Aerodynamic optimisation of sports stadiums towards wind comfort

The aim of this work was to investigate the aerodynamic performance of sports stadiums located in the built environment and conduct a design optimisation study to improve the wind comfort conditions for both players and spectators. A 1:300 scale semi-open stadium model was assessed with combined Atmospheric Boundary Layer (ABL) wind tunnel experimentation and Computational Fluid Dynamics (CFD) techniques against pressure and velocity distribution patterns in both interior and exterior areas of the stadium bowl. The validation of the numeric analysis was performed with the experimental results of pressure coefficients. The aerodynamic performance analysis compared two impinging wind angles (0o and 90o) and two building envelope porosities, defined by the existence of an elevated and non-elevated roof configuration. The results indicated that the wind direction caused small differentiations on the developed wind distribution patterns, with the wind angle of 90o generating smaller negative pressures in both interior and exterior stadium surfaces. Further analysis of the air velocity distribution results indicated that the provision of a horizontal ventilation opening between the roof and the upper spectator tiers substantially improves the airflow distribution for the benefit of spectators, but induces up to 25 % higher velocities at the centre of the pitch level. Parametric studies were performed to evaluate the impact of the roof geometry changes on the developed wind comfort conditions for the players and the spectators. By employing coupled CFD-Response Surface Methodology (RSM) techniques, it was found that the wind speeds and the flow homogeneity at the stadium bowl are more susceptible to firstly the roof height and secondly the roof radius. Finally, the generated response surfaces formed the basis for the conduction of a multi-objective optimisation study, which revealed that a drastic reduction of the roof height and the roof radius by 96.9 % and 50 % respectively may reduce the wind speeds and the flow heterogeneity up to 37 % and 49.6 % in the occupied areas

Modelling the Eddy Pattern in the harbour of Zeebrugge

Hydrodynamic

A Statistical Approach to the Alignment of fMRI Data

Multi-subject functional Magnetic Resonance Image studies are critical. The anatomical and functional structure varies across subjects, so the image alignment is necessary. We define a probabilistic model to describe functional alignment. Imposing a prior distribution, as the matrix Fisher Von Mises distribution, of the orthogonal transformation parameter, the anatomical information is embedded in the estimation of the parameters, i.e., penalizing the combination of spatially distant voxels. Real applications show an improvement in the classification and interpretability of the results compared to various functional alignment methods

A comparison of the CAR and DAGAR spatial random effects models with an application to diabetics rate estimation in Belgium

When hierarchically modelling an epidemiological phenomenon on a finite collection of sites in space, one must always take a latent spatial effect into account in order to capture the correlation structure that links the phenomenon to the territory. In this work, we compare two autoregressive spatial models that can be used for this purpose: the classical CAR model and the more recent DAGAR model. Differently from the former, the latter has a desirable property: its ρ parameter can be naturally interpreted as the average neighbor pair correlation and, in addition, this parameter can be directly estimated when the effect is modelled using a DAGAR rather than a CAR structure. As an application, we model the diabetics rate in Belgium in 2014 and show the adequacy of these models in predicting the response variable when no covariates are available