|Institution:||Delft University of Technology|
|Keywords:||wave drag; meta-modeling|
|Full text PDF:||http://resolver.tudelft.nl/uuid:8741189f-1006-4e79-89d8-8c7bc11d6baa|
There is a need for a wave drag method that combines the speed of handbook methods with the accuracy of computational methods. Especially determining the onset of wave drag as well as the initial drag rise is important in initial design stages. Meta-models allow this by capturing the trends present in previously computed data, providing an accurate and fast representation. In this report, it is investigated what gains can be achieved by applying the meta-modeling method GT-Approx to the aerodynamic tool MSES. The total drag calculated by MSES for a super critical airfoil was verified using wind tunnel experiments. It was found that aerodynamic characteristics and pressure distributions are accurate up until M = 0.76. GT-Approx was critically evaluated. It was found that the general prediction quality was good, but that the error increased substantially for complex cases, such as high M or high cl This issue is solved by increasing the resolution of the input data. By optimizing the resolution for the different input variables the average prediction error decreased by 30% for cdv and 70% for cdw. Especially for the difficult cases, the accuracy greatly improved. Two A320 variants are evaluated using GT-Approx and a direct application of MSES. The performance of GTApprox is good. An average difference of 0.21 drag counts between MSES and GT-Approx was achieved, with an in-calculation computation time of 5.13∙10⁻⁴s per calculation instead of 5.58s using a direct application of MSES. GT-Approx is extended to a quasi-3Dmethod, using the simple sweep method. This quasi-3D method is used to calculate the value of CDw for two test cases. The calculated values of CDw are compared with CFD data. It was found that the region of validity of the quasi-3D method is highly limited. Up until 60% of the wing, root and tip effects, fuselage effects and engine installation effects render any comparison useless. Beyond this value the first test case showed no correlation, whereas the second showed reasonable accuracy. Due to lack of more 3D CFD data, no clear explanation for the difference was found. In general it is concluded that the combination of an aerodynamic tool with a meta-model is able to combine low computation times with high accuracy, but only if the aerodynamic model is accurate.