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This article reviews selected solar energy systems that utilize solar energy for heat generation and storage. Particular attention is given to research on individual components of these systems, aimed at improving their efficiency and performance. It focuses on an analysis of the literature concerning the design of thermal storage units, with an emphasis on the use of computational fluid dynamics (CFD) as a research tool. Conclusions from scientists' research regarding the impact of tank shape, thermal insulation, flow parameters, and the use of stratification partitions on heat storage efficiency have been presented. The literature review indicates that thermal storage units play a key role in the efficiency of solar systems, and thermal stratification within them can significantly improve their performance. The methodology was based on an analysis of journals, primarily from after 2008, focusing on articles related to the application of CFD methodology in the study of solar systems and heat storage. [ABSTRACT FROM AUTHOR]

This study proposes a dual-fuel approach combining diesel and ammonia in a single-cylinder compression ignition engine to reduce harmful emissions from internal combustion. Diesel is directly injected into the combustion chamber, while ammonia is introduced through the intake manifold with intake air. In this study, injection timing and the percentage of ammonia energy fraction was varied. A computational fluid dynamics (CFD) model simulates the combustion and emission processes to assess the impact of varying diesel injection timings and ammonia energy contributions. Findings indicate that as ammonia content increases, the engine experiences reductions in peak in-cylinder pressure, temperature, heat release rate, as well as overall efficiency and power output. Emission results suggest that greater ammonia usage leads to a reduction in soot, carbon monoxide, carbon dioxide, and unburned hydrocarbons, though a slight increase in nitrogen oxides emissions is observed. This analysis supports ammonia's potential as a low-emission alternative fuel in future compression ignition engines. [ABSTRACT FROM AUTHOR]

This review investigates the role of windcatchers in modern architecture, exploring their optimization through the integration of traditional designs with contemporary technologies. Historically utilized in hot and arid climates for passive cooling, windcatchers offer energy-efficient solutions for improving indoor air quality (IAQ). This study examines the sustainability of traditional windcatcher designs and their relevance in preserving heritage structures. Using advanced tools like computational fluid dynamics (CFD) modeling, modern adaptations of windcatchers can be optimized for urban environments. This review also explores hybrid systems, combining windcatchers with solar chimneys, evaporative cooling, or heat pumps, to enhance performance in low-wind conditions by balancing natural and mechanical ventilation. Additionally, it addresses the role of artificial intelligence (AI) in heritage planning, facilitating the design and integration of windcatchers into contemporary architecture. The findings suggest that windcatchers, combined with modern design strategies and hybrid systems, continue to be viable and sustainable solutions for passive cooling, contributing to energy-efficient and climate-resilient buildings across different environmental and urban contexts. [ABSTRACT FROM AUTHOR]

Numerical analysis of a U-type solid oxide fuel cell stack was performed using computational fluid dynamics to investigate the effects of stack capacities and fuel/air utilization rates on the internal flow uniformity. The results indicated that increasing the fuel/air utilization rate improved the gas flow uniformity within the stack for the same stack capacity. The uniformity in the anode fluid domain was better than that in the cathode fluid domain. Furthermore, the flow uniformity within the stack was associated with the percentage of pressure drop in the core region of the stack. The larger the percentage of pressure drop in the core region, the more uniform the flow inside the stack. Additionally, under a fuel utilization rate of 75%, the computational results exhibited excessively high fuel utilization rates in the top cell of a 3 kWe stack, indicating a potential risk of fuel depletion during actual stack operation. [ABSTRACT FROM AUTHOR]

The work presents an analysis of the Gorlov helical turbine (GHT) design using both computational fluid dynamics (CFD) simulations and response surface methodology (RSM). The RSM method was applied to investigate the impact of three geometric factors on the turbine's power coefficient (CP): the number of blades (N), helix angle (γ), and aspect ratio (AR). Central composite design (CCD) was used for the design of experiments (DOE). For the CFD simulations, a three-dimensional computational domain was established in the Ansys Fluent software, version 2021R1 utilizing the k- ω SST turbulence model and the sliding mesh method to perform unsteady flow simulations. The objective function was to achieve the maximum CP, which was obtained using a high-correlation quadratic mathematical model. Under the optimum conditions, where N, γ , and AR were 5, 78°, and 0.6, respectively, a CP value of 0.3072 was achieved. The optimal turbine geometry was validated through experimental testing, and the CP curve versus tip speed ratio (TSR) was determined and compared with the numerical results, which showed a strong correlation between the two sets of data. [ABSTRACT FROM AUTHOR]

Machine learning tools represent a key methodology for the shape optimization of complex geometries in the turbomachinery field. One of the current challenges is to redesign High-Pressure Turbine (HPT) stages to couple them with innovative combustion technologies. In fact, recent developments in the gas turbine field have led to the introduction of pioneering solutions such as Rotating Detonation Combustors (RDCs) aimed at improving the overall efficiency of the thermodynamic cycle at low overall pressure ratios. In this study, a HPT vane equipped with diffusive endwalls is optimized to allow for ingesting a high-subsonic flow ( M a = 0.6 ) delivered by a RDC. The main purpose of this paper is to investigate the prediction ability of machine learning tools in case of multiple input parameters and different objective functions. Moreover, the model predictions are used to identify the optimal solutions in terms of vane efficiency and operating conditions. A new solution that combines optimal vane efficiency with target values for both the exit flow angle and the inlet Mach number is also presented. The impact of the newly designed geometrical features on the development of secondary flows is analyzed through numerical simulations. The optimized geometry achieved strong mitigation of the intensity of the secondary flows induced by the main flow separation from the diffusive endwalls. As a consequence, the overall vane aerodynamic efficiency increased with respect to the baseline design. [ABSTRACT FROM AUTHOR]

In order to reduce CO2 emissions in the brick manufacturing process, the effectiveness of the energy-intensive firing process needs to be improved. This can be achieved by enhancing the heat transfer in order to reduce firing times. As a result, current development of tunnel kilns is oriented toward fast firing as a long-term goal. However, a struggling building sector and complicated challenges, such as different requirements for product quality, have impeded developments in this direction. This creates potential for the further development of oven designs, such as improved airflow through the kiln. In this article, numerical flow simulations are used to investigate two different reconstruction measures and compare them to the initial setup. In the first measure, the kiln height is reduced, while in the second measure, the kiln cars are adjusted to alternate the height of the bricks so that every other pair of bricks is elevated, creating a staggered arrangement. Both measures are investigated to determine the effect on the heating rate compared to the initial configuration. A transient grid independence study is performed, ensuring numerical convergence and the setup is validated by experimental results from measurements on the initial kiln configuration. The simulations show that lowering the kiln height improves the heat transfer rate by 40 % , while the staggered arrangement of the bricks triples it. This leads to an average brick temperature after two hours which is around 130 °C higher compared to the initial kiln configuration. Therefore, the firing time can be significantly reduced. However, the average pressure loss coefficient rises by 70 % to 90 % , respectively, in the staggered configuration. [ABSTRACT FROM AUTHOR]

The geometric configuration, particularly the inner tube diameter, plays a significant role in the thermal performance of pulsating heat pipes (PHPs). Previous experimental research has demonstrated that single-loop triple-diameter PHPs (TD-PHPs) outperform single-loop single-diameter PHPs (SD-PHPs) and dual-diameter PHPs (DD-PHPs) in terms of thermal performance under moderate heating input powers ranging from 25 W to 75 W. However, a reduction in heat input from 75 W to 25 W leads to a diminished impact of TD-PHPs on the thermal performance. Therefore, to improve the overall performance of TD-PHPs, this study used two-dimensional transient computational fluid dynamics simulations to identify the optimal inner tube diameters for TD-PHPs at a low heat input by evaluating the thermal resistance of five TD-PHPs with various inner diameters. The findings reveal that the TD-PHP configuration exhibits minimum thermal resistance, with inner diameters of 4.5 mm for the upper arch (the condenser section), 4.0 mm for the wide branch, and 2.5 mm for the narrow branch, primarily due to its full circulation flow pattern. Furthermore, the overall heat transfer performance of the optimal TD-PHP was compared with that of an SD-PHP at low heat inputs (10 and 18 W), indicating that although the optimal TD-PHP shows lower thermal resistance, it does not significantly affect the start-up time. [ABSTRACT FROM AUTHOR]

This paper proposes a method based on Computational Fluid Dynamics (CFD) and the detection of Wind Energy Extraction Latency for a given wind turbine (WT) designed for ultra-short-term (UST) wind energy forecasting over complex terrain. The core of the suggested modeling approach is the Wind Spatial Extrapolation model (WiSpEx). Measured vertical wind profile data are used as the inlet for stationary CFD simulations to reconstruct the wind flow over a wind farm (WF). This wind field reconstruction helps operators obtain the wind speed and available wind energy at the hub height of the installed WTs, enabling the estimation of their energy production. WT power output is calculated by accounting for the average time it takes for the turbine to adjust its power output in response to changes in wind speed. The proposed method is evaluated with data from two WTs (E40-500, NM 750/48). The wind speed dataset used for this study contains ramp events and wind speeds that range in magnitude from 3 m/s to 18 m/s. The results show that the proposed method can achieve a Symmetric Mean Absolute Percentage Error (SMAPE) of 8.44% for E40-500 and 9.26% for NM 750/48, even with significant simplifications, while the SMAPE of the persistence model is above 15.03% for E40-500 and 16.12% for NM 750/48. Each forecast requires less than two minutes of computational time on a low-cost commercial platform. This performance is comparable to state-of-the-art methods and significantly faster than time-dependent simulations. Such simulations necessitate excessive computational resources, making them impractical for online forecasting. [ABSTRACT FROM AUTHOR]

An auxiliary structure can significantly improve the wind-trapping capacity of the Savonius wind turbine. In this study, a novel auxiliary structure called a wind energy gathering structure (WEGS) is proposed, and its five parameters, namely the lengths of the shrinkage and diffusion tubes, the length of the centerboard, the length of the throat, the length of the wind board, and the shrinkage and diffusion angles, are investigated using computational fluid dynamics (CFD) and Taguchi's method. Meanwhile, Taguchi's method and ANOVA reveal that among the studied parameters, the shrinkage and diffusion angles, the length of the centerboard, and the lengths of the shrinkage and diffusion tubes have a more significant influence on the performance of the WEGS. At a tip speed ratio (TSR) value of 1 and a wind speed of 7 m/s, the optimized combination of the WEGS parameters obtained by Taguchi's method improves the mean torque coefficient of the turbine by 42.1%. Moreover, at other TSRs (0.6–1.2), the turbine with the WEGS also outperforms an open turbine in terms of aerodynamic (increases of 20.1–53%) and lifetime performance. [ABSTRACT FROM AUTHOR]

Gas evolution and flow patterns inside an alkaline electrolyzer cell strongly affect efficiency, although such effects have not been explored in detail to date. The present study aims to critically analyze the dependence of cell performance on the multiphase flow phenomena, defining some key metrics for its assessment using CFD. Six performance indicators, involving gas accumulation, bubble coverage, and flow uniformity, are applied to a 3D CFD model of an alkaline cathodic cell, and possible optimizations of the cell geometry are evaluated. The results demonstrate the complexity of defining the optimal indicator, which strictly depends on the case study and on the analysis at hand. For the cell analyzed herein, the parameters linked to the electrode volume fraction were indicated as the most influential on the cell efficiency, allowing us to define the best geometry case during the optimization. Furthermore, a sensitivity analysis was conducted, which showed that higher mass flow rates are generally preferable as they are linked to higher bubble removal. Higher current densities, allowing enhanced gas production, are instead associated with slightly lower efficiencies and stronger nonuniformity of the electrolyte flow inside the cell. [ABSTRACT FROM AUTHOR]

This study represents the development and optimization of a micro-baffle design to enhance heat transfer in film boiling. Numerical simulations are performed using an open-source computational fluid dynamics (CFD) model, which incorporates the Lee model for momentum source associated with the phase change, and the Volume of Fluid (VOF) method to capture bubble dynamics. A comparison of the numerical results with the previous numerical and experimental data confirmed the validity of the numerical model. The influence of key design parameters was systematically investigated. The results revealed that a vertical baffle provided the maximum performance. The optimal baffle design achieved a 57.4% improvement in the Nusselt number and a 66.4% increase in critical heat flux (CHF). Furthermore, the proposed design facilitated continuous bubble formation, even with a reduced temperature difference between the heated surface and the subcooled liquid, which is crucial for energy-efficient thermal management in engineering systems. Ultimately, this study demonstrates the potential of micro-baffle designs in controlling bubble dynamics and improving heat transfer in film boiling, thereby aiding the design of efficient thermal systems. [ABSTRACT FROM AUTHOR]

Machine learning-based predictions of heat transfer characteristics in lid-driven cavities are transforming the field of computational fluid dynamics (CFD). Lid-driven cavities are a fundamental problem in fluid mechanics, characterized by the motion of a fluid inside a square cavity driven by the motion of one of its walls. The goal of this study was to develop multiple machine-learning regression models and highlight the discrepancies between the predicted and actual average Nusselt numbers. Additionally, the study utilized physics-informed neural networks (PINNs) to model the flow and thermal behavior at both low and high Reynolds numbers. The results were compared among actual data from computational fluid dynamics (CFD) simulations, PINN models trained with CFD data, and purely PINN models created without any prior data input. The findings of this study showed that the random forest model exhibited an exceptional stability in its predictions, consistently maintaining low errors even as the Reynolds number increased compared with other machine-learning regression models. Further, the results of this study in terms of flow and thermal behavior within the cavity were found to depend significantly on the PINN method. The data-driven PINN exhibited a much lower mean average errors at both Reynolds numbers, while the physics-based PINN showed lower physics loss. [ABSTRACT FROM AUTHOR]

In order to investigate the effects of different shapes of hydrogen inlet ports on the behavioral characteristics of hydrogen in Type IV hydrogen storage cylinders under rapid refueling conditions, a mathematical model of hydrogen temperature rise and a three-dimensional numerical analysis model were developed. The rectangular, hexagonal, triangular, Reuleaux triangular, circular, elliptical and conical inlet ports were researched by using computational fluid dynamics methods. The results showed that, for the same refueling flow rate and cross-sectional area, the hydrogen temperature inside a cylinder with a rectangular inlet port is higher and the jet tilt angle is larger than for a hexagonal port, while the thermal stratification phenomenon is not obvious. The hydrogen temperature inside a cylinder with a triangular inlet port is lower than that with a Reuleaux triangle port and the jet tilt angle is larger, and neither has significant thermal stratification. The hydrogen temperature inside a cylinder with a circular inlet port is higher than that with an ellipse port, the jets are not tilted on either one, and the phenomenon of thermal stratification is prominent. Further analysis indicated that enlarging the cross-sectional area and increasing the refueling flow rate results in a higher hydrogen temperature and intensified thermal stratification and an upward-angled jet can effectively reduce or eliminate thermal stratification. [ABSTRACT FROM AUTHOR]

With the breakthrough in mixing hydrogen into natural gas pipelines for urban use, the widespread application of hydrogen-blended natural gas (HBNG) in energy delivery is imminent. However, this development also introduces significant safety concerns due to notable disparities in the physical and chemical properties between methane and hydrogen, heightening the risks associated with gas leaks. Current models that simulate the diffusion of leaked HBNG from buried pipelines into the atmosphere often employ fixed average leakage rates, which do not accurately represent the dynamic nature of gas leakage and diffusion. This study uses computational fluid dynamics (CFD) 2024R1 software to build a three-dimensional simulation model under a soil–atmosphere coupling model for HBNG leakage and diffusion. The findings reveal that, in the soil–atmosphere coupling model, the gas diffusion range under a fixed leakage rate is smaller than that under a dynamic leakage rate. Under the same influencing factors in calm wind conditions, the gas primarily diffuses in the vertical direction, whereas under the same influencing factors in windy conditions, the gas mainly diffuses in the horizontal direction. [ABSTRACT FROM AUTHOR]

An air-rock bed thermal storage system was designed for small-scale powered generation and analyzed with computational fluid dynamics (CFD) using ANSYS-Fluent simulation. An experimental system was constructed to compare and validate the simulation model results. The storage unit is a cylindrical steel container with granite rock pebbles as a storage medium. The CFD simulation used a porous flow model. Transient-state simulations were performed on a 2D axisymmetric model using a pressure-based solver. During charging, heat input that keeps the bottom temperature at 550 °C was applied to raise the storage temperature. Performance analysis was conducted under various porosities, considering natural and forced convection. The natural convection analysis showed insignificant convection contribution after 10 h of charging, as observed in both average air velocity and the temperature profile plots. The temperature distribution profiles at various positions for both convection modes showed good agreement between the simulation and experimental results. Additionally, both cases exhibited similar temperature growth trends, further validating the models. Forced convection reduced the charging time from 60 h to 5 h to store 70 MJ of energy at a porosity of 0.4, compared to natural convection, which stored only 50 MJ in the same time. This extended charging period was attributed to poor natural convective heat transfer, indicating that relying solely on natural convection for thermal energy storage under the given conditions is not practical. Using a small fan to enhance heat transfer, forced convection is a more practical method for charging the system, making it suitable for power generation applications. [ABSTRACT FROM AUTHOR]

This study proposes novel and modified conventional flow fields for a high-temperature PEM fuel cell, and predicts the fluid dynamic behavior with a 3D, computational fluid dynamics model. Five base flow field patterns (FFPs) are selected: a 4-channel serpentine, a hybrid design, a 2-channel spiral, a dual-triangle sandwich, and a parallel pin-type flow field. For each base FFP, sub-patterns are developed through modification of the channels and ribs. The 4-channel serpentine is taken as the state-of-the-art reference flow field. Simulations are carried out at two different mass flow rates. The result shows that the incorporation of a dead end in flow channels or the merging of channels into a single channel before connecting to the outlet enhances the average and maximum GDL mass flux, but it also increases the pressure drop. The parallel pin-type design-3 and dual-triangle sandwich design-1 exhibit a more even distribution but yield a lower average GDL mass flux than the 4-channel serpentine, which could be beneficial for reducing MEA degradation and thus used at low load conditions where a high mass flux is not needed. In contrast, the uniform hybrid design and 2-channel spiral design-2 provide a higher average and maximum mass flux with a more non-uniform distribution and greater pressure drop. The high average GDL mass flux would be beneficial during high load conditions to ensure enough reactants reach the catalyst. [ABSTRACT FROM AUTHOR]

Hydrokinetic arrays, or farms, offer a promising solution to the global energy crisis by enabling cost-effective and environmentally friendly energy generation in locations with water flows. This paper presents research focused on the design and optimization of a Gorlov-type vertical-axis hydrokinetic turbine array for power generation. The study involved (i) numerical simulations using computational fluid dynamics (CFD) software with the six degrees of freedom (6DoF) tool, (ii) optimization techniques such as response surface methodology, and (iii) experimental testing in natural environments. The objective was to develop an efficient system with low manufacturing and maintenance costs. A key finding was that the separation distance between rotors, both along and across the fluid flow, is a critical parameter in designing hydrokinetic arrays. For this study, a triangular array configuration, termed Triframe, was used, consisting of three Gorlov-type turbines with four blades each. The optimization process led to separation distances based on the diameter (D) of the turbines, with 15.9672D along the fluid flow (X) and 4.15719D across the flow (Y). Finally, an experimental scale model of the hydrokinetic array was successfully constructed and characterized, demonstrating the effectiveness of the optimization process described in this study. [ABSTRACT FROM AUTHOR]

Following the operational success of the Hywind Scotland, Kincardine, WindFloat Atlantic, and Hywind Tampen floating wind farms, the floating offshore wind industry is expected to play a critical role in the global clean energy transition. However, there is still significant work needed in optimizing the design and implementation of floating offshore wind turbines (FOWTs) to justify the widespread adoption of this technology and ensure that it is commercially viable compared to other more-established renewable energy technologies. The present review explores the application of fully coupled computational fluid dynamics (CFD) modeling approaches for achieving the cost reductions and design confidence necessary for floating wind to fully establish itself as a reliable and practical renewable energy technology. In particular, using these models to better understand and predict the highly nonlinear and integrated environmental loading on FOWT systems and the resulting dynamic responses prior to full-scale implementation is of increased importance. [ABSTRACT FROM AUTHOR]

The growing demand to reduce emissions of pollutants and CO2 from internal combustion engines has led to a critical need for the development of ultra-lean burn engines that can maintain combustion stability while mitigating the risk of knock. One of the most effective techniques is the pre-chamber spark-ignition (PCSI) system, where the primary combustion within the cylinder is initiated by high-energy reactive gas jets generated by pilot combustion in the pre-chamber. Due to the complex physical and chemical processes involved in PCSI systems, performing 3D CFD simulations is crucial for in-depth analysis and achieving optimal design parameters. Moreover, combining a detailed CFDs model with a calibrated 0D/1D model is expected to provide a wealth of new insights that are difficult to gather through experimental methods alone, making it an indispensable tool for improving the understanding and optimization of these advanced engine systems. In this context, numerous previous studies have utilized CFD models to optimize key design parameters, including the geometric configuration of the pre-chamber, and to study combustion characteristics under various operating conditions in PCSI engines. Recent studies indicate that several advanced models designed for conventional spark-ignition (SI) engines may not accurately predict performance under the demanding conditions of Turbulent Jet Ignition (TJI) systems, particularly when operating in lean mixtures and environments with strong turbulence–chemistry interactions. This review highlights the pivotal role of Computational Fluid Dynamics (CFDs) in optimizing the design of pre-chamber spark-ignition (PCSI) engines. It explores key case studies and examines both the advantages and challenges of utilizing CFDs, not only as a predictive tool but also as a critical component in the design process for improving PCSI engine performance. [ABSTRACT FROM AUTHOR]

Oil-filled motors (OFMs) are widely used in deep-sea exploration and oil well extraction. During motor operation, the rotor stirs the oil in the air gap, causing viscous loss. Viscous loss affects the temperature distribution inside the motor. Accurately calculating the viscous loss and temperature rise in OFMs can provide a basis for optimizing the motor's structural design. Motor structural parameters, including the rotor's outer diameter, air gap, and slot opening, have a significant impact on viscous loss. The working conditions of OFMs, such as rotor speed and environmental temperature, also affect viscous loss. The viscosity of hydraulic oil is highly influenced by temperature, and changes in viscosity can lead to changes in viscous loss. These changes in viscous loss, in turn, alter the temperature distribution. Therefore, the coupling relationship between viscous loss and temperature must be considered. Additionally, when Taylor vortices occur in the fluid, the surface roughness of the rotor also has a significant influence on viscous loss. Currently, both domestic and international research on viscous loss and thermal analysis struggle to simultaneously consider the coupling of viscous loss and the temperature field, rotor surface roughness, and the effect of motor structure. This paper summarizes the methods used in recent years for studying viscous loss and thermal analysis, and puts forward some suggestions for future research on the coupling of the OFM temperature field and viscous loss. [ABSTRACT FROM AUTHOR]

Lithium ion (Li-ion) battery packs have become the most popular option for powering electric vehicles (EVs). However, they have certain drawbacks, such as high temperatures and potential safety concerns as a result of chemical reactions that occur during their charging and discharging processes. These can cause thermal runaway and sudden deterioration, and therefore, efficient thermal management systems are essential to boost battery life span and overall performance. An electrochemical-thermal (ECT) model for Li-ion batteries and a conjugate heat transfer model for three-dimensional (3D) fluid flow and heat transfer are developed using COMSOL Multiphysics®. These are used within a novel computational fluid dynamics (CFD)-enabled multi-objective optimization approach, which is used to explore the effect of the mini-channel cold plates' geometrical parameters on key performance metrics (battery maximum temperature ( T m a x ), pressure drop ( ∆ P ), and temperature standard deviation ( T σ )). The performance of two machine learning (ML) surrogate methods, radial basis functions (RBFs) and Gaussian process (GP), is compared. The results indicate that the GP ML approach is the most effective. Global minima for the maximum temperature, temperature standard deviation, and pressure drop ( T m a x , T σ , and ∆ P , respectively) are identified using single objective optimization. The third version of the generalized differential evaluation (GDE3) algorithm is then used along with the GP surrogate models to perform multi-objective design optimization (MODO). Pareto fronts are generated to demonstrate the potential trade-offs between T m a x , T σ , and ∆ P . The obtained optimization results show that the maximum temperature dropped from 36.38 to 35.98 °C, the pressure drop dramatically decreased from 782.82 to 487.16 Pa, and the temperature standard deviation decreased from 2.14 to 2.12 K; the corresponding optimum design parameters are the channel width of 8 mm and the horizontal spacing near the cold plate margin of 5 mm. [ABSTRACT FROM AUTHOR]

Wind energy is essential for sustainable energy development, providing a clean and reliable energy source through the wind turbine. However, the vortices and turbulence generated as wind passes through turbines reduce wind speed and increase turbulence, leading to significant power losses for downstream turbines in wind farms. This study investigates wake characteristics in wind turbines by examining the effects of different scale ratios on wake dynamics, using both experimental and numerical approaches, utilizing scaled-down models of the Aeolos H-20 kW turbine at scales of 1:33, 1:50, and 1:67. The experimental component involved wind tunnel tests in an open-circuit tunnel with adjustable wind speeds and controlled turbulence intensity. Additionally, Computational Fluid Dynamics (CFD) simulations were conducted using STAR-CCM+ (Version 15.06.02) to numerically analyze the wake characteristics. Prior to the simulation, a convergence test was performed by varying grid density and y+ values to establish optimized simulation settings essential for accurately capturing wake dynamics. The results were validated against experimental data, reinforcing the reliability of the simulations. Despite minor inconsistencies in areas affected by tower and nacelle interference, the overall results strongly support the methodology's effectiveness. The discrepancies between the experimental results and CFD simulations underscore the limitations of the rigid body assumption, which does not fully account for the deformation observed in the experiment. [ABSTRACT FROM AUTHOR]

This review paper provides an overview of recent advances in computational fluid dynamics (CFD) simulations of ejector pumps for vacuum generation. It examines various turbulence models, multiphase flow approaches, and numerical techniques employed to capture complex flow phenomena like shock waves, mixing, phase transitions, and heat/mass transfer. Emphasis is placed on the comprehensive assessment of flow characteristics within ejectors, including condensation effects such as nucleation, droplet growth, and non-equilibrium conditions. This review highlights efforts in optimizing ejector geometries and operating parameters to enhance the entrainment ratio, a crucial performance metric for ejectors. The studies reviewed encompass diverse working fluids, flow regimes, and geometric configurations, underscoring the significance of ejector technology across various industries. While substantial progress has been made in developing advanced simulation techniques, several challenges persist, including accurate modeling of real gas behavior, phase change kinetics, and coupled heat/mass transfer phenomena. Future research efforts should focus on developing robust multiphase models, implementing advanced turbulence modeling techniques, integrating machine learning-based optimization methods, and exploring novel ejector configurations for emerging applications. [ABSTRACT FROM AUTHOR]

Amidst the growing demand for efficient and sustainable energy storage solutions, Flywheel Energy Storage Systems (FESSs) have garnered attention for their potential to meet modern energy needs. This study uses Computational Fluid Dynamics (CFD) simulations to investigate and optimise the aerodynamic performance of FESSs. Key parameters such as radius ratio, aspect ratio, and rotational velocity were analysed to understand their impact on windage losses and heat transfer. This study reveals the critical role of Taylor–Couette flow on the aerodynamic performance of FESSs. The formation of Taylor vortices within the airgap was examined, demonstrating their effect on temperature distribution and overall system performance. Through a detailed examination of the skin friction coefficient and Nusselt number under different conditions, this study identified a nonlinear relationship between rotor temperature and rotational speed, highlighting the accelerated temperature rise at higher speeds. The findings indicate that optimising these parameters can significantly enhance the efficiency of FESSs, reducing windage losses and improving heat transfer. This research provides valuable insights into the aerodynamic and thermal optimisation of FESSs, offering pathways to improve their design and performance. The results contribute to advancing guidelines for the effective implementation of FESSs in the energy sector, promoting more sustainable energy storage solutions. [ABSTRACT FROM AUTHOR]

This study analyzes the performance degradation of traditional hybrid wind turbines under high blade-tip-speed ratio conditions and proposes solutions through two-dimensional Computational Fluid Dynamics (CFD) simulations. It also introduces the design of two innovative asynchronous-hybrid dual-rotor wind turbines. The results indicate a remarkable 98.5% enhancement in torque performance at low blade-tip-speed ratios with the hybrid wind turbine model. However, as the blade-tip-speed ratio increases, it leads to negative torque generation within the inner rotor of the conventional design, resulting in a reduction of the power coefficient by up to 13.1%. The introduction of the new wind turbine design addresses this challenge by eliminating negative torque at high blade-tip-speed ratios through adjustments in the inner rotor's operating range. This modification not only rectifies the negative torque issue but also enhances the performance of the outer rotor in the leeward region, consequently boosting the overall power coefficient. Moreover, the optimized inner rotor configuration effectively disrupts and shortens the wake length by 16.7%, with this effect intensifying as the rotational speed increases. This optimization is pivotal for enhancing the efficiency of multi-machine operations within wind farms. [ABSTRACT FROM AUTHOR]

To achieve net-zero objectives, the expansion of renewable energy sources is anticipated to be accompanied by an increased use of carbon-free fuels, such as hydrogen. Internationally, there are proposals for transporting hydrogen by synthesizing it into carriers like ammonia or Liquid Organic Hydrogen Carriers (LOHCs). However, considering the energy consumption required for hydrogenation and dehydrogenation processes and the need for high-purity hydrogen production, the development of liquid hydrogen transportation technologies is becoming increasingly important. Liquid hydrogen, with a density approximately one-sixth that of liquid natural gas and a boiling point roughly 90 K lower, poses significant challenges in suppressing and managing boil-off gas during transportation. Slush hydrogen, a mixture of liquid and solid phases, offers potential benefits. with an approximate 15% increase in density and an 18% increase in thermal capacity compared to liquid hydrogen. The latent heat of fusion of solid hydrogen effectively suppresses boil-off gas (BOG), and the increased density can reduce transportation costs. This study experimentally validated the long-duration storage and transportation concept of slush hydrogen by adapting NASA's (National Aeronautics and Space Administration) proposed IRAS (Integrated Refrigeration and Storage) technology for compact and mobile tanks. Slush hydrogen was successfully produced by reaching the triple point of hydrogen, resulting in a composition of 47% solid and 53% liquid, with a density of approximately 80.9 kg/m3. Most importantly, methodologies were presented to observe and measure whether the hydrogen was indeed in the slush state and to determine its density. Additionally, CFD (Computational Fluid Dynamics) analysis was performed using solid hydrogen properties, and the results were compared with experimental values. Notably, this analytical technique can be utilized in designing large-capacity tanks for storing slush hydrogen. [ABSTRACT FROM AUTHOR]

The existing natural gas transportation pipelines can withstand a hydrogen content of 0 to 50%, but further research is still needed on the pathways of NO and CO production under moderate or intense low oxygen dilution (MILD) combustion within this range of hydrogen blending. In this paper, we present a computational fluid dynamics (CFD) simulation of hydrogen-doped jet flame combustion in a jet in a hot coflow (JHC) burner. We conducted an in-depth study of the mechanisms by which NO and CO are produced at different locations within hydrogen-doped flames. Additionally, we established a chemical reaction network (CRN) model specifically for the JHC burner and calculated the detailed influence of hydrogen content on the mechanisms of NO and CO formation. The findings indicate that an increase in hydrogen content leads to an expansion of the main NO production region and a contraction of the main NO consumption region within the jet flame. This phenomenon is accompanied by a decline in the sub-reaction rates associated with both the prompt route and NO-reburning pathway via CHi=0–3 radicals, alongside an increase in N2O and thermal NO production rates. Consequently, this results in an overall enhancement of NO production and a reduction in NO consumption. In the context of MILD combustion, CO production primarily arises from the reduction of CO2 through the reaction CH2(S) + CO2 ⇔ CO + CH2O, the introduction of hydrogen into the system exerts an inhibitory effect on this reduction reaction while simultaneously enhancing the CO oxidation reaction, OH + CO ⇔ H + CO2, this dual influence ultimately results in a reduction of CO production. [ABSTRACT FROM AUTHOR]

The approach for achieving efficient and clean combustion in a diesel–natural gas (NG) heavy-duty engine at low loads was studied by computational fluid dynamics simulation. This study proposed the concentration and temperature-stratified combustion technology and clarified its mechanism. The results revealed that different stratified combustions can be organized by controlling the pressures, timings, and durations of diesel and NG injections, and stratified combustion can be classified into moderate, lean, and rich stratified combustion modes. Efficient and clean combustion can be realized simultaneously at low engine loads: the gross indicated thermal efficiency (ITEg) of engine breakthrough was improved to 47.9%, and the indicated-specific emissions of unburned hydrocarbon (ISUHC) were greatly reduced to 1.6 g/kWh, while the indicated-specific emissions of nitrogen oxide (ISNOx) remained at 0.6 g/kWh. Moreover, the detailed analysis of three typical stratified combustion modes demonstrates that coupling control of the concentration and temperature of the charge is the key to obtaining excellent engine performance. Most of the NG-stratified mixture should burn in the react ratio range of 0.4 to 0.8 for low unburned hydrocarbon emissions, low nitrogen oxides emissions, and rapid combustion. The proper temperature stratification should ensure that a high-temperature charge is around the over-lean NG mixture. This study can provide the fundamentals of stratified combustion control and feasible solutions for commercial applications of NG engines. [ABSTRACT FROM AUTHOR]

This paper employs Computational Fluid Dynamics (CFD) methods to develop a numerical model of an oscillating buoy-wave energy converter and investigates the impact of steep seabed topography near islands and reefs on its performance. The model's accuracy is validated by comparison with experimental results from the published literature. Subsequently, the influence of deployment location, reef-front slope gradient, and reef-flat water depth on the device's performance is analyzed. The results indicate that the strategic utilization of steep seabed topography can significantly enhance the energy capture efficiency of the device in long-wave regions. This study provides valuable references for the design and deployment of oscillating buoy-wave energy converters in near-reef areas. [ABSTRACT FROM AUTHOR]

The growing interest in renewable energy solutions for sustainable development has significantly advanced the design and analysis of floating offshore wind turbines (FOWTs). Modeling FOWTs presents challenges due to the considerable coupling between the turbine's aerodynamics and the floating platform's hydrodynamics. This review paper highlights the critical role of computational fluid dynamics (CFD) in enhancing the design and performance evaluation of FOWTs. It thoroughly evaluates various CFD approaches, including uncoupled, partially coupled, and fully coupled models, to address the intricate interactions between aerodynamics, hydrodynamics, and structural dynamics within FOWTs. Additionally, this paper reviews a range of software tools for FOWT numerical analysis. The research emphasizes the need to focus on the coupled aero-hydro-elastic models of FOWTs, especially in response to expanding rotor diameters. Further research should focus on developing nonlinear eddy viscosity models, refining grid techniques, and enhancing simulations for realistic sea states and wake interactions in floating wind farms. The research aims to familiarize new researchers with essential aspects of CFD simulations for FOWTs and to provide recommendations for addressing challenges. [ABSTRACT FROM AUTHOR]

Deep-sea minerals are regarded as the most economically viable and promising mineral resource. Vertical hydraulic lifting represents one of the most promising methods for deep-sea mining lifting systems. To mitigate the potential for clogging due to the aggregation of particles in vertical pipe transport during deep-sea mining operations, this paper employs numerical simulations utilizing the computational fluid dynamics and discrete element method (CFD-DEM) model to investigate the swirling flow transportation of mineral particles. The characteristics of the swirling flow field and the motion law of double-size particles at different swirling ratios are investigated. The findings demonstrate that, in comparison to axial transport within the pipeline, the particle movement observed in swirling flow transport exhibits an upward spiral trajectory. This phenomenon facilitates the orderly movement of particles, thereby enhancing the fluidization of particles within the pipeline. An increase in the swirling ratio (SR) has a considerable impact on the velocity within the pipe. The tangential velocity distribution undergoes a gradual transition from centrosymmetric to non-centrosymmetric as the distance from the inlet increases. An increase in the SR results in an enhanced aggregation of particles at the wall, accompanied by a notable rise in the local particle concentration. The value of SR = 0.3 represents a critical threshold. When SR exceeds this value, the distribution of particles in the cross-section reaches a relatively stable state, rendering it challenging to further alter the distribution and concentration of particles, even if the SR is augmented. Furthermore, the maximum local particle concentration in the vicinity of the wall tends to be stable. These results provide valuable insights into vertical pipe swirling flow transport for deep-sea mining. [ABSTRACT FROM AUTHOR]

The precise design of heat exchangers in automobile air conditioning systems for more sustainable electric vehicles requires an enhanced assessment of CFD mechanistic models for the subcooled boiling flow of pure eco-friendly refrigerant. Computational Multiphase Flow Dynamics (CMFDs) relies on two-phase closure models to accurately depict the complex physical phenomena involved in flow boiling. This paper thoroughly examines two-phase CMFD flow boiling, incorporating sensitivity analyses of critical parameters such as boiling closures, momentum closures, and population balance models. Three datasets from the DEBORA experiment, involving vertical pipes with subcooled boiling flow of refrigerant at three different pressures and varying levels of inlet liquid subcooling, are used for comparison with CFD simulations. This study integrates nucleate site density and bubble departure diameter models to enhance wall boiling model accuracy. It aims to investigate various interfacial forces and examines the S-Gamma and Adaptive Multiple Size-Group (A-MuSiG) size distribution methods for their roles in bubble break up and coalescence. These proposed approaches demonstrate their efficacy, contributing to a deeper understanding of flow boiling phenomena and the development of more accurate models. This investigation offers valuable insights into selecting the most appropriate sub-closure models for both boiling closure and momentum closure in simulating boiling flows. [ABSTRACT FROM AUTHOR]

Nuclear energy, as an important component of the power system, has become a key focus of future energy development research. Various equipment and pipelines in nuclear power plants require regular inspection, maintenance, and repair. The pipelines in nuclear power plants are typically large, necessitating a device that can locally isolate sections of the pipeline during maintenance operations. Ice plug freezing technology, an economical and efficient method for maintaining and replacing equipment without shutdown, has been widely applied in nuclear power plants. The structure of the ice plug jacket, a type of low-temperature jacket heat exchanger, affects the flow path of the working fluid within the jacket and consequently impacts heat transfer. This study utilizes Computational Fluid Dynamics (CFD) to establish five types of jacket structures: standard, center-offset (center-in, side-out), helical, helical fin, and labyrinth. The effects of different structures on the freezing characteristics of ice plugs are analyzed and compared. The research indicates that the labyrinth jacket enhances the heat transfer performance between liquid nitrogen and the liquid inside the pipe, forming a larger ice layer at the same liquid nitrogen flow rate. Additionally, the standard jacket has the shortest sealing time at high liquid nitrogen flow rates. [ABSTRACT FROM AUTHOR]

Underground gas storage (UGS) is a beneficial economic method of compensating for the imbalance between natural gas supply and demand. This paper addresses the problem of a lack of research on the two-phase distribution pattern and seepage law during the water–gas alternated flooding in gas storage reservoirs. The study constructed a three-dimensional digital core of the aquifer reservoir based on Computed Tomography (CT) scanning technology, and extracted the connecting pore structure to establish the tetrahedral mesh model. A two-phase microscopic seepage model was established based on the Volume of Fluid (VOF)method, and microscopic gas and gas–liquid two-phase unsaturated microscopic seepage simulation was carried out. The results show that the effective reservoir capacity increases with the increase in the number of alternated flooding cycles. The irreducible water is mainly distributed in the dead-end of the pore space and small pore throats, and the residual gas is mainly distributed as a band in the gas–water interface and the dead-end of the pore space of the previous round. The reservoir capacity can be increased by appropriately increasing the intensity of injection and extracting and decreasing the pressure of the reservoir. [ABSTRACT FROM AUTHOR]

High-resolution wind datasets are crucial for ultra-short-term wind forecasting. Penetration of WT installations near urban areas that are constantly changing will motivate researchers to understand how to adapt their models to terrain changes to reduce forecasting errors. Although CFD modelling is not widely used for ultra-short-term forecasting purposes, it can overcome such difficulties. In this research, we will spatially extrapolate vertical profile LIDAR wind measurements into a 3D wind velocity field over a large and relatively complex terrain with the use of stationary CFD simulations. The extrapolated field is validated with measurements at a hub height of three WTs located in the area. The accuracy of the model increases with height because of the terrain anomalies and turbulence effects. The maximum MAE of wind velocity at WT hub height is 0.81 m/s, and MAPE is 7.98%. Our model remains accurate even with great simplifications and scarce measurements for the complex terrain conditions of our case study. The models' performance under such circumstances establishes it as a promising tool for the evolution of ultra-short-term forecasting as well as for the evaluation of new WT installations by providing valuable data for all models. [ABSTRACT FROM AUTHOR]

Examining dual vertical-axis wind turbines (VAWTs) across various turbulence scenarios is crucial for advancing the efficiency of urban energy generation and promoting sustainable development. This study introduces a novel approach by employing two-dimensional numerical analysis through computational fluid dynamics (CFD) software to investigate the performance of VAWTs under varying turbulence intensity conditions, a topic that has been relatively unexplored in existing research. The analysis focuses on the self-starting capabilities and the effective utilization of wind energy, which are key factors in urban wind turbine deployment. The results reveal that while the impact of increased turbulence intensity on the self-starting performance of VAWTs is modest, there is a significant improvement in wind energy utilization within a specific turbulence range, leading to an average power increase of 1.41%. This phenomenon is attributed to the more complex flow field induced by heightened turbulence intensity, which delays the onset of dynamic stall through non-uniform aerodynamic excitation of the blade boundary layer. Additionally, the inherent interaction among VAWTs contributes to enhanced turbine output power. However, this study also highlights the trade-off between increased power and the potential for significant fatigue issues in the turbine rotor. These findings provide new insights into the optimal deployment of VAWTs in urban environments, offering practical recommendations for maximizing energy efficiency while mitigating fatigue-related risks. [ABSTRACT FROM AUTHOR]

Small wind turbines operating in low wind speed regions have not had any significant success. In addition, small wind speed regions occupy a large area of the world, so they represent a potential area for installing small wind turbines in the future. In this paper, a method to design an efficient airfoil for small wind turbines in low wind speed conditions using XFLR5 and CFD simulations is implemented. Because the impact of the airflow on the blade surface under low Re number conditions can change suddenly for small geometries, designing the airfoil shape to optimize the aerodynamic performance is essential. The tuning of the key geometric parameters using inversion techniques for better aerodynamic performance is presented in this study. A two-dimensional model was used to consider the airflow on the airfoil surface with differences in the angle of attack. The original S1010 airfoil was used to design a new airfoil for increasing the aerodynamic efficiency by using V6.57 XFLR5 software. Subsequently, the new VAST-EPU-S1010 airfoil model was adjusted to the maximum thickness and the maximum thickness position. It was simulated in low wind speed conditions of 4–6 m/s by a computational fluid dynamics simulation. The lift coefficient, drag coefficient, and CL/CD coefficient ratio were evaluated under the effect of the angle of attack and the maximum thickness by using the k-ε model. The simulation results show that the VAST-EPU-S1010 airfoil achieved the greatest aerodynamic efficiency at an angle of attack of 3°, a maximum thickness of 8%, and a maximum thickness position of 20.32%. The maximum value of CL/CD of the new airfoil at 6 m/s was higher than at 4 m/s by about 6.25%. [ABSTRACT FROM AUTHOR]

The investigation of aerodynamics and the establishment of flow patterns around finite-length cylinders with various end shapes in a free, boundless air flow with longitudinal and transverse flow over a wide range of geometric and regime parameters is sketchy and does not have a wide range of geometric and regime parameters. This, in turn, affects the entire aerodynamics of the streamlined body. This paper considers the numerical simulation of a wind turbine made of combined blades. CFD (computational fluid dynamics) methods based on the realisable k-ε turbulence model were used in the study. The results on the influence of the position of the fixed blade on the angle of inclination are obtained (0°, 15°, 30°, 45°, and 60°). The authors found that the pressure of a fixed blade at an optimal angle increases the power coefficient Cp by 35–40%. The dependence of the Cp power coefficient on the rotational speed (speed coefficient) for a three-bladed wind turbine was also established, and it was determined that the maximum value of Cp = 0.28 at Z = 4.9. Based on the results obtained, it was determined that the wind turbine has a maximum power coefficient at an angle of inclination of 0 degrees. [ABSTRACT FROM AUTHOR]

This paper focuses on proton exchange membrane fuel cell (PEMFC) operation at current densities in the order of 6 A/cm2. Such high current densities are conceivable when the traditional carbon fiber papers are replaced with perforated metal plates as the gas diffusion layer to enhance waste heat removal, and at the same time the relative humidity inside the fuel cell is kept below 100% by applying appropriate operating conditions as was found in previous one-dimensional modeling work. In the current paper, we applied a three-dimensional, multi-phase computational fluid dynamics model based on Ansys-CFX to obtain additional insight into the underlying physics. The calculated pressure drops are in very good agreement with previous one-dimensional modeling work, and the current densities in all case studies are in the order of 5–6 A/cm2, but different from the previous one-dimensional study, the results suggest that the relative humidity is very close to 100% throughout the entire channel length when the inlet relative humidity is 100%, ensuring best hydration cell conditions and hence best performance. Importantly, the model results suggest that fuel cell performance at a high current density in conjunction with relatively low stoichiometric flow ratios around 1.5–2 is possible. [ABSTRACT FROM AUTHOR]

To investigate the impact of blending natural gas with hydrogen on the combustion performance of partially premixed gas water heaters, a framelet-generated manifold (FGM) was employed for lower-order simulation of combustion processes. Coupled with the 30-step methane combustion mechanism simplified by GRI3.0, a three-dimensional computational fluid dynamics (CFD) simulation of the combustion chamber of a partially premixed gas water heater was carried out. A numerical simulation was performed to analyze the combustion process of a mixture including 0–40% natural gas and hydrogen in the combustion chamber of a partially premixed gas water heater. The results indicate that the appropriate hydrogen blending ratio for some premixed gas water heaters should be less than 20%. Furthermore, it was observed that after blending hydrogen, there was a significant increase in the combustion temperature of the water heater. Additionally, there was a slight increase in NOx. [ABSTRACT FROM AUTHOR]

The need for a cleaner and more efficient transportation sector emphasizes the development of new technologies aimed at the integrated reduction of pollutant emissions and increases in efficiency. Among these, promising technologies such as low-temperature combustion (LTC) systems operate in the field of the combustion physics, combining the attributes of both spark-ignited (SI) and compression-ignited (CI) engines. In particular, in a gasoline compression ignition (GCI) engine, gasoline is injected in closely spaced multiple pulses near the top dead center (TDC), creating a highly stratified charge which locally auto-ignites based on the thermodynamic conditions. In this work, a sectorial mesh of the combustion chamber was built. Initial and boundary conditions were set according to a one-dimensional model of the engine from a GT-suite platform. Then, a dedicated Matlab R2023b code was used to capture the effect of the pressure wave propagation on the shape of the fuel mass rate in closely spaced multiple injection events. Finally, a 3D-CFD code was validated comparing pressure trace, rate of heat release (RoHR) and emissions with experimental data provided by the test bench. The results highlight the robustness of the tabulated combustion model, which is able to capture the auto-ignition delay with a considerably low amount of computational time compared to common detailed kinetic solvers. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive three-dimensional Computational Fluid Dynamics (CFD) analysis of the pre-cooling process of a Type B LNG tank using various refrigerants, including liquid nitrogen (LN), nitrogen gas (NG), liquefied natural gas (LNG), boil-off gas (BOG), and their combinations. The simulation model accounts for phase change (through the mixture multiphase model), convective heat transfer, and conjugate heat exchange between the fluid and the tank structure. The results indicate that liquid nitrogen is the most efficient refrigerant, achieving the highest cooling rate through both latent and sensible heat. LNG also demonstrated a relatively high cooling rate, 79% of that of liquid nitrogen. Gas-only pre-cooling schemes relying solely on sensible heat exhibited slower cooling rates, with BOG achieved 79.4% of the cooling rate of NG. Mixed refrigerants such as NG + LN and BOG + LNG can achieve comparable, while slightly slower, cooling than the pure liquid refrigerants, outperforming gas-only strategies. A further assessment of the heat transfer coefficient suggests the mixed cooling schemes have almost identical heat transfer coefficient on the inner tank surface to the liquid cooling scheme, over 5% higher than the gas refrigerants. The study also highlighted the uneven temperature distribution within the tank due to the bulkhead's blockage effect, which can induce significant thermal stress and potentially compromise structural integrity. Mixed schemes exhibit thermal gradients higher than those of gas schemes but lower than those of liquid schemes, while achieving cooling speeds comparable to liquid schemes if the inlet velocity of the refrigerants is properly configured. These findings offer valuable insights for developing safer and more efficient pre-cooling procedures for Type B LNG tanks and similar cryogenic storage tanks. [ABSTRACT FROM AUTHOR]

Operating centrifugal pumps under two-phase flow conditions presents challenges such as phase separation, cavitation, and flow instabilities, compromising reliability and performance. A specialized design is crucial to mitigate these issues. This study utilized computational fluid dynamics (CFDs) to understand two-phase flow behavior and assess the impact of different blade geometries on pump performance under such conditions. For this purpose, the inhomogeneous multiphase model was employed, wherein the momentum and continuity flow equations were individually solved for each phase across three different impellers with varying blade angle distributions. The computational results indicated higher gas concentrations on the pressure side of the blade, with gas pocket size correlating with flow rate and inlet gas concentration. The blade angle distribution's effect was more pronounced with increased gas concentrations, while a tendency of gas bubbles to coalesce towards the impeller shroud was also observed. The presence of gas promoted flow recirculation and separation, substantially reducing impeller performance. Blade angle distribution critically influenced the flow field, affecting flow separation, stability, efficiency, and overall performance, highlighting the importance of optimized blade design for enhanced centrifugal pump performance in liquid–gas two-phase flow conditions. [ABSTRACT FROM AUTHOR]

Modeling the atmospheric boundary layer (ABL) in the area of a wind farm using computational fluid dynamics (CFD) methods allows us to study the characteristics of air movement, the shading effect, the influence of relief, etc., and can be actively used in studies of local territories where powerful wind farms are planned to be located. The operating modes of a wind farm largely depend on meteorological phenomena, the intensity and duration of which cause suboptimal operating modes of wind farms, which require the use of modern tools for forecasting and classifying precipitation. The methods and approaches used to predict meteorological phenomena are well known. However, for designed and operated wind farms, the influence of meteorological phenomena on the operating modes, such as freezing rain and hail, remains an urgent problem. This study presents a multi-layered neural network for the classification of precipitation zones, designed to identify adverse meteorological phenomena for wind farms according to weather stations. The neural network receives ten inputs and has direct signal propagation between six hidden layers. During the training of the neural network, an overall accuracy of 81.78%, macro-average memorization of 81.07%, and macro-average memorization of 75.05% were achieved. The neural network is part of an analytical module for making decisions on the application of control actions (control of the boundary layer of the atmosphere by injection of silver iodide, ionization, etc.) and the formation of the initial conditions for CFD modeling. Using the example of the Ulyanovsk wind farm, a study on the movement of air masses in the area of the wind farm was conducted using the initial conditions of the neural network. Digital models of wind turbines and terrain were created in the Simcenter STAR-CCM+ software package, version 2022.1; an approach based on a LES model using an actuating drive disk model (ADM) was implemented for modeling, allowing calculation with an error not exceeding 5%. According to the results of the modeling of the current layout of the wind turbines of the Ulyanovsk wind farm, a significant overlap of the turbulent wake of the wind turbines and an increase in the speed deficit in the area of the wind farm were noted, which significantly reduced its efficiency. A shortage of speed in the near and far tracks was determined for special cases of group placement of wind turbines. [ABSTRACT FROM AUTHOR]

This study reviews existing simulation models and describes a selected model for analysing combustion dynamics in hydrogen and natural gas mixtures, specifically within non-ferrous melting furnaces. The primary objectives are to compare the combustion characteristics of these two energy carriers and assess the impact of hydrogen integration on furnace operation and efficiency. Using computational fluid dynamics (CFD) simulations, incorporating actual furnace geometries and a detailed combustion and NOx emission prediction model, this research aims to accurately quantify the effects of hydrogen blending. Experimental tests on furnaces using only natural gas confirmed the validity of these simulations. By providing precise predictions for temperature distribution and NOx emissions, this approach reduces the need for extensive laboratory testing, facilitates broader exploration of design modifications, accelerates the design process, and ultimately lowers product development costs. [ABSTRACT FROM AUTHOR]

This research investigates the energy efficiency of a novel double-glazing system incorporating solid–solid phase change materials (SSPCMs), which offer significant advantages over traditional liquid–solid phase change materials. The primary objective of this study is to develop a 3D numerical model using the finite volume method, which will be followed by a parametric study under real climatic boundary conditions. A proposed double-glazing setup featuring a 2 mm layer of SSPCM applied on the inner glass pane within the air gap is modeled and analyzed. The simulations consider various transient temperatures and ranges of the SSPCM to evaluate the energy performance of the system under different weather conditions of Miami, FL during the coldest and hottest days of the year, both in sunny and cloudy conditions. The results demonstrate a notable improvement in energy performance compared to standard double-glazing windows (DGWs), with the most efficient SSPCM configuration exhibiting a phase transition temperature and range of 25 °C and 1 °C, respectively. This configuration achieved energy savings of 24%, 26%, and 23% during summer sunny, winter sunny, and winter cloudy days, respectively, relative to DGWs during cooling and heating degree hours. However, a 3% energy loss was observed during summer cloudy days. Overall, the findings of this study have shown the potential for energy savings by incorporating SSPCM with suitable thermophysical properties into double-glazing systems. [ABSTRACT FROM AUTHOR]

A large proportion of building energy consumption in tropical countries like Thailand primarily comes from air conditioning systems used to maintain the comfort level of building occupants. This paper aims to evaluate the performance of an alternative cooling system based on the evaporative principle in terms of thermal characteristics and energy consumption. A simulation model using computational fluid dynamics (CFD) software ANSYS version 16.0 and an actual experimental setup at the laboratory level were built to verify the results of the proposed cooling system. Additionally, factors that influence performance, such as components of the building envelope and the building's orientation, are considered. This research aims to demonstrate the impact of building envelope material and building characteristics on the energy usage in air conditioning systems and to propose an energy-efficient cooling system. The results demonstrate that the proposed cooling system can reduce the temperature inside the building. However, the characteristics of the building also affect the energy performance. Thus, the proposed cooling system, in combination with an efficient envelope material, can achieve energy savings of around 35–43%. Therefore, a combination of the proposed cooling system and optimal building design can ensure comfort for building occupants while saving energy. [ABSTRACT FROM AUTHOR]

This work presents a comprehensive study of the burst of an LPG tank in Gravedona, Italy. The possible causes of the burst were investigated through analytical methods and numerical simulations. That is, an analytical lumped system analysis was conducted to accurately predict the thermodynamic properties of the LPG–air mixture within the tank during filling operations. Additionally, computational fluid dynamics (CFD) simulations were carried out to (i) better capture local effects and (ii) determine if the mixture reached explosive conditions during these operations. The likelihood that possible mechanical defects led to the burst of the tank during filling operations was also evaluated through numerical simulations. The proposed methods were validated against experimental observations, confirming their accuracy and reliability. Furthermore, a specifically developed analytical model was used to describe the tank's dynamic response after the burst. The results provided a comprehensive understanding of the cause of the burst thanks to the combination of analytical models and numerical simulations. The derived insights not only pinpointed the factors leading to the incident, but also provided valuable perspectives for predicting and preventing similar occurrences. [ABSTRACT FROM AUTHOR]

In the present study, using a combination of theoretical discussions, practical examples, and case studies, we sought to gain a comprehensive understanding of how numerical solutions could be used to improve the design and optimize the thermal efficiency of a heat exchanger that utilizes wastewater to reduce the domestic consumption of hot water. To this end, we developed a validated numerical model. We also carried out simulations and experiments, the results of which are presented in this paper. The novelty of this work derives from our use of a new heat exchanger design for a domestic shower, and from the presented experimental–numerical evidence that proves its efficiency. We found that use of our newly designed appliance improved thermal efficiency from 14% to 27%. Moreover, we estimated that the cost of manufacturing and installing such a device did not exceed that of a widely available drain grid. Using our newly designed exchanger, a family of four living in Poland could save EUR 38 (at 2022 values) and reduce CO2 emissions by 192 kg. An average European family could save EUR 68 and reduce CO2 emissions by 76 kg. [ABSTRACT FROM AUTHOR]