Optimal Blade Research Articles

Study on silage mixing device of King Grass stalk particles based on DEM simulation and bench test

This study designed a silage mixing device for King Grass stalk particles and optimized the core component, the blender, based on the discrete element method (DEM). Through simulation tests, the effect of different blender forms, blade lengths and blade orientations on the Lacey mixing index (LMI) was studied, and the structural form of the blender was selected as the inclined blade-same-up impeller blender. Based on simulation tests, to verify the reliability of the simulation test and further determine the optimal blade inclination angle and mixing speed of the blender, a mixing experimental bench was built for bench tests. The LMI was compared between simulation and bench tests. At three speeds of 60, 80 and 100 r min- −1, the average relative errors are 2.3%, 2.1% and 1.5%, indicating that the simulation test can simulate actual tests well. The central composite design (CCD) was used to establish a binary quadratic regression model of the effects of blade inclination angle and mixing speed on LMI and mixing energy consumption. Using the NSGA-II algorithm, it was determined that the best inclination angle of the mixing blade is 42° and the best mixing speed is 78 r min−1.

Optimization of low-temperature multi-stage submersible pump based on blade load

The multi-stage submersible pump is a power conveyor for low-temperature media, which is conveyed by the rotating of centrifugal impellers. In this study, the impellers of a multi-stage submersible pump were optimized to improve the efficiency under the premise of the constant total blade load and head. Based on the analysis of performance and flow for each stage of the 18-stage submersible pump, the optimization scheme composed of the first stage, the middle stage, and the last stage was determined. The blade outlet angle, average blade wrapping angle, and blade wrapping angle difference were selected as optimization parameters through Plackett–Burman experimental design and significance analysis, and the blade profile was redrawn by changing the blade load distribution. The performance prediction model was built based on the Kriging response surface model, and then, the global optimal blade profile was found by non-dominated Sorting Genetic Algorithm II. The efficiencies of the 3-stage submersible pump and 18-stage submersible pump with optimized impeller increased by 2.35% and 2.01%, respectively. Under the design condition, the flow rate loss and pressure pulsation at the impeller outlet decreased and the stator–rotor interaction between the impeller and guide vane was weakened. This will lead to a reduction in unstable flow such as secondary flow and vortices, and an improvement of flow stability at the impeller outlet.

Parametric study of passive flow enhancement on a magnus VAWT blade using response surface methodology and direct-forcing immersed boundary method

The Magnus vertical axis wind turbine harnesses the principle of the Magnus effect in conjunction with a vertical axis orientation. This mechanism is based on the lift and drag produced by rotating cylinders to propel the rotor and generate power. The proposed method involved installing a flat plate near each rotating cylinder to generate a higher unidirectional torque. As the configuration of the plate affects both the flow pattern and the forces exerted on the blade, the current study aims to identify an optimal blade configuration consisting of a rotating cylinder and a flat plate. A numerical model of the direct-forcing immersed boundary method was used to simulate the flow past a single blade using the static rotor simulation approach, and the Box–Behnken design for the response surface methodology (RSM) was applied to find an optimized flat plate arrangement that would produce the highest mean torque coefficient (CT¯). Three design parameters were examined, specifically the length of the plate (L/D), the gap between the plate and the cylinder (g/D), and the plate's shift angle with respect to the cylinder axis (β). The Reynolds number was 5000, and the cylinder spin ratio (α) was 3. The optimum configuration to achieve a maximum CT¯ was identified at L/D=0.53, g/D=0.1, and β=0°. Validating this optimal CT¯ yielded a value of 0.290, indicating an increase in torque of almost 70% compared to the central design. Furthermore, this value corresponds closely to the predicted result obtained through the RSM optimization method. Considering the flow analysis at various positions, it is crucial to emphasize a critical scenario where the potential for countertorque emerges due to excessive drag at ψ=0° and ψ=315°.

Effects of the morphed trailing-edge flap parameters on the aerodynamic performance of NREL Phase II wind turbine

This study assesses the impact of three morphed trailing-edge flap (MTEF) parameters (flap deflection angle β, flap length b, and flap span length l) on increasing power and axial thrust coefficients and their comprehensive effect on wind turbines using computational fluid dynamics (CFD) method. The detailed analysis is performed on seven morphed blades at eight different wind velocities. The obtained results show that β results in the largest unit power coefficient increase rate and unit axial thrust coefficient increase rate, while l results in the smallest ones. In addition, b results in the largest power-thrust ratio increase rate. The optimum blade is achieved for β = 3°, b/ c = 0.3, and l/ R = 0.3, which results in additional power increase of 15.24% and axial thrust increase of 9.53% at a tip speed ratio of 5.949, compared with the original wind turbine.

Modeling of Wind Power Generation in Tegal Region using Matlab Simulink

The increasing energy demands require larger energy production. However, fossil energy sources are depleting, necessitating the use of renewable energy to replace fossil fuels and meet energy needs in Indonesia. Indonesia has a significant wind energy potential. Wind power generation modeling is carried out in one of the cities in Indonesia, namely Tegal. By using Matlab Simulink, it is expected to assist in predicting renewable energy production. Tegal is one of the regions with high wind speeds in Indonesia, specifically at 3 m/s. From the modeling, the optimal blade radius and rotor angular velocity that can generate maximum power at a wind speed of 3 m/s can be determined. Wind power generation in Tegal with a wind speed of 3 m/s has the potential to produce electrical power of 768.55 W.

Optimal blade design of a spherical water turbine

The use of in-pipe water turbines for small-scale energy harvesting from pipe networks is starting to gain popularity. However, limited research have looked into whether adding helical blade turbines would be feasible with a spherical lift base in a water supply network. Three Naca airfoil (0012, 2412, 4412) were used to study the ratio of lift to drag force for each wing, Benefit from Qblade and ANSYS CFX software, and choosing the wing that has the highest ratio. The study investigates the feasibility of improving the design of spherical turbine blades by increasing the ratio of lift to drag. The results show that the Naca airfoil 4412 had the highest lift-to-drag force ratio, which was equal to 19.95. Through the improvement process for the Naca 4412 airfoil, the increase was made by 13.34 %, and the lift-to-drag ratio became 22.61. The study also dealt with the design of a turbine through the improved airfoil. 230 mm. It has the engineering characteristics of the number of helical blades, 5, The measurement of the blade's length chord 15 % of the turbine diameter, and the Angle of Attack, 9.5°

Knowledge transfer accelerated turbine blade optimization via an sample-weighted variational autoencoder

The aerodynamic shape optimization (ASO) of turbine blades is a typical expensive black-box problem. With the ever increasingly strict design requirements, high-fidelity simulations are demanded, and the related simulation cost increases sharply, which means fewer simulation calls are allowed within a design optimization cycle. Then, the problem as “how to achieve better solution with fewer simulations” becomes rather crucial. Inspired by the concept of transfer learning, we propose to leverage the samples of related completed tasks (also known as source samples) to address the above problem. Specifically, an sample-weighted variational autoencoder (VAE) is proposed, which includes the source samples as part of the training dataset to boost the proportion of high-scoring solution candidates in the learnt design space of target problem, and thus increasing the probability of attaining substantially better solutions. The including of source samples in VAE training also helps to increase the accuracy of reparameterizing the source samples in target design space. Furthermore, a multi-fidelity surrogate is used to guide the optimization search, which extracts information from the source samples to help the algorithm to more quickly arrive at the small neighborhood of the true optimal of the target problem. With the above, a knowledge transfer accelerated aerodynamic shape optimization procedure is proposed for the turbine blade design, labeled as KT-ASO. Through test on a highly-loaded low-pressure turbine blade and compared against the ASO procedures without knowledge transfer, the proposed KT-ASO is shown to reduce at least 50% function calls when achieving similar optimal solutions. In the meantime, under the same sample budget, our proposed KT-ASO is shown to attain much better solutions than the compared ASO procedures.

DLFSI: A deep learning static fluid-structure interaction model for hydrodynamic-structural optimization of composite tidal turbine blade

Horizontal axis tidal turbines (HATT) conversion of ocean tidal waves into electricity represents a promising source of clean and sustainable energy. However, the widespread adoption of these turbines has been hindered by persistent challenges, primarily stemming from the high costs associated with their construction and maintenance; and efficient conversion of tidal energy. Addressing these challenges is paramount for propelling tidal turbine technology and ensuring its economic viability. This study focuses on the efficient conversion of tidal energy into electricity by optimization of composite material turbine blades which is a complex problem that spans multiple physical domains, including hydrodynamics (the study of water flow) and structural mechanics (the study of material behavior under loads). To tackle these multifaceted challenges, we introduce an innovative DLFSI (Deep learning fluid-structure interaction) model which represents a groundbreaking approach to predict and optimize the hydrodynamic and structural performance of tidal turbine blades. DLFSI leverages the power of convolutional neural networks (CNN) to recognize intricate geometric features of turbine blades rapidly and accurately. By seamlessly integrating the blade element momentum (BEM) theory and finite element method (FEM), the DLFSI model facilitates comprehensive predictions of how composite blades will perform in real-world conditions. With this approach, we have achieved substantial improvements in critical performance metrics such as the power coefficient (a measure of energy conversion efficiency) and the maximum equivalent stress (a key indicator of structural integrity). The innovative DLFSI model presented in this study holds the potential for practical application within the realm of tidal turbine design and is poised to catalyze the sustainable progression of renewable energy technologies.

A Numerical Study of Blade Geometry Effects in a Vertical-Axes Wind Turbines

Several geometrical elements influence the aerodynamic properties of the Darrieus vertical axis wind turbines (VAWTs). Many extant studies have examined properties, such as solidity, pitching axis position (x/c), length of chord (c), blade quantity (N), diameter (d) of the rotor, and aspect ratio. However, not many have examined the shape of the airfoil (AF), which is a vital property that remains to be thoroughly investigated. Therefore, this present study used computational fluid dynamics (CFD) to investigate many airfoils blade characteristics, such as blade thickness (BT), maximum camber ratio (MCR), MCR location (MCRL), and air speed (AS), to determine their impact on VAWT performance. The results demonstrate a blade thickness BT of 10 to 12%, MCR of 0 to 22%, and MCRL of 24 to 23% yield a comparatively high coefficient of power, adequate optimal blade rotation to airspeed ratio (TSR), broader operational area, and high band efficiency while air velocities of 15 to 10% yield a comparatively higher power coefficient.

Evolving a Novel Blade Shape of a Savonius Wind Rotor Using an Optimization Technique Coupled With Numerical Simulations and Wind Tunnel Tests

Abstract The global adoption of Savonius wind rotors as an eco-friendly means of small-scale power production is on the rise. However, their suboptimal performance remains a significant challenge due to the generation of higher unproductive torque. This paper aims to address this issue by obtaining an optimal blade profile considering the power coefficient (CP) as an output function using optimization techniques. The objective function includes the overlap ratio, intermediate points on the curve, inlet velocity, and tip speed ratio (TSR) as the optimization geometric parameters. To achieve this, the simplex search method and the non-dominated sorting genetic algorithm II are opted to develop the blade profile. The blade profile is developed using a natural cubic spline curve with fixed end points and variable intermediate points along with other parameters. The computational analysis is done using ansys fluent software with shear stress transport k−ω turbulence model. The solver setup employs the finite volume method to simulate the transient 2D flow around the blade profile. A direct comparison is made between the optimized blade profile and the conventional semicircular one over a range of TSRs. The results clearly indicate the superior performance of the former, exhibiting a higher CPmax by 23% compared to the conventional one at TSR = 0.8. Finally, experiments have been conducted in a wind tunnel to find the practical feasibility of the optimized blade profile generated through the simplex search method.

Effect of blade number on rotor efficiency and noise emission at hovering condition

The configuration of rotors significantly impacts the aerodynamic efficiency and noise emission of multicopters. To date, there are no general guidelines regarding how many blades a rotor should use for optimal aerodynamic performance and minimum noise emission. From the perspectives of aerodynamics and acoustics during the hovering condition, two key parameters, i.e., figure of merit (FM) and overall sound pressure level (OASPL), are evaluated to determine the optimal blade number (BN). The number of blades chosen in this study is BN = 2–6, which is largely observed in commercial multicopters. A genetic algorithm was developed to optimize blade design for each BN-rotor configuration. The individuals are evaluated by steady computational fluid dynamics (CFD) simulations and acoustic analogy for optimizations, and the detailed analyses of optimal ones are further explored by unsteady CFD simulations. The planform of the baseline blade is maintained, and the radial distribution of twist angles is the parameter for optimization. While generating the same thrust, the value of FM keeps increasing as the number of blades increases from 2 to 4, after which the FM value reaches a plateau. The value of OASPL keeps decreasing as the number of blades increases. The reason for the FM and OASPL value trends vs blade number is explained with the numerical simulation results, and a general design rule is suggested at the end.

Study on cavitation performance improvement of high-power centrifugal pump impeller

High power centrifugal pump is frequently used in large project for water resources allocation. Cavitation phenomenon causes noise and vibration and affects the centrifugal pump unit stability. The impeller model was used an initial impeller to be developed, and the impeller geometry, the blade profile, blade inlet edge were optimized by design method based on numerical simulation technique to improve cavitation performances. The 3D model with the initial and optimized impeller were simulated to obtain cavitation characteristic. The results of optimization impeller are compared and verified by model test. The numerical simulation results show that the pressure distribution is distributed on the blade surface is uniform and the location of lowest pressure is reasonable. The test results show that the optimized design significantly increases the ratio of plant cavitation coefficient σp to incipient cavitation coefficient σi and critical cavitation coefficient σ1 of the impeller under normal operation conditions, the safety margin of cavitation is increased. It was confirmed from numerical simulation and model test results that the impeller blade optimization is a reasonable and effective method for cavitation performance improvement. The study results provides design reference for the cavitation performance improvement and safe operation of high power centrifugal pump.

Design optimization of three‐dimensional geometry of a micro horizontal axis wind turbine blade using the response surface method

AbstractThis study presents an aerodynamic design optimization of a micro micro‐horizontal‐axis wind turbine (HAWT). To obtain an optimal design, it is essential to understand the design parameters and select the responsible factors that affect the blade efficiency. The aim of this work is to redesign a 3D micro‐HAWT to improve aerodynamic performance, through improving the distribution of chord length and twist angle along the blade. Performance analysis and flow visualization of the initial design and the optimal design were carried out using CFD analyzer. In the blade optimization design, eight significant input parameters were selected, five to characterize the chord length distribution and three to represent the twist angle along the blade. To maximize the efficiency, design points that are created by Design of Experiment (DoE) are evaluated through (Multi‐Objective‐Genetic Algorithm) MOGA method. The results showed a reduction on the separation effect area on the optimal blade surface compared to the initial one. The use of response surface optimization (RSO), when combined with CFD simulation, has proven beneficial in selecting the optimal HAWT design. Finally, the open source software (Qblade) was used to investigate and to compare the performance of the initial and optimum design. An efficiency enhancement of approximately 3.6% is achieved at tip speed ration TSR = 3.4.

Numerical modelling and simulation analysis of wind blades: a critical review

Abstract Wind energy has emerged as a promising renewable energy source and wind turbine technology has developed rapidly in recent years. Improved wind turbine performance depends heavily on the design and optimization of wind blades. This work offers a critical evaluation of the state of the art in the field of numerical modelling and simulation analysis, which have become crucial for the design and optimization of wind blades. The evaluation of the literature includes considerable research on the application of numerical methods for the structural and aerodynamic performance of wind blades under various operating situations, as well as for analysis and optimization of wind blades. The article illustrates how numerical techniques can be used to analyse wind blade performance and maximize design efficiency. The study of blade performance under various wind conditions has also been made possible through the use of simulation analysis, thus enhancing the efficiency and dependability of wind turbines. Improvements in wind turbine efficiency and dependability, and ultimately the move towards a more sustainable energy future, will be greatly helpful for the development of numerical modelling and simulation techniques.

An Improved Passage-Flow Turning Model for Forward-Curved Blades of Squirrel-Cage Fan

Abstract An improved passage-flow turning model (IPTM) was developed in this study to design high-performance forward-curved blades for squirrel-cage fans. The flow separation in blade passages and the corresponding fan performance were compared between IPTM and traditional methods through computational fluid dynamics (CFD). The results show that correcting the blade inlet angle, based on the zero-incidence design, is crucial to prevent separation of the passage mainstream from the blade pressure surface. The blade shape with second-order smoothness also exhibits the thinnest separation and highest efficiency when other design parameters remain constant. Considering these findings, the blades designed by IPTM outperform traditional blades with the same inlet and outlet angles. The optimal values of the turning radius R¯T and the decelerating factor of the leading half blade ɛ were determined based on the CFD results. The designed blade achieves high pressure when these two parameters satisfy R¯T=−0.185ε+0.29175, while achieving high efficiency when they satisfy R¯T=−0.31ε+0.4425. To confirm the advantages of IPTM, an optimal IPTM-based blade was manufactured and measured. The results indicated that the maximum increase in fan pressure and efficiency reaches 10% and 6%, respectively.

Genetic algorithm based three-dimensional shape optimization of rotor blade for a Mars multi-rotor aircraft

In the context of Mars exploration, the Mars multi-rotor aircraft plays a significant role, with its blades being the key components for achieving flight. Due to the thin Martian atmosphere, conventional Earth blades struggle to generate the required thrust for comprehensive aerial missions on the Red Planet. To solve these challenging conditions, there arises a compelling need to refine the rotor’s design, optimizing it to provide sufficient thrust while minimizing power consumption. In this research, a novel method is introduced, combining genetic algorithms and computational fluid dynamics simulations. This approach focuses on enhancing the three-dimensional structure of the rotor blade. The results of this research are verified in experiments conducted within the Martain Atmosphere Simulator, where the blade after optimization demonstrated the ability to achieve the same level of thrust while significantly reducing power consumption. Consequently, this study represents a promising avenue for improving the efficiency of Mars multi-rotor aircraft.

CFD and Taguchi based optimization of air driven single stage partial admission axial turbine blade profiles

Single-stage axial flow turbines are typically used in underground mining machines and underwater vehicles due to their safety and small size. However, the high-pressure ratio and small mass flow rates force the flow inside the turbine to be supersonic. The blade design of such turbines with high-flow velocity leads to high losses and low turbine efficiencies at conventional design values. In this paper, the 1D design of the turbine is carried out using the meanline design method. The results of the design algorithm are compared with both experimental, CFD (Computational Fluid Dynamics), and a well-known commercial software AxSTREAM. After validating the design, Taguchi method is used to analyze 6 different parameters (Blade Shape, Nozzle Shape, Cord Length, Solidity Ratio, Nozzle Angle and Blade Thickness) affecting the turbine performance and the optimum blade profile is compared with the conventional blade design. The optimum design isentropic efficiency (68.267%) outperformed the conventional design turbine isentropic efficiency (61.759%) by about 11%. This paper provides a different insight into the conventional turbine design method.

Optimization of a High Pressure Turbine Blade and Sector-Based Annular Rig Design for Supercritical CO2 Power Cycle Representative Testing

Abstract As part of the ongoing research into the design of hardware for zero emission cycles, a first-stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design three-dimensional with objectives of increasing efficiency and decreasing heat load to the blade. Supercritical CO2 property tables are constructed from NIST REFPROP data for the condensable gas simulation in FINE/Turbo. A detailed mesh sensitivity study is performed for a baseline design to identify the proper-grid refinement and efficiently allocate resources for the optimization. Seventy design variables are selected for the initial population generation. Self-organizing maps are then used to focus the design variables on the most important ones affecting the objective functions. The optimization results in approximately 3000 three-dimensional Reynolds Averaged Navier Stokes simulations of different blade shapes with increases in efficiency of up to 0.85% and decreases in heat load of 14%. Families of blade shapes are identified for experimental testing in an annular rig at the Purdue Experimental Turbine Aerothermal Laboratory. A design to adapt the annular cascade for testing optimized geometries is introduced, which features eccentric radius sectors allowing for scaled-up geometries of sCO2 optimized blade profiles to be tested at design cycle representative conditions at high Reynolds numbers in dry air. Analysis into the effects of Reynolds number, working fluid, and geometric relations are presented to prove the efficacy of the test method.

Experimental Investigation and CFD Analysis of Wind Turbine Blades with Different Attack Angles

The escalating global demand for energy coupled with escalating environmental concerns has underscored the imperative of efficacious energy conversion from renewable reservoirs. Among these, wind energy has ascended as a pragmatic and ecologically conscientious solution. Its ascent, outpacing conventional fuels such as coal, underscores the necessity to comprehend its performance intricately. This study zeroes in on an airfoil model, subjecting it to a dual scrutiny encompassing empirical investigation and computational simulation. Employing Computational Fluid Dynamics (CFD) analyses executed in ANSYS software, the study prognosticates pressure and velocity patterns for the 2D iteration of the Model 1 airfoil by the National Advisory Committee for Aeronautics (NACA). This exhaustive scrutiny spans across velocities of 10 m/s and diverse angles of attack (-5°, 2°, and 8°). Remarkably, a robust 90% correlation manifests between the outcomes of empirical experimentation and computational simulation. Within the aerodynamic schema of the Horizontal Axis Wind Turbine (HAWT), the 8° angle of attack emerges as the vanguard, distinctly illustrating the pinnacle of optimal pressure distribution and velocity gradient. Noteworthy is the consistent augment in airfoil performance as the blade angle escalates, substantiated by elevated apex velocities and pressures in juxtaposition to the -5° and 2° angles. The findings of this inquiry engender a significant stride in airfoil refinement for the optimization of wind turbine blades, thereby conferring invaluable insights in the realms of blade design, aerodynamic contemplations, and the augmentation of wind turbine performance.

The impact of the grinding angle of the soil dredging tool on its performance

This investigation explores the optimization of the backhoe blade's entry angle, addressing its crucial role in enhancing energy efficiency and operational effectiveness in subsoil manipulation - a fundamental aspect of agricultural tillage technologies. Utilizing an integrated approach that combines detailed field experiments with robust theoretical simulations, the study methodically quantifies the effects of angular variations on energy demands and mechanical performance during soil dredging. Our results reveal precise angular configurations that offer optimal reductions in energy use while significantly improving the disruption and aeration of the subsoil layer. This optimization contributes directly to the development of advanced, precision-engineered agricultural implements aimed at boosting sustainability and productivity in farming practices. Furthermore, the outcomes of this research provide pivotal insights into soil health management strategies, potentially influencing crop yield through improved root penetration and water absorption. These findings are expected to serve as a benchmark for future innovations in agricultural machinery design, aligning with global trends towards more sustainable agricultural practices and enhanced food security. This study sets a new standard for agricultural tool engineering, paving the way for transformative changes in the sector.