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A novel method for generating turbulent inflow boundary conditions for aeroelastic computations is proposed, based on interfacing hybrid hot-wire and particle image velocimetry measurements performed in a wind tunnel to a full-scale load simulation conducted with FAST. This approach is based on the use of proper orthogonal decomposition (POD) to interpolate and extrapolate the experimental data onto the numerical grid. The temporal dynamics of the temporal POD coefficients is driven by the high-frequency hot-wire measurements used as input for a lower-order model built using a multi-time-delay linear stochastic estimation (LSE) approach. Being directly extracted from the data, the generated three-component velocity fields later used as inlet conditions present correct one- and two-point spatial statistics and realistic temporal dynamics. Wind tunnel measurements are performed at a scale of 1: 750, using a properly scaled porous disk as a floating wind turbine model. The motions of the platform are imposed by a linear actuator. Between all 6 degrees of freedom (DOFs) possible, the present study focus on the streamwise direction motion of the model (surge motion). The POD analysis of the flow, with or without considering the presence of the surge motion of the model, shows that a few modes are able to capture the characteristics of the most energetic flow structures and the main features of the wind turbine wake, such as its meandering and the influence of the surge motion. The interfacing method is first tested to estimate the performance of a wind turbine in an offshore boundary layer and then those of a wind turbine immersed in the wake of an upstream wind turbine subjected to a sinusoidal surge motion. Results are also compared to those obtained using the standard inflow generation method provided by TurbSim available in FAST. [ABSTRACT FROM AUTHOR]

Intra-array wake meandering increases fatigue loading in downstream turbines and decreases farm total power output. In the case of floating offshore wind turbines (FOWTs), the motions of the floating substructure could have a non-neglectable contribution to wake meandering dynamics. This research experientially analyses the influence of imposed motions on the far-wake meandering of a FOWT. The study considers a 1:500 scaled porous disc representation of the 2 MW FLOATGEN system (BW Ideol) located off the coast of Le Croisic, France. A representative marine neutral atmospheric boundary layer is generated in a wind tunnel whilst monochromic and multi-frequency content three degrees of freedom (surge, heave, pitch) motion is imposed on the model tower. The stereoscopic particle image velocimetry (S-PIV) is then utilised to measure velocity vectors at a cross-section located at 8.125 D downstream of the model. No significant effect on the far-wake recovery in the velocity, turbulence and turbulent kinetic energy distribution is observed. However, the frequency characteristics of the imposed motions were observed in the far-wake meandering spectral content and streamwise characteristics of far-wake, such as normalised available power. While the frequency spectrum of the vertical oscillations showed more sensitivity to the three degrees of freedom (3DoF) imposed motion in all frequency ranges, the lateral oscillation was sensitive for the reduced frequency above 0.15. The monochromic motions with a reduced frequency of less than 0.15 also did not influence the far-wake centre distribution in both lateral and vertical directions. Regardless of reduced frequency, imposed motions show a strong effect on average power, in which the harmonic signature can distinguish in far-wake memory. This study provides an investigation, which its result could be beneficial to developing and examining wake models for offshore wind turbines, with a particular focus on the influence of FOWTs motions. [ABSTRACT FROM AUTHOR]

High-resolution data from the large-eddy simulation of the atmospheric boundary layer (ABL) over a vegetation canopy are used to investigate the interaction between the most energetic large-scale structures from the ABL and the smaller scales from the near-canopy region. First, evidence of amplitude modulation (AM) involving the three velocity components is demonstrated. A multi-scale analysis of the transport equation of both the turbulent kinetic energy (TKE) and Reynolds shear stress (RSS) is then performed using a multi-level filtering procedure. It is found that, on average, in the investigated region, large scales are a source of TKE for the small scales (e.g. forward scatter of TKE) through nonlinear interscale transfer ($T_r^L$) with a maximum at canopy top while they are a sink via turbulent transport ($T_t^L$). Close to the canopy, the small-scale RSS transport behaves the same while, above the roughness sublayer, $T_r^L$ and $T_t^L$ switch roles showing the existence of RSS backscatter. The standard deviation of the transfer terms shows that there are intense instantaneous forward and backscatter of both TKE and RSS via all the transfer terms. It is therefore demonstrated that there is a two-way coupling between the ABL and the near-canopy scales, the well-known top-down mechanism through TKE transfer being complemented by a bottom-up feedback through RSS transfer. This analysis is extended to several stability regimes, confirming the above conclusions and showing the increasing role of the large-scale wall-normal component in AM and TKE or RSS transfers when the flow becomes buoyancy driven. [ABSTRACT FROM AUTHOR]

Urban-type rough-wall boundary layers developing over staggered cube arrays with plan area packing density, $\unicode[STIX]{x1D706}_{p}$ , of 6.25 %, 25 % or 44.4 % have been studied at two Reynolds numbers within a wind tunnel using hot-wire anemometry (HWA). A fixed HWA probe is used to capture the outer-layer flow while a second moving probe is used to capture the inner-layer flow at 13 wall-normal positions between $1.25h$ and $4h$ where $h$ is the height of the roughness elements. The synchronized two-point HWA measurements are used to extract the near-canopy large-scale signal using spectral linear stochastic estimation and a predictive model is calibrated in each of the six measurement configurations. Analysis of the predictive model coefficients demonstrates that the canopy geometry has a significant influence on both the superposition and amplitude modulation. The universal signal, the signal that exists in the absence of any large-scale influence, is also modified as a result of local canopy geometry suggesting that although the nonlinear interactions within urban-type rough-wall boundary layers can be modelled using the predictive model as proposed by Mathis et al. (J. Fluid Mech., vol. 681, 2011, pp. 537–566), the model must be however calibrated for each type of canopy flow regime. The Reynolds number does not significantly affect any of the model coefficients, at least over the limited range of Reynolds numbers studied here. Finally, the predictive model is validated using a prediction of the near-canopy signal at a higher Reynolds number and a prediction using reference signals measured in different canopy geometries to run the model. Statistics up to the fourth order and spectra are accurately reproduced demonstrating the capability of the predictive model in an urban-type rough-wall boundary layer. [ABSTRACT FROM AUTHOR]

The influence of a cube-based canopy on coherent structures of the flow was investigated in a high Reynolds number boundary layer (thickness $\unicode[STIX]{x1D6FF}\sim 30\,000$ wall units). Wind tunnel experiments were conducted considering wall configurations that represent three idealised urban terrains. Stereoscopic particle image velocimetry was employed using a large field of view in a streamwise–spanwise plane ($0.55\unicode[STIX]{x1D6FF}\times 0.5\unicode[STIX]{x1D6FF}$) combined to two-point hot-wire measurements. The analysis of the flow within the inertial layer highlights the independence of its characteristics from the wall configuration. The population of coherent structures is in agreement with that of smooth-wall boundary layers, i.e. consisting of large- and very-large-scale motions, sweeps and ejections, as well as smaller-scale vortical structures. The characteristics of vortices appear to be independent of the roughness configuration while their spatial distribution is closely linked to large meandering motions of the boundary layer. The canopy geometry only significantly impacts the wall-normal exchanges within the roughness sublayer. Bi-dimensional spectral analysis demonstrates that wall-normal velocity fluctuations are constrained by the presence of the canopy for the densest investigated configurations. This threshold in plan area density above which large scales from the overlying boundary layer can penetrate the roughness sublayer is consistent with the change of the flow regime reported in the literature and constitutes a major difference with flows over vegetation canopies. [ABSTRACT FROM AUTHOR]

The non-linear energy transfer between the most energetic structures in the logarithmic layer (referred to here as large-scales) and those in the roughness sublayer induced by the presence of the roughness (referred to here as small-scales) is studied in a boundary layer developing over a rough-wall consisting of staggered cubes with a plan area packing density,  = 25%, in the wind tunnel using combined Particle Image Velocimetry (PIV) and Hot-Wire Anemometry (HWA). The energy transfer between the mean flow, large-scales and small-scales is quantified using scale decomposition of the Turbulent Kinetic Energy (TKE) budget. Multi-time delay Linear Stochastic Estimation (LSE) is used to decompose the flow into large- and small-scales. Using scale decomposition of the TKE budget it is shown that although the greatest mean energy transfer occurs between the mean flow and the small-scales a significant instantaneous energy transfer between the large- and small-scales exists. Finally, it is confirmed through spatio-temporal cross correlation that the non-linear relationship that exists between large-scale coherent structures and small-scales created through interaction with the roughness elements is linked to instantaneous energy transfer between these structures. [ABSTRACT FROM AUTHOR]

High-Reynolds-number experiments are conducted in the roughness sublayer of a turbulent boundary layer developing over a cubical canopy. Stereoscopic particle image velocimetry is performed in a wall-parallel plane to evidence a high degree of spatial modulation of the small-scale turbulence around the footprint of large-scale motions, despite the suppression of the inner layer by the high roughness elements. Both Fourier and wavelets analyses show that the near-wall cycle observed in smooth-wall-bounded flows is severely disrupted by the canopy, whose wake in the roughness sublayer generates a new range of scales, closer to that of the outer-layer large-scale motions. This restricts significantly scale separation, hence a diagnostic method is developed to divide carefully and rationally the fluctuating velocity fields into large- and small-scale components. Our analysis across all turbulent kinetic energy terms sheds light on the spatial imprint of the modulation mechanism, revealing a very different signature on each velocity component. The roughness sublayer shows a preferential arrangement of the modulated scales similar to what is observed in the outer layer of smooth-wall-bounded flows – small-scale turbulence is enhanced near the front of high momentum regions and damped at the front of low momentum regions. More importantly, accessing spanwise correlations reveals that modulation intensifies the most along the flanks of the large-scale motions. [ABSTRACT FROM AUTHOR]

The effects on turbulent street canyon flow of the morphological model and the existence of an upstream tall building are investigated in a wind tunnel, using Stereoscopic Particle Image Velocimetry (S-PIV) measurements on two orthogonal vertical planes. The cathedral in the "Rue de Strasbourg, (Nantes, France)" morphological model is regarded as a local tall building and is tested and then replaced by generic, square planform buildings of 4 different heights. The cathedral induces an asymmetrical wake while no obvious different influence on the street canyon flow can be identified, in comparison with a generic building of the same height. A strong along-canyon flow occurs which may be due to the intersections, while the along-canyon ventilation decreases with increasing building height. The higher the building, the stronger its sheltering effect, leading to a reduction of the vertical ventilation and mass transport across the canyon opening, at least in the canyon portion directly downstream of the building. • A strong along-canyon flow is observed in the morphological model studied. • Turbulence statistics in the street canyon are larger than in an idealized canyon. • The mass flux across the canyon roof reduces with a higher upstream building. • Tall building shape does not impact turbulence statistics within a street canyon. [ABSTRACT FROM AUTHOR]

In the present work, a boundary layer developing over a rough-wall consisting of staggered cubes with a plan area packing density λp = 25% is studied within the wind tunnel using Particle Image Velocimetry (PIV) to investigate the Turbulent Kinetic Energy (TKE) budget. To access the full TKE budget, an estimation of the dissipation (ε) using both the transport equation of the resolved-scale kinetic energy and Large-Eddy (LE) PIV models based on the use of a subgrid-scale model following the methodology used in large-eddy simulations is employed. A low-pass filter, larger than the Taylor microscale, is applied to the data prior to the computation of the velocity gradients ensuring a clear cutoff in the inertial range where the models are valid. The presence of the cube roughness elements has a significant influence on the TKE budget due to the region of strong shear that develops over the cubes. The shear layer is shown to produce and dissipate energy, as well as transport energy through advection, turbulent transport, and pressure transport. The recirculation region that forms through the interaction of the shear layer and the canopy layer, which is the region below the height of the cube roughness, creates rapid longitudinal evolution of the mean flow thereby inducing weak production. Finally, through stochastic estimation of the conditional average, it is shown that localized regions of backscatter (energy transfer from unresolved to resolved scales) and forward scatter (energy transfer from resolved to unresolved scales) occur as a result of coherent vortical structures. [ABSTRACT FROM AUTHOR]

In the present work, a boundary layer developing over a rough-wall consisting of staggered cubes with a plan area packing density, λp = 25%, is studied within a wind tunnel using combined particle image velocimetry and hot-wire anemometry to investigate the non-linear interactions between large-scale momentum regions and small-scale structures induced by the presence of the roughness. Due to the highly turbulent nature of the roughness sub-layer and measurement equipment limitations, temporally resolved flow measurements are not feasible, making the conventional filtering methods used for triple decomposition unsuitable for the present work. Thus, multi-time delay linear stochastic estimation is used to decompose the flow into large-scales and small-scales. Analysis of the scale-decomposed skewness of the turbulent velocity (u′) shows a significant contribution of the non-linear term u′Lu′S², which represents the influence of the large-scales (u′L) onto the small-scales (u′S). It is shown that this non-linear influence of the large-scale momentum regions occurs with all three components of velocity in a similar manner. Finally, through two-point spatio-temporal correlation analysis, it is shown quantitatively that large-scale momentum regions influence small-scale structures throughout the boundary layer through a non-linear top-down mechanism. [ABSTRACT FROM AUTHOR]

Generation of turbulent inflow boundary conditions is performed by interfacing an experimental database acquired by particle image velocimetry to a computational code. The proposed method ensures that the velocity fields introduced as inlet conditions in the computational code present correct one- and two-point spatial statistics and a realistic temporal dynamics. This approach is based on the use of the proper orthogonal decomposition (POD) to interpolate and extrapolate the experimental data onto the numerical mesh and to model both the temporal dynamics and the spatial organization of the flow in the inlet section. Realistic representation of the flow is achieved by extracting and modeling independently its coherent and incoherent parts. A low-order dynamical model is derived from the experimental database in order to provide the temporal evolution of the most energetic structures. The incoherent motion is modeled by employing time series of Gaussian random numbers to mimic the temporal evolution of higher order POD modes. Validation of the proposed method is provided by performing a large-eddy simulation of a turbulent plane mixing layer, which is compared to experimental results. [ABSTRACT FROM AUTHOR]

Low-order modelling based on POD approach has proved to be an efficient tool to analyze turbulent flows as well as to build control systems. In this paper, a novel method to identify low-order dynamical system (LODS) is proposed. This approach relies on the fact that all the POD-Galerkin LODS based on Navier–Stokes equations can be written in polynomial form. One proposes here to estimate the polynomial coefficients arising in such a formalism by the following. The projection coefficients of the flow field onto its POD basis and their time derivatives being known, a statistical approach involving correlations between these quantities, are used to provide an estimate of the coefficients of the dynamical system. The identification method is described and tested in the case of the analytical Lorenz system. Finally, the LODS identification is performed in the case of experimental data of a supersonic jet-mixing layer interaction. Dynamical systems based on flow visualizations are derived and lead to relevant short-time and long-term predictions. [ABSTRACT FROM AUTHOR]

Despite enormous progress in fundamental knowledge in neuroscience, no revolutionary therapies in psychiatry (and neurology) have emerged in the past ten years. Most drugs alleviate symptoms, rather than restoring the 'set point' of brain function from a pathological position to a more normal one. We propose a hypothesis-driven, systems-level approach to drug discovery and development that is based on pathophysiology and which uses new animal models. [ABSTRACT FROM AUTHOR]

1. The electroencephalographic (EEG) effects of the propsychotic agent phencyclidine (PCP), were studied in conscious rats using power spectra (0 - 30 Hz), from the prefrontal cortex or sensorimotor cortex. PCP (0.1 - 3 mg kg(-1) s.c.) caused a marked dose-dependent increase in EEG power in the frontal cortex at 1 - 3 Hz with decreases in power at higher frequencies (9 - 30 Hz). At high doses (3 mg kg(-1) s.c.) the entire spectrum shifted to more positive values, indicating an increase in cortical synchronization. MK 801 (0.05 - 0.1 mg kg(-1) i.p.) caused similar effects but with lesser changes in power. 2. In contrast, the non-competitive AMPA antagonists GYKI 52466 and GYKI 53655 increased EEG power over the whole power spectrum (1 - 10 mg kg(-1) i.p.). The atypical antipsychotic clozapine (0.2 mg kg(-1) s.c.) synchronized the EEG (peak 8 Hz). The 5-HT(2A)-antagonist, M100907, specifically increased EEG power at 2 - 3 Hz at low doses (10 and 50 microg kg(-1) s.c.), whereas at higher doses (0.1 mg kg(-1) s.c.) the profile resembled that of clozapine. 3. Clozapine (0.2 mg kg(-1) s.c. ), GYKI 53655 (5 mg kg(-1) i.p.), prazosin (0.05 and 0.1 mg kg(-1) i.p.), and M100907 (0.01 and 0.05 mg kg(-1) s.c.) antagonized the decrease in power between 5 and 30 Hz caused by PCP (1 mg kg(-1) s.c.), but not the increase in power at 1 - 3 Hz in prefrontal cortex. [ABSTRACT FROM AUTHOR]

Despite enormous progress in fundamental knowledge in neuroscience, no revolutionary therapies in psychiatry (and neurology) have emerged in the past ten years. Most drugs alleviate symptoms, rather than restoring the 'set point' of brain function from a pathological position to a more normal one. We propose a hypothesis-driven, systems-level approach to drug discovery and development that is based on pathophysiology and which uses new animal models.

Although many new potential drug targets have been discovered subsequent to the cloning of the human genome and the discovery of most of the relevant receptors, the role of these receptors in psychiatric disease is still not clear. We argue that research into the disease process leading to new animal models that can be transposed to man is critical to drug discovery, and present an example of an animal model for schizophrenia using electroencephalography.