During past years, to improve the quality of wind tunnel data in transonic configurations, researchers first designed new wind tunnel geometries (as porous and/or slotted wind tunnels), then developed more accurate correction laws giving acceptable results in certain conditions but absolutely not sufficient to satisfy the increasing aeronautical requirements. Recent studies showed that the quality of wind tunnel data can be improved by using test sections provided with variable streamwise porosity distributions instead of the typical uniform ones. Some authors identified this new concept of variable porosity distribution as the third generation of porous wind tunnels.

In order to improve knowledge about effects of the porosity distribution on the wall interference in subsonic/transonic conditions, an experimental investigation was carried out in the PT-1 CIRA transonic wind tunnel in the Mach range between 0.3 and 0.9 (over 400 test points were measured on different models and wall porosity configurations). At this aim, a dedicated experimental setup consisting in five plates positioned on the top and bottom walls of the PT-1 porous test section, has been designed and realized. Setting independently each plate, it is possible to obtain practically unlimited combinations of porosity distributions along the streamwise direction.

The final purpose of the present activity was to evaluate the optimal porosity distribution able to minimize wind tunnel wall interferences in the considered Mach range. The huge number of factors (Mach number and the positions of the five plates setting the porosity distribution) made practically impossible to study the porosity distribution effects by using a traditional One Factor At a Time (OFAT) approach. Therefore, the optimum porosity distribution has been achieved through an experiment designed with a Modern Design of Experiment (MDOE) approach. Within the MDOE approach, the RSM (Response Surface Modeling) has been selected. The objective of the experiment, designed with the RSM approach, is to acquire a sufficient number of data to create one or more response surface models to be used to predict the response variable of interest (within a specified uncertainty) as function of the factors which can affect the selected response variables.

The best porosity distribution able to improve the quality of wind tunnel data has been found for the PT-1 Wind Tunnel (but results and/or the procedure are applicable to all similar Wind Tunnels).

In the present paper, to contextualize the activity, after a short summary of the historical wind tunnel development, the stat of art of the variable streamwise porosity distribution is discussed. Then, the experimental setup to simulate in wind tunnel several streamwise variable porosity distribution and the design of Experiment are described. Finally, the main experimental results are reported and critically analyzed.

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