TY  - JOUR
A1  - Weber, Tobias
A1  - Ruff-Stahl, Hans-Joachim K.
T1  - Advances in Composite Manufacturing of Helicopter Parts
JF  - International Journal of Aviation, Aeronautics, and Aerospace
Y1  - 2017
U6  - https://doi.org/10.15394/ijaaa.2017.1153
SN  - 2374-6793
VL  - 4
IS  - 1
ER  - 
TY  - CHAP
A1  - Otten, D.
A1  - Schmidt, M.
A1  - Weber, Tobias
T1  - Advances in Determination of Material Parameters for Functional Simulations Based on Process Simulations
T2  - SAMPE Europe Conference 16 Liege
Y1  - 2016
SN  - 978-1-5108-3800-0
SP  - 570
EP  - 577
ER  - 
TY  - CHAP
A1  - Weber, Tobias
A1  - Tellis, Jane J.
A1  - Duhovic, Miro
T1  - Characterization of tool-part-interaction an interlaminar friction for manufacturing process simulation
T2  - ECCM 17, 17th European Conference on Composite Materials, München, DE, Jun 26-30, 2016
Y1  - 2016
SN  - 978-3-00-053387-7
SP  - 1
EP  - 7
ER  - 
TY  - CHAP
A1  - Hailer, Benjamin
A1  - Weber, Tobias
A1  - Arent, Jan-Christoph
T1  - Manufacturing Process Simulation for Autoclave-Produced Sandwich Structures
T2  - Proceedings of SAMPE Europe Conference 2019, Nantes, France
Y1  - 2019
SP  - 1
EP  - 8
ER  - 
TY  - CHAP
A1  - Weber, Tobias
A1  - Englhard, Markus
A1  - Hailer, Benjamin
A1  - Arent, Jan-Christoph
T1  - Manufacturing Process Simulation for the Prediction of Tool-Part-Interaction and Ply Wrinkling
T2  - Proceedings of SAMPE Europe Conference 2019, Nantes, France
Y1  - 2019
SP  - 1
EP  - 10
ER  - 
TY  - CHAP
A1  - Weber, Tobias
A1  - Englhard, Markus
A1  - Hailer, Benjamin
A1  - Arent, Jan-Christoph
T1  - Manufacturing Process Simulation for the Prediction of Tool-Part-Interaction and Ply Wrinkling
T2  - Proceedings of SAMPE Europe Conference, Amiens , France
Y1  - 2015
SP  - 1
EP  - 10
ER  - 
TY  - CHAP
A1  - Weber, Tobias
T1  - Manufacturing Process Simulation for Tooling Optimization: Reduction of Quality Issues During Autoclave Manufacturing of Composite Parts
T2  - Proceedings of SAMPE Europe Conference 2015, Amiens, France
Y1  - 2015
SP  - 1
EP  - 8
ER  - 
TY  - CHAP
A1  - Otten, D.
A1  - Schmid, M.
A1  - Weber, Tobias
T1  - Advances In Sheet Metal-Forming: Reduction Of Tooling Cost By Methodical Optimization
T2  - Proceedings of SAMPE Europe Conference, Amiens , France
Y1  - 2015
ER  - 
TY  - JOUR
A1  - Hoeveler, B.
A1  - Bauknecht, André
A1  - Wolf, C. Christian
A1  - Janser, Frank
T1  - Wind-Tunnel Study of a Wing-Embedded Lifting Fan Remaining Open in Cruise Flight
JF  - Journal of Aircraft
N2  - It is investigated whether a nonrotating lifting fan remaining uncovered during cruise flight, as opposed to being covered by a shutter system, can be realized with limited additional drag and loss of lift during cruise flight. A wind-tunnel study of a wing-embedded lifting fan has been conducted at the Side Wind Test Facility Göttingen of DLR, German Aerospace Center in Göttingen using force, pressure, and stereoscopic particle image velocimetry techniques. The study showed that a step on the lower side of the wing in front of the lifting fan duct increases the lift-to-drag ratio of the whole model by up to 25% for all positive angles of attack. Different sizes and inclinations of the step had limited influence on the surface pressure distribution. The data indicate that these parameters can be optimized to maximize the lift-to-drag ratio. A doubling of the curvature radius of the lifting fan duct inlet lip on the upper side of the wing affected the lift-to-drag ratio by less than 1%. The lifting fan duct inlet curvature can therefore be optimized to maximize the vertical fan thrust of the rotating lifting fan during hovering without affecting the cruise flight performance with a nonrotating fan.
Y1  - 2020
U6  - https://doi.org/10.2514/1.C035422
SN  - 1533-3868
VL  - 57
IS  - 4
PB  - AIAA
CY  - Reston, Va.
ER  - 
TY  - JOUR
A1  - Khayyam, Hamid
A1  - Jamali, Ali
A1  - Bab-Hadiashar, Alireza
A1  - Esch, Thomas
A1  - Ramakrishna, Seeram
A1  - Jalili, Mahdi
A1  - Naebe, Minoo
T1  - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0
JF  - IEEE Access
N2  - 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.
Y1  - 2020
U6  - https://doi.org/10.1109/ACCESS.2020.2999898
SN  - 2169-3536
VL  - 8
IS  - Art. 9108222
SP  - 111381
EP  - 111393
PB  - IEEE
CY  - New York, NY
ER  -