L'hypercube is proud to have contributed to the Grand Prix National de l'Ingénierie 2021, won by AREP teams, for the transformation project of the Saint-Michel Notre-Dame station (RER C).
Subsequently, we had to deal with other site constraints, such as acoustics and flood control. It is precisely this collective and iterative work of the different engineering departments that was rewarded by the GPNI!
Below is a video presentation of the main challenges of the project:
In the beginning of 2021, we completed the development of a tool for simulating surface temperatures in an urban environment, using a weak coupling approach between temperatures and air velocities
The approach allows for comfort indexes computations at each point in space. It integrates the coupling of fluid mechanics simulations, together with sunlight and thermal dynamic regimes for the built environment.
Results of a case study around the Strasbourg train station (France) are presented next.
Flux solaires en fin de journéeVitesses d’air à une heure donnéeAverage comfort levels on the forecourt of the Strasbourg Train Station, during the hottest week of the year.
The following animation shows the evolution of comfort levels over the first week of the year Sit back and relax!
Hourly comfort levels during the first week of the year.
A study on possible variants for the improvement of summer and winter comfort of the side halls as well as the transverse platform implementing :
A CFD/BES coupling with solar fluxes for the indoor spatial comfort levels computation,
A sensitivity analysis with the Morris method, on comfort objective to determine the most relevant leverages
The use of genetic optimization in order to obtain the sets of parameters that maximize summer and winter comfort.
Below is an animation about the evolution of comfort levels during genetic optimization, according to the "growth" of generations:
Genetic optimization: optimal solutions evolution over generations
Each "dot" that appears corresponds to a complete comfort study (point 1 above) and each color change corresponds to a new generation. The objective of genetic optimization is to find the best compromise between summer and winter comfort (Pareto front).
Development of a differential equation physical model for the prediction of PM10 / PM2.5 concentration in underground stations, in order to evaluate the relevance of technical solutions aimed at improving air quality (ventilation, filtration, etc.).