Deep-sea Manganese Nodules Research Articles

Grabbing Path Extraction of Deep-Sea Manganese Nodules Based on Improved YOLOv5

In an effort to enhance the efficiency and accuracy of deep-sea manganese nodule grasping behavior by a manipulator, a novel approach employing an improved YOLOv5 algorithm is proposed for the extraction of the shortest paths to manganese nodules targeted by the manipulator. The loss function of YOLOv5s has been improved by integrating a dual loss function that combines IoU and NWD, resulting in better accuracy for loss calculations across different target sizes. Additionally, substituting the initial C3 module in the network backbone with a C2f module is intended to improve the flow of gradient information while reducing computational demands. Once the geometric center of the manganese nodules is identified with the improved YOLOv5 algorithm, the next step involves planning the most efficient route for the manipulator to pick up the nodules using an upgraded elite strategy ant colony algorithm. Enhancements to the ACO algorithm consist of implementing an elite strategy and progressively decreasing the number of ants in each round. This method reduces both the number of iterations and the time required for each iteration, while also preventing the occurrence of local optimal solutions. The experimental findings indicate that the improved YOLOv5s detection algorithm boosts detection accuracy by 2.3%. Furthermore, when there are fewer than 30 target planning points, the improved algorithm requires, on average, 24% fewer iterations than the ACO algorithm to determine the shortest path. Additionally, the speed of calculation for each iteration is quicker while still providing the optimal solution.

Effects of operating parameters and particle friction on water usage of deep-sea manganese nodules hydraulic conveying equipment

One of the primary concerns for commercialising deep-sea mining is the environmental impact associated with the pumping seawater. Therefore, this study developed an unresolved coupled model of Computational Fluid Dynamics - Discrete Element Method (CFD-DEM) to explore water usage under various operating conditions. The model was validated by experimental results from previous research. The study specifically focused on examining the effects of particle friction on the particle output rate and water usage. The results indicated that to minimise the usage of seawater, the injecting speed should be set at a relatively high value to achieve a high discharge rate, such as 3 m/s in this work. The injecting speed for large particles can be set lower than that for small particles. It is recommended to set the pumping flow rate at a relatively low value, as long as it can generate enough lift force to transport the particles.

New insights on the Jacobsite mineral from Bahia and related synthetic manganese-ferrite nanoparticles.

Jacobsite is a relatively rare mineral of composition MnFe2O4, found in Urandi (Bahia State) in Brazil. It is also a common species in the deep-sea manganese nodules, attracting the interest of many mineral-extracting companies. Because of its spinel constitution similar to magnetite, Jacobsite is commonly called a manganese-ferrite. However, the manganese/iron content may vary substantially according to its origin, demanding specific studies in each case. The Jacobsite mineral inspired our laboratory synthesis of the analogous manganese ferrite nanoparticles. The direct synthesis by the coprecipitation method has not been successful; however, it can be carried in the presence of citrate ions, yielding strongly magnetic nanoparticles, with a maximum magnetization of 45.6 emu.g1. Although they were structurally identical to Jacobsite, the mineral from Bahia exhibited a rather weak magnetism, because it involves a ferrimagnetic coupling. For this reason, the synthetic method seems to provide a better way of obtaining strongly magnetic manganese ferrites. These magnetic nanoparticles have been investigated in detail, including their interaction with diatoms, providing interesting magnetic bio-silicate carriers in drug delivery.

Research on path planning of autonomous manganese nodule mining vehicle based on lifting mining system.

Deep-sea manganese nodules are abundant in the ocean, with high exploitation potential and commercial value, and have become mineral resources that coastal countries compete to develop. The pipeline-lifting mining system is the most promising deep-sea mining system at present. A deep-sea mining vehicle is the core equipment of this system. Mining quality and efficiency rely on mining vehicles to a great extent. According to the topographic and geomorphic environmental characteristics of deep-sea manganese nodules at the bottom of the ocean, a new deep-sea mining system based on an autonomous manganese nodule mining vehicle is proposed in this paper. According to the operating environment and functional requirements of the seabed, a new mining method is proposed, and the global traverse path planning research of the autonomous manganese nodule mining vehicle based on this mining method is carried out. The arc round-trip acquisition path planning method is put forward, and the simulation verification shows that the method effectively solves the problems of low efficiency of mining vehicle traversing acquisition and obstacle avoidance.

Life cycle impact on climate change caused by metal production from deep sea manganese nodules versus land-based deposits

At the "UN Climate Change Conference" (COP27), France called for a ban on deep sea mining. The topic has gained momentum over the last years as some businesspeople and politicians are promoting the mining of manganese nodules as a less CO2-intensive way to meet the rising demand for the battery metals nickel, copper, cobalt and manganese. In this study, we modelled the impact on climate change caused by metal production from manganese nodules vs. mining on land. The total climate impact of producing these metals from manganese nodules (∼2.0 kg CO2eq/kg dry nodules) compared to current land-based projects is about 27% lower. Comparing it to values reported in the literature by industry associations and by the ecoinvent database, the climate impact from manganese nodules is about 16% lower or 28% higher, respectively. Based on their monetary values, the allocation of the total climate impact to each metal assigns the highest contribution to FeMn. Our research shows that producing Ni, Cu, Co and FeMn from manganese nodules could lead to higher or lower impact on climate change depending on the model input data and methodological choices. The authors share the opinion that climate change should not be the central argument regarding the realization of manganese nodule projects. The discussion should instead explicitly include further environmental impacts, e.g., biodiversity or plumes as well as economic considerations.

An Application of Hyperspectral Image Clustering Based on Texture-Aware Superpixel Technique in Deep Sea

This paper aims to study the application of hyperspectral technology in the classification of deep-sea manganese nodules. Considering the spectral spatial variation of hyperspectral images, the difficulty of label acquisition, and the inability to guarantee stable illumination in deep-sea environments. This paper proposes a local binary pattern manifold superpixel-based fuzzy clustering method (LMSLIC-FCM). Firstly, we introduce a uniform local binary pattern (ULBP) to design a superpixel algorithm (LMSLIC) that is insensitive to illumination and has texture perception. Secondly, the weighted feature and the mean feature are fused as the representative features of superpixels. Finally, it is fused with fuzzy clustering method (FCM) to obtain a superpixel-based clustering algorithm LMSLIC-FCM. To verify the feasibility of LMSLIC-FCM on deep-sea manganese nodule data, the experiments were conducted on three different types of manganese nodule data. The average identification rate of LMSLIC-FCM reached 83.8%, and the average true positive rate reached 93.3%, which was preferable to the previous algorithms. Therefore, LMSLIC-FCM is effective in the classification of manganese nodules.

Research on contact model of track-soft sediment and traction performance of four-tracked seabed mining vehicle

In response to the global demand for commercial mining of deep-sea manganese nodules, the four-tracked mining vehicle (FTMV) with excellent tractive and travelling performance is crucial for constructing the entire commercial system. In order to better evaluate the tractive and travelling performance of the FTMV, the dynamic sinkage phenomenon concerning soft seabed and front-rear track effect are proposed. Meanwhile, the pressure-sinkage and traction force-slip rate mathematical models are established based on terramechanics theory. The quantitative calculation was carried out based on the model and found that the grouser's parameters affect the sinkage depth of the FTMV. In the range of 10 ~ 20 cm, the height of the rectangular grouser increases by 1 cm, which will lead to a 0.15 cm of sinkage depth decreased. When the ratio of rectangular grouser thickness to track shoe length is between 0.1 and 0.3, every 1% increase in this ratio will decrease a 0.13 cm of sinkage depth. The maximum traction force obtained by the FTMV from the soft seabed sediment was 54.5 kN, which occurred when the slip rate of the track was 16%. Moreover, due to the front-rear track effect, the traction force of the front and rear tracks showed a significant difference, the front track contributed 32.4 kN, and the rear track contributed 22.1 kN when the traction force reached the peak. Furthermore, the optimization directions for track parameters were suggested according to the relationship surface of the track dimensional parameters-slip-traction. It was found that each track was 4.2 ~ 6 m long, with a length-width ratio of 3.2, which was conducive to the reduction of track slip and got relatively much traction force from soft seabed sediment. The simulation results confirm dynamic sinkage and front-rear track effect and verify the accuracy of the new traction force-slip rate model, providing a valuable reference for the development of commercial deep-sea mining vehicles.

Corrosion Properties of Mn-Based Alloys Obtained by Aluminothermic Reduction of Deep-Sea Nodules.

Deep-sea manganese nodules are polymetallic oxidic ores that can be found on a seabed. Aluminothermic reduction is one of the possibilities of manganese nodules processing. This process obtains the polymetallic alloy with a high content of Mn and a varying content of Al, depending on the ratio between aluminum and nodules. The corrosion behaviors of three experimental Mn-based alloys produced by aluminothermic reduction with a content of Mn > 50 wt % were studied. The electrochemical testing in potable water and model seawater was used to explain the corrosion mechanism of Mn-based alloys. The results showed that the corrosion rate of experimental Mn-based alloy decreases with the increase in aluminum content in both potable water and model seawater. It was observed that the uniform corrosion of experimental Mn-based alloys is changed with an increase in aluminum content in alloy to localized corrosion, which was caused by microcells in an environment of model seawater. In contrast, the formation of a semi-protective layer of corrosion products was observed on the surface of Mn-based alloys with a higher content of aluminum in potable water. Moreover, the pitting corrosion of tested Mn-based alloys was observed neither in potable water nor in model seawater.

Aluminum Alloys with the Addition of Reduced Deep-Sea Nodules

An innovative way to utilize deep-sea manganese nodules is described in this paper. The manganese nodules were reduced by aluminothermy and subsequently added into aluminum as a mixture of alloying elements in their natural ratio. The microstructure and properties of aluminum alloys containing 1.2, 7.7, and 9.7 wt % of reduced nodules were studied. The alloys were formed by Al matrix and minor amounts of Al6(Fe,Mn) and Al11Fe7 intermetallic phases. The alloys containing a higher amount of reduced nodules are characterized by very good thermal stability. The obtained alloys were studied by X-ray diffraction, their microstructure was observed by scanning electron microscopy, and their local chemical composition was analyzed by energy dispersive spectrometer. The hardness of the samples was measured on the initial materials and after long-term annealing. Based on the obtained results, the aluminum alloys, with the addition of reduced deep-sea nodules, can serve as precursors for processing, e.g., by rapid solidification or hot working methods.

Identification of marginal and joint CDFs using bivariate type I interval multiply censored data for RBDO of a pick-up device of a pilot mining robot

In this paper, joint probability distribution for the size and mass of deep-sea manganese nodules is investigated and reliability-based design optimization (RBDO) of a deep-sea pilot mining robot is performed. As the size and mass of the manganese nodules are strongly correlated and their data are given as bivariate type I interval multiply censored data, a new statistical modeling method should be developed to deal with these issues. However, this is significantly difficult as the conventional methods cannot resolve these issues and there is no prior knowledge of the two physical properties. The proposed method, which employs the multinomial distribution to define the likelihood function and the Akaike information criterion to select the fittest marginal distribution and copula, provides a systematic approach to find the joint probability distribution using the type I interval multiply censored data. To demonstrate the accuracy and effectiveness of the proposed method, two numerical examples are tested. Then, the RBDO of the pilot mining robot is performed using the joint probability distribution resulted from the proposed method.

Using multibeam backscatter strength to analyze the distribution of manganese nodules: A case study of seamounts in the Western Pacific Ocean

Multibeam backscatter strength can be used to characterize seafloor acoustic characteristics, and classify seabed substrate types. Herein, we use acoustic reflectance data to examine the distribution of manganese nodules in deep-sea substrates in a seamount region of the Western Pacific Ocean. Based on the multibeam backscatter strength, the backscatter mosaic image is firstly corrected by a series of error corrections, and then a size-insensitive integrity-based Fuzzy C-Means (siib-FCM) technique is used to analyze the distribution of manganese nodules. The results show that the method can reveal the distribution of deep-sea manganese nodules and is suitable for the classification of seabed substrates with few sampling points. The distribution of manganese nodules has two characteristics: (1) In basin and plain areas with relatively flat terrain, manganese nodules are associated with sediment, occur in patches and their distribution is relatively sparse. (2) In seamount areas with complex terrain, manganese crusts are distributed mainly at mid-slope elevations displaying a circular distribution around the seamount. The processing technique and results of the present study form a basis for future investigations into the occurrence and distribution of manganese nodule resources in the deep oceans.

Removal of Heavy Metals Using Rhamnolipid Biosurfactant on Manganese Nodules

The objective of this study is to identify the feasibility of using rhamnolipid biosurfactant to remediate heavy metals contained in manganese nodules collected from the Clarion-Clipperton Fracture Zone, Pacific Ocean. Deep-sea manganese nodules may represent one of the most important future natural resources for heavy metals due to the depletion of resources on land. Since international marine environment guidelines for deep-sea mining will be set up by international organisations in the 2020s, remediation technologies are urgently required for deep-sea mining tailings. We show that rhamnolipid biosurfactant is an environmentally friendly substance and can be successfully used for the remediation of heavy metals in deep-sea mining tailings under various reaction conditions. Rhamnolipids therefore represent a useful extracting agent for heavy metals in deep-sea mining tailings. The removal of nickel (Ni), copper (Cu), and cadmium (Cd) would be enhanced in the presence of rhamnolipids with specific reaction times and concentrations. Future actual remediation technologies should be developed using rhamnolipid biosurfactant on the basis of these results.

The economics of mining seabed manganese nodules: A case study of the Indian Ocean nodule field

Because of ever-growing demand for strategic metals, the focus of the international community has fallen on deep sea manganese nodules occurring at a water depth of more than 4500 m. We present an economic appraisal and strategy for mining of nodules from the Indian Ocean Nodule Field- one of the four economically potential areas in the world oceans. In contrast to the prevailing perception of non-viability of nodule mining, our analysis indicates a fair degree of economic feasibility and commercial sustainability to mine the deep-sea manganese nodules.

Probability distribution for size and mass of a nodule in the KR5 area for the development of a manganese nodule miner

In this paper, probability distribution for the size and mass of seafloor manganese nodules is investigated to improve the reliability of a pick-up device in a deep-sea manganese nodule miner. Because the size and mass of the manganese nodules are strongly correlated, statistical models for the size and mass cannot be estimated independently. In order to consider the correlation between the size and mass in a statistical model, the joint probability density function (PDF) is estimated by using copula. This method requires the estimation of the marginal distributions and copula for the two correlated environmental variables. However, this is significantly difficult when there is no prior knowledge of the two physical properties. The proposed method, which employs the Akaike information criterion to select the fittest marginal distributions and copula, provides a systematic procedure to determine a statistical model of correlated environmental variables without any prior knowledge of their distributions. To demonstrate the effectiveness of the proposed method, the joint PDF for the size and mass of manganese nodules is modeled by using the multivariate normal distribution and the proposed method. It was found that the proposed method provides more accurate and reliable estimation results for the two correlated environmental variables.

Use of Industrial Waste (Al-Dross, Red Mud, Mill Scale) as Fluxing Agents in the Sulfurization of Fe-Ni-Cu-Co Alloy by Carbothermic Reduction of Calcium Sulfate

The use of industrial waste [mill scale (MS), red mud (RM), Al-dross (AD)] as fluxing agents in the sulfurization of Fe-Ni-Cu-Co alloy to matte (Fe-Ni-Cu-Co-S) by carbothermic reduction of CaSO4 was investigated at 1673 K (1400 °C). The sulfurization efficiency (SE) was 76 (± 2) pct at RM or AD single fluxing. However, SE drastically increased to approximately 89 pct at a ‘5AD + 5MS’ combination, which was equivalent to reagent-grade chemical ‘5Al2O3 + 5Fe2O3’ fluxing (SE = 88 pct). The present results can be used to improve the cost-effective recovery of rare metals (Ni and Co) from deep sea manganese nodules.

The Flow Analysis of Buffer System in Lifting System of Deep-sea Manganese Nodules

The Flow Analysis of Buffer System in Lifting System of Deep-sea Manganese Nodules

Species diversity of dinophysoid dinoflagellates in the Clarion–Clipperton Fracture Zone, eastern Pacific

Species diversity of dinophysoid dinoflagellates is especially high in subtropical and tropical oceans. Only a few studies about the diversity of these dinoflagellates exist from the eastern Pacific. The offshore, subtropical Clarion–Clipperton Fracture Zone (CCZ), in the eastern part of the Pacific between Mexico and Hawaii, is an area of interest for deep sea manganese nodule mining. Therefore, geological research is ongoing, but also biodiversity research from the deep sea up to the surface is of importance. This study adds to the biodiversity knowledge by describing dinophysoid dinoflagellates in the area for the first time. Phytoplankton samples were collected during two cruises to the CCZ, MANGAN 2013 (April and May 2013) and ABYSSLINE AB01 (October 2013), and investigated morphologically. Sixty-six species of dinophysoid dinoflagellates were found and documented by light and scanning electron microscopy. These species belonged to 11 genera: Amphisolenia F.Stein (9), Citharistes F.Stein (1), Dinophysis Ehrenb. (15), Histioneis F.Stein (8), Latifascia sp. (1), Metaphalacroma L.S.Tai (1), Parahistioneis Kof. & Skogsb. (3), Phalacroma F.Stein (16), Pseudophalacroma Jorg. (2), Ornithocercus F.Stein (9) and Triposolenia Kof. (1). Seven of the taxa, Amphisolenia sp. 1 and 2, Phalacroma sp. 1, Dinophysis sp. 1, Pseudophalacroma sp. 1, Histioneis spec. and cf. Latifascia spec., could be identified only to the genus level and may represent new species. This diversity was unexpected compared to the available open ocean records for the eastern Pacific (14 species, four genera). Almost half the number of species recorded before in the eastern Pacific (including coastal samples) was observed, corresponding to about one-fifth of the known dinophysoid diversity.

Sulfurization of Fe-Ni-Cu-Co Alloy to Matte Phase by Carbothermic Reduction of Calcium Sulfate

Calcium sulfate (CaSO4) is proposed as an alternative sulfur source to convert the Fe-Ni-Cu-Co alloy to the matte phase. Solid carbon was used as a reducing agent and the influence of oxide fluxes on the sulfurization efficiency at 1673 K (1400 °C) in a CO-CO2-SO2-Ar atmosphere was investigated. When CaSO4 was equilibrated with the Fe-Ni-Cu-Co alloy without any reducing agent, it was reduced by Fe in the liquid alloy, resulting in the formation of FeS. The sulfurization efficiency was about 56 pct, even though an excess amount of CaSO4 (gypsum equivalent, G eq = 1.7) was added. Adding solid carbon as the reducing agent significantly shortened the equilibration time from 36 to 3.5 hours and increased the sulfurization efficiency from 56 to 91 pct, even though the amount of carbon was lower than the theoretical equivalent for carbothermic reduction of CaSO4, viz. C eq = 0.7. Although CaS (not FeS) was formed as a primary reaction product, it continuously reacted with CaSO4, forming CaO-rich slag. Neither the carbothermic reduction time nor the sulfurization efficiency were affected by the addition of Al2O3 (-SiO2) fluxes, but the equilibration time fell to 2.5 hours with the addition of Al2O3-Fe2O3 flux because the former systems produced primarily calcium silicate and calcium aluminate, which have relatively high melting points, whereas the latter system produced calcium ferrite, which has a lower melting point. Consequently, calcium sulfate (waste gypsum) can replace expensive pure sulfur as a raw material in the sulfurization of Fe-Ni-Cu-Co alloy with small amounts of iron oxide (Fe2O3) as a flux material. The present results can be used to improve the recovery of rare metals, such as Ni and Co, from deep sea manganese nodules.

중도절단 해류속도자료를 이용한 심해저 시험집광기의 주행성능에 관한 신뢰성 기반 최적설계

Deep-seabed test miner operated by a self-propelled mining system moving on soft soil is an essential device to secure floating and towing performances. The performances of the tracked vehicle are seriously influenced by noise factors such as the shear strength of the seafloor, bottom current, seafloor slope, speed of tracked vehicle, reaction forces of flexible hose, steering ratio, etc. Due to uncertainties related to noise factors, the design of a deep-sea manganese nodules test miner that satisfies target reliabilities is difficult. Therefore, reliability-based design optimization (RBDO) is required to guarantee system reliability under circumstances where uncertainties related to noise factors prevail. Among noise factors, the bottom current, a bimodal distribution, is censored due to the observation limit of measurement devices. Therefore, estimated distribution of the bottom current is inaccurate without considering these characteristics and the result of RBDO cannot be guaranteed. In this paper, we define censored data as unknown values over the limit of observation. If this data is estimated by using Akaike information criterion (AIC) that cannot consider the characteristics of censored data, the distribution of estimated data cannot guarantee accurate reliability. Therefore, censored AIC that can consider the characteristics of data is used to estimate accurate distribution of the bottom current. Finally, RBDO, under circumstances where uncertainties related to noise factors combined censored data are present, is performed on the mobility of a deep-sea manganese nodules test miner.

Deep-Sea Nodules and Co-rich Mn Crusts

The mining of deep-sea manganese nodules has been a topic of interest since J.L. Mero undertook his preliminary studies in the 1960s to evaluate the prospects for mining deep-sea nodules. Despite the great deal of investment in deep-sea mining over more than 40 years, there has still been no successful attempt to mine the deep-sea nodules on a commercial scale. One of the major problems is that the nodules cannot be brought to the surface with the necessary amounts of recoverable nickel, cobalt and zinc to warrant the initial high investment necessary for this operation. It therefore appears that in the short term, deep-sea manganese and Co-rich Mn crusts will not be mined on a commercial scale in the foreseeable future. Nonetheless, investigations of deep-sea mineral deposits by a number of nations will continue and enable us to understand the deep-sea environment in increasing detail, which is necessary in view of the great extent of the deep oceans which cover an area of about 66% of the Earth's surface.