@inproceedings{KapoorBraunBoller2010, author = {Kapoor, Hrshi and Braun, Carsten and Boller, Christian}, title = {Modelling and optimisation of maintenance intervals to realize structural health monitoring applications on aircraft}, series = {Structural health monitoring 2010 : proceedings of the Fifth European Workshop on Structural Health Monitoring held at Sorrento, Naples, Italy, June 28 - July 4, 2010 ; [EWSHM]}, booktitle = {Structural health monitoring 2010 : proceedings of the Fifth European Workshop on Structural Health Monitoring held at Sorrento, Naples, Italy, June 28 - July 4, 2010 ; [EWSHM]}, editor = {Casciati, Fabio}, publisher = {DEStech Publ.}, address = {Lancaster, Pa.}, isbn = {978-1-60595-024-2}, pages = {55 -- 63}, year = {2010}, language = {en} } @misc{KeimerGirbigMayntzetal.2022, author = {Keimer, Jona and Girbig, Leo and Mayntz, Joscha and Tegtmeyer, Philipp and Wendland, Frederik and Dahman, Peter and Fisher, Alex and Dorrington, Graham}, title = {Flight mission optimization for eco-efficiency in consideration of electric regeneration and atmospheric conditions}, series = {AIAA AVIATION 2022 Forum}, journal = {AIAA AVIATION 2022 Forum}, publisher = {AIAA}, address = {Reston, Va.}, doi = {10.2514/6.2022-4118}, year = {2022}, abstract = {The development and operation of hybrid or purely electrically powered aircraft in regional air mobility is a significant challenge for the entire aviation sector. This technology is expected to lead to substantial advances in flight performance, energy efficiency, reliability, safety, noise reduction, and exhaust emissions. Nevertheless, any consumed energy results in heat or carbon dioxide emissions and limited electric energy storage capabilities suppress commercial use. Therefore, the significant challenges to achieving eco-efficient aviation are increased aircraft efficiency, the development of new energy storage technologies, and the optimization of flight operations. Two major approaches for higher eco-efficiency are identified: The first one, is to take horizontal and vertical atmospheric motion phenomena into account. Where, in particular, atmospheric waves hold exciting potential. The second one is the use of the regeneration ability of electric aircraft. The fusion of both strategies is expected to improve efficiency. The objective is to reduce energy consumption during flight while not neglecting commercial usability and convenient flight characteristics. Therefore, an optimized control problem based on a general aviation class aircraft has to be developed and validated by flight experiments. The formulated approach enables a development of detailed knowledge of the potential and limitations of optimizing flight missions, considering the capability of regeneration and atmospheric influences to increase efficiency and range.}, language = {en} } @phdthesis{Keinz2018, author = {Keinz, Jan}, title = {Optimization of a Dry Low NOx Micromix Combustor for an Industrial Gas Turbine Using Hydrogen-Rich Syngas Fuel}, publisher = {Universit{\´e} Libre de Bruxelles - Brussels School of Engineering Aero-Thermo-Mechanics}, address = {Br{\"u}ssel}, year = {2018}, language = {en} } @inproceedings{KemperHellenbroichEsch2009, author = {Kemper, Hans and Hellenbroich, Gereon and Esch, Thomas}, title = {Concept of an innovative passenger-car hybrid drive for European driving conditions}, series = {Hybrid vehicles and energy management : 6th symposium ; 18th and 19th February 2009, Stadthalle Braunschweig}, booktitle = {Hybrid vehicles and energy management : 6th symposium ; 18th and 19th February 2009, Stadthalle Braunschweig}, publisher = {Gesamtzentrum f{\"u}r Verkehr (GZVB)}, address = {Braunschweig}, isbn = {978-3-937655-20-8}, pages = {264 -- 287}, year = {2009}, abstract = {The downsizing of spark ignition engines in conjunction with turbocharging is considered to be a promising method for reducing CO₂ emissions. Using this concept, FEV has developed a new, highly efficient drivetrain to demonstrate fuel consumption reduction and drivability in a vehicle based on the Ford Focus ST. The newly designed 1.8L turbocharged gasoline engine incorporates infinitely variable intake and outlet control timing and direct fuel injection utilizing piezo injectors centrally located. In addition, this engine uses a prototype FEV engine control system, with software that was developed and adapted entirely by FEV. The vehicle features a 160 kW engine with a maximum mean effective pressure of 22.4 bar and 34 \% savings in simulated fuel consumption. During the first stage, a new electrohydraulically actuated hybrid transmission with seven forward gears and one reverse gear and a single dry starting clutch will be integrated. The electric motor of the hybrid is directly connected to the gear set of the transmission. Utilizing the special gear set layout, the electric motor can provide boost during a change of gears, so that there is no interruption in traction. Therefore, the transmission system combines the advantages of a double clutch controlled gear change (gear change without an interruption in traction) with the efficient, cost-effective design of an automated manual transmission system. Additionally, the transmission provides a purely electric drive system and the operation of an air-conditioning compressor during the engine stop phases. One other alternative is through the use of CAI (Controlled Auto Ignition), which incorporates a process developed by FEV for controlled compression ignition.}, language = {en} } @article{KezerashviliDachwald2021, author = {Kezerashvili, Roman Ya and Dachwald, Bernd}, title = {Preface: Solar sailing: Concepts, technology, and missions II}, series = {Advances in Space Research}, volume = {67}, journal = {Advances in Space Research}, number = {9}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0273-1177}, doi = {10.1016/j.asr.2021.01.037}, pages = {2559 -- 2560}, year = {2021}, language = {en} } @article{KhayyamJamaliBabHadiasharetal.2020, author = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalil, Mahdi and Naebe, Minoo}, title = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0}, series = {IEEE Access}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York, NY}, isbn = {2169-3536}, doi = {10.1109/ACCESS.2020.2999898}, pages = {1 -- 12}, year = {2020}, abstract = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.}, language = {en} } @article{KhayyamJamaliBabHadiasharetal.2020, author = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalili, Mahdi and Naebe, Minoo}, title = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0}, series = {IEEE Access}, volume = {8}, journal = {IEEE Access}, number = {Art. 9108222}, publisher = {IEEE}, address = {New York, NY}, issn = {2169-3536}, doi = {10.1109/ACCESS.2020.2999898}, pages = {111381 -- 111393}, year = {2020}, abstract = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.}, language = {en} } @inproceedings{KleineKallweitMichauxetal.2016, author = {Kleine, Harald and Kallweit, Stephan and Michaux, Frank and Havermann, Marc and Olivier, Herbert}, title = {PIV Measurement of Shock Wave Diffraction}, series = {18th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2016, Lissabon}, booktitle = {18th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2016, Lissabon}, pages = {1 -- 14}, year = {2016}, language = {en} } @inproceedings{KnoblochKowalskiBoesigeretal.2011, author = {Knobloch, V. and Kowalski, Julia and B{\"o}siger, P. and Kozerke, S.}, title = {Probabilistic Streamline Estimation from Accelerated Fourier Velocity Encoded Measurements}, series = {Proceedings of the 19th ISMRM International Society for Magnetic Resonance in Medicine}, booktitle = {Proceedings of the 19th ISMRM International Society for Magnetic Resonance in Medicine}, pages = {1215 -- 1215}, year = {2011}, language = {de} } @article{KochBoehnischVerdoncketal.2024, author = {Koch, Christopher and B{\"o}hnisch, Nils and Verdonck, Hendrik and Hach, Oliver and Braun, Carsten}, title = {Comparison of unsteady low- and mid-fidelity propeller aerodynamic methods for whirl flutter applications}, series = {Applied Sciences}, volume = {14}, journal = {Applied Sciences}, number = {2}, publisher = {MDPI}, address = {Basel}, issn = {2076-3417}, doi = {10.3390/app14020850}, pages = {1 -- 28}, year = {2024}, abstract = {Aircraft configurations with propellers have been drawing more attention in recent times, partly due to new propulsion concepts based on hydrogen fuel cells and electric motors. These configurations are prone to whirl flutter, which is an aeroelastic instability affecting airframes with elastically supported propellers. It commonly needs to be mitigated already during the design phase of such configurations, requiring, among other things, unsteady aerodynamic transfer functions for the propeller. However, no comprehensive assessment of unsteady propeller aerodynamics for aeroelastic analysis is available in the literature. This paper provides a detailed comparison of nine different low- to mid-fidelity aerodynamic methods, demonstrating their impact on linear, unsteady aerodynamics, as well as whirl flutter stability prediction. Quasi-steady and unsteady methods for blade lift with or without coupling to blade element momentum theory are evaluated and compared to mid-fidelity potential flow solvers (UPM and DUST) and classical, derivative-based methods. Time-domain identification of frequency-domain transfer functions for the unsteady propeller hub loads is used to compare the different methods. Predictions of the minimum required pylon stiffness for stability show good agreement among the mid-fidelity methods. The differences in the stability predictions for the low-fidelity methods are higher. Most methods studied yield a more unstable system than classical, derivative-based whirl flutter analysis, indicating that the use of more sophisticated aerodynamic modeling techniques might be required for accurate whirl flutter prediction.}, language = {en} }