Velocity Deficit Research Articles

A momentum-conserving wake superposition method for wind-farm flows under pressure gradient

Pressure gradient over topography will significantly affect wind-farm flow. However, knowledge gaps still exist on how to superpose wind-turbine wakes in the wind-farm flow analytical model to account for this effect, leading to systematic errors in evaluating wind-farm wake effects. To this end, we derive an implicit momentum-conserving wake superposition method under pressure gradient (PG-IMCM) based on the total momentum deficit equation, which is linearised by the convection velocity introduced by Zong & Porté-Agel (J. Fluid Mech., vol. 889, 2020, A8). The PG-IMCM method consists of the linear-weighted sum of individual velocity deficits, the sum of the individual pressure correction terms and the total pressure correction term. Based on a sensitivity analysis, we demonstrate that the last two terms nearly cancel out and, thus, can be neglected, resulting in a simplified form, which has the same form as its counterpart under zero pressure gradient but with the single-wake quantities redefined based on the wake model under pressure gradient. This motivates us to further examine the performance of the combination of five empirical superposition methods and the stand-alone wake model under pressure gradient. Validation results based on large-eddy simulation show that PG-IMCM has an overall satisfactory performance in both the magnitude and shape of the velocity-deficit profiles, provided that the stand-alone turbine wake can be modelled accurately, which is virtually identical with its simplified form. Further comparison with empirical superposition methods shows that local linear and wind product superposition methods based on the updated base flow also have comparable performance, with only discernable differences with the PG-IMCM method in the near-wake region of downstream turbines. Therefore, they are two attractive methods for engineering applications.

A radius and minimum velocity Jensen model for far wake distribution prediction of tidal stream turbine

The rational layout of tidal stream turbines (TSTs) is beneficial for making full use of tidal stream energy. It is essential to consider the wake radius and velocity distribution for determining the spacing between the TSTs. The wake is primarily affected by the turbulence intensity. The attenuation of turbulence results in the non-linear expansion of the wake. Additionally, the high turbulence in the near wake region inhibits the velocity deficit, which is more evident under high ambient turbulence intensity. Therefore, a radius and minimum velocity Jensen (RMV-Jensen) model is proposed to predict the wake radius and the wake velocity distribution downstream of a TST. The RMV-Jensen model consists of a radius block (R-Block) and a minimum velocity block (MV-Block). The R-Block is a piecewise exponential function based on the turbulence attenuation in the wake region, accurately describing the change of the wake expansion coefficient. The MV-Block is a wake minimum velocity model, and the inhibitory effect of turbulence on velocity deficit is considered for the first time. The RMV-Jensen model is applied to predict the wake distribution in the Zhoushan sea area. The prediction accuracy of the RMV-Jensen model is improved by 10%–20% compared to that of the classical Jensen model, according to the experimental results.

Analytical study of rotating detonation and engine operating conditions

In this paper, the mechanism of rotating detonation is analytically discussed using a two-dimensional sheet model. Two ratios are employed in this discussion: the ratio of the sonic point width to the detonation front width, and the ratio of the effective mixture injection area to the injection area. In the rotating detonation, the unconfined boundary can increase the width at the sonic point and decrease the detonation wave speed. Although the high detonation pressure hinders mixture injection, effectively preventing some injectors from functioning, the high pressure acting on the injection end wall produces thrust. Mass, momentum, energy, and angular momentum conservations are used to determine these ratios. The calculated results are in reasonable agreement with past experimental and numerical findings. The present model succeeds to clarify the features, parameter relationships, and overall mechanism of the rotating detonation analytically and to specify flow field of the rotating detonation under given boundary conditions, e.g., the velocity deficit and the effective injection area ratio. The specific impulse of a rotating detonation engine was lower than that of an ordinary rocket engine due to the lower combustion gas pressure when the combustion gas expanded to 1 atm. The thrust coefficient and the specific impulse of an air-breathing rotating detonation engine were shown to be lower than those of a ramjet engine, respectively, primarily because of the smaller airflow rate into the engine.

Influences of lidar scanning parameters on wind turbine wake retrievals in complex terrain

Abstract. Scanning lidars enable the collection of spatially distributed measurements of turbine wakes and the estimation of wake properties such as magnitude, extent, and trajectory. Lidar-based characterizations, however, may be subject to distortions due to the observational system. Distortions can arise from the resolution of the measurement points across the wake, the projection of the winds onto the beam, averaging along the beam probe volume, and intervening evolution of the flow over the scan duration. Using a large-eddy simulation and simulated measurements with a virtual lidar model, we assess how scanning lidar systems may influence the properties of the retrieved wake using a case study from the Perdigão campaign. We consider three lidars performing range-height indicator sweeps in complex terrain, based on the deployments of lidars from the Danish Technical University (DTU) and German Aerospace Center (DLR) at the Perdigão site. The unwaked flow, measured by the DTU lidar, is well-captured by the lidar, even without combining data into a multi-lidar retrieval. The two DLR lidars measure a waked transect from different downwind vantage points. In the region of the wake, the observation system reacts to the smaller spatial and temporal variations of the winds, allowing more significant observation distortions to arise. While the measurements largely capture the wake structure and trajectory over its 4–5 D extent, limited spatial resolution of measurement points and volume averaging lead to a quicker loss of the two lobes in the near wake, smearing of the vertical bounds of the wake (< 30 m), wake center displacements up to 10 m, and dampening of the maximum velocity deficit by up to a third. The virtual lidar tool, coupled with simulations, provides a means for assessing measurement capabilities in advance of measurement campaigns.

The universal gaseous detonation dynamics

The present communication proposes a new scaling approach to unify the dynamics of gaseous detonations subject to wall losses in both the narrow channels and small tubes, by compiling the published experimental data of detonations in 23 different mixtures with a very large range of cellular instabilities. A kinetic induction length Δi,loss can be determined from the detonation velocity deficit and detailed chemistry. In order to take into account the sensitivity of the latter length to post-shock temperature fluctuations (through the reduced activation energy θ), which is a partial and indirect marker of the cellular structure, and to bring out energetics (through the Chapman–Jouguet detonation Mach number MCJ), an effective kinetic length of Δi,loss(MCJ4/θ3) was built and has been shown to collapse the different detonation dynamics of various gaseous mixtures, subjected to wall losses, into a single universal curve for detonation velocity deficits.Novelty and Significance: Scaling analysis of large sets of published data of gaseous detonation experiments in narrow channels and small tubes has been made for 23 different mixtures with varied cellular instabilities and activation energies. The universal dynamics of gaseous detonations subject to wall losses in different mixtures has been achieved, for the first time, by adopting an effective kinetic length by taking into account the effect of both the activation energy and the energetics.

Analysis of waves dynamics in a rotating detonation combustor fueled by kerosene

The wave dynamics play a crucial role in the operation characteristics of the rotating detonation engine. We conducted numerical simulations of a rotating detonation combustor (RDC) using multicomponent reactive Navier–Stokes equations coupled with a discrete phases model. The RDC in this research employs a configuration with multiple coaxial injectors supplying oxygen-enriched air and kerosene spray at room temperature. To accurately identify and analyze waves within the RDC, we proposed a three-dimensional transient detonation wave detection method based on the combined parameters of normal Mach number and heat release rate in the flow field. Two typical wave modes, referred to as single-wave mode and counter-waves mode, are identified and then selected to conduct a detailed wave dynamics analysis. The general wave behavior is discussed, and velocity deficit is compared for these two wave modes. For the single-wave mode, intermittent micro-explosions are observed generating retonation waves periodically in the unburnt pockets behind the rotating detonation shock front. For the counter-waves mode, we analyzed the collision process of the two waves and the coupling/decoupling of the shock front with the detonative heat release zone, revealing the reason for significant velocity deficits in this wave mode. This research demonstrates that micro-explosions intermittently occur in the multiphase RDC in both single-wave and counter-waves modes and generate micro explosion shock waves periodically, which influence the complicated wave dynamics behavior.

Discovering an interpretable mathematical expression for a full wind-turbine wake with artificial intelligence enhanced symbolic regression

The rapid expansion of wind power worldwide underscores the critical significance of engineering-focused analytical wake models in both the design and operation of wind farms. These theoretically derived analytical wake models have limited predictive capabilities, particularly in the near-wake region close to the turbine rotor, due to assumptions that do not hold. Knowledge discovery methods can bridge these gaps by extracting insights, adjusting for theoretical assumptions, and developing accurate models for physical processes. In this study, we introduce a genetic symbolic regression (SR) algorithm to discover an interpretable mathematical expression for the mean velocity deficit throughout the wake, a previously unavailable insight. By incorporating a double Gaussian distribution into the SR algorithm as domain knowledge and designing a hierarchical equation structure, the search space is reduced, thus efficiently finding a concise, physically informed, and robust wake model. The proposed mathematical expression (equation) can predict the wake velocity deficit at any location in the full-wake region with high precision and stability. The model's effectiveness and practicality are validated through experimental data and high-fidelity numerical simulations.

Effect of radial inlet distortion on aerodynamic stability in a high load axial flow compressor

Radial inlet distortion induced by boundary layer separation can significantly affect the aerodynamic performance of the compressor. The effect of radial inlet distortion on the flow structure is numerically investigated in a high load axial flow compressor. The inlet boundary is determined by the experimental results at the downstream of the distortion generator. The results reveal that tip distortion leads to a reduction in the stall margin, whereas hub distortion extends it. Radial distortion redistributes the main flow toward undistorted region due to the obstructive effect of lattice ring. The deficit in axial velocity with tip radial distortion causes the rotor to operate at a higher incidence angle near the casing, while hub radial distortion alleviates the tip blade loading. The detailed three-dimensional flow field analysis indicates that increased blade loading with tip distortion shifts the trajectories of both primary and secondary tip leakage flow toward the leading edge, thereby expanding the blockage region. Conversely, hub radial distortion unloads the rotor tip region, thereby reducing the blockage region induced by tip leakage flow. Additionally, with hub distortion, the location of separation line on the blade suction surface moves closer to the leading edge, and the flow separation around the trailing edge is intensified.

Control of the von Kármán vortex street with focusing and vectoring of jet using synthetic jet array

In the present study, a novel flow control technique based on jet focusing and vectoring from a synthetic jet array (SJA) for controlling the wake of a bluff body is proposed and demonstrated. A numerical investigation into the flow past a square cylinder modified by the SJA has been carried out at a free stream Reynolds Number of 100. The SJA consists of four independently controlled synthetic jet actuators operating at a peak velocity of eight times the free stream and fifteen times the natural vortex shedding frequency of the square cylinder. The SJA is operated in two different regimes; a focusing regime involving phase delay (Δφ) with non-linear variation between the actuators and a vectoring regime with a linear phase delay without changing the geometric or operating parameters of the SJA. It has been found that jet focusing is able to reduce the coefficient of drag by as much as 43% for Δφ=90°. Focusing is also observed to reduce the fluctuations in the wake velocity with the maximum reduction in fluctuations also corresponding to Δφ=90°. Jet vectoring is able to deflect the von Kármán vortex street in a singular direction along with shifting of the front stagnation point with maximum deflection for Δφ=60°. Furthermore, vectoring leads to an asymmetry in the wake velocity field with the shifting of the velocity deficit region in the direction of the vectoring along with an asymmetry in the wake velocity fluctuations. This novel approach toward synthetic jet induced active flow control allows for greater manipulation of the flow field characteristics of bluff bodies than present methods with applications in areas of underwater and micro air vehicle maneuvering, automobile, and building aerodynamics among others.

Sheared turbulent flows and wake dynamics of an idled floating tidal turbine

Ocean energy extraction is on the rise. While tides are the most predictable amongst marine renewable resources, turbulent and complex flows still challenge reliable tidal stream energy extraction and there is also uncertainty in how devices change the natural environment. To ensure the long-term integrity of emergent floating tidal turbine technologies, advances in field measurements are required to capture multiscale, real-world flow interactions. Here we use aerial drones and acoustic profiling transects to quantify the site- and scale-dependent complexities of actual turbulent flows around an idled, utility-scale floating tidal turbine (20 m rotor diameter, D). The combined spatial resolution of our baseline measurements is sufficiently high to quantify sheared, turbulent inflow conditions (reversed shear profiles, turbulence intensity >20%, and turbulence length scales > 0.4D). We also detect downstream velocity deficits (approaching 20% at 4D) and trace the far-wake propagation using acoustic backscattering techniques in excess of 30D. Addressing the energy-environment nexus, our oceanographic lens on flow characterisation will help to validate multiscale flow physics around offshore energy platforms that have thus far only been simulated.

Numerical investigation of turbulent flow over a small-scale vertical axis wind turbine

The present paper aims to analyse the aerodynamics of turbulent fluid flow over a vertical axis wind turbine (VAWT). A 2D study is carried out for a two-bladed SAVONIUS wind turbine, where the rotor diameter is D=20cm. The governing equations (Unsteady Reynolds Averaged Navier Stokes URANS) are solved numerically using a CFD (computational fluid dynamics) open-source code based on the finite volume method; the SST turbulence model is applied for the system closure. An arbitrary mesh interface (AMI) technique is applied at the sliding interface boundary, which is a circular surface separating between the rotating zone and the fixed zone where the mesh remains stationary. The numerical results allow predicting the vorticity and pressure distributions over a rotating wind turbine for different tip speed ratios in order to characterize the generated wake. The velocity deficit is calculated for different positions behind the rotor to characterize the disturbance rate of the flow.

Computational Fluid Dynamics (CFD) Investigation of NREL Phase VI Wind Turbine Performance Using Various Turbulence Models

This study presents a detailed computational fluid dynamics (CFD) investigation into the aerodynamic performance of the NREL Phase VI wind turbine, focusing on torque and power generation under different turbulence models. The primary objective was to analyse the effect of various turbulence models and their responses in wind turbine torque generation. Furthermore, it also investigates the distance effect on wind velocity deficit. The research utilizes 2D and 3D simulations of the S809 airfoil and the full rotor, examining the predictive capabilities of the k-epsilon, k-omega, and k-omega SST turbulence models. The study incorporates both experimental validation and wake analysis using the Gaussian wake model to assess wind velocity deficits. Simulations were conducted for a wind speed range of (6–10 m/s), with results indicating that the k-epsilon model provided the closest match to experimental data, particularly at higher wind speeds within the targeted range. Even though k-epsilon results had better agreement when validated with experimental data, theoretically k-omega (SST) should perform better as it combines k-epsilon and k-omega advantages in predicting the flow regardless of its farness from the wall. However, in simulations using the k-omega (SST), the separation of flow and the shear stress transients were only visible at wind speeds of 10 m/s or higher. Wake effects, on the other hand, were found to cause significant velocity deficits behind the turbine, following an exponential decay pattern. The findings offer valuable insights into improving wind turbine performance through turbulence model selection and wake impact analysis, providing practical guidelines for future wind energy optimizations.

Investigating the interactions between wakes and floating wind turbines using FAST.Farm

Abstract. As floating offshore wind progresses to commercial maturity, wake and array effects across a farm of floating offshore wind turbines (FOWTs) will become increasingly important. While wakes of land-based and bottom-fixed offshore wind turbines have been extensively studied, only recently has this topic become relevant for floating turbines. This work presents an investigation of the mutual interaction between the motions of floating wind turbines and wakes using FAST.Farm. While FAST.Farm has been extensively validated across a wide range of conditions, it has never been validated for FOWT applications. Hence, in the first part of this work, we validate FAST.Farm by comparing simulations of a single FOWT against high-fidelity results from large-eddy simulations available in the literature. The validation is based on wake meandering, mean wake deflection, and velocity deficit at different downstream locations. This validation showed that the original axisymmetric (polar) wake model of FAST.Farm overpredicts the vertical wake deflection induced by shaft tilt and floater pitch, while the new curled wake model is capable of properly capturing the vertical wake deflection. In the second part, we use FAST.Farm to analyze a small three-unit array of FOWTs with a spacing of 7 diameters across a wide range of environmental conditions. The same National Renewable Energy Laboratory 5 MW reference wind turbine atop the OC4-DeepCwind semisubmersible is adopted for the three FOWTs and for the validation against high-fidelity simulations. To assess the effect of the floating substructure, we compare the power production, tower-base moments, and blade-root moments obtained for the floating turbines with the results obtained in a fixed-bottom configuration. The main differences introduced by the floating substructure are the motions induced by the waves, the change in the natural frequencies of the tower caused by differences in the boundary condition at its base, and the larger vertical deflection of the wake deficit due to the mean pitch of the platform. The impact of these differences, as well as other minor effects, are analyzed in detail.

Potential of Wake Scaling Techniques for Vertical-Axis Wind Turbine Wake Prediction

Analytical wake models are widely used to predict wind turbine wakes. While these models are well-established for horizontal-axis wind turbines (HAWTs), the analytical wake models for vertical-axis wind turbines (VAWTs) remain under-explored in the wind energy community. In this study, the accuracy of two wake scaling techniques is evaluated to predict the change in the normalized maximum wake velocity deficit behind VAWTs by re-scaling the maximum wake velocity deficit behind an actuator disk with the same thrust coefficient. The wake scaling is defined in terms of equivalent diameter, considering the geometrical properties of the wake-generating object. Two different equivalent diameters are compared, namely the momentum diameter and hydraulic diameter. Different approaches are used to calculate the change in the normalized wake velocity deficit behind a disk with the same thrust coefficient as the VAWT. The streamwise distance is scaled with the equivalent diameter to predict the normalized maximum wake velocity deficit behind the desired VAWT. The performance of the proposed framework is assessed using large-eddy simulation data of VAWTs operating in a turbulent boundary layer with varying operating conditions and aspect ratios. For all of the cases, the momentum diameter scaling provides reasonable predictions of the VAWT normalized maximum wake velocity deficit.

Effect of background turbulence on the wakes of horizontal-axis and vertical-axis wind turbines

We report a wind tunnel study on the wake generated by a horizontal-axis (HAWT) and a vertical-axis wind turbine (VAWT). Two scaled models, one of each type, have been tested in a wind tunnel, under low blockage and at Reynolds numbers, based on the rotor diameter D, of ReD=265×103 for the HAWT and 330×103 for the VAWT. The models scale with respect to the largest commercially deployed turbines is of 1/383 and 1/65.5, for the HAWT and the VAWT, respectively. Furthermore, two different inflows were tested: low and moderate turbulence conditions. For each type of turbine and inflow, different values of tip-speed ratio and ReD were tested.Hot-wire anemometry was used to characterize the wake at different streamwise positions, exploring the range 1<x/D<30 for the HAWT and 1<x/D<15 for the VAWT.We find that, under a low-turbulence inflow, both turbines generate significantly different wakes, characterized by the velocity deficit, wake width and the profiles of average and rms streamwise velocities. More specifically, in low-turbulence conditions, the VAWT presents faster recovery than the HAWT. Remarkably, we observe that a moderately turbulent inflow results in similar wake shapes for both turbines, presenting similar recovery and structure under all studied conditions.

A study on the dynamic characteristics of alternative arrangements of floating wind farms with varying hub heights

Wind farms with multiple hub heights have the potential to effectively mitigate velocity deficits resulting from wake effects and reduce the levelized cost of energy (LCOE). While existing research has predominantly focused on studying wake effects on floating wind farms with identical hub heights, there is a notable absence of research on floating wind farms with multiple hub heights. Therefore, a comprehensive understanding of the impact of vertical arrangements on floating wind farms is essential. In light of this gap, this study examines the characteristics of two distinct arrangements of a semi-submersible floating wind farm with multiple hub heights. The configuration includes two 15 MW semi-submersible floating offshore wind turbines (FOWT) and two 5 MW semi-submersible FOWTs. A novel wind farm modeling tool utilizing dynamic wake meandering (DWM) is employed to investigate the power production performance, wake characteristics, global dynamic responses, and fatigue damage of crucial components of each individual FWT, associated with the two different arrangements. The paper presents a discussion of the advantages and disadvantages of the two arrangements, accompanied by a summary of the key findings. The insights gained from this research can serve as a foundational basis for improving the design and analysis processes of floating wind farms with various arrangements.

A numerical simulation framework for wakes downstream of large wind farms based on equivalent roughness model

Accurate assessment of the wake effect of wind farm clusters is of great significance for the development of wind power bases, yet there is currently a deficiency in numerical simulation methods with high accuracy and simple modeling. To address this issue, a numerical simulation framework for large wind-farm wakes based on a wind farm parameterization model is proposed, and is then implemented based on the open-source CFD software OpenFOAM. In this framework, a newly proposed wind farm equivalent roughness model is adopted to parameterize wind farms and incorporated into the simulation via the wall stress model. To validate the method, the large-eddy simulation based on the actuator disk model resolving all the turbines in the wind farm is taken as a benchmark. Thirty two cases including spanwise infinite wind farms and finite wind farms with different streamwise turbine spacings, spanwise turbine spacings, wind turbine thrust coefficients, and roughness lengths of ground surface are set to analyze the sensitivity of the framework to different wind farm parameters. Results show that the proposed method predicts the velocity deficit and turbulence intensity downstream of the wind farm accurately. Compared to the classical wake superposition model, the prediction accuracy of the velocity deficit is improved by more than 30 %. Furthermore, without resolving the turbines using fine mesh, the framework shows a high potential to reduce computational costs compared with the turbine-resolved simulation.

Numerical simulation of wind turbine wake characteristics by flux reconstruction method

In the paper, a CFD method that employs the flux reconstruction (FR) method and the actuator line method (ALM) is proposed, to develop a novel numerical framework to improve the efficiency and accuracy of turbulent wake predictions of horizontal axis wind turbines (HAWT). The PyFR solver, which is an open-source program that uses the FR method is applied. The ALM is for the first time implemented in the FR solver to simulate HAWTs. To increase the fidelity of the wake prediction, the nacelle and tower of the HAWT are also modeled, and the proposed numerical simulation method is named as AL-PyFR(N&T) model. The NTNU “Blind Test 1” wind turbine is used to validate the proposed model. First, the mesh and time step dependence of the AL-PyFR(N&T) model are verified. Second, the accuracy of the proposed model is verified by comparing the velocity deficits and turbulent kinetic energy results at different downstream locations with the measured values and the results from other CFD studies. By comparison of the results with and without the effect of the nacelle and tower, it is found that tower wake plays a significant role in wake asymmetry. Crucially, the AL-PyFR(N&T) model demonstrates a capacity for accurate wake predictions with fewer mesh requirements compared to conventional CFD models. This efficiency marks a significant advancement for high-fidelity numerical simulations of offshore wind farms.

Numerical analysis on hydrodynamic performance and wake recovery of helical-bladed hydrokinetic turbine: Impact of section inclination angle

In the context of exploiting renewable sources, cross-flow helical hydrokinetic turbine is conceded as one of the promising choices to unlock the potential in free-flowing water bodies. This study examines the impact of blade section inclination angle (−10° to +8°) and operational parameters, namely, tip speed ratio (0.6–1.4) and inflow velocity (1.0–2.5 m/s) on the performance as well as wake recovery of a 4-bladed rotor. The coefficients of power and section-averaged mean streamwise velocity deficit values are computed by solving the unsteady Reynolds-Averaged Navier-Stokes equations coupled with k-ε RNG turbulence model using numerical simulations to assess the performance and velocity recovery, respectively. The power coefficients are seen to be improved with an increase in negative section inclination angle and are found optimum in the range from −6° to −10° at a tip speed ratio of 1.0. The simulation results also reveal that the section inclination angle and tip speed ratio parameters significantly influence the velocity recovery. Furthermore, the performance decreases as the inflow velocity increases; however, the wake recovery is unaffected, with an identical wake length of 13 times the rotor diameter along the streamwise direction at a tip speed ratio of 1.0.

Comparison Of Full-Scale PIV Measurements With CFD Simulations Of A Ship Propeller Inflow

Flow around the ship's hull and specifically the inflow conditions of the propeller(s) critically influence the propeller efficiency and cavitation behaviour. In a typical single-propeller vessel, the hull of the ship creates a velocity deficit in the top part of the propeller disk. This creates suitable conditions for cavitation, which is the main source of noise and vibration both inside the vessel as well as in the marine environment. Recently, two measurement campaigns were performed using a novel full-scale stereo-PIV device built to measure flows around vessels sailing at sea. During the first campaign, performed in one of MARIN's basins, the device was commissioned. The second campaign was performed during a sea trial; it resulted in propeller inflow data that can be used for validating CFD codes. The uncertainty of the PIV measurements was assessed using both campaigns. In the basin, uncertainty bias could be determined by comparing the PIV results with the carriage speed. At sea, the random part of uncertainty was determined by quantifying the standard deviation of the mean velocity for all three velocity components in the wake peak area of the propeller inflow. Overall, the uncertainty was found to be acceptably small, given the scale of the measurement and the necessity to work with naturally occurring seeding particles in the sea. CFD calculations of the same full-scale flow were performed using an in-house flow solver. The CFD results predicted the propeller RPM and the delivered power measured during the full-scale trial well, which gives confidence in the ability of CFD to predict ship trial performance. The comparison of the flow fields was good, with the PIV results demonstrating that full-scale PIV can be done reliably, and that the CFD is able to capture the major features of the flow in the considered area. For a large part of the flow field, the CFD was within the measurement uncertainty band. The wake peak was slightly underpredicted, which may be related to roughness effects on the boundary layer thickness.