the rapidly developing deep learning segmentation algorithms in recent years. By comparing the segmentation effects of these three algorithms on various mineral thin-section images, the Gaussian pyramid segmentation algorithm based on bilateral filtering was selected as the optimal one. This was then combined with the directional maximum intercept method to measure the particle size of ilmenite and pyrite images. The experimental results show that the segmentation method based on the bilateral filtering Gaussian pyramid technique has higher segmentation accuracy than the other two algorithms, and can accurately measure the particle size of minerals under the microscope. Compared with manual measurement, this method can effectively and accurately measure the microscopic particle size of target minerals, greatly reducing the workload of measurement personnel and reducing the time spent on measurement.

Mechanical properties and fracture behavior of sandstone similar materials with different joint positions and thicknesses based on triaxial testing and PFC simulation

The mechanical properties and failure characteristics of joined rocks have an important impact on the disaster prevention of underground engineering and the sustainable development of mineral resources. The effects of confining pressure, joint location, and joint thickness on the mechanical properties of rock-like specimens under triaxial test have been studied. Furthermore, using the "DFN-age" function of PFC numerical simulation, the stress characteristics, and failure characteristics of rock specimens under different confining pressure, joint location and joint thickness are analyzed. The research results indicate that as the thickness of the joint increases and the joint position approaches the center of the specimen, the compressive strength of the specimen decreases. As the confining pressure increases, the compressive strength increases and failure modes of rock like specimens with different joint types also tend to be similar. The specimens manifest complex shear-tensile composite failures. In addition, the initiation cracks and main control cracks at the joint terminus can be classified as reverse tensile wing cracks, reverse shear cracks, shear cracks and tensile wing cracks. When the joint thickness of the specimen is 1.0 mm and the distance from the joint position to the center of the specimen is 10–20 mm, the crack evolution characteristics and stress distribution law of the specimen will undergo a transformation.

Research Progress on Intelligent Control Heading Machine

Background: With the development of society, the demand for underground works, such as to control road traffic and enhance the development of mineral resources, is increasing. Simple human and mechanical resources can no longer meet people's needs. Therefore, the development of the heading machine has advanced the construction of underground engineering and the development of mineral resources, leading to a significant change in tunneling efficiency. However, the increase in the scale of engineering facilities, changes in geological conditions, the reduction in human resources, and other factors, accompanied by the arrival of the era of big data, have prompted the heading machine to become more and more efficient, advanced, and intelligent. Objective: This article aimed to describe the classification, characteristics, and development of existing heading machines. It also takes into account the impact of changing engineering facilities, geological conditions, and limited human resources. The research and development direction of the equipment in intelligent perception, intelligent construction, and safety management is proposed. Methods: In this study, the working principle and related patents of the heading machine have been summarized. The structural characteristics, differences, and application characteristics of the heading machines in different fields are introduced, and the limitations of previous methods have been analyzed. Results: By analyzing and comparing the existing heading machines and summarizing their typical features, the main problems in the development of heading machines have been analyzed and the development trend of heading machines is predicted. Finally, the current research status and future development trends of heading machines and their patents are discussed. Conclusion: The heading machines are divided into two types based on the operation object: tunnel boring machine and ordinary heading machine. Among these, the full-face heading machine is the most widely used, and heading machines with different working faces are the most typical among ordinary heading machines. Currently, the application of intelligence in heading machines has gained widespread traction both domestically and internationally. The future development direction of heading machines must focus on intelligence, ensuring safety and efficiency, lightweight design, and environmental sustainability.

Resilient Semi-Supervised Meta-Learning Network based on wavelet transform and K-means optimization for fluid classification

In the field of geological exploration, accurately distinguishing between different types of fluids is crucial for the development of oil, gas, and mineral resources. Due to the scarcity of labeled samples, traditional supervised learning methods face significant limitations when processing well log data. To address this issue, this paper presents a novel fluid classification method known as the Resilient Semi-Supervised Meta-Learning Network (RSSMLN) based on wavelet transform and K-means optimization, which combines the advantages of few-shot learning and semi-supervised learning, aiming to optimize fluid recognition in well log data. Initially, this study employs a small set of labeled samples to train the initial model and utilizes pseudo-label generation and K-means clustering to optimize prototypes, thereby enhancing the model's accuracy and generalization ability. Subsequently, during the feature extraction process, wavelet transform preprocessing techniques are introduced to enhance the time-frequency feature representation of well log data through multi-scale decomposition. This process effectively captures high-frequency and low-frequency features, providing structured information for subsequent convolution operations. By employing a dual-channel heterogeneous convolutional kernel feature extractor, RSSMLN can effectively capture subtle features of the fluids and significantly improve classification accuracy. Experimental results indicate that compared to various standard deep learning models, RSSMLN achieves superior performance in fluid identification tasks. This research provides a reliable solution for few-shot fluid recognition in oilfield applications and offers scientific support for resource exploration and evaluation.

The Spatiotemporal Evolution of Vegetation in the Henan Section of the Yellow River Basin and Mining Areas Based on the Normalized Difference Vegetation Index

The Yellow River Basin is rich in coal resources, but the ecological environment is fragile, and the ecological degradation of vegetation is exacerbated by the disruption caused by high-intensity mining activities. Analyzing the dynamic evolution of vegetation in the Henan section of the Yellow River Basin and its mining areas over the long term run reveals the regional ecological environment and offers a scientific foundation for the region’s sustainable development. In this study, we obtained a long time series of Landsat imageries from 1987 to 2023 on the Google Earth Engine (GEE) platform and utilized geographically weighted regression models, Sen (Theil–Sen median) trend analysis, M-K (Mann–Kendall) test, coefficient of variation (CV), and the Hurst index to investigate the evolution of vegetation cover based on the kNDVI (the normalized difference vegetation index). This index is used to explore the spatial and temporal characteristics of vegetation cover and its future development trend. Our results showed that (1) The kNDVI value in the Henan section of the Yellow River Basin exhibited a trend of fluctuating upward at a rate of 0.0509/10a from 1987 to 2023. The kNDVI trend in the mining areas of the region aligned closely with the overall trend of the Henan section; however, the annual kNDVI in each mining area consistently remained lower than that of the Henan section and displayed a degree of fluctuation, predominantly characterized by medium–high variability, with areas of moderate and high fluctuations accounting for 73.5% of the total. (2) The kNDVI in the study area showed a significant improvement in vegetation cover and its future development trends. We detected a significant improvement in the kNDVI index in the area; yet, significant improvement in this index in the future might cause vegetation degradation in 87% of the study area, which may be closely related to multiple factors such as the intensity of mining at the mine site, anthropogenic disturbances, and climate change. (3) The vegetation status of the Henan section of the Yellow River Basin shows a significant positive correlation with distance from mining areas, accounting for 90.9% of the total, indicating that mining has a strong impact on vegetation cover. This study provides a scientific basis for vegetation restoration, green development of mineral resources, and sustainable development in the Henan section of the Yellow River Basin.

Research on the response of different flight modes under concave and convex terrain by Semi-Airborne Transient Electromagnetic Method (SATEM)

With the development and utilization of various mineral resources in horizontal terrain areas gradually becoming saturated, the study of transient electromagnetic method has gradually shifted from flat terrain areas to complex fluctuating and high altitude areas. Due to the characteristics of transmitting source on the ground and receiving point in the air, the Semi-Airborne transient electromagnetic method (SATEM) has advantages such as superior working efficiency, large exploration depth and higher signal-to-noise ratio of collected signals. At present, there are few researches on the influence of the flight mode of the UAV on the collected data. In this paper, the concave terrain and convex terrain are described by using unstructured tetrahedral mesh, and the response of terrain model is calculated. Then the terrain response under different flight modes has been researched and analyzed systematically. The corresponding relative error graph is obtained and compared to summarize the law. Through simulation with different influence parameters, it is found that when the flight mode of the UAV is the same altitude, the SATEM response is less affected by the fluctuating terrain, and when the flight mode of the UAV is along the terrain, the SATEM response is more affected by the fluctuating terrain. The study of the response of UAV to the undulating terrain under different flight modes can provide a reference for the processing and interpretation of SATEM data in the undulating terrain region.

The Loss and Recovery Potential of Net Ecosystem Productivity in Mining Areas: A Global Assessment Based on Data for 2000–2020

Climate change control requires more land to increase ecosystem carbon sequestration. With the high-intensity development of mineral resources in past decades, massive mining areas have been generated worldwide. However, few studies have evaluated the carbon sequestration of these mining areas. In this study, we analyzed the net ecosystem productivity (NEP) changes and calculated the NEP losses in global terrestrial mining areas. We adopted the random forest model to evaluate the NEP recovery potential and its driving factors. The key findings are that (1) the NEP of global mining areas exhibited a relatively obvious decreasing trend from 2000 to 2020, with an overall reduction of 29.1% and a maximum decline of 35.7%. By 2020, the NEP loss in mining areas was 11.9 g C m−2 year−1, and the total loss reached 576.9 Gg C year−1. (2) Global mining areas demonstrate significant NEP recovery potential, with an average of 12.0 g C m−2 year−1. Notably, Oceania and South America have significantly higher recovery potentials, with average mine site NEP recovery potentials of 15.9 g C m−2 year−1 and 16.1 g C m−2 year−1. In contrast, European mines have considerably lower recovery potentials of less than 10 g C m−2 year−1. In Asia, North America and Africa, the NEP recovery potential varies widely from mine to mine, but generally meets the global average. (3) The annual precipitation, population density, organic soil carbon, and average slope are important drivers of NEP recovery in mining areas and exhibit positive correlations with the NEP recovery potential. In contrast, mine area and minimum temperature exhibit a negative correlation. The dependency curves of the three drivers, standardized precipitation evapotranspiration index, average elevation, and annual maximum temperature, are U-shaped, indicating that the recovery potential was poorer in the tropical and frigid zones with less precipitation. The results of this study provide a scientific basis for ecological restoration and sustainable development of mining areas worldwide.

3D Inversion and Interpretation of Airborne Multiphysics Data for Targeting Porphyry System, Flammefjeld, Greenland

The exploration of porphyry deposits in Greenland has become increasingly important due to their significant economic potential. We utilized total magnetic intensity (TMI) and mobile magnetotelluric (MobileMT) airborne data to delineate potential porphyry mineralization zones. The TMI method was employed to map variations in the Earth’s magnetic field caused by subsurface geological features, including mineral deposits. By analyzing anomalies in TMI data, potential porphyry targets were identified based on characteristic magnetic signatures associated with mineralized zones. Complementing TMI data, MT airborne surveys provided valuable insights into the electrical conductivity structure of the subsurface. Porphyry deposits exhibited distinct conductivity signatures due to the presence of disseminated sulfide minerals, aiding in their identification and delineation. Integration of the TMI and MobileMT datasets allowed for a comprehensive assessment of porphyry exploration targets in Flammefjeld. The combined approach facilitates the identification of prospective areas with enhanced geological potential, optimizing resource allocation and exploration efforts. Overall, this study demonstrates the efficacy of integrating TMI and MobileMT airborne data for porphyry exploration in Greenland, offering valuable insights for mineral exploration and resource development in the region.

Injected phase change seismic source construction and monitoring experiment

Scientific assessment of the transport channels and distribution of oil, gas, water, and other fluids is the key to enhancing oil and gas production capacity and ensuring the safe and efficient development of mineral resources. Traditional microseismic monitoring has been suffering from limitations such as ambiguous attribute characteristics of the seismic source and low signal-to-noise ratios of the data, leading to poor location accuracy and large uncertainties. We develop a phase change seismic source monitoring method that allows for a detailed characterization of the spatial distribution of subsurface fluid transport by accurately locating the equivalent seismic source within supportive fractures. A phase change seismic source is developed and constructed based on the phase change material, enabling control over phase change temperature, source energy, and source scale through the principle of phase change energy storage. The source introduces an active approach to seismic signal generation, diverging from the conventional passive method reliant on rock rupture. Then, 3D homogeneous models are constructed for ground monitoring and in-well monitoring using impulse source propagation theory. The numerical simulation of the wavefield uses the finite-difference method, and the equivalence of discrete sources is confirmed using the Pearson correlation function. The reliability of the monitoring method is verified through a seismic monitoring experiment and comprehensive feasibility analysis.

Research on the development of recycling technology for magnesium refractory materials

Abstract Magnesium refractory materials are rich in substances such as alumina and magnesium oxide, and the recycling and reuse of their waste is an important way to achieve energy conservation, environmental protection, and sustainable development of mineral resources. This article analyzes and elucidates the current recycling and utilization technologies of refractory materials from the perspectives of refractory waste used in desulfurization mixing heads, recycled magnesia carbon brick refractory materials, magnesia calcium brick refractory materials, and blast furnace lining refractory materials. By analyzing the key issues in the recycling and utilization technology of Magnesium refractory waste, important references are provided for the development direction of deep processing of high-quality refractory recycled products.

Realization of Integrated Regional Ecological Management Based on Ecosystem Service Supply and Demand Flow Networks: An Example from a Dominant Mineral Resources Development Area

Understanding the flow processes and pattern optimization of ecosystem services (ESs) supply and demand is crucial for integrated regional ecological management. However, the understanding of the flow process of ESs at the 1 km grid scale is still limited, especially in areas dominated by mineral resource development. The landscape in these areas has undergone significant changes due to mining activities. It is urgent to construct a regional management model that integrates the flow of ecosystem services and mine restoration. This study developed a framework that links ecosystem service flows (ESFs) and ecological security patterns (ESP) based on multi-source ecological monitoring data, constructed an ES supply-demand flow network through the flow properties, and determined the sequence and optimization strategies for mine rehabilitation to achieve integrated regional management. The results show that, except for food production (FP), other services were in surplus overall, mostly in synergistic relationships, but the spatial distribution of their supply and demand was not coordinated. Surplus areas were located mainly in the eastern woodlands, and deficit areas were located in the northwestern production agglomeration centers, suggesting that areas of supply-demand imbalance can be mitigated through ecological integration. Among these, water yield (WY) had a small number of sources and sinks and is limited in area range. Habitat quality (HQ) sources and sinks had the largest area coverage and the highest number. The distribution of ESF corridors, influenced by factors such as the number of sources and sinks, flow characteristics, and spatial resistance, varied significantly. HQ exhibited a more uniform distribution range, while WY had a longer average length of flow path. Overlaying ecological and mining factors, we identified ecological strategic spots, important supply areas, beneficiary areas, and mine priority restoration areas to further optimize the overall layout and rationally allocate the intrinsic structure of the patches based on ES supply and demand.

Towards Sustainable Development of Mineral Resources in Sub-Saharan Africa: A Structural Equation Modeling Approach

This study focuses on economic, governmental, social, and environmental factors and their impact on the sustainable development of mineral resources in sub-Saharan Africa. Using structural equation modeling (SEM) and data from 40 countries from 2010 to 2022, the research examines the hypothesized links between these factors and sustainable development. The results reveal a positive and statistically significant relationship between economic factors and sustainable development, underlining the crucial role of economic growth in achieving sustainable development goals. Furthermore, effective governance and policy implementation are strongly associated with better sustainable development, underscoring the importance of robust government action. This study also highlights the importance of social factors, demonstrating that increased community involvement and participation contribute positively to sustainable development. Contrary to the initial hypothesis, the research reveals a positive relationship between environmental factors and sustainable development, challenging existing ideas and suggesting the need for a more nuanced understanding of the interaction between environmental practices and sustainability. This study concludes with concrete recommendations, including prioritizing economic growth, improving governance and policy effectiveness, promoting social inclusion, and reassessing environmental conservation strategies. These findings provide valuable information for policymakers, corporations, and communities in sub-Saharan Africa, thus contributing to a more comprehensive understanding of the dynamics of sustainable development in the region.

Multi-polar group cationic collector HTTPD: Mechanistic insights into selective flotation of bastnaesite

To address the challenge of separating bastnaesite rare earth minerals from gangue minerals, this study independently synthesized a novel multi-polar group cationic surfactant,2,2-bis(hydroxymethyl)-N1,N1,N3,N3-tetramethyl-N1,N3-bis(3-tridecanamidopropyl)propane-1,3-diaminium bromide (HTTPD), as a collector. The flotation results showed that HTTPD could obtain REO grade of 69.71% and recovery of 89.33%, significantly outperforming conventional collectors and proving to be an excellent collector. Density functional theory (DFT) calculation displayed that two quaternary ammonium groups and –NH/OH polar groups were main active sites with strong reactivity. The quaternary ammonium groups of HTTPD strongly adsorbed on the bastnaesite surface through electrostatic attraction, thereby enhancing the flotation selectivity from calcite. The –NH/–OH polar groups adsorbed with bastnaesite by hydrogen bonding interaction. Multi-polar group synergistic adsorption, formed through electrostatic attraction and hydrogen bonding interaction, was the primary mechanism for the efficient separation of bastnaesite and calcite. This research not only provided new insight and theoretical guidance for the design and application of novel collectors but also promoted the efficient development and utilization of rare earth mineral resources.

Research on Predicting the Mechanical Characteristics of Deep-Sea Mining Transportation Pipelines

Deep-sea mining, as a critical direction for the future development of mineral resources, places significant importance on the mechanical characteristics of its transportation pipelines for the safety and efficiency of the entire mining system. This paper establishes a simulation model of the deep-sea mining system based on oceanic environmental loads and the mechanical theory of deep-sea mining transportation pipelines. Through a static analysis, the effective tension along the pipeline length, the maximum values of bending moment, and the minimum values of bending radius are determined as critical points for the dynamic analysis of pipeline mechanical characteristic monitoring. A dynamic simulation analysis of the pipeline’s mechanical characteristics was conducted, and simulation sensor data were obtained as inputs for the prediction model construction. A prediction model of pipeline mechanical characteristics based on the BP neural network was constructed, with the model’s prediction correlation coefficients all exceeding 0.95, enabling an accurate prediction of pipeline state parameters.

Study on spatio-temporal evolution of ecosystem services, spatio-temporal pattern of tradeoff/synergy relationship and its driving factors in Shendong mining area

Objectives: The game between socio-economic development and ecological development has always been the core issue in coal areas, but the internal mechanism of tradeoff and cooperative dynamic change of ecosystem services in mining areas under long-term mineral resources development is still lacking in in-depth research.Methods: Therefore, taking Shendong mining area as an example, this study used InVEST model to evaluate the changes of four major ecosystem service functions in Shendong mining area from 1990 to 2020, namely, water yield (WY), net primary productivity (NPP), soil conservation (SC) and habitat quality (HQ). Meanwhile, correlation analysis was used to explore the trade-off and synergistic relationship among these services. On this basis, the coupling effect between the four ecosystem services is further discussed by using the constraint line method. Finally, the key drivers of ecosystem service trade-offs/synergies in the region are explored by using geodetectors and the explanations of each influence factor for RMS errors are obtained.Results: The results show that 1) from 1990 to 2020, the water yield and soil retention in the mining area decrease first and then increase, and the net primary productivity and habitat quality increase slowly, mainly in the southeast of the mining area. 2) In terms of constraint relationship, all the four ecosystem services showed hump-like constraint relationship, that is, there was obvious constraint threshold effect. 3) In the Shendong mining area, the synergistic relationship is the dominant relationship between ecosystem services, and the tradeoff effect mainly occurs between water yield and habitat quality. 4) In terms of the driving mechanism of tradeoff/synergy, land use type, temperature, and rainfall are the main factors that cause the spatial differentiation of tradeoff synergy intensity among ecosystem services in Shendong mining area.Conclusions: The results of this study provide a scientific basis for the improvement of ecological environment and sustainable utilization of mineral resources under long-term exploitation.

Open-Pit Mining Area Extraction Using Multispectral Remote Sensing Images: A Deep Learning Extraction Method Based on Transformer

In the era of remote sensing big data, the intelligent interpretation of remote sensing images is a key technology for mining the value of remote sensing big data and promoting a number of major applications, mainly including land cover classification and extraction. Among these, the rapid extraction of open-pit mining areas plays a vital role in current practices for refined mineral resources development and management and ecological–environmental protection in China. However, existing methods are not accurate enough for classification, not fine enough for boundary extraction, and poor in terms of multi-scale adaptation. To address these issues, we propose a new semantic segmentation model based on Transformer, which is called Segmentation for Mine—SegMine—and consists of a Vision Transformer-based encoder and a lightweight attention mask decoder. The experimental results show that SegMine enhances the network’s ability to obtain local spatial detail information and improves the problem of disappearing small-scale object features and insufficient information expression. It also better preserves the boundary details of open-pit mining areas. Using the metrics of mIoU, precision, recall, and dice, experimental areas were selected for comparative analysis, and the results show that the new method is significantly better than six other existing major Transformer variants.

Research Progress of Advanced Design Method, Numerical Simulation, and Experimental Technology of Pumps in Deep-Sea Resource Exploitation

Amid the escalating global demand for raw materials, the gradual exhaustion of terrestrial mineral resources, and the rise in extraction costs and energy consumption, the development of deep-sea mineral resources has become a focal point of international interest. The pipeline lifting mining system, distinguished by its superior mining efficiency and minimized environmental impact, now accounts for over 50% of the total energy consumption in mining operations. Serving as the “heart” of this system, the deep-sea lifting pump’s comprehensive performance (high pressure tolerance, non-clogging features, elevated lift capacity, wear resistance, corrosion resistance, and high reliability, etc.), is critical to transport efficiency, operational stability, and lifespan of the mining system. As a mixed transport pump for solid and liquid media under extreme conditions, its internal flow structure is exceedingly complex, incorporating gas–liquid–solid multiphase flow. A precise understanding of its internal flow mechanisms is essential for breaking through the design limitations of deep-sea lifting pumps and enhancing their operational stability and reliability under various working conditions and multiphase media, thereby providing technical support for advancing global marine resource development and offshore equipment upgrades. This paper comprehensively reviews the design theory, optimization methods, numerical simulations, and experimental studies of deep-sea lifting pumps. It discusses the application of various design optimization techniques in hydraulic lifting pumps, details the multiphase flow numerical algorithms commonly used in deep-sea lifting pumps along with their modified models, and summarizes some experimental methodologies in this field. Lastly, it outlines the forthcoming challenges in deep-sea lifting pump research and proposes potential directions to promote the commercial development of deep-sea mining, thereby offering theoretical and engineering support for the development of deep-sea mining slurry pumps.

Experimental study on coagulation and adsorption treatment of wastewater in combustion cavity for underground coal gasification

Underground Coal Gasification (UCG) is a promising mineral resource development technology that can transform in-situ coal into combustible gas by controlling combustion. However, wastewater generated during the UCG process can lead to environmental pollution in adjacent areas through diffusion or infiltration. In order to seek an efficient and inexpensive in-situ treatment method for underground gasification combustion zone wastewater, UCG model experiments were conducted to obtain wastewater, and the treatment effects of chemical coagulation and physical adsorption methods were compared in this work. The COD concentration in wastewater from underground combustion zone ranges between 555 ∼ 703 mg/L, with a pH value between 8.26 ∼ 8.85. The organic pollutants mainly come from the dissolution of high carbon components, mainly aromatic compounds in tar, which leads to high toxicity and pollution risk of wastewater. For chemical coagulation method, the removal effect of organic pollutants in combustion zone wastewater by ferric sulfate is better than that of aluminum sulfate due to excellent hydrolysis reaction of Fe3+. The corresponding COD removal rate and COD removal cost are 24.34 % and 0.176 ¥/g, respectively. For physical adsorption method, due to the large total pore volume and wide specific surface area of organic bentonite, it can effectively remove COD content. The COD removal rate and COD removal cost, and COD adsorption capacity are 60.23 %, 0.213 ¥/g, and 89.75 mg/g, respectively. Comprehensive comparison shows that physical adsorption is more suitable for in-situ treatment of combustion zone wastewater.