Centrifugal pumps are extensively utilized across various industries, including water supply, agriculture, and energy, where they consume significant amounts of electricity. As demands for energy efficiency and reduced operating costs increase, enhancing pump efficiency has become crucial. This study focuses on optimizing the pump impeller geometry, which plays a vital role in minimizing energy losses. A hydraulic and hydrodynamic model was developed, alongside a parametric study based on numerical simulations (CFD), to analyze the influence of geometric parameters—specifically the angles and shapes of the blade’s inlet and outlet edges—on energy losses and hydraulic efficiency. The study utilized experimental data provided by the manufacturer for model verification. The results revealed that Ivanovsky’s method displayed deviations in the blade width at the leading edge and trailing edge of 25% and 43%, respectively, while Spiridonov’s method indicated deviations of 13% in the outer diameter $D_2$ and 27.5% in the blade width at the trailing edge. In contrast, the combined method proposed by the authors achieved high accuracy, with deviations under 9%. Additionally, parametric analysis identified two key parameters affecting the pump efficiency: the angle of the trailing edge and its shape. These findings underscore the necessity of optimizing the blade geometry to enhance the performance and energy efficiency of centrifugal pumps.

The ground source heat pump heating system is considered as one of the best solutions for the transition towards green heating under the continental climate conditions like Kazakhstan. In this paper, experimental and theoretical investigations were carried out to develop a ground source heat pump-based heating system under the weather conditions in Kazakhstan and to evaluate its thermodynamic performance. The water-to-water heat pump heating system, integrated with a ground source heat exchanger and used refrigerant R134a, was designed to provide hot water to meet the requirements for space heating. The predicted values of the coefficient of performance and the experimental results were found to be in good agreement within 6.2%. The thermodynamic performance of the system was also assessed using various environment-friendly refrigerants, such as R152a, R450A, R513A, R1234yf and R1234ze, as potential replacements for R134a. Although R152a is found to be a good alternative for R134a in terms of coefficient of performance and total equivalent warming impact, its flammability hinders its application. The heating system using refrigerants R450A, R513A, R1234yf and R1234ze shows 2–3% lower coefficient of performance than that of R134a. The highest exergy destruction is found to be attributed to the compressor, followed by the expansion valve, evaporator, and condenser. Considering their low flammability and low environmental impact, R450A, R513A, R1234yf and R1234ze are identified as valuable replacements for R134a.

The purpose of the present work was to determine the thermal performance of borehole heat exchangers, considering the influences of their geometric configurations and the thermophysical properties of the soil, grout and pipe wall material. A three-dimensional model was developed for the heat and mass transfer in soil (a porous medium) and grout, together with one-dimensional conductive heat transfer through the pipe walls and one-dimensional convective heat transfer of the heat transfer fluid circulating in the pipes. An algorithm was developed to solve the mathematical equations of the model. The COMSOL Multiphysics software was used to implement the algorithm and perform the numerical simulations. An apparatus was designed, installed and tested to implement the thermal response test (TRT) method. Two wells of depth 50 m were drilled in the Almaty region in Kazakhstan. Gravel and till/loam were mainly found, which are in accordance with the stratigraphic map of the local geological data. In each well, two borehole heat exchangers were installed, which were an integral part of the ground source heat pump. The TRT measurements were conducted using one borehole heat exchanger in one well and the data were obtained. The present TRT data were found to be in good agreement with those available in literature. The numerical results of the model agreed well with the present TRT data, with the root-mean-square-deviation within 0.184 °C. The TRT data, together with the predictions of the line-source analytical model, were utilized to determine the soil thermal conductivity (${\lambda }_g$ = 2.35 W/m K) and the thermal resistance of the borehole heat exchanger from the heat transfer fluid to the soil ($R_b$ = 0.20 m K/W). The model was then used to predict the efficiencies of the borehole heat exchangers with various geometric configurations and dimensions. The simulation results show that the spiral borehole heat exchanger extracts the highest amount of heat, followed by the multi-tube, double U-type parallel, double U-type cross and single U-type. It is also found that the spiral configuration can save 34.6% drilling depth compared with the conventional single U-type one, suggesting that the spiral configuration is the best one in terms of the depth and the maximum heat extracted. The simulation results showed that (i) more heat was extracted with a higher thermal conductivity of grout material, in the range of 0.5–3.3 W/m K; (ii) the extracted heat remained unchanged for a thermal conductivity of pipe material higher than 2.0 W/m K (experiments in the range of 0.24–0.42 W/m K); (iii) the extracted heat remained unchanged for a volumetric flow rate of water higher than 1.0 m³/h (experimental flow rate 0.6 m³/h); and (iv) the heat extracted by the borehole heat exchanger increased with an increase in the thermal conductivity of the soil (experiments in the range of 0.4–6.0 W/m K). The numerical tool developed, the TRT data and simulation results obtained from the present work are of great value for design and optimization of borehole heat exchangers as well as studying other important factors such as the heat transfer performance during charging/discharging, freezing factor and thermal interference.

This study presents a comprehensive 3D numerical analysis of thermal stratification, fluid dynamics, and heat transfer efficiency across six hot water storage tank configurations, identified as Tank-1 through Tank-6. The objective is to determine the most effective design for achieving uniform temperature distribution, stable stratification, and efficient heat retention in sensible heat storage systems, with potential for integration with phase change materials (PCMs). Using COMSOL Multiphysics 5.6, simulations were conducted to evaluate key performance indicators, including the Richardson number, capacity ratio, and exergy efficiency. Among the tanks, Tank-1 demonstrated the highest efficiency, with a capacity ratio of 84.6% and an exergy efficiency of 72.5%, while Tank-3, which achieved a capacity ratio of 70.2% and exergy efficiency of 50.5%, was identified as the most practical for real-world applications due to its balanced heat distribution and feasibility for PCM integration. Calculated dimensionless numbers (Reynolds number: 635, Prandtl number: 4.5, and Peclet number: 2858) indicated laminar flow and dominant convective heat transfer across all the configurations. These findings provide valuable insights into the design of efficient thermal storage systems, with Tank-3’s configuration offering a practical balance of thermal performance and operational feasibility. Future work will explore the inclusion of PCM containers within Tank-3, as well as applications for heat pump and solar water heaters, and high-temperature heat storage with various working fluids.

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.

The Caspian Sea’s unique environment and intense hydrocarbon extraction make it a high-risk, understudied region for oil spill modelling. This review assesses the physical, chemical, and biological processes governing oil spill transport and fate, and evaluates the principal numerical tools available for the Caspian Sea context. The weathering processes are reviewed from foundational formulations to operational implementations. Key research challenges identified include the absence of photo-oxidation from operational models, limited laboratory data for Caspian crude oil types, and simplified biodegradation parameterizations. Hydrodynamic forcing uncertainty, arising from the lack of a dedicated operational ocean model, remains the dominant source of trajectory forecast error. Seven operational oil spill modelling tools and the ROMS hydrodynamic platform are reviewed. Only OSCAR and MIKE 21 have documented applications to the Caspian Sea, representing a significant regional gap. ROMS is identified as the most suitable hydrodynamic platform for future operational forecasting. Finally, the integration of machine learning and deep learning methods, including neural network trajectory prediction and SAR detection, is discussed as a promising frontier for improving forecast accuracy in this data-sparse environment.