High-fidelity Computational Fluid Dynamics Research Articles

Numerical Investigation and Validation of Noise Sources of a Distributed Propulsion System

This study delves into the exploration of a distributed propulsion system consisting of three co-rotating propellers in front of a high-lift wing system, with a primary focus on understanding its acoustic characteristics. Employing high-fidelity computational fluid dynamics simulations, the flow field is simulated in climb condition. Subsequently, acoustic transport to far-field observers is conducted using the Ffowcs–Williams and Hawkings equation. Because the noise mechanisms of such a configuration are not fully understood yet, several permeable and impermeable surfaces as input for the acoustic simulation are used, aiming to separate the various noise source contributions. Results reveal that in addition to the rotor-alone noise from the propellers, noise arising from propeller–wing interaction emerges as dominant, emitting mostly at the blade passing frequency. Moreover, a boundary element method tool is applied to observe the scattering effect of propeller-generated noise by the wing. Furthermore, this study incorporates consideration of structural components in close proximity to the model, thereby achieving a more realistic acoustic field. With this knowledge, the simulation is validated with experimental data from an open wind tunnel test campaign. An overall good agreement is observed between the simulated and experimental results, substantiating the reliability of both aerodynamic and acoustic predictions.

Toward aerodynamic surrogate modeling based on β-variational autoencoders

Surrogate models that combine dimensionality reduction and regression techniques are essential to reduce the need for costly high-fidelity computational fluid dynamics data. New approaches using β-variational autoencoder (β-VAE) architectures have shown promise in obtaining high-quality low-dimensional representations of high-dimensional flow data while enabling physical interpretation of their latent spaces. We propose a surrogate model based on latent space regression to predict pressure distributions on a transonic wing given the flight conditions: Mach number and angle of attack. The β-VAE model, enhanced with principal component analysis (PCA), maps high-dimensional data to a low-dimensional latent space, showing a direct correlation with flight conditions. Regularization through β requires careful tuning to improve overall performance, while PCA preprocessing helps to construct an effective latent space, improving autoencoder training and performance. Gaussian process regression is used to predict latent space variables from flight conditions, showing robust behavior independent of β, and the decoder reconstructs the high-dimensional pressure field data. This pipeline provides insight into unexplored flight conditions. Furthermore, a fine-tuning process of the decoder further refines the model, reducing the dependence on β and enhancing accuracy. Structured latent space, robust regression performance, and significant improvements in fine-tuning collectively create a highly accurate and efficient surrogate model. Our methodology demonstrates the effectiveness of β-VAEs for aerodynamic surrogate modeling, offering a rapid, cost-effective, and reliable alternative for aerodynamic data prediction.

Breakup dynamics in a pressure-swirl injector for urea-water solution applications: A computational study

The co-optimization of in-cylinder combustion and after-treatment technology has become a major aspect in engine design and development, with the goal of meeting the increasingly restrictive emission regulations in the transportation industry. Selective Catalytic Reduction is a robust technology to control the emission of NOx, and the injection of urea in water solution is the exhaust tailpipe is a key aspect of its operation. The proposed work uses high-fidelity Computational Fluid Dynamics to characterize the atomization dynamics of the liquid jet in relevant cross-flow conditions. The study focuses on a commercial low-pressure (9 bar) pressure-swirl injector which is characterized in its internal geometry through high-resolution X-ray micro-computational tomography. The internal two-phase flow has been modeled according to the volume-of-fluid approach in a large eddy simulation framework and validated against near-nozzle X-ray radiography measurement. Moreover, characterizing the breakup dynamics for the swirling hollow cone formation, and assessing the influence of the cross-flow in the breakup dynamics was completed. The results have been reported proposing Re-Oh maps and probability density functions of the spray kinematics. Higher cross-flow momentum generates an increase in the jet intact length and a reduction of the liquid droplet diameters. The axial momentum of the jet is affected by the cross-flow already in the near-nozzle region, determining a relevant deviation of the spray velocities. This work aims to inform the initialization of Eulerian-Lagrangian spray models through the assignment of droplet kinematics and static one-way coupling between volume-of-fluid results and Lagrangian spray parcels, to be used for system-size domain simulations.

High-Fidelity Simulations of Rotors in a Compact Configuration

High-fidelity computational fluid dynamics (CFD) simulations of seven rotors in compact configuration at three different flight scenarios are performed. The cases are hover as well as 50 and 100 km/h forward flights. For comparison, each rotor is simulated as an isolated rotor with the same RPM and pitch angle as in the configuration. Additionally, a bigger isolated rotor with the same diameter as the complete configuration is simulated. For the configuration as well as the bigger rotor a flight mechanics trim is performed using the flight mechanics tool VFAST. The CFD simulations are performed with FLOWer. In hover, only the center rotor showed a significant figure of meritdrop of 16% compared to the isolated rotor. The thrust of the outer rotors is increased at the tip areas facing outwards, while the tip areas towards the center and the tip areas of the center rotor showed reduced thrust compared to the isolated rotor. The wake contraction at the outer rotors is increased compared to the bigger rotor. For the 50 km/h forward flight, the efficiency of the front rotors is increased (10???17%) and the rear ones decreased (11???16%). In this case, the wake is directly convected from the front rotors into the rear rotor planes and strong vortex interactions occur. For the 100 km/h case, the efficiency of the front rotors increases by 3???11%, while it decreases by 5???9% for the rear rotors. Due to the higher pitch, the wake of the rotors flows away from the rotor plane and the rotor???rotor interactions are reduced.

A non-linear unsteady vortex-lattice method for rotorcraft applications

Abstract The present work aims to extend the capabilities of DUST, a mid-fidelity aerodynamic solver developed at Politecnico di Milano, for the aerodynamic simulation of rotorcraft applications. With this aim, a numerical element was implemented in the solver obtained by a coupling between the potential unsteady vortex lattice method and viscous aerodynamic data of aerofoil sections available from two-dimensional high-fidelity computational fluid dynamics (CFD) simulations or experimental wind-tunnel tests. The paper describes the mathematical formulation of the method as well as a validation of the implementation performed by comparison with both high-fidelity CFD simulation results and experimental data obtained over aerodynamics and aeroelastic fixed-wing benchmarks. Then, the method was used for the evaluation of the aerodynamic performance of two rotorcraft test cases, i.e. the full-scale proprotor of the XV-15 tiltrotor operating in different flight conditions and two propellers in tandem with overlapping disks. Simulation results comparison with high-fidelity CFD and data from wind tunnel tests highlighted the potentialities and advantages of the implemented approach to be used for the design and investigation of rotorcraft configurations characterised by consistent viscosity effects.

Comparing Large-Eddy Simulation and Gaussian Plume Model to Sensor Measurements of an Urban Smoke Plume

The fast prediction of the extent and impact of accidental air pollution releases is important to enable a quick and informed response, especially in cities. Despite this importance, only a small number of case studies are available studying the dispersion of air pollutants from fires in a short distance (O(1 km)) in urban areas. While monitoring pollution levels in Southampton, UK, using low-cost sensors, a fire broke out from an outbuilding containing roughly 3000 reels of highly flammable cine nitrate film and movie equipment, which resulted in high values of PM2.5 being measured by the sensors approximately 1500 m downstream of the fire site. This provided a unique opportunity to evaluate urban air pollution dispersion models using observed data for PM2.5 and the meteorological conditions. Two numerical approaches were used to simulate the plume from the transient fire: a high-fidelity computational fluid dynamics model with large-eddy simulation (LES) embedded in the open-source package OpenFOAM, and a lower-fidelity Gaussian plume model implemented in a commercial software package: the Atmospheric Dispersion Modeling System (ADMS). Both numerical models were able to quantitatively reproduce consistent spatial and temporal profiles of the PM2.5 concentration at approximately 1500 m downstream of the fire site. Considering the unavoidable large uncertainties, a comparison between the sensor measurements and the numerical predictions was carried out, leading to an approximate estimation of the emission rate, temperature, and the start and duration of the fire. The estimation of the fire start time was consistent with the local authority report. The LES data showed that the fire lasted for at least 80 min at an emission rate of 50 g/s of PM2.5. The emission was significantly greater than a ‘normal’ house fire reported in the literature, suggesting the crucial importance of the emission estimation and monitoring of PM2.5 concentration in such incidents. Finally, we discuss the advantages and limitations of the two numerical approaches, aiming to suggest the selection of fast-response numerical models at various compromised levels of accuracy, efficiency and cost.

Towards the prediction of flame transfer functions: Evaluation of a hybrid LES-CAA with compressible LES

The prediction of flame transfer functions, particularly in practically relevant systems, remains challenging and computationally demanding. Numerical approaches are a valuable addition to experimental acoustic characterizations of industrial configurations. Conventionally, fully compressible numerical simulations are used that naturally include acoustic fluctuations in their computations, but can be computationally expensive depending on the configuration. Therefore, a convenient approach to use tailored numerics for the underlying physics is considered in this work. In this work, this is realized by applying a runtime-coupled method of computational fluid dynamics and computational aeroacoustics to a single-sector aero-engine combustor. This hybrid computational fluid dynamics and computational aeroacoustics method captures fluid flow behavior and combustion dynamics in a low-Mach computational fluid dynamics domain while allowing for acoustic perturbations in the computational aeroacoustics. Runtime exchange of hydrodynamic and acoustic quantities between the two solvers allows for a bidirectional coupling and, by extension, a complete description of the combustion system. In this work, the hybrid computational fluid dynamics and computational aeroacoustics is applied in a high-fidelity large eddy simulation configuration. The flame transfer function is evaluated for both compressible and hybrid simulations. The results for both numerical approaches are validated with each other and compared to the experimentally obtained flame transfer function. Finally, the computational effort for the numerical approaches is considered. This article presents the first application of a high-fidelity computational fluid dynamics framework using large eddy simulation with bidirectional coupling with the acoustic solver to an industry-relevant configuration. The aim is to provide a roadmap towards investigating thermoacoustic instabilities in a real gas turbine engine at reduced computational costs.

An assessment of Dragonfly-Backshell aerodynamics preparing for the initial flight on Titan

The Dragonfly mission has the scope of studying the surface of Titan, Saturn’s largest moon, using a rotorcraft lander. A mission-critical event in the timeline involves Dragonfly’s initial flight as it descends into Titan’s atmosphere. The preparation for this initial flight involves releasing the heat shield and utilizing the lander’s rotors to damp motion while still attached to the parachute-supported aeroshell to ensure a smooth release. The aerodynamics of this event are studied in Titan conditions using high-fidelity computational fluid dynamics (CFD). The CFD model is benchmarked using available experimental measurements relevant to subcomponents of the event and include: (1) an open backshell, (2) bluff bodies similar to the Dragonfly fuselage, and (3) a rotor-body interaction from a helicopter rotor. The CFD results correlate well with measurements to provide confidence in the present studies focused on Titan. The novel studies presented in this work focus on the rotor-based control of the lander–backshell combination and its ability to mitigate spinning about the main parachute support line. This effort finds that the relatively large fuselage combined with near-fuselage rotors (driven by aeroshell space limitations) drives an unexpected aerodynamic interaction between the rotor and fuselage. Specifically, we observe low-pressure zones on the fuselage adjacent to the rotor that create a “suction” force. This first-order force creates an unexpected aerodynamic interaction that demands careful attention. In this paper, this force is documented and solutions are proposed to mitigate undesirable control character.

Reconstruction of the turbulent flow field with sparse measurements using physics-informed neural network

Accurate high-resolution flow field prediction based on limited experimental data is a complex task. This research introduces an innovative framework leveraging physics-informed neural network (PINN) to reconstruct high-resolution flow fields using sparse particle image velocimetry measurements for flow over a periodic hill and high-fidelity computational fluid dynamics data for flow over a curved backward-facing step. Model training utilized mean flow measurements, with increased measurement sparsity achieved through various curation strategies. The resulting flow field reconstruction demonstrated marginal error in both test cases, showcasing the ability of the framework to reconstruct the flow field with limited measurement data accurately. Additionally, the study successfully predicted flow fields under two different noise levels, closely aligning with experimental and high-fidelity results (experimental, direct numerical simulation, or large eddy simulation) for both cases. Hyperparameter tuning conducted on the periodic hill case has been applied to the curved backward-facing step case. This research underscores the potential of PINN as an emerging method for turbulent flow field prediction via data assimilation, offering reduced computational costs even with sparse, noisy measurements.

A RELAP5-3D Model of the Lobo Lead Loop

The goal of our research is to build upon the capability of RELAP5-3D to model molten lead systems. Molten lead has several potential uses in future advanced reactors, like the lead fast reactor or fusion reactors that utilize dual-coolant lead lithium blankets. This potential for use in future generations of reactors highlights the necessity of developing molten lead models to ensure that they can accurately predict thermohydraulic behavior. We have developed a RELAP5-3D model of the Lobo Lead Loop facility located at the University of New Mexico to verify the accuracy of RELAP5-3D via comparison to existing computational fluid dynamics results and analytical calculations. It was found that RELAP5-3D accurately calculated radiative heat transfer (within <1%) when compared to theoretical calculations. In addition, pressure drop calculations done in RELAP5-3D demonstrated reasonable agreement within 20 kPa, mostly within ~7% to 15%, when compared to the computational fluid dynamics model of the facility developed by the University of New Mexico, and captured the dependence of pressure drop on flow velocity accurately. Finally, a hypothetical loss-of-flow transient was imposed on the RELAP5-3D model to determine the feasibility of performing a similar experiment with the Lobo Lead Loop. It was found that such an experiment could be possible, as the RELAP5-3D model indicated that the temperatures of the fluid would not exceed the limiting temperatures of the structure (1658 K) nor the maximum temperature of the electromagnetic pump inlet (823 K). Although there are no experimental data to begin validation, the model will be readily available for future validation studies when the experimental data are generated, especially as the model continues to evolve over time. The results so far demonstrate a promising first step in the verification/validation of the RELAP5-3D model of the Lobo Lead Loop. The highlights from our research are as follows: 1. The Lobo Lead Loop facility at the University of New Mexico is a good candidate for molten lead system code validation. 2. The Lobo Lead Loop currently has extensive pressure drop results from a high-fidelity computational fluid dynamics model, which offers the opportunity for code-to-code verification of pressure drop in RELAP5-3D. 3. A RELAP5-3D model of the Lobo Lead Loop has been developed to begin verification studies and to prepare for potential validation studies. 4. Development of the model will continue throughout the future to prepare for potential validation studies.

Analysis, optimization, and testing of a tilt-body aircraft

This paper proposes a new multidisciplinary design optimization framework for tilt-bodies to obtain the optimal combination of geometry and powertrain, achieving both long endurance and low transition power consumption at a 5 kg takeoff weight. A low-fidelity vortex lattice method is used to derive the aerodynamic coefficients. The tandem wings are trimmed using an optimization-based method, considering the effect of distributed propulsion on the trim solution through aero-propulsive interaction at low flight speed. Detailed powertrain parameters are fitted with fewer design variables to calculate power consumption. By analyzing the unique constraints of tilt-bodies, the optimization problem is established as a simultaneous analysis and design architecture, and solved with different numbers of rotors. The impact of the relative geometric relationship between the front and rear wings on aerodynamic performance and constraints is analyzed. Results demonstrate the full angle-of-attack flight capability of tilt-bodies. The optimal design can save nearly 1000 W in transition, with a pure cruise endurance of over 1 hour, which is competitive among other configurations. With an empty weight of only 2 kg, a portion of the battery can be allocated to a heavier payload. High-fidelity computational fluid dynamics corrects the errors of the vortex lattice method on non-lifting components, including the fuselage, nacelles, and landing gear. Finally, the feasibility of the optimal design and the accuracy of the framework are validated by wind tunnel tests and in-flight drag measurements on a test platform.

High-fidelity computational study of aerodynamic noise of side-by-side rotor in full configuration

This paper presents a numerical study of side-by-side rotor aircraft in full configuration during hover using high-fidelity computational fluid dynamics (CFD) and aeroacoustic simulations. CFD simulations are performed using HPCMP CREATE™-AV Helios, while acoustic calculations are conducted with PSU-WOPWOP. Overset structured grids are applied using the SA-DES turbulence model along with adaptive mesh refinement in the near- and off-body meshes. Four overlap cases at a specific collective pitch angle of 8° are considered. Results reveal a substantial influence of the fuselage on rotor performance, with improvement in the figure of merit being observed for each overlap configuration due to a partial ground effect. There is considerable increase in blade sectional thrust, pressure fluctuations, and noise levels seen in the 0% overlap configuration compared to the 25% overlap configuration. This increase is primarily due to the absence of rotor overlap, resulting in a lower induced velocity allowing for flow to travel upward, and reaching the rotor disk plane. The acoustic spectrum appears at all harmonics of the blade passing frequency for the 0% and 5% overlap configurations. In contrast, the acoustic spectrum is distinctly present only at even harmonics for the 15% and 25% overlap cases. A noise reduction benefit of 3-5 dBA is noticed in the full configuration cases having rotor overlap compared to the 0% overlap configuration. Acoustic destructive interference is observed in the directivity plot only for the 15% and 25% overlap configurations. Overall, this paper reveals that the fuselage has a significant impact on the performance, aerodynamics, and aeroacoustics of the side-by-side UAM vehicle in hover.

Utilizing global-local neural networks for the analysis of non-linear aerodynamics

In addressing the computational challenges pervasive in engineering where time and cost limitations are key concerns, particularly within the Computational Fluid Dynamics (CFD) domain, Reduced Order Models (ROMs) have emerged as instrumental tools. Focused on reducing computational complexity without intrusively modifying the computational model, this study centres on the strategic application of aerodynamic ROMs, which provide efficient computation of distributed quantities and aerodynamic forces. This work presents ROMs for non-linear aerodynamic applications, integrating principal component analysis (PCA) with Global Local Neural Networks (GLNN). The effectiveness of the proposed methodology is demonstrated by leveraging dependency on the parameter space created with non-linear high-fidelity CFD data, incorporating viscous simulation for a comprehensive approach. Results are first presented for a two-dimensional airfoil case and then for a three-dimensional test case featuring a transonic wing-body-tail transport aircraft configuration (NASA Common Research Model). In transonic flows, the proposed ROMs demonstrate the ability to accurately capture both the location and strength of shocks, as well as forces and moments for unseen prediction points. This highlights the efficiency of the proposed method in navigating complex aerodynamic scenarios, achieving comparable accuracy to full-order modelling but at orders of magnitude less computational time, for unseen parameters outside the ROM training set within the parameter space.

Wind Tunnel Testing of Tethered Inflatable Wings

A wind tunnel testing approach for tethered inflatable wings is presented. Use cases for such wings range from airborne wind energy systems to high-altitude communication platforms. The tests were conducted for two tethered inflatable wings, one made out of nylon fabric and the other an ultra-high-molecular-weight polyethylene fabric. They were tested within a speed range of 15–32.5 m/s for three tether attachment configurations. Stereo photogrammetry data, force and moment measurements, and wake pressure measurements were recorded for each speed and test configuration. These measurements provide an experimental database for aeroelastic model validation and comparison with high-fidelity computational fluid dynamics studies. The effects of wing fabric material and tether attachment configurations on aerodynamic performance were explored and found to have a profound impact. These tests also highlight the possibility of passive aeroelastic tailoring of the wing configuration to achieve desired aerodynamic performance in the form of high lift and load alleviation. Some testing challenges and possible sources of measurement uncertainty are also discussed.

Direct numerical simulation of flow in a membrane channel under oscillating inlet conditions

Effects of inflow oscillation in feed channels of spiral wound membranes are investigated. Pulsation has previously been used as a membrane cleaning method in Reverse Osmosis (RO) and other membrane desalination processes. However, there is still a gap in the fundamental fluid dynamics study of pulsation and fouling mitigation. Three-dimensional, transient, high-fidelity Computational Fluid Dynamics investigation using Direct Numerical Simulation has been performed on a geometry of 9 × 3 feed square space elements at Reynolds number of 350 based on inlet velocity. Sinusoidal-wave and step function pulsations are simulated at three frequencies (1, 4, 8 Hz). Five levels of permeate velocity are investigated, from 0.2 % to 0 % (impermeable). Pulsating inflow produces a fully-unstable flow regime. Flow streamlines show no large recirculation regions, unlike for the steady inflow, and flow structures show higher levels of instabilities with a larger range of scales, resulting in smaller stagnation regions near the surfaces. Consequently, the area of low shear decreases and its distribution is limited to the spacer filament crossings instead of the permeate walls. These findings show that inflow oscillation for a membrane channel creates flow conditions that could be beneficial for reducing fouling propensity in RO and other membrane processes with similar feed channel geometry.

Multiple boundary layer suction slots technique for performance improvement of vertical-axis wind turbines: Conceptual design and parametric analysis

Vertical-axis wind turbines (VAWTs) are gaining attention for urban and offshore applications. However, their development is hindered by suboptimal power performance, primarily attributable to the complex aerodynamic characteristics of the blades. Flow control techniques are expected to regulate the flow on the blade surface and improve blade aerodynamics. In the present study, an effective active flow control technique, multiple boundary layer suction slots (MBLSS), is designed for VAWTs performance improvement. The impact of MBLSS on the aerodynamic performance of VAWTs is examined using high-fidelity computational fluid dynamics simulations. The response surface methodology is employed to identify the relatively optimal configuration of MBLSS. Three key parameters are considered, i.e., number of slots (n), distance between slots (d), and slot length (l), which vary from 2 to 4, 0.025c to 0.125c, and 0.025c to 0.075c, respectively. The results show that MBLSS positively affects the power performance and aerodynamics of VAWTs. Parameter n has the most significant effect on VAWT power performance and the importance of d and l is determined by tip speed ratios (TSRs). Tight and loose slot arrangements are recommended for high and low TSRs, respectively. The relatively optimal configuration (n = 2, d = 0.025c, l = 0.05c) results in a remarkable 31.02% increase in the average net power output of the studied TSRs. The flow control mechanism of MBLSS for VAWT blade boundary layer flow has also been further complemented. MBLSS can prevent the bursting of laminar separation bubbles and avoid the formation of dynamic stall vortices. This increases the blade lift-to-drag ratio and mitigates aerodynamic load fluctuations. The wake profiles of VAWTs with MBLSS are also investigated. This study would add value to the application of active flow control techniques for VAWTs.

AI-enabled damage estimation of hurricane-impacted residential communities through CFD simulations and stratified sampling

This study introduces a novel framework for estimating hurricane-induced damage to individual buildings by integrating AI-based 3D building modeling, Computational Fluid Dynamics (CFD), and stratified sampling. By leveraging the precise geometric characteristics of individual buildings extracted from digital data, the framework enables the accurate computation of pressure distributions for individual buildings through high-fidelity CFD simulations. The subsequent integration of an AI-based building component detection technique with vulnerability modeling and enhanced stratified sampling enables the rapid computation of the component and building-level failure probabilities. Applied to a case study in Atlantic City, NJ, the research underscores the effectiveness of realistic geometric characterizations and the inclusion of neighboring buildings in estimating individual-building level damage. Unlike conventional archetype-based approaches, the proposed methodology offers individual-building level risk assessment, reflecting the crucial role played by geometric and aerodynamic variables. The framework offers a promising step towards automated high-fidelity assessments of hurricane risks, leveraging detailed modeling and simulation to contribute to more resilient communities.

Efficient aerodynamic optimization of turbine blade profiles: an integrated approach with novel HDSPSO algorithm

PurposeThis paper delves into the aerodynamic optimization of a single-stage axial turbine employed in aero-engines.Design/methodology/approachAn efficient integrated design optimization approach tailored for turbine blade profiles is proposed. The approach combines a novel hierarchical dynamic switching PSO (HDSPSO) algorithm with a parametric modeling technique of turbine blades and high-fidelity Computational Fluid Dynamics (CFD) simulation analysis. The proposed HDSPSO algorithm introduces significant enhancements to the original PSO in three pivotal aspects: adaptive acceleration coefficients, distance-based dynamic neighborhood, and a switchable learning mechanism. The core idea behind these improvements is to incorporate the evolutionary state, strengthen interactions within the swarm, enrich update strategies for particles, and effectively prevent premature convergence while enhancing global search capability.FindingsMathematical experiments are conducted to compare the performance of HDSPSO with three other representative PSO variants. The results demonstrate that HDSPSO is a competitive intelligent algorithm with significant global search capabilities and rapid convergence speed. Subsequently, the HDSPSO-based integrated design optimization approach is applied to optimize the turbine blade profiles. The optimized turbine blades have a more uniform thickness distribution, an enhanced loading distribution, and a better flow condition. Importantly, these optimizations lead to a remarkable improvement in aerodynamic performance under both design and non-design working conditions.Originality/valueThese findings highlight the effectiveness and advancement of the HDSPSO-based integrated design optimization approach for turbine blade profiles in enhancing the overall aerodynamic performance. Furthermore, it confirms the great prospects of the innovative HDSPSO algorithm in tackling challenging tasks in practical engineering applications.

Impact of rotor blade aerodynamics on tower vortex induced vibration of modern wind turbines

Modern wind turbines in standstill or idling could experience vortex induced vibrations (VIV); the origin of these vibrations is either shedding from the wind turbine blade referred to as blade VIV or shedding from tower termed as tower (or turbine) VIV. When the whole structure of the wind turbine is considered and the blades are pitched out, the dominant 1st order mode for blade deformation in edgewise direction leads to negligible motion of the tower top, while when the whole turbine vibrates with first tower mode, blades also undergo significant periodic translations and deformations. In this study, forced motion is used to study the impact of aerodynamic damping due to rotor moving with 1st tower mode. In the literature no comprehensive work is available to characterize the impact of blades aerodynamics in the turbine mode either using systematic tests or high-fidelity computational fluid dynamics (CFD). In this article high-fidelity numerical simulations are performed to compute the power injections from the rotor blades when the turbine moves in 1st tower mode. Depending on the inflow angle and the azimuthal position, blades can inject significant power. Thus, the estimated damping from tower-only empirical models could severely underestimate the total aerodynamic power if the power injection from the rotor is neglected.

CFD wind farm evaluation in complex terrain under free and wake induced flow conditions

Massive deployment of wind energy is critical to achieving the renewable energy production targets. This requires the development and improvement of models and tools for the optimal exploitation of high altitude and complex terrain sites for wind energy installations. Predicting the wind resource assessment of these sites is very challenging, as is predicting the interaction of wind farms in complex terrain with neighbouring installations, which is necessary to maximise the efficiency of wind energy. To address these challenges, the use of high-fidelity Computational Fluid Dynamics (CFD) models is recommended. In this study, the wind resource at the complex terrain site of the CENER experimental wind farm (Alaiz) is evaluated using steady-state RANS CFD simulations performed with OpenFOAM v2212, taking into account the effects of terrain topography and vegetation. Furthermore, a virtual wind farm located at Alaiz is modelled with the Actuator Disk (AD) method to analyse the effect of topography on the the wake evolution.