The Reynolds number (Re), introduced in the late 19th century, has become a fundamental parameter in a lot of scientific fields—the main one being fluid mechanics—as it allows for the determination of flow characteristics by distinguishing between laminar and turbulent regimes, or some intermediate stage. Reynolds’ 1895 paper, which decomposed velocity into average and fluctuating components, laid the foundation for modern turbulence modeling. Since then, the concept has been applied to various fields, including external flows—the science that studies friction—as well as wear, lubrication, and heat transfer. Literature research in recent times has explored new interpretations of Re, and despite its apparent simplicity, the precise prediction of Reynolds numbers remains a computational challenge, especially under conditions such as the study of multiphase flows, non-Newtonian fluids, highly turbulent flow conditions, flows on very small scales or nanofluids, flows with complex geometries, transient or non-stationary flows, and flows of fluids with variable properties. Reynolds’ work, which encompasses both scientific and engineering contributions, continues to influence research and applications in fluid dynamics.

Mineral leaching is the key unit operation in metallurgical processes and corresponds to the dissolution of metals. The study of leaching is carried out in many areas, such as geology, agriculture and metallurgy. This paper provides an introduction to the theoretical background regarding the mathematical modelling of the leaching process of copper minerals, establishing an overall picture of the scientific literature on technological developments and the generation of representative mathematical and theoretical models, and indicating the challenges and potential contributions of comprehensive models representing the dynamics of copper mineral leaching.

The average lithium content in the Earth’s crust is estimated at about 0.007%. Despite this, lithium is considered abundant and widely distributed, with significant extraction from various sources. Notably, the brines in the Salar de Atacama are highlighted for their high lithium concentration ~1800 mg/L. Lithium is currently recovered from these brines through a solar evaporation process. The brine is transferred through a series of ponds, increasing the lithium concentration from 0.2% to 6% over 18 months, while decanting other minerals like potassium, magnesium, and boron. This method is the most efficient and cost-effective globally due to the Salar de Atacama’s high lithium concentration of approximately 1800 ppm and the region’s intense solar radiation, which facilitates evaporation at no economic cost. This manuscript describes in detail the lithium and potassium extraction processes used in the Salar de Atacama.

The importance of mine planning is often underestimated. Nonetheless, it is essential in achieving high performance by identifying the potential value of mineral resources and providing an optimal, practical, and realistic strategy for extraction, which considers the greatest quantity of options, materials, and scenarios. Conventional mine planning is based on a mostly deterministic approach, ignoring part of the uncertainty presented in the input data, such as the mineralogical composition of the feed. This work develops a methodology to optimize the mineral recovery of the heap leaching phase by addressing the mineralogical variation of the feed, by alternating the mode of operation depending on the type of ore in the feed. The operational changes considered in the analysis include the leaching of oxide ores by adding only sulfuric acid (H₂SO₄) as reagent and adding chloride in the case of sulfide ores (secondary sulfides). The incorporation of uncertainty allows the creation of models that maximize the productivity, while confronting the geological uncertainty, as the extraction program progresses. The model seeks to increase the expected recovery from leaching, considering a set of equiprobable geological scenarios. The modeling and simulation of this productive phase is developed through a discrete event simulation (DES) framework. The results of the simulation indicate the potential to address the dynamics of feed variation through the implementation of alternating modes of operation.