Real Metal Research Articles

A new outlier rejection approach for non-Lambertian photometric stereo

Photometric stereo (PS) has garnered increasing attention due to its adeptness in restoring local fine textures. However, non-Lambertian reflections present in almost all real-world objects limit the effectiveness of the Lambertian model for surface normal vector estimation. Although BRDF-based and deep learning-based methods have become mainstream, recent research shows that comparable accuracy can also be achieved through simple filtering of observed intensity values. Nevertheless, these methods only consider the relative bias of pixel values and require manual specification of the number of pixels to be culled and the number of iterations. To address these issues, this paper proposes corresponding improvement methods. Firstly, a weighted inter-relationship function (IRF) fused with Huber loss is introduced to robustly and effectively evaluate the abnormal degree of pixel value. Secondly, based on the IRF curve and histogram statistical analysis, the number of excluded pixels is adaptively calculated. Thirdly, linear equations are then constructed based on the photometric equations, and the maximum between-class variance method is employed to achieve a high degree of sparsity, enabling fast and effective normal vector estimation. Finally, to verify the effectiveness of the proposed algorithm for non-Lambertian PS vision, quantitative verification tests on the synthetic dataset and the open-source datasets “DiLiGenT” and “DiLiGenT-PI” in real-world scenarios, and qualitative assessment experiments on real metal roughness samples are conducted. The experimental results demonstrate that, compared with the position threshold and IRF methods, our algorithms not only significantly enhance the accuracy of normal vector solutions but also markedly improve the operational efficiency of the algorithm, laying a solid foundation for practical online applications. These results fully validate the correctness and effectiveness of the proposed algorithm and provide a reference for the further development of outlier removal algorithms.

Determination of trace analytes in nuclear grade Calcium Metal Samples by Axially Viewed Inductively Coupled Plasma – Atomic Emission Spectrometric technique

An Inductively Coupled Plasma – Atomic Emission Spectrometric (ICP-AES) method has been developed for the direct determination of 19 analytes namely, Al, B, Be, Cd, Co, Cr, Cu, Fe, Li, Mg, Mo, Mn, Ni, Pb, Pd, Si, Ta, V and W at trace concentration levels in calcium matrix. In nuclear industry, quality control and assurance of nuclear fuels and associated materials for trace metallic impurity contents form an integral part of the system for the smooth functioning of the reactor for the stipulated time span. In this context, it was required to determine trace analytes in nuclear grade Calcium which is used as a reducing agent for the production of U, Th, Pu, etc. in nuclear industry. Using axial ICP-AES, initially calibration curve for Ca with 396.847nm analytical line was obtained. Systematic studies were carried out to identify various analytical wavelengths of the analyte elements which are almost free from Ca, being the main matrix and calibration curves were obtained. For all analytes and Ca, detection limits and sensitivity values were calculated. To validate the method, three synthetic samples with analyte contents in the range of 0.1 - 5 g/mL and Ca at 1 mg/mL were analyzed, the % recovery being in the range of 80-120% with precision better than 5% RSD. The method was found to be useful for the direct determination of the elements of interest in calcium matrix and was applied for the analysis of two nuclear grade real life calcium metal samples.

Deep eutectic solvent microemulsions with abundant hydrogen ions in supercritical CO2 for decontamination of radioactive solid waste: Overcoming roadblocks to hydrogen ions deficiency

Deep eutectic solvents (DESs) dispersed in supercritical CO2 (SC-CO2) as microemulsions have shown promise for the removal of radioactive contaminants from solid surfaces. However, the current technology needs urgent improvement in terms of decontamination performance. This study reported a novel strategy to enhance the decontamination ability of DESs-in-CO2 systems by adding hydrogen ion (H+) supplemental reagents. The type and acidity of the added H+ reagents were found to be critical factors in dictating the decontamination performance. For instance, fluorinated carboxylic acids with higher acidity and higher CO2 affinity were more competitive for decontamination compared to other non-fluorinated carboxylic acids. Additionally, when nitric acid was used as the H+ supplemental reagent for microemulsions in SC-CO2, outstanding decontamination results were achieved. It could remove 99 % of UO3 contaminants on the specimen surfaces. The formation of microemulsions was demonstrated by molecular dynamics (MD) simulations. Meanwhile, low-cost nitric acid was more promising for scale-up applications. Remarkably, the versatility of the decontamination technology with the addition of nitric acid was demonstrated by its ability to completely decontaminate multiple radioactive wastes made of various materials, as well as different simulated radionuclides. Decontamination efficiency reached more than 99.0 %. More importantly, the DESs-in-CO2 systems with nitric acid also reduced the radioactivity of real radioactive metal waste to the clearance level with the decontamination efficiency reaching 99.0 %. Overall, this study provided valuable insights into the design of advanced decontamination technologies based on microemulsions of DESs in SC-CO2 and opened new avenues for the sustainable management of radioactive waste.

First tungsten radiation studies in DIII-D’s ITER baseline demonstration discharges

ITER Baseline Scenario plasmas were studied in DIII-D using krypton and xenon gases as a proxy for the tungsten that will be present in ITER. These impurities were chosen for having the same radiative loss rate Lz as tungsten would exhibit in the hotter ITER core. Results show that the scenario with these core radiators spans the range of impurity concentration and W radiated fraction expected for ITER, and up to 50% higher values, explored at zero injected torque, as well as 1 Nm and full co-torque injection with T ∼ 3 Nm. Stationary discharges with duration >2–4 τR are achieved with f rad ⩾ 30% leading to a reduction in confinement of ∼10%, and a comparison with real metal radiators in the same range of f rad shows that the higher Lz at the lower temperatures in these plasmas yields too pessimistic results on the survivability and performance of this scenario in ITER. Simulations of ITER power balance including W radiation show that with concentration up to three times higher than in the DIII-D plasmas the scenario can be stationary, remaining at acceptable core radiated fraction values.

Innovative deep decontamination of radioactive solid surfaces using microemulsions of deep eutectic solvents in supercritical carbon dioxide

Radioactive solid wastes resulting from the application of nuclear energy pose a risk to the environment, yet traditional decontamination methods generate many secondary wastes. Thus, sustainability-driven innovations are receiving increasing attention to achieve eco-friendly decontamination methods characterized by minimizing secondary waste generation. Here, we proposed a sustainable and pioneering approach to decontaminate radioactive solid wastes using microemulsions of deep eutectic solvents (DESs) in supercritical carbon dioxide (SC-CO2). We also determined the optimal ratios of the additives as follows: prepared DESs with a molar ratio of choline chloride (ChCl) to p-toluenesulfonic acid monohydrate (ptsa) of 1:2, and nonyl phenol polyoxyethylene ether (NP-10) to ChCl:ptsa DESs in a molar ratio of 0.8. Remarkably, after optimization of the decontamination process in terms of pressure, temperature and cleaning time, the radioactivity on the sample surface can be reduced to a level that is reusable in the nuclear field. Detailed analyses provided insights into the intermolecular interactions within the DESs. And the decontamination mechanisms involved the spontaneous evolution of microemulsions with ChCl:ptsa as the core to facilitate the solvation and removal of radioactive contaminants. Additionally, repeated cleaning was proved to be effective for ultra-deep decontamination, with the radioactivity on the sample surface reaching a clearance level and a decontamination efficiency of 99.8%. The DESs-in-CO2 systems successfully decontaminated various materials and simulated radionuclides, even real radioactive metal wastes from the nuclear industry. It was notable that the DESs-in-CO2 systems achieved decontamination efficiencies of more than 95.0% for radioactive contaminants on these solid surfaces. Overall, this innovative approach provided a green alternative to conventional radioactive solids decontamination, meeting the need for sustainable development of nuclear energy.

Forced convective heat transfer performance of foam-like structures – comparison of the Weaire-Phelan and the Kelvin structures with real metal foam

Real foam and foam-liked structures have been widely used in the field of flow and heat transfer but whether foam-like structures can be used as an alternative to metal foams for forced convective heat transfer needs to be further investigated. In this study, three foam structures (Weaire-Phelan, Kelvin and metal foam) were compared by simulation under turbulent conditions and the flow heat transfer characteristics have been evaluated. The 3D models of the two foam-liked structures were constructed using CAD software and the 3D model of the metal foam was scanned and reconstructed using CT. All three structures were constrained by the same pore size parameters. The results reveal that neither the Weaire-Phelan structure nor the Kelvin structure can serve as a substitute model for the real metal foam. The Weaire-Phelan structure demonstrates the best effective overall heat transfer performance (OHTP) while the Kelvin structure exhibits the worst. With an inlet velocity of 10 m/s, the area goodness factor (j/f) of the Weaire-Phelan structure is similar to the metal foam structure which is 12.3 % higher than that of the Kelvin structure. With an inlet velocity of 25 m/s, the j/f value of the metal foam structure becomes comparable to that of the Kelvin structure. However, the j/f value of the Weaire-Phelan structure exhibits 12.18% higher than the other two structures.

Can rare earth elements be recovered from abandoned mine tailings by means of electrokinetic-assisted phytoextraction?

Given the high impact of traditional mining, the recovery of rare earth elements (REEs) from hazardous waste materials could become an option for the future in accordance with the principles of the circular economy. In this work, the technical feasibility of REEs recovery from metal mine tailings has been explored using electrokinetic-assisted phytoremediation with ryegrass (Lolium perenne L.). Phytoextraction combined with both AC current and DC current with reversal polarity was applied (1 V cm−1, 8 h day−1) to real mine tailings containing a total concentration of REEs (Sc, Y, La, Ce, Pr, and Nd) of around 146 mg kg−1. Changes in REEs geochemical fractionation and their concentrations in the soil pore water showed the mobilization of REEs caused by plants and electric current; REE availability was increased to a higher extent for combined electrokinetic-assisted phytoextraction treatments showing the relevant role of plants in the process. Our results demonstrated the initial hypothesis that it is feasible to recover REEs from real metal mining waste by phytoextraction and that the performance of this technology can be significantly improved by applying electric current, especially of the AC type, which increased REE accumulation in ryegrass in the range 57–68% as compared to that of the treatment without electric field application.

A semantic model-based systems engineering approach for assessing the operational performance of metal forming process

Metal Forming is a basic and essential industrial process to provide materials for constructing complex products. To design an efficient metal forming process, the functional requirements and operational performance are two important aspects to be considered. In this paper, a semantic Model-based Systems Engineering (sMBSE) approach is proposed to support the design of the entire metal forming process. A multi-architecture modeling language KARMA is used to develop meta-models and architecture models of the metal forming process from the perspectives of mission, operation, function, logic flow and physical structure. Enabled by customized software, the KARMA models are transformed to ontology models, which are then converted to Petri Net (PN) models. Simulations are conducted based on the PN models to evaluate the operational performance of the created processes. A case study based on a real metal forming scenario is conducted to evaluate the proposed approach using quantitative and qualitative analysis. The result proves that the proposed approach enables to formalize the entire architecture modeling for metal forming process; and to provide an efficient approach for evaluating the operational performance of the designed solution for initial verification.

Implementing new Approaches of Digitization in Conventional Metal Forming Processes: A German perspective

The Institute for Metal Forming Technology (IFU) at the University of Stuttgart / Germany since more than six years strongly strives to future oriented research work focusing on far-reaching concepts for digitization of metal forming processes. Main activities of engaged research groups are integrating sensors and actuators into metal forming machines or dies to analyse process data gained that way. Also, development of advanced methods for production data mining are related to those fields of activities. The paper therefore highlights strategies and practical applications of such digitization concepts. Also, important issues in terms of metal forming production processes will be addressed such as avoidance of scrap during ramp up phases and batch processing. Finally, the practical use of machine learning algorithms will be demonstrated in real trimming and metal forming processes.

The Selection of Leveler Parameters Using FEM Simulation.

The aim of this research was to select parameters for the roll pre-leveler to provide sheet metal waviness reduction after unwinding from the coil. Straightening parameters were selected based on the results of numerical simulations with the use of an FEM-based computer program. The material used for research was a hot-rolled sheet metal of grade S235JR + AR with a thickness of 3 mm and width of 1500 mm after unwinding from the coil. A mathematical model was developed to determine straightening roll arrangements in the pre-leveler. It enabled roll arrangement selection and a straightening scheme to be elaborated. The model's innovative feature was conducting straightening numerical simulations for the real sheet metal geometric models obtained as a result of 3D laser scanning, which increased the accuracy of the numerical calculations.

Real time lithium metal calendar aging in common battery electrolytes

Li metal anodes are highly sought after for high energy density applications in both primary commercial batteries and next-generation rechargeable batteries. In this research, Li metal electrodes are aged in coin cells for a year with electrolytes relevant to both types of batteries. The aging response is monitored via electrochemical impedance spectroscopy, and Li electrodes are characterized post-mortem. It was found that the carbonate-based electrolytes exhibit the most severe aging effects, despite the use of LiBF4-based carbonate electrolytes in Li/CFx Li primary batteries. Highly concentrated LiFSI electrolytes exhibit the most minimal aging effects, with only a small impedance increase with time. This is likely due to the concentrated nature of the electrolyte causing fewer solvent molecules available to react with the electrode surface. LiI-based electrolytes also show improved aging behavior both on their own and as an additive, with a similar impedance response with time as the concentrated LiFSI electrolytes. Since I− is in its most reduced state, it likely prevents further reaction and may help protect the Li electrode surface with a primarily organic solid electrolyte interphase.

Sequential Recovery of Critical Metals from Leached Liquor of Processed Spent Lithium-Ion Batteries

The processing and extraction of critical metals from black mass is important to battery recycling. Separation and recovery of critical metals (Co, Ni, Li, and Mn) from other metal impurities must yield purified metal salts, while avoiding substantial losses of critical metals. Solvent extraction in batch experiments were conducted using mixed metal sulphates obtained from the leach liquor obtained from spent and shredded lithium-ion batteries. Selective extraction of Mn2+, Fe3+, Al3+ and Cu2+ from simulated and real leached mixed metals solution was carried out using di-2-ethylhexylphophoric acid (D2EPHA) and Cyanex-272 at varying pH. Further experiments with the preferred extractant (D2EPHA) were performed under different conditions: changing the concentration of extractant, organic to aqueous ratio, and varying the diluents. At optimum conditions (40% v/v D2EPHA in kerosene, pH 2.5, O:A = 1:1, 25 °C, and 20 min), 85% Mn2+, 98% Al3+, 100% Fe3+, and 43% Cu2+ were extracted with losses of only trace amounts (<5.0%) of Co2+, Ni2+, and Li+. The order of extraction efficiency for the diluents was found to be kerosene > Exxal-10 >>> dichloromethane (CH2Cl2) > toluene. Four stages of stripping of metals loaded on D2EPHA were performed as co-extracted metal impurities were selectively stripped, and a purified MnSO4 solution was produced. Spent extractant was regenerated after Fe3+ and Al3+ were completely stripped using 1.0 M oxalic acid (C2H2O4).

The Casimir Force between Two Graphene Sheets: 2D Fresnel Reflection Coefficients, Contributions of Different Polarizations, and the Role of Evanescent Waves

We consider the Casimir pressure between two graphene sheets and contributions to it determined by evanescent and propagating waves with different polarizations. For this purpose, the derivation of the 2-dimensional (2D) Fresnel reflection coefficients on a graphene sheet is presented in terms of the transverse and longitudinal dielectric permittivities of graphene with due account of the spatial dispersion. The explicit expressions for both dielectric permittivities as the functions of the 2D wave vector, frequency, and temperature are written along the real frequency axis in the regions of propagating and evanescent waves and at the pure imaginary Matsubara frequencies using the polarization tensor of graphene. It is shown that in the application region of the Dirac model nearly the total value of the Casimir pressure between two graphene sheets is determined by the electromagnetic field with transverse magnetic (TM) polarization. By using the Lifshitz formula written along the real frequency axis, the contributions of the TM-polarized propagating and evanescent waves into the total pressure are determined. By confronting these results with the analogous results found for plates made of real metals, the way for bringing the Lifshitz theory using the realistic response functions in agreement with measurements of the Casimir force between metallic test bodies is pointed out.

MARGANVAC: metal artifact reduction method based on generative adversarial network with variable constraints

Objective. Metal artifact reduction (MAR) has been a key issue in CT imaging. Recently, MAR methods based on deep learning have achieved promising results. However, when deploying deep learning-based MAR in real-world clinical scenarios, two prominent challenges arise. One limitation is the lack of paired training data in real applications, which limits the practicality of supervised methods. Another limitation is that image-domain methods suitable for more application scenarios are inadequate in performance while end-to-end approaches with better performance are only applicable to fan-beam CT due to large memory consumption. Approach. We propose a novel image-domain MAR method based on the generative adversarial network with variable constraints (MARGANVAC) to improve MAR performance. The proposed variable constraint is a kind of time-varying cost function that can relax the fidelity constraint at the beginning and gradually strengthen the fidelity constraint as the training progresses. To better deploy our image-domain supervised method into practical scenarios, we develop a transfer method to mimic the real metal artifacts by first extracting the real metal traces and then adding them to artifact-free images to generate paired training data. Main results. The effectiveness of the proposed method is validated in simulated fan-beam experiments and real cone-beam experiments. All quantitative and qualitative results demonstrate that the proposed method achieves superior performance compared with the competing methods. Significance. The MARGANVAC model proposed in this paper is an image-domain model that can be conveniently applied to various scenarios such as fan beam and cone beam CT. At the same time, its performance is on par with the cutting-edge dual-domain MAR approaches. In addition, the metal artifact transfer method proposed in this paper can easily generate paired data with real artifact features, which can be better used for model training in real scenarios.

A dynamic combination algorithm based scenario construction theory for mine water-inrush accident multi-objective optimization

Mine safety is a crucial aspect of national infrastructure. In recent years, there have been frequent mine safety accidents in China, and the proportion of mine water-inrush accidents (MWAs) is high among them. It causes significant challenges for governments and mine managers. The emergency response of MWAs is a multi-scale expert decision-making system that involves considerable cost, time, and energy consumption. The Mine Accidents Central Control Office is constituted of mine managers and government officials, and it lacks scientific validity in analyzing the risk correlation only based on sensory-historical experience. It can lead to deviations in emergency response capability and cause unnecessary waste of costs, time, and energy. This study introduces scenario construction theory and multi-attribute dynamic combination algorithms to address this systemic challenges based on the data-driven model. Firstly, the dataset is structured by the induction method based on historical MWAs from 2003 to 2023 in China, and it is divided into nine accident attributes and three calculated categories. Secondly, the scenario parameters are selected with bottom-line thinking and correlation analysis of accident attributes. Thirdly, the scenario queue model and scenario disposal model are constructed based on the scenario construction theory with the dynamic combination algorithm; a systemic mathematical model is established to optimize the multi-objective (cost, time, and energy consumption) in emergency response. Finally, a real metal mine is selected for model simulation, based on data results to analyze algorithm variable reflected handle measure. This study provides a novel approach and scientific reference to improve emergency plans in mine safety management. It enhances the effectiveness and timeliness of emergency response in the MWAs.

Mathematical modelling of waste rock management through incorporating open-pit waste rocks in underground stope filling: An environmental approach

Reducing the footprint of waste rock dumping would result in cost savings and mitigate the environmental impacts of mining. This study develops a mixed integer programming model for waste rock management, aimed at identifying the optimal dump location among surface waste dumps and underground stopes. The model generates an optimal waste rock dumping schedule and proposes the best destination, with the objectives of minimizing the total cost of waste rock hauling and maximizing the supply of filling materials for backfilling underground stopes from the waste rocks. By applying the model to a real metal mine, a total cost reduction of approximately 14% was accomplished by utilizing open-pit waste rocks as underground filling materials, replacing alternative sources. Sensitivity analysis approved that supplying the filling materials from waste rocks was a priority, which resulted in a reduction of 3,750,000 tonnes of dumping waste rocks on the surface and a significant reduction of the waste dump environmental footprint. The model not only improves the economics of mining operations but also mitigates the environmental impacts of open-pit waste rock dumping by using waste rocks for backfilling underground stopes instead of supplying materials from outside the mine.

Studies on structural heterogeneity of high-strength sheet materials

The work is devoted to the actual scientific and practical task of applying the methods of researching the processes of damage accumulation in metals under the conditions of active operation of structures and selecting the necessary parameters characterizing the degree of material degradation to assess the load-bearing capacity of structural elements, taking into account their current damage.
 The approbation of the express control method for diagnosing the current state of the surface of a large area based on the characteristics of the dispersion of material hardness values is described. It is shown that it is possible to obtain a quantitative characteristic of the state of the metal using the LM - hardness method, according to which the parameters of the dispersion of its values during mass measurements of hardness are accepted as informative signs of the state of the metal. Experimental results were obtained during the study of high-strength materials such as Armox 500T, Hardox 450, etc. The obtained results made it possible to improve the quality of non-destructive testing of metal by the characteristics of dispersion of material hardness values and to perform a number of practical works on assessing the condition of real metal blanks used in the creation of responsible technical products or structural elements

Human Metal ESD: Design of a Full-Wave Model and an Improved Compact Generator

A full-size, full-wave human body model has been designed. Compared with a real human-metal electrostatic discharge (ESD), similar fields and currents are obtained from the numerical model. A resistive surface sheet is used in microwave studio to control the currents on the air-filled body. Its performance is verified by comparing it to the currents and fields from the real human ESD. A subcircuit models the time-dependent resistance of the spark using the well-known Rompe–Weizel spark resistance model. Real human metal ESD does not reveal the double hump shape as shown in the IEC standard. To create a generator that reproduces the real human metal ESD current waveform, a compact ESD generator was designed, which is based on matching the impedance of real human metal mode ESD with the impedance of the compact ESD generator. Furthermore, a circuit-based simulator is presented. It is based on a PCB implementation of the equivalent circuit of the human metal ESD.

Confirming High-Valent Iron as Highly Active Species of Water Oxidation on the Fe, V-Coupled Bimetallic Electrocatalyst: In Situ Analysis of X-ray Absorption and Mössbauer Spectroscopy.

Iron (Fe)-based bimetallic oxides/hydroxides have been widely investigated for promising alkaline electrochemical oxygen evolution reactions (OERs), but it still remains argumentative whether Fe3+ or Fe4+ intermediates are highly active for efficient OER. Here, we rationally designed and prepared one Fe, V-based bimetallic composite nanosheet by employing the OER-inert V element as a promoter to completely avoid the argument of real active metals and using our recently developed one-dimensional conductive nickel phosphide (NP) as a support. The as-obtained hierarchical nanocomposite (denoted as FeVOx/NP) was evaluated as a model catalyst to gain insight into the iron-based species as highly active OER sites by performing in situ X-ray absorption spectroscopy and 57Fe Mössbauer spectroscopy measurements. It was found that the high-valent Fe4+ species can only be detected during the OER process of the FeVOx/NP nanocomposite instead of the iron counterpart itself. Together with the fact that the OER activities of both the vanadium and iron counterparts are by far worse than that of the FeVOx/NP composite, we can confirm that the high-valent Fe4+ formed are the highly active species for efficient OER. As demonstrated by density functional theory simulations, the composite of Fe and V metals is proposed to cause a decreased Gibbs free energy as well as theoretical overpotential of water oxidation with respect to its counterparts, as is responsible for its excellent OER performance with extremely low OER overpotential (290 mV at 500 mA cm-2) and extraordinary stability (1000 h at 100 mA cm-2).

Highly efficient decomplexation of chelated nickel and copper effluent through CuO–CeO2–Co3O4 nanocatalyst loaded on ceramic membrane

A novel CuO–CeO2–Co3O4 nanocatalyst loaded on Al2O3 ceramic composite membrane (CCM-S) was synthesized through spraying-calcination method, which can be beneficial to the engineering application of scattered granular catalyst. BET and FESEM-EDX testing revealed that CCM-S possessed a porous character with high BET surface area of 22.4 m2/g and flat modified surface with extremely fine particle aggregation. The CCM-S calcined above 500 °C presented excellent anti-dissolution effect due to the formation of crystals. XPS indicated that the composite nanocatalyst possessed the variable valence states, which were conducive to exert the catalytic effect of Fenton-like reaction. Subsequently, the effects of experimental parameters including fabricate method, calcination temperature, H2O2 dosage, initial pH value, and CCM-S amount were further investigated considering the removal efficiency of Ni(II)-complex and COD after decomplexation and precipitation (pH = 10.5) treatment within 90 min. Under the optimal reaction condition, the residual Ni(II)-complex and Cu(II)-complex concentration from actual wastewater was all lower than 0.18 mg/L and 0.27 mg/L, respectively; meanwhile, the removal efficiency of COD was all higher than 50% in the mixed electroless plating effluent. Besides, the CCM-S could still maintain high catalytic activity after a six-cycle test, and the removal efficiency was slightly declined from 99.82% to 88.11%. These outcomes indicated that CCM-S/H2O2 system was provided with a potential applicability on treatment of real chelated metal wastewater.