With the development of the wind power industry, wind turbine blades are increasingly adopting ultra-large-scale designs. However, as the size of blades continues to increase, existing aerodynamic calculation methods struggle to achieve both relatively high computational accuracy and efficiency simultaneously. To tackle this challenge, this research focuses on the low accuracy issues of the traditional Blade Element Momentum theory (BEM) in predicting the aerodynamic performance of wind turbine blades. Consequently, a correction framework is proposed, to integrate the Computational Fluid Dynamics (CFD) method with the Multilayer Perceptron (MLP) neural network. In this approach, the CFD method is used to predict the airflow characteristics around the blades, and the MLP neural network is employed to model the intricate functional relationships between multiple influencing factors and key aerodynamic parameters. This process results in high-precision predictive functions for key aerodynamic parameters, which are then used to correct the traditional BEM. When this correction framework is applied to the rotor of the IEA 15 MW wind turbine, the effectiveness of MLP in predicting key aerodynamic parameters is demonstrated. The research findings suggest that this framework can enhance the accuracy of BEM aerodynamic load predictions to a level comparable to that of RANS.

The flow rate through hydraulic resistance increases with the pressure drop across it, but this correlation is no longer valid under cavitation conditions. This study investigates choked flow in calibrated screw-in orifices, widely used for control and damping in fluid power components. An experimental campaign was conducted on orifices with diameters ranging from 1 to 0.4 mm at various upstream pressures using hydraulic oil. A computational fluid dynamics (CFD) model was developed and validated against experiments, then used to analyze the effects of geometric parameters such as edge chamfers, hex wrench sockets, and length-to-diameter ratio. From CFD results, an analytical correlation between flow rate and pressure drop was derived, incorporating flow saturation effects. The study revealed that under saturation conditions, flow rate is largely unaffected by geometry, except for the ideal case of a perfectly sharp-edged orifice, which is rarely encountered. Even minimal chamfers of a few hundredths of a millimeter make the restrictor non-ideal. The derived correlation can be integrated into lumped parameter models of fluid power components to account for choked flow.

This paper discusses in detail the classification, historical development, and application of diffuse interface-capturing models (DIMs) for compressible multiphase flows. The work begins with an overview of the development of DIMs, highlighting important contributions and key moments from classical studies to contemporary advances. The theoretical foundations and computational methods of the diffuse interface method are outlined for the full models and the reduced models or sub-models. Some of the difficulties encountered when using DIMs for multiphase flow modelling are also discussed.

Boiling heat transfer plays a crucial role in various engineering applications, requiring accurate numerical modeling to capture phase-change dynamics. This study employs the pseudopotential lattice Boltzmann method (LBM) to simulate boiling heat transfer at different reduced temperatures, aiming to provide deeper insights into bubble dynamics and heat transfer mechanisms. The LBM framework incorporates a multi-relaxation-time approach and the Peng–Robinson equation of state to enhance numerical stability and thermodynamic consistency. Simulations were performed to analyze bubble nucleation, growth, and detachment across varying reduced temperatures, considering the influence of surface wettability, surface tension and gravitational acceleration. The results indicate a strong dependence of bubble behavior on the reduced temperature, affecting both heat flux and boiling regimes. The numerical findings show reasonable agreement with theoretical predictions and experimental trends, validating the effectiveness of the LBM approach for phase-change simulations. Additionally, this study highlights the role of contact angle variation in modifying boiling characteristics, emphasizing the necessity of accurate surface interaction modeling. The outcomes of this work contribute to advancing computational methodologies for boiling heat transfer, supporting improved thermal management in industrial applications.

This review investigates the role of vortex-induced vibrations (VIVs) in hydrokinetic energy harnessing, shedding light on their dual nature as both a challenge in offshore engineering and an untapped resource for renewable energy. VIVs serve as a novel energy source, converting the kinetic energy of fluid flows into mechanical or electrical power. The review discusses the various energy conversion mechanisms, highlighting the unique benefits and challenges of electromagnetic, piezoelectric, and triboelectric systems. A significant emphasis is placed on optimizing VIV energy harnessing to balance maximizing energy output while maintaining structural stability. The review provides insights into the geometric configurations, material properties, and advanced computational methods that are pivotal in this optimisation process. In conclusion, this review provides a comprehensive analysis of the current progress and persistent challenges in VIV research, offering actionable insights and innovative solutions that will advance the field of efficient and sustainable energy.

The current examination used a multi-criteria decision-making (MCDM) approach to optimize the roughness parameters of S-shaped ribs (SSRs) in a solar thermal collector (STC) duct using air as the working fluid. Different SSRs were tested to identify the combination of parameters resulting in the best performance. Geometrical parameters such as relative roughness pitch (PR/eRH) varied from 4 to 12, relative roughness height (eRH/Dhd) from 0.022 to 0.054, arc angle (αArc) from 30° to 75°, and relative roughness width (WDuct/wRS) from 1 to 4. The Nusselt number (NuRP) and friction factor (fRP), findings which impact the STC performance, rely on SSRs. The performance measurements show that no combination of SSR parameters lead to the best enhancement heat transfer rate at low enhancement in the friction. So, a hybrid multi-criteria decision-making strategy using the Analytical Hierarchy Process (AHP) for criterion significance and Multi Attributive Border Approximation Area Comparison (MABAC) for alternative ranking was used to determine which combination of geometrical parameters will result in the optimum performance of a roughened STC. This work employs a hybrid MCDM technique to optimise the effectiveness of an STC roughened with SSRs. To optimize the SSR design parameters, this study used the hybrid AHP-MABAC technique for analytical assessment of a roughened STC. The optimization results showed that the STC roughened with SSRs achieved the optimum performance at PR/eRH = 8, eRH/Dhd = 0.043, αArc = 60° and WDuct/wRS = 3.

This study presents a micro-scale hybrid wind turbine that integrates a Savonius rotor with a Helical Darrieus rotor, aiming to enhance energy conversion efficiency and adaptability for decentralized renewable energy generation. The hybrid design leverages the high torque generation of the Savonius rotor and the aerodynamic efficiency of the Helical Darrieus rotor. Computational analyses using CFD simulations and experimental validation with a 3D-printed prototype in a closed wind tunnel were conducted at speeds ranging from 3 to 8 m/s. The results demonstrate that the hybrid turbine achieves a power coefficient of 0.26 at an optimal tip-speed ratio of 2.7, marking a 180% improvement over standalone Savonius rotors. The hybridization process mitigates the low-speed inefficiencies of the Savonius rotor. It compensates for the high-speed limitations of the Darrieus rotor, resulting in a turbine capable of operating efficiently over a wider range of wind speeds. This balanced integration maximizes energy harvesting and improves adaptability to varying wind conditions, achieving balanced and synergistic performance.

Complex fluid interfaces are commonplace in natural and engineered systems and a major topic in the fields of rheology and soft matter physics, providing boundary conditions for a system’s hydrodynamics. The relationship between structure and function dictates how constituents within complex fluids govern flow behavior via constituents changing conformation in response to the local microenvironment to minimize free energy. Both hydrodynamics, such as shear flow, and the presence of air–liquid interfaces are principal aspects of a complex fluid’s environment. The study of fluid interfaces coupled to bulk flows can be uniquely advanced through experimentation in microgravity, where surface tension containment can be achieved at relatively large length scales. This computational investigation assesses flow in the ring-sheared drop (RSD), a containerless biochemical reactor operating aboard the International Space Station for the study of complex fluids and soft matter physics. Specifically, the hydrodynamic effects of a generalized Boussinesq–Scriven interface with a shear-thinning surface shear viscosity are examined in flow regimes where the air–liquid interface remains coupled to the Newtonian bulk fluid. The results verify this interfacial model’s ability to affect system-wide hydrodynamics under specific parameter regimes, enabling future model validation with high-precision rheological measurements.

A numerical simulation of the circular cylinder as an obstacle in a double forward-facing (DFFS) step was performed. The size and position of the upstream cylinder (c1) and downstream cylinder (c2) were varied to explore their role in heat transfer in both laminar and turbulent conditions. Comparative results of the upper and lower half of the downstream cylinder were plotted as results to understand the heat transfer and flow characteristics around the downstream cylinder due to the effect of the upstream cylinder’s dimension and position. For Re = 800, when the c1 is placed near the bottom of the wall, it results in a pair of rear-side symmetrical vortices, and the c2 cylinder vortices become larger when the c1 is shifted towards the top wall. Additional flow separation happens adjacent to the steps when c1 is greater than c2. These vortices strongly influence the convection heat transfer from the step. However, when Reynolds number (Re) is increased from 800 to 80,000, these vortices’ size is decreased. When c1 moves from 0.375H to 0.75H, the average Nusselt number is increased significantly. Moreover, a hike in Re results in a higher average Nusselt number irrespective of the position of obstacles. The upstream cylinder significantly enhances the Nusselt number when it is placed near the top wall rather than the bottom wall.

This study aims to contribute to the optimization of bio-methanation in bubble columns, making it a more viable alternative to stirred tank reactors. The primary challenge to be addressed is the enhancement of mass transfer, which strongly depends on parameters such as bubble size and gas hold-up. Various disperser designs were examined in a 0.14 mm diameter column, comparing their performance in terms of bubble diameter distribution and gas hold-up. The results indicate that an optimized plate disperser featuring a porous structure outperformed other designs by maintaining high gas retention without significant coalescence. Additionally, newly developed plug-in dispersers allowed for counter-current flow operation, enhancing process flexibility. Commercially available porous pin dispersers produced smaller bubbles compared to the other designs, yielding high gas hold-ups at lower gas velocities. Correlations between disperser type and column design parameters were established, laying the foundation for apparatus optimization. The findings contribute to the development of digital twin models, facilitating the refinement of bio-methanation processes within bubble columns for increased efficiency.