Search Results (158)

The frictional resistance of impeller machinery blades such as aircraft engines, gas turbines, and wind turbines has a decisive impact on their efficiency and energy consumption. Inspired by the micro-tooth structure on the surface of shark skin, microstructural drag reduction technology has become a cutting-edge research direction for improving aerodynamic performance and a continuous focus of researchers over the past 20 years. However, the significant difficulty in fabricating microstructures on three-dimensional curved surfaces has led to the limited widespread application of this technology in engineering. Addressing the issue of drag reduction and efficiency improvement for small axial flow fans (local Reynolds number range: (36,327–40,330), this paper employs Design of Experiments (DOE) combined with high-precision numerical simulation to clarify the drag reduction law of bionic microgroove surfaces and determine the dimensions of bionic microstructures on fan blade surfaces. The steady-state calculation uses the standard k-ω model and simpleFoam solver, while the unsteady Large Eddy Simulation (LES) employs the pimpleFoam solver and WALE subgrid-scale model. The dimensionless height (h⁺) and width (s⁺) of microgrooves are in the range of 8.50–29.75, and the micro-grooved structure achieves effective drag reduction. The microstructured surface is fabricated on the suction surface of the blade via a spray coating process, and the dimensions of the microstructures are determined according to the drag reduction law of grooved flat plates. Aerodynamic performance tests indicate that the shaft power consumed by the bionic fan blades during the tests is significantly reduced. The maximum static pressure efficiency of the bionic fan with micro-dimples is increased by 2.33%, while that of the bionic fan with micro-grooves is increased by 3.46%. The fabrication method of the bionic microstructured surface proposed in this paper is expected to promote the engineering application of bionic drag reduction technology. Full article

Short fibre-reinforced adhesives (SFRAs) are increasingly used in wind turbine blades to enhance stiffness and fatigue resistance, yet their heterogeneous microstructure poses significant challenges for predictive modelling. This study presents a fully automated digital workflow that integrates micro-computed tomography (µCT), image processing, and finite element modelling (FEM) to investigate the mechanical response of SFRAs. Our aim is also to establish a computational foundation for data-driven modelling and future AI surrogates of adhesive joints in wind turbine blades. High-resolution µCT scans were denoised and segmented using a hybrid non-local means and Gaussian filtering pipeline combined with Otsu thresholding and convex hull separation, enabling robust fibre identification and orientation analysis. Two complementary modelling strategies were employed: (i) 2D slice-based FEM models to rapidly assess microstructural effects on stress localisation and (ii) 3D voxel-based FEM models to capture the full anisotropic fibre network. Linear elastic simulations were conducted under inhomogeneous uniaxial extension and torsional loading, revealing interfacial stress hotspots at fibre tips and narrow ligaments. Fibre clustering and alignment strongly influenced stress partitioning between fibres and the matrix, while isotropic regions exhibited diffuse, matrix-dominated load transfer. The results demonstrate that image-based FEM provides a powerful route for structure–property modelling of SFRAs and establish a scalable foundation for digital twin development, reliability assessment, and integration with physics-informed surrogate modelling frameworks. Full article

This study presents the development and evaluation of a technology for producing geopolymer-based granulates, which act as sustainable substitutes for natural aggregates by utilizing waste materials. The technology is demonstrated to be energy-efficient compared to other manufactured aggregate processes (such as sintering), as it relies on a cold-bonding process and achieves self-hardening at room temperature. The granulation of geopolymer materials using an intensive counter-current mixer represents an innovative solution in the field of producing substitutes for natural aggregates. Coal fly ash (CFA) was used as the primary aluminosilicate precursor, with composite regrind from decommissioned wind turbine blades (CR) and steelmaking dust (SD) tested as additives. Reactive solids and alkaline activator liquids were mixed and granulated in a single operation using an intensive counter-current mixer; moistening and surface powdering were applied to improve granule sphericity. The granules were cold-cured at room temperature and characterized after 28 days by grain size distribution, crushing resistance, water absorption, abrasion (micro-Deval), SEM/EDS and leaching tests. The results indicate that the additives significantly improved the mechanical performance: PM + PK granules reached crushing strengths > 6 MPa, while CFA + SD granules reached > 11 MPa, exceeding many commercial lightweight aggregates (such as LECA or Lytag), as detailed in the paper. The CFA + CR granulates exhibited a compact microstructure and the effective immobilization of several heavy metals, whereas the CFA + DS samples demonstrated the excessive leaching of Cr, Pb and Mo. The process achieved a high solid-to-liquid ratio (>2.0), reducing activator consumption. Composite regrind is recommended as a promising additive. Full article

Leading-edge erosion (LEE) of wind-turbine blades, driven primarily by rain erosion, particulate erosion, and environmental ageing, remains one of the most pervasive causes of performance loss and maintenance cost in offshore and onshore wind farms. Self-healing coatings, which autonomously or semi-autonomously restore barriers and mechanical function after damage, promise a paradigm shift in blade protection by combining immediate impact resistance with in-service reparability. This review surveys the state of the art in self-healing coating technologies (intrinsic chemistries such as non-covalent interactions or dynamic covalent bonds; extrinsic systems including micro/nanocapsules and microvascular networks) and evaluates their suitability for anti-erosion, mechanical robustness, and multifunctional protection of leading edges. The outcomes of theoretical, experimental, modelling and field-oriented studies on the leading-edge protection and coating characterisation identify which self-healing concepts best meet the simultaneous requirements of toughness, adhesion, surface finish, and long-term durability of wind blade applications. Key gaps are highlighted, notably trade-offs between healing efficiency and mechanical toughness, challenges in large-area and sprayable application methods, and the need for standardised characterisation and testing of self-healing coating protocols. We propose a roadmap for targeted materials research, accelerated testing, and field trials. This review discusses recent studies to guide materials scientists and renewable-energy engineers toward promising routes to deployable, multifunctional, self-healing anti-erosion coatings, especially for wind-energy infrastructure. Full article

Aiming at the nonlinear high-frequency micro-vibration (HFMV) phenomenon that would cause hidden faults of blade fracture failure of a wind turbine, this study calibrated a new type of HFMV aerodynamic force, elaborated on the nonlinear aeroelastic behavior of a 2D airfoil-based structural nonlinear system driven by HFMV aerodynamic forces, and proposed a control plan based on flutter suppression. Based on structural reinforcement based on a nonlinear tuned vibration absorber (NTVA), the flutter wind speed was increased, and artificial structural damping was introduced to analyze the flutter wind speed. The control planning adopted a new unified pitch control system based on the “screw rod–translational slider (nut)” transmission, which was driven by the hydraulic system to drive the ball screw and further drive the slider translation, achieving pitch motion. The control method adopted an optimal trajectory control and the optimal proportional-derivative (PD) controller adjustment technology based on the differential evolution algorithm (DEA). It achieved analysis of flap-wise bending/twist displacement responses, analysis of pitch angle changing, and display of slider driving force. The robustness of the control algorithm was validated by the control results displayed at different wind speeds near the flutter wind speed. The robustness of engineering applications for controlling performance was also validated on the controller hardware-in-the-loop simulation platform through an “object linking and embedding (OLE)” technology based on process control. Finally, the driving performance and wear consumption in engineering applications were discussed. On the basis of ensuring the control effect, the control algorithm was improved, and the fractional-order optimal PD control was adopted, so that the system could stabilize at the “0” consumption state when achieving flutter suppression. Full article

This study introduces a hybrid siting approach for Offshore Wind Farms by combining bottom-fixed and floating wind turbines to address seabed variability in the Mediterranean region. Using Heraklion Bay, Crete, as a case study, a multi-step methodology was adopted, integrating GIS tools, micro-siting analysis, and WAsP simulations to estimate the energy output of three layout scenarios. A comprehensive energy and economic assessment was performed, including key metrics such as Net Present Value, Internal Rate of Return, Payback Period and Levelised Cost of Energy. Scenario 2, which featured a mixed deployment of Vestas and Siemens Gamesa turbines, proved to be the most financially attractive option, yielding the highest Net Present Value (€167 million) and shortest Payback Period. Sensitivity analysis under a 20% reduction in wind resources confirmed the robustness of this scenario. Results demonstrate that hybrid configurations offer a flexible and scalable solution, particularly in island regions with varied bathymetry and seasonal energy demands. The findings highlight the potential of hybrid offshore systems to accelerate energy transitions, optimise spatial utilisation, and improve cost-effectiveness in medium-depth seas. Full article

Newfoundland and Labrador have strong wind and water resources, making hybrid renewable energy systems an important option for the region. This paper presents the design and simulation of a system that combines wind turbines and micro-hydro power to deliver clean electricity for water treatment in remote communities. Many isolated areas still rely on diesel and other conventional sources, which create environmental concerns. Using HOMER Pro 3.17.1 software, the system was modeled based on local climate and resource conditions. Results show that it can produce over 35,000 kWh per year, enough to power a standard water treatment unit serving more than 240 people. By integrating wind and hydro with battery storage, the system ensures stable operation and reduces dependence on fossil fuels. The environmental analysis confirms that it avoids over 9 tons of CO₂ emissions annually. The novelty of this work is its site-specific approach, showing how renewable energy can improve both energy security and water quality in remote Canadian communities while providing a model for sustainable rural development. Full article

This study examines the effects of incorporating recycled carbon fibers obtained from decommissioned wind turbine blades into cementitious composites. An extensive experimental program was carried out, varying fiber content (0–8 kg/m³), fiber length (25, 38, 50 mm), water-to-cement ratio (0.4, 0.5), and cement type (CEM I 42.5, CEM II 42.5R/A-V). The mechanical properties of the fiber-reinforced concretes, including compressive strength, flexural strength, splitting tensile strength, and modulus of elasticity, were evaluated. The addition of recycled carbon fibers significantly improved flexural and splitting tensile strengths, with increases exceeding 60% and 100%, respectively, at the highest fiber dosage (8 kg/m³), attributed to efficient crack-bridging capability. Compressive strength was mainly influenced by the water-to-cement ratio, while the modulus of elasticity showed slight reductions in some mixes due to fiber clustering and increased micro-porosity. Regression analysis indicated that shorter fibers (25 mm) were more effective in enhancing flexural strength, whereas longer fibers (50 mm) improved splitting tensile strength. Classical predictive models generally underestimated the flexural capacity of recycled-carbon-fiber-reinforced concretes, highlighting the need for recalibration. Optical microscopy confirmed uniform fiber dispersion at lower dosages and a dominant pull-out failure mechanism. The findings demonstrate the feasibility of using recycled carbon fibers to enhance the mechanical performance of concrete while supporting sustainability through waste diversion and circular economy strategies. Full article

With the increasing integration of renewable energy, virtual power plants (VPPs) have emerged as key market participants by aggregating distributed energy resources. However, their involvement in electricity markets is increasingly challenged by two major uncertainties: price volatility and the intermittency of renewable generation. This study presents the first application of Information Gap Decision Theory (IGDT) within a two-stage cooperative scheduling framework for VPPs. A novel bidding strategy model is proposed, incorporating both robust and opportunistic optimization methods to explicitly account for decision-making behaviors under different risk preferences. In the day-ahead stage, a risk-responsive bidding mechanism is designed to address price uncertainty. In the real-time stage, the coordinated dispatch of micro gas turbines, energy storage systems, and flexible loads is employed to minimize adjustment costs arising from wind and solar forecast deviations. A case study using spot market data from Shandong Province, China, shows that the proposed model not only achieves an effective balance between risk and return but also significantly improves renewable energy integration and system flexibility. This work introduces a new modeling paradigm and a practical optimization tool for precision trading under uncertainty, offering both theoretical and methodological contributions to the coordinated operation of flexible resources and the design of electricity market mechanisms. Full article

Micro and small wind turbines (MAWTs) are increasingly integrated into residential and prosumer hybrid energy systems. However, their real-world performance often falls short of catalog specifications due to mismatched wind resources, siting limitations, and insufficient attention to human comfort. This paper presents a comprehensive decision-support framework for selecting the type and scale of MAWTs under actual local conditions. The energy assessment module combines aerodynamic performance scaling, wind speed-frequency modeling based on Weibull distributions, turbulence intensity adjustments, and component-level efficiency factors for both horizontal and vertical axis turbines. The framework addresses three key design objectives: efficiency—aligning turbine geometry and control strategies with local wind regimes to maximize energy yield; comfort—evaluating candidate designs for noise emissions, shadow flicker, and visual impact near buildings; and climate adaptation—linking turbine siting, hub height, and rotor type to terrain roughness, turbulence, and built environment characteristics. Case studies from low and moderate wind locations in Central Europe demonstrate how multi-criteria filtering avoids oversizing, improves the autonomy of hybrid PV–wind systems, and identifies configurations that may exceed permissible limits for noise or flicker. The proposed methodology enables evidence-based deployment of MAWTs in decentralized energy systems that balance technical performance, resilience, and occupant well-being. Full article

This research presents an experimental analysis of the influence of atmospheric pressure plasma on the performance of a micro horizontal-axis wind turbine blade. The investigation was conducted using an NACA 4412 airfoil equipped with a dielectric barrier discharge (DBD) plasma actuator. The electrodes were configured asymmetrically, with a 2 mm gap and copper electrodes that are 0.20 mm in thickness. A high voltage of 6 kV was applied, resulting in a current of 0.071 mA and a power output of 0.426 W. Optical emission spectroscopy identified the excited components through the interaction of the high-voltage AC electric field with air molecules: ${\mathrm{N}}_2$, ${\mathrm{N}}_2^{+}$, ${\mathrm{O}}_2^{+}$, and O. The electrohydrodynamic force mainly results from the observed charged ions that, when accelerated by the electric field, transfer momentum to neutral molecules via collisions, leading to the formation of the observed jet plasma. The findings indicated a notable enhancement in aerodynamic performance attributable to the electrohydrodynamic (EHD) flow generated by the plasma. The estimated electrohydrodynamic force ($8.712\times {10}^{-4}$ N) is capable of maintaining the flow attached to the airfoil surface, thereby augmenting flow circulation and, consequently, enhancing the lift force. According to blade element theory, the lift and drag coefficients directly influence the torque and mechanical power generated by the wind turbine rotor. Schlieren imaging was utilized to observe alterations in air density and flow patterns. Lissajous curve analysis was used to examine the electrical discharge behavior, showing that only 7.04% of the input power was converted into heat. This indicates that nearly all input electric energy was transformed into EHD force by the atmospheric pressure plasma. Compared to traditional aerodynamic control methods, DBD actuators are a feasible alternative for small wind turbines due to their lightweight design, absence of moving parts, ability to be surface-embedded without altering blade geometry, and capacity to generate active, dynamic flow control with reduced energy consumption. Full article

Critical components in support structures for wind turbines, flange joints, are fundamental to ensure the structural integrity of mechanical assemblies under varying operational conditions. This paper investigates the structural performance of L-type flange joints, focusing on the influence of bolt grades and bolt pretension through a finite element analysis (FEA) study of its key performance indicators, including stress distribution, deformation, and force–displacement behaviors. This paper studies two high-strength bolt grades, Grade 10.9 and Grade 12.9, and two main steps—first, bolt pretension and, second, external loading (tower shell tensile load)—to investigate the influence on joint reliability and safety margins. The novelty of this study lies in its specific focus on static axial loading conditions, unlike the existing literature that emphasizes fatigue or dynamic loads. Results show that the specimen carrying a higher bolt grade (12.9) has 18% more ultimate load carrying capacity than the specimen with a lower bolt grade (10.9). Increased pretension increases the stability of the joint and reduces the micro-movements between A and B (on model specimen), but could result in material fatigue if over-pretensioned. Comparative analysis of the different bolt grades has provided practical guidance on material selection and bolt pretension in L-type flange joints for wind turbine support structures. The findings of this work offer insights into the proper design of robust flange connections for high-demand applications by highlighting a balance among material properties, bolt pretension, and operational conditions, while also proposing optimized pretension and material recommendations validated against classical analytical models. Full article

The increasing adoption of Renewable Energy Sources (RESs), due to international energy policies mainly related to the decarbonization of electricity production, raises several operating issues for power systems, which need “flexibility” in order to guarantee reliable and secure operation. RESs can be considered examples of Distributed Energy Resources (DERs), which are typically electric power generators connected to distribution networks, including photovoltaic and wind systems, fuel cells, micro-turbines, etc., as well as energy storage systems. In this case, improved operation of power systems can be achieved through coordinated control of groups of DERs by “aggregators”, who also offer a “flexibility service” to power systems that need to be appropriately remunerated according to market rules. The implementation of the aggregator function requires the development of tools to optimally operate, control, and dispatch the DERs to define their overall flexibility as a “market product” in the form of bids. The contribution of the present paper in this field is to propose a new optimization strategy for flexibility bidding to maximize the profit of the aggregator in flexibility markets. The proposed optimal scheduling procedure accounts for important practical and technical aspects related to the DERs’ operation and their flexibility estimation. A case study is also presented and discussed to demonstrate the validity of the method; the results clearly highlight the efficacy of the proposed approach, showing a profit increase of 10% in comparison with the base case without the use of the proposed methodology. It is evident that quantitatively more significant results can be obtained when larger aggregations (more participants) are considered. Full article

Ultra-high-power wind turbine generator bearings are susceptible to micro-spalling and electrical erosion in long-cycle operation, which seriously affects the operating efficiency and service life of the unit. For this reason, this paper adopts a kind of composite grease containing nano-hydroxy magnesium silicate powder and, through the wind turbine assembly machine test and raceway surface analysis, systematically investigates its impact on bearing temperature rise, bearing vibration, and wind turbine power under actual working conditions to meet the lubrication requirements of wind turbine generator bearings. The results of the study showed that the composite grease significantly reduced the operating temperature of the wind turbine bearings under full operating conditions. It is worth noting that the reduction in generator bearing temperature varied among the three turbines due to uncertain environmental factors. In addition, the grease effectively increased the output power of the turbine under medium wind speed loading conditions, further verifying its potential value and practical effect in the application of wind turbines. Full article

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. Full article