Periodic Reporting for period 2 - ALVAR (Advance Laminar Flow Control with Variable Porosity)
Okres sprawozdawczy: 2021-08-01 do 2022-05-31
The DNW-LLF is one of the world’s largest low speed facilities and offers unique capabilities for wind tunnel tests with large scale models at representative flow conditions. The framework provided for by ALVAR includes state-of-the-art data acquisition, aerodynamic data, lift, drag, static pressure distributions, transition location with infrared and hot films, and the extremely high flow quality of the LLF 8x6 m test section configuration.
One of the root problems in wind tunnel tests with hybrid laminar flow control is that it is technically unfeasible to actually measure the local suction flow rate over individual surface areas, but only the overall suction flow rate including a number of additional values, such as pressures at certain locations, is feasible. However, the local flow rate can be post-processed based on a complex measurement chain, employing data mappings (e.g. calibration of the suction skin), interpolation/extrapolation schemes of the pressure distribution, and geometry measurements. This makes the local flow rate prone to the propagation of uncertainties and errors. ALVAR therefore provides a scientific analysis of the whole measurement chain to establish a precise uncertainty of the local flow rate using Bayesian inference. Based on this, and through analysis, design, optimization and implementation of a specific main mass flow meter including a proven pumping system to provide stable suction rates a comprehensive quantification of boundary layer suction is performed by ALVAR.
TUBS has established a comprehensive computation chain for inferring the spatial distribution of surface suction velocities and its uncertainties from measurable data. The method comprises a model of the porous suction skin, a re-building of the surface pressure distribution, the readings of internal model sensors, and the wind tunnel onset flow data, and measured wind tunnel model geometry. The input data are accompanied by estimates of uncertainty. The new computation method allows to predict the mean suction velocities and its uncertainty bounds by Bayesian inference.
The method has been successfully employed to evaluate the sensitivities of suction flow with respect to uncertain parameters, and to compute final uncertainty data based on the measurements in the wind tunnel.
DNW and TU Braunschweig established a joint test plan of the wind tunnel experiments and its constraints. The plan comprises detailed suction flow experiments with variations of the relevant flow parameters, and transpiration experiments at off-design conditions at high yawing angle. Based on carefully performed pre-testing of the wind tunnel model and its instrumentation, the windtunnel test campaign took place in February 2022. The test data were carefully evaluated and analysed for pressure distributions, transition location and flow field characteristics. The results show that the TSSD concept of hybrid laminar flow control is viable for large suction inserts and for Reynolds numbers representative for flight application. Uncertainties of the local suction velocities, which are most important for characterising the flow control effect were comprehensively quantified. The project results have resulted in a unique aerodynamic data set, that can be used for future vaildation of development methods in hybrid laminar flow control, and for further developing compliant suction structures.