The objective of this study was to develop a method for quantitatively characterizing tetravalent Ru complexes, namely [RuCl6]2− and [Ru2OCl10]4−, in concentrated hydrochloric acid by ultraviolet-visible absorption spectroscopy. To obtain the standard spectra of each complex, measurements on K2RuCl6 and K4[Ru2OCl10] dissolved in hydrochloric acid containing an oxidizing agent were performed. Test solutions were prepared by fusing Ru with NaOH and Na2O2, followed by dissolving in hydrochloric acid. Using cuvettes with appropriate pass lengths for each solution, the spectra were measured over a wide range of Ru concentrations, from 0.000323 to 0.0321 mol・dm−3. Then the spectra of the test solutions were separated into the contributions of [RuCl6]2− and [Ru2OCl10]4− to quantify the Ru complexes. Among the tests conducted, [RuCl6]2− was mainly formed in hydrochloric acid when the amount of Ru added was relatively small, whereas [Ru2OCl10]4− was more likely to be formed when the amount of Ru was large. [RuCl6]2− and [Ru2OCl10]4− coexisted at comparable concentrations at the intermediate condition. Heat treatment on the Ru solution to improve the accuracy of the analysis was also demonstrated.
This study examines the effects of rock spalling on support elements in order to prevent cracking and to ensure the integrity of the support system and safety during shaft sinking. When the ventilation shaft at the Horonobe Underground Research Center reached a depth of more than 250 m, severe rock spalling occurred, and cracks developed in the concrete lining immediately above the spalling zone. Therefore, a three-dimensional numerical analysis of the shaft was conducted to estimate changes in the stress distribution within the concrete lining caused by the spalling. The simulation results indicated that the vertical tensile stress in the concrete lining increased as the spalling progressed. By integrating the analytical results with field observations and considering various support patterns to prevent further rock spalling, a flowchart for selecting the optimal support pattern was developed. Shaft sinking was subsequently completed to a depth of 500 m without significant damage to the concrete lining or excessive spalling. The flowchart developed in this study will contribute to the selection of optimal support patterns for future shaft sinking projects.
Rock excavators equipped with cutting functions, such as roadheaders, surface miners, and various coal mining machinery, are widely used in civil engineering and mine operations. In the design and development of these machines, numerous researchers have conducted theoretical, experimental, and numerical studies to understand the rock cutting mechanisms using bits. This review article summarized research trends and future challenges concerning rock cutting mechanisms, focusing on theoretical and experimental studies. First, the technical terminology for cutting processes of a chisel bit or a point attack bit was introduced, and various equations for calculating cutting resistance based on the two- or three-dimensional cutting theory were described in detail, including their background, derivation processes, and relationships. Then, recent experimental studies on the factors affecting cutting resistance of a point attack bit were reviewed while mentioning key achievements with a chisel bit. The law of similarity and the cutting processes of multi bits mounted on a rotating drum were also explained since they are essential for the design and development of actual rock excavators. Studies on cutting hard rocks and mining deep seafloor mineral resources are ongoing, and hence it will be necessary to clarify the rock cutting mechanisms under these complicated severe conditions with utilizing accumulated knowledge introduced in this review article.
This paper provided an overview of recent advances in simulation technologies for comminution processes, focusing on analysis techniques based on the Discrete Element Method (DEM), categorized into grinding media behavior and material particle behavior. Regarding the simulation of grinding media behavior, we explained that engineering-important physical quantities such as power consumption, grinding rate, mechanochemical reaction rate, and wear amount have strong correlations with indicators calculable from simulations, such as dissipated energy and collision energy. This indicates that a part of the design of comminution processes, which has long relied on experience and intuition, is transitioning toward theory-based design. Additionally, regarding the simulation of material particle behavior, we explained the remarkable evolution of fracture models, in addition to the analysis of grinding and agglomeration mechanisms through coupled analysis with fluids. In particular, addressing the conventional challenge of arbitrariness in parameter determination, the establishment of methods that link experimentally measurable physical quantities with model parameters represents a significant step forward in enhancing the practical utility of simulations. This enables the reproduction of real phenomena in virtual space, even for comminution processes involving complex fracture phenomena, and is expected to contribute to eliminating the black box nature of grinding.
In the future, larger-scale and more detailed simulations are anticipated to become possible with further improvements in computational capabilities. Furthermore, by integrating such advanced simulation technologies with AI (Artificial Intelligence) and IoT (Internet of Things) technologies, the digital twinning of comminution processes is expected to accelerate. If systems can be constructed that instantaneously search for optimal operating conditions in virtual space and provide feedback for autonomous control of actual equipment, maximization of energy efficiency and realization of nano-level precision grinding can be reasonably expected. We hope this paper serves as a useful resource for understanding the technological progress in comminution and the current state of simulation technologies.
In secured landfill sites, accurate prediction of leachate volume is essential for stable operation and environmental management purposes. In this study, a tank model was developed using meteorological and operational data to predict seasonal variation in leachate volume. To improve estimation accuracy, the model also incorporates snow accumulation and snowmelt processes. Although the tank model is relatively simple, it demonstrates good performance in simulating leachate volume trends based on weather data. By incorporating snow-related hydrological processes, the correlation coefficient between the estimated and measured leachate volumes during winter and early spring improved significantly, from 0.15 to 0.72. The annual leachate volumes estimated using the model showed over 90% agreement with the measured values, confirming the model’s validity. The results also indicate that refining the estimation of evapotranspiration could further enhance prediction accuracy. This approach provides a practical and accessible tool for the daily management of landfill operations under varying climatic conditions.