Centrifugal pumps are vital components in various industrial and domestic applications for fluid transportation. Understanding the complex hydrodynamic behavior inside these pumps is crucial for their efficient design and operation. This study presents a detailed hydrodynamic analysis of a single-stage single-suction centrifugal pump using computational fluid dynamics (CFD) techniques. The focus is on modeling turbulent flow phenomena within the pump to improve its performance and energy efficiency. The numerical simulations are conducted using ANSYS CFX software, which allows for a comprehensive examination of the pump’s internal flow characteristics. The study investigates the effects of impeller design, blade angles, and operating conditions on the pump’s efficiency and hydraulic performance. The results highlight the importance of accurate numerical modeling in optimizing pump design and achieving higher efficiency. This research contributes to the advancement of centrifugal pump technology by providing insights into the complex flow dynamics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

As the matter of fact, the Caspian Sea is an inland water structure that has no physical connection with the World Ocean, and has a high sensitive level for changes in various aspects. The live activity and mineral resources near the Caspian Sea was organized on the basis of the economic views of the states located on its coast since ancient times. Two-thirds of the earth's surface is covered by water ecosystem, and more than half of humanity is concentrated in a strip 50 miles wide along the coast. We are intimately connected to vast areas of water, and the health and quality of life in our oceans has a direct impact on the health of our lives. Systematic monitoring of water bodies should be an organizational and technological scheme for regular and continuous observations, assessment and forecasting of the state of water resources under the influence of natural and anthropogenic factors. The main purposes of monitoring are supplying water management and environmental complexities with reliable and latest updated information that allows scientists to assess the functional integrity of the state of ecosystems, and additionally, identify the causes of changes and evaluate their consequences of determination of corrective measures. Supportive information of that artificial reservoirs research should contain a large amount of various options and data on the physical-geographical and socio-economic features of the regions adjacent to the reservoir. This paper describes a state of knowledge of the dynamic evaluation of the coastline of the Caspian Sea region today, as well as the consequences may affect to the future economical situation of that area. Analysis of this research is devoted to the study of the practical application of photogrammetric methods and coastline monitoring technologies, using system of satellite images with high spatial resolution. The results of that observation reveal the high technological efficiency and comparison of the proposed methods with indication of updated techniques productivity. © 2023, National Academy of Sciences of the Republic of Kazakhstan. All rights reserved.

This research aims to evaluate the impact of implementing digital twins on companies’ operational activities in terms of enhancing their efficiency. Research methods include data analytics and visualization to explore the intricacies of creating and utilizing digital twins among high-tech leaders, as well as the correlation between expenses on innovative digital twin solutions and company revenues, followed by clustering to assess the impact of costs associated with the development and implementation of digital twins on enhancing the efficiency of business operational activities. In this context, the research presents a novel approach to measuring the influence of digital twin implementation on the efficiency of operational activities of high-tech companies based on correlation and cluster analysis. The findings indicate that all selected high-tech companies analyzed successfully applied digital twins to enhance their operational efficiency, as evidenced by the high correlation coefficient between expenses on digital twins and company revenues. Cluster analysis, distinguishing between two clusters of leaders and followers in the use of digital twins, allowed for identifying some distinctive characteristics of a leader in digital twin utilization and presenting a vision for transitioning to management based on the digitization of all company business processes. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

Currently, due to the high rate of development of the rare-earth industry, new sources of raw materials are being mastered and new technologies for obtaining rare-earth metals (REM) are being developed. Studies have shown that REM in kaolinite clays of Alexeevskoe deposit in Kazakhstan and Egypt deposits in Sinai Peninsula (K-Watt, K-Tech) and in Aswan region (KB,KPL) are mainly represented by erbium (Er). Production of Er concentrate is considered as a by-product in a comprehensive middlings processing of kaolinite clays to produce alumina and building materials. The possibility of obtaining Er concentrate by sulfuric acid leaching and sorption concentration methods has been determined. Optimal technological conditions of kaolinite clays leaching is the use of 5% solution of H2SO4, at temperature 50 °C, duration 60 min and L:S ratio = 5. Under these conditions the separation of REM from the main components Fe2O3, Al2O3, SiO2 is achieved. Concentrates were obtained with the content of the sum of REM oxides from 91.3 to 93.4%, in which the relative content of Er was from 64.89 to 90.82%. The results showed that the developed technology can be used for processing of erbium-containing kaolinite clays of various deposits. © 2023 The Authors

Assessing glaciers using recent and historical data and predicting the future impacts on them due to climate change are crucial for understanding global glacier mass balance, regional water resources, and downstream hydrology. Computational methods are crucial for analyzing current conditions and forecasting glacier changes using remote sensing and other data sources. Due to the complexity and large data volumes, there is a strong demand for accelerated computing. AI-based approaches are increasingly being adopted for their efficiency and accuracy in these tasks. Thus, in the current state-of-the-art review work, available research results on the application of AI methods for glacier studies are addressed. Using selected search terms, AI-based publications are collected from research databases. They are further classified in terms of their geographical locations and glacier-related research purposes. It was found that the majority of AI-based glacier studies focused on inventorying and mapping glaciers worldwide. AI techniques like U-Net, Random forest, CNN, and DeepLab are mostly utilized in glacier mapping, demonstrating their adaptability and scalability. Other AI-based glacier studies such as glacier evolution, snow/ice differentiation, and ice dynamic modeling are reviewed and classified, Overall, AI methods are predominantly based on supervised learning and deep learning approaches, and these methods have been used almost evenly in glacier publications over the years since the beginning of this research area. Thus, the integration of AI in glacier research is advancing, promising to enhance our comprehension of glaciers amid climate change and aiding environmental conservation and resource management. © 2024 by the authors.

Relevance: The global transition to electrification of transportation, aerospace, and industry is increasing the demand for efficient, lightweight, and heat-resistant electric motor systems. Advances in additive manufacturing (AM), especially in the field of metal-ceramic composites, are a breakthrough in the field of electric motor modernization. This study examines overcoming the limitations associated with polymer and aluminum structures by integrating metal-ceramic composites into brushless DC motors (BLDC). Objective: To evaluate the practical feasibility, thermal efficiency, and design advantages of 3D-printed metal-ceramic composites for DC motors under standard thermal and electromagnetic conditions. Methods: Three 500-watt motor designs were modeled in Autodesk Fusion 360: a polymer-based motor (PETG, ABS, PEEK via FDM), an engine with a metal-ceramic body based on ALO₃ and ceramic bearings, and a conventional aluminum motor. Each design provided 240 watts of power on 12 windings. Thermal loads, bearing friction, and magnetic fields were evaluated in the simulation. AM methods included SLS, DML, and SLM. Results: The temperature in the plastic engines reached 285.7 °C, in the aluminum engines-117.5 °C, and in the metal-ceramic version-89.9 °C. The composite engine has a thinner body and integrated cooling. Discussion and conclusions: The AM metal-ceramic coating provides excellent thermal control, structural strength and design freedom-an ideal solution for next-generation electric drive systems, despite the higher cost and complexity of processing. © National Academy of Sciences of the Republic of Kazakhstan, 2025.

The article presents the results of the functional zoning of the delta of transboundary river Syr Darya, which is located in an ecological disaster zone and is the only watercourse in modern conditions that supplies the remained part of Aral Sea. Under the conditions of global climate change, the territories of river deltas in arid regions are subject to active degradation processes, which are associated both with decrease of their water content and increase of anthropogenic impact. To determine the current condition of Syr Darya river delta landscapes, a component-by-component analysis of its main components was carried out. Based on the assessment of use of delta natural resource potential, the degradation processes associated with the types and intensity of anthropogenic impact in the conditions of arid climate were identified. The conducted studies formed the basis for the functional zoning of the territory of Syr Darya river delta, which is a spatial planning of sustainable land use and landscapes preservation. The developed scheme of functional zoning of Syr Darya River delta allowed to propose a number of measures with allocation of landscapes recommended for conservation, restoration, or sustainable use by the certain type of land use with the minimization of degradation processes. © 2022 by the authors. Licensee MDPI, Basel, Switzerlan

The mineral–industrial mega complex (MIMC) in Kazakhstan is described. The place of the complex in the world mineral resources and reserves is shown, and the volumes of the main products of MIMC during the last years are given. The high-priority objectives of MIMC in modern conditions are highlighted. The mathematical models of mineral raw materials at each stage of mining and processing are given. On this basis, recommendations on integrated and comprehensive utilization of mineral resources are given. The technical and economic criteria are substantiated for selecting effective methods for extraction of rare earth metals (REM) from multi-component ores. It is shown that new technologies and equipment adaptable to natural and process properties of a raw material from a particular mineral object can provide high level of REM extraction in order to worthily represent MIMC in the world market of rare earth metals. © Rakishev B. R., 2024.

Objective: The purpose of this study was to investigate the relationship of soil pollution factors such as heavy metal ions with the incidence of cancer in the Kyzylorda region of Kazakhstan. Methods: Concentrations of heavy metal ions in the soils of different sites of Kyzylorda region, Kazakhstan, were sampled and correlated with incidence of cancer in 2021. Results: Chromium content in the soil exceeded maximum permissible concentration (MPC) in the samples for all sites except Kazaly and Shieli, and the highest excess of 2.8 MPC was found in Terenozek. Content of copper, lead, and cobalt ions was also increased and varied in the range 1.9-15.4, 1.2-4, and 1.2-2.44 MPC, respectively. In addition, lung cancer incidence was statistically significantly correlated with soil concentration to MPC ratio of copper, cobalt, and lead; colorectal cancer was correlated with soil concentration of chromium. Cases of invasive cancer and mutations were recorded Terenozek and Kyzylorda areas. Conclusion: The higher the soil concentration correlate with higher cancer incidence in Kyzylorda region, Kazakhstan. © (2024), This work is licensed under a Creative Commons Attribution-Non Commercial 4.0 International License.

Bottom sediments play a crucial role in the environmental and agricultural management of freshwater reservoirs, acting as repositories for organic matter, chemical elements, and potential pollutants. This study investigates the chemical and granulometric composition of bottom sediments in the Verkhnetobolskoe and Karatomarskoe reservoirs in North Kazakhstan, focusing on the relationships between sediment particle sizes, organic matter, and heavy metal content. Sediment and water samples were collected during winter under ice-covered conditions using specialized sampling equipment and analyzed with advanced spectrometric and analytical methods. The study reveals significant correlations between fine-grained sediment fractions (<0.16mm) and the accumulation of organic matter and heavy metals, including cobalt, arsenic, and chromium, which exceeded permissible concentration limits. These findings underscore the ecological importance of fine sediment fractions as adsorptive sites for pollutants. The study concludes with methodological recommendations for sediment quality assessment and provides baseline data for environmental monitoring and agricultural planning in temperate freshwater ecosystems. © 2025, Unique Scientific Publishers. All rights reserved.