@article{BindalSharmaJanseretal.2013,
  author    = {Bindal, Gaurav and Sharma, Sparsh and Janser, Frank and Neu, Eugen},
  title     = {Detailed analysis of variables affecting wing kinematics of bat flight},
  series = {SAE International Journal of Aerospace},
  volume    = {6},
  journal   = {SAE International Journal of Aerospace},
  number    = {2},
  issn      = {1946-3901},
  doi       = {10.4271/2013-01-9003},
  pages     = {811 -- 818},
  year      = {2013},
  language  = {en}
}
@inproceedings{BergmannGoettenBraunetal.2022,
  author    = {Bergmann, Ole and G{\"o}tten, Falk and Braun, Carsten and Janser, Frank},
  title     = {Comparison and evaluation of blade element methods against RANS simulations and test data},
  series = {CEAS Aeronautical Journal},
  volume    = {13},
  booktitle = {CEAS Aeronautical Journal},
  publisher = {Springer},
  address   = {Wien},
  issn      = {1869-5590 (Online)},
  doi       = {10.1007/s13272-022-00579-1},
  pages     = {535 -- 557},
  year      = {2022},
  abstract  = {This paper compares several blade element theory (BET) method-based propeller simulation tools, including an evaluation against static propeller ground tests and high-fidelity Reynolds-Average Navier Stokes (RANS) simulations. Two proprietary propeller geometries for paraglider applications are analysed in static and flight conditions. The RANS simulations are validated with the static test data and used as a reference for comparing the BET in flight conditions. The comparison includes the analysis of varying 2D aerodynamic airfoil parameters and different induced velocity calculation methods. The evaluation of the BET propeller simulation tools shows the strength of the BET tools compared to RANS simulations. The RANS simulations underpredict static experimental data within 10\% relative error, while appropriate BET tools overpredict the RANS results by 15-20\% relative error. A variation in 2D aerodynamic data depicts the need for highly accurate 2D data for accurate BET results. The nonlinear BET coupled with XFOIL for the 2D aerodynamic data matches best with RANS in static operation and flight conditions. The novel BET tool PropCODE combines both approaches and offers further correction models for highly accurate static and flight condition results.},
  language  = {en}
}
@article{NeuJanserKhatibietal.2016,
  author    = {Neu, Eugen and Janser, Frank and Khatibi, Akbar A. and Orifici, Adrian C.},
  title     = {Automated modal parameter-based anomaly detection under varying wind excitation},
  series = {Structural Health Monitoring},
  volume    = {15},
  journal   = {Structural Health Monitoring},
  number    = {6},
  publisher = {Sage},
  address   = {London},
  issn      = {1475-9217},
  doi       = {10.1177/1475921716665803},
  pages     = {1 -- 20},
  year      = {2016},
  abstract  = {Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions.},
  language  = {en}
}