В статье рассмотрена задача повышения информативности электрических методов каротажа при оценке фильтрационных свойств урановмещающих песков пластово-инфильтрационных месторождений. На основе статистической обработки данных кажущегося сопротивления, индукционного каротажа, керновых материалов и результатов опытных гидрогеологических откачек были установлены аналитические зависимости между электрическими параметрами пород, медианным диаметром зерен D50 и коэффициентом фильтрации Кф. Показано, что использование данных индукционного каротажа обеспечивает более высокую точность оценки фильтрационных свойств по сравнению с традиционным методом кажущегося сопротивления.

В статье рассмотрена научно-методическая проблема выбора и применения эффективных геофизических технологий на разных этапах геологоразведочных и горно-геологических работ на урановых месторождениях Казахстана. Основное внимание уделено систематизации физико-геологических и петрофизических характеристик пород и руд Шу-Сарысуской урановой провинции. На основе фондовых геологических материалов, опубликованных данных и статистической обработки были обобщены диапазоны физических свойств пород и скважинных геофизических полей. Полученные результаты показали необходимость более детального изучения проницаемых и непроницаемых пород по электрическим свойствам, плотности и скоростям сейсмических волн для повышения информативности геофизических методов и оптимизации технологий in-situ leaching.

В статье применены методы машинного обучения для выявления и классификации редких и аномальных минералов в крупной минералогической базе данных. С помощью Isolation Forest и One-Class SVM были определены минералы с нетипичными физико-химическими свойствами, после чего KMeans clustering был использован для группировки аномалий в три геологически интерпретируемые категории, связанные с эвапоритовыми, метаморфическими и магматическими условиями формирования. Полученные результаты показывают, что методы unsupervised learning могут повысить эффективность классификации минералов и прогнозирования редких минеральных месторождений.

Global energy and environmental issues are driving the development of modern advances in efficient and environmentally friendly energy storage systems. Such systems must meet a range of requirements, which include high energy and power density, long service life, flexibility, industrial scalability, security and reliability. Progressive achievements in the field of energy storage are associated with the development of various kinds of batteries and supercapacitors. Supercapacitors are state-of-the-art energy storage devices with high power density, long lifespan, and the ability to bridge the power/energy gap between conventional capacitors and batteries/fuel cells. However, supercapacitors have limitations associated with low energy density, which can be solved by using various types of current collectors, since current collectors are one of the main massive components of supercapacitors. This review gives a complete understanding of the effect of current collectors on the actual performance and properties of supercapacitors. We reviewed current collectors based on carbon and metal-containing materials, and supercapacitor configurations to identify possible improvements in electrochemical performance in terms of specific capacitance, energy density, power density, service life and variability in their application. © 2022 The Author(s)

Short-term (daily) and long-term (seasonal) thermal energy storage allows efficient use of renewable thermal energy by replacing fossil fuel systems. In the present research, a three-dimensional numerical simulation of the thermal efficiency of a single-stage and three-stage cascaded shell-and-tube type latent heat thermal energy storage device is carried out using various phase change materials. The mathematical model is based on the fundamental conservation laws of mass, momentum, and energy. Numerical implementation was carried out using built-in solvers of COMSOL Multiphysics v.5.6 software. The numerical solver was verified by comparison with experimental data with acceptable agreement. A comparison of calculations between single and cascade configurations showed that the use of a multi-stage configuration allows for an increase in the temperature range of considered thermal energy storage devices. The use of the internal finned structure of containers almost halves the charging and discharging time. The developed numerical calculation tool can be used in the future to study the thermal efficiency of more complex thermal energy storage device configurations, considering three dimensions and phase transitions. © 2024 American Institute of Physics Inc.. All rights reserved.

The motion of planar hinge-lever mechanisms with flexible and elastic links in a closed pre-stressed contour is considered. Modeling of the mechanism motion is carried out on the basis of their kinetic-elastodynamic analysis, which takes into account the inertial relationship between the large-scale motion of mechanisms as a rigid body and nonlinear vibrations of the links as a result of their elastic deformation. This work pays attention to both longitudinal and lateral vibrations of elastic links. The equations of motion of the mechanisms are obtained by the use of Novozhilov’s nonlinear theory of elasticity, according to which the link deformations are assumed to be finite. Based on Biot’s theory of incremental deformations, the field of initial stresses in flexible elements is taken into account due to their preliminary tension, which determines the geometric nonlinearity of dynamic models. As an example, the dynamics of a planar five-link hinge-lever mechanism with closed pre-stressed contour is studied. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Hydrotechnical structures, being vital infrastructural objects, at the same time represent a great danger for human activity and the environment. The article discusses the results of geophysical studies of an earth dam in Kazakhstan. Despite its key role in agricultural water supply, the loam dam has not previously been subjected to a thorough geophysical evaluation. The study combines seismic refraction tomography using the correlation method of refracted waves with self-potential measurements to non-invasively detect internal heterogeneities and potential seepage pathways. Over one kilometre of seismic profiling has been performed with both P- and S-wave registrations by using standard geophones and pulse sources, allowing imaging to depths of up to 40 meters. Data processing included noise reduction, first arrival sampling, and velocity modelling with vertical gradients. The results show significant lithological and structural variability in the dam body. Subsidence anomalies with increasing permeable loams and low velocity zones have been identified, and soil loosening has been detected, indicating a possible seepage site. The comparison of seismic data and self-potential measurements has showed the highest correlation near the dam crest, with partial overlap elsewhere due to soil heterogeneity, metal structures, moisture changes, and complex topography. The combined interpretation has allowed identifying the main seepage zones in the dam body. The results of the study confirm the effectiveness of combining the correlation method of refracted waves and the self-potential method for detailed diagnostics of earth dams. The integrated approach allows for depth-resolved characterization and the development of a seepage regime model that identifies critical risk zones. Further detailed permeability testing, real-time seepage monitoring, and regular geophysical and hydrogeological surveys are recommended, especially near residential areas. The results of the surveys provide a solid foundation for engineering measures to enhance dam safety and mitigate the risk of failure. As part of the Geographic Information System platform, the data obtained are useful for monitoring the condition of dams, assessing their risks and impact on the environment, and for effective water resource management.

Abstract. Relevance. This study presents a machine learning (ML) approach for petrophysical core classification, applied to data from the southeastern margin of the Precaspian Depression - a geologically complex region characterized by heterogeneous reservoirs and diverse lithofacies. The Random Forest (RF) algorithm was chosen as the primary method due to its proven efficiency in handling nonlinear relationships and high-dimensional datasets, making it particularly suitable for complex geological environments. Objective. A Python based workflow integrating Scikit-learn, Pandas, and Streamlit was developed to support the complete petrophysical analytical cycle — from data preprocessing to interactive visualization and interpretation. Methods. The RF model achieved 89% accuracy and an F1-score of 0.90 in lithotype classification (sandstones and siltstones). Porosity and permeability emerged as the most influential features, with the application of a logarithmic permeability scale significantly enhancing interpretability in low-permeability zones. Feature importance was rigorously quantified using the Gini index, enabling effective dataset optimization and 8 ISSN 2224-5278 2.2026 dimensionality reduction. Results and conclusions. The model exhibited strong generalization capabilities, with over 90% test accuracy, and demonstrated robust resistance to overfitting, ensuring reliable performance on unseen data. The interactive web application further enhances usability by offering tools for hyperparameter tuning, feature importance analysis, and dynamic data visualization, supporting rapid and informed decision-making by petrophysicists. In conclusion, the proposed ML framework offers a practical, scalable, and adaptable solution that significantly improves the speed, accuracy, and reliability of lithotype classification, making it a valuable tool for modern petrophysical workflows in geologically complex and heterogeneous reservoir settings.

This work presents a generalization and analysis of the physical properties of rocks and ores from the Zhezkazgan ore district. Studies were carried out to identify general patterns in variations in the magnetic, density, velocity, and electrical parameters of the rocks that make up the geological section of the region. Based on the physical parameter measurements of the rock samples and drill cores collected in large quantities evenly throughout the region, a spatial analysis and quantitative assessment were conducted for the magnetic susceptibility, density, specific electrical resistivity, polarizability, and seismic velocity of the rocks. These properties were systematized at the level of formations, individual suites, and lithological heterogeneities. Correlations between the physical properties of the rocks, their composition, and the conditions of their formation were established. This study demonstrated the potential of using petrophysical characteristics in tectonic studies, geological mapping, and the identification of the exploration and ore-controlling factors in copper mineralization. It was found that the deposits of the productive horizons of the Zhezkazgan and Taskuduk suites are characterized by consistent physical parameters across the entire area, due to their relative homogeneity in lithological, structural–textural, and other features. The physical parameters of the rocks are influenced by several factors associated with mineralization processes, including changes in the total porosity, structure, and texture of the host rocks, alteration of the original mineral composition of the ores, fragmentation, fracturing, fissuring, and others. The obtained results significantly improve the reliability of geologically interpreting geophysical anomalies, especially in areas covered by loose sediments and where productive horizons are deeply buried. The detailed petrophysical analysis of the region has made it possible to provide recommendations for selecting an optimal set of geophysical methods for further successful work at the prospecting-evaluation and exploration stages in the Zhezkazgan ore district. Keywords: physical properties; systematization; variation curves; statistical processing; patterns; Zhezkazgan; stratiform deposits; productive horizon

The study aimed to investigate the impact of plasticizers on the properties of metal-ceramic hard alloys and develop recommendations for optimizing their composition, concentration, and production process parameters. WC8 alloy powder containing 8% cobalt binder and varying tungsten carbide grain sizes (2.5–8 μm) was used. Plasticizers tested included paraffin and polyethylene glycol (PEG) in concentrations of 1–3%. Powder mixtures were pressed under high pressure and subjected to vacuum-compression sintering. Mechanical properties such as bending strength, hardness, and density were analyzed using standard measurement techniques. Plasticizers improved the flowability of powder mixtures and the quality of pressing. Paraffin at concentrations of 1–2% provided the best results, achieving a bending strength of 2030 MPa, a density of 14.8 g/cm³, and a hardness of 88 HRA. PEG showed lower performance due to increased porosity, especially at concentrations of 3%. Reducing tungsten carbide grain size to 2.5 μm further enhanced the mechanical properties of the alloys. Optimal plasticizer concentrations for sintering hard alloys under vacuum-compression conditions were established for the first time. It was determined that paraffin is more effective in forming a homogeneous material structure compared to PEG. The results can be applied in the production of hard alloys for various industries, including mechanical engineering, metallurgy, aerospace, and defense, ensuring improved product quality and reliability.