TY - CHAP A1 - Janke, Christian A1 - Goller, M. A1 - Martin, Ivo A1 - Gaun, Lilia A1 - Bestle, Dieter T1 - 3D-CFD Compressor Map Computation of a Multi-Stage Axial Compressor with Off-Design Adjusted Rotor Geometries T2 - ASME Turbo Expo 2016, Turbomachinery Technical Conference and Exposition, Volume 7A, Structures and Dynamics, Seoul, South Korea, June 13–17, 2016 Y1 - 2016 SN - 978-0-7918-4983-5 N1 - Paper No. GT2016-56745 PB - ASME CY - New York, NY [u.a.] ER - TY - GEN A1 - Martin, Ivo A1 - Bestle, Dieter T1 - Automated eigenmode classification for airfoils in the presence of fixation uncertainties T2 - Engineering Applications of Artificial Intelligence N2 - Abstract Automated structural design optimization should take into acc ount risk of failure which depends on eigenmodes, since eigenmode shap es determine failure risk by their characteristic stress concentration pattern, as well as by their specific interaction with excitations. T hus, such a process needs to be able to identify eigenmodes with low e rror rate. This is a rather challenging task, because eigenmodes depen d on the geometry of the structure which is changing during the design process, and on boundary conditions which are not clearly defined due to uncertainties in the assembly and running conditions. The present investigation aims to find a proper classification method for eigenmod es of compressor airfoils. Specific data normalization and data depend ent initialization of a neural network using principle-component direc tions as initial weight vectors have led to the development of a class ification and decision procedure enabling automatic assignment of prop er uncertainty bands to eigenfrequencies of a specific eigenmode shape . Application to compressor airfoils of a stationary gas-turbine with hammer-foot and dove-tail roots demonstrates the high performance of t he proposed procedure. KW - Principle-component analysis Y1 - 2018 UR - https://www.sciencedirect.com/science/article/pii/S0952197617302361 U6 - https://doi.org/https://doi.org/10.1016/j.engappai.2017.09.022 SN - 0952-1976 VL - 67 SP - 187 EP - 196 ER - TY - GEN A1 - Fischer, Thomas A1 - Marchetti-Deschmann, Martina A1 - Assis, Ana Cristina A1 - Elad, Michal Levin A1 - Algarra, Manuel A1 - Barac, Marko A1 - Bogdanovic Radovic, Iva A1 - Cicconi, Flavio A1 - Claes, Britt A1 - Frascione, Nunzianda A1 - George, Sony A1 - Guedes, Alexandra A1 - Heaton, Cameron A1 - Heeren, Ron A1 - Lasic, Violeta A1 - Lerma, José Luis A1 - del Valle Martinez de Yuso Garcia, Maria A1 - Nosko, Martin A1 - O'Hara, John A1 - Oshina, Ilze A1 - Palucci, Antonio A1 - Pawlaczyk, Aleksandra A1 - Pospíšková, Kristýna A1 - de Puit, Marcel A1 - Radodic, Ksenija A1 - Rēpele, Māra A1 - Ristova, Mimoza A1 - Romolo, Francesco Saverio A1 - Šafařík, Ivo A1 - Siketic, Zdravko A1 - Spigulis, Janis A1 - Szynkowska-Jozwik, Malgorzata Iwona A1 - Tsiatsiuyeu, Andrei A1 - Vella, Joanna A1 - Dawson, Lorna A1 - Rödiger, Stefan A1 - Francese, Simona T1 - Profiling and imaging of forensic evidence – A pan-European forensic round robin study part 1: Document forgery T2 - Science & Justice Y1 - 2022 U6 - https://doi.org/10.1016/j.scijus.2022.06.001 SN - 1876-4452 SN - 1355-0306 VL - 62 IS - 4 SP - 433 EP - 447 ER - TY - CHAP A1 - Martin, Ivo A1 - Bestle, Dieter T1 - Automated Mode Identification of Airfoil Geometries to be used in an Optimization Process T2 - ASME Turbo Expo 2016, Turbomachinery Technical Conference and Exposition, Volume 7A, Structures and Dynamics, Seoul, South Korea, June 13–17, 2016 Y1 - 2016 SN - 978-0-7918-4983-5 U6 - https://doi.org/10.1115/GT2016-56987 N1 - Paper No. GT2016-56987 PB - ASME CY - New York, NY ER - TY - RPRT A1 - Bestle, Dieter A1 - Lockan, Michael A1 - Hartwig, Lennard A1 - Martin, Ivo T1 - Q3D Optimierung vielstufiger Verdichter in der Vorauslegung und robuste multidisziplinäre Schaufelauslegung Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus4-42225 SN - 978-3-940471-30-7 PB - Brandenburgische Technische Universität Cottbus-Senftenberg, IKMZ-Universitätsbibliothek CY - Cottbus ; Senftenberg ER - TY - THES A1 - Martin, Ivo T1 - Automated Process for Robust Airfoil Design-Optimization Incorporating Critical Eigenmode Identification and Production-Tolerance Evaluation N2 - For many countries, gasturbine technology is one of the key technologies for the reduction of climate-damaging pollutant emissions. The profitability of such facilities, however, is highly dependent on the price for the utilized fossil fuel, which is why there is a constant need for increased efficiency. The potential of increasing the efficiency of the individual components is basically limited by factors which will reduce operating life. The goal of this thesis is to develop methods for improved automated structural design optimization, which shall be developed on the basis of compressor airfoils. Special attention is payed to avoid the excitation of failure critical eigenmodes by detecting them automatically. This is achieved by introducing a method based on self-organizing neural networks which enables the projection of eigenmodes of arbitrary airfoil geometries onto standard surfaces, thereby making them comparable. Another neural network is applied to identify eigenmodes which have been defined as critical for operating life. The failure rate of such classifiers is significantly reduced by introducing a newly developed initialization method based on principle components. A structural optimization is set up which shifts the eigenfrequency bands of critical modes in such a way that the risk of resonance with engine orders is minimized. In order to ensure practical relevance of optimization results, the structural optimization is coupled with an aerodynamic optimization in a combined process. Conformity between the loaded hot-geometry utilized by the aerodynamic design assessment and the unloaded cold-geometry utilized by the structural design assessment is ensured by using loaded-to-unloaded geometry transformation. Therefor an innovative method is introduced which, other than the established time-consuming iterative approach, uses negative density for a direct transformation taking only a few seconds, hence, making it applicable to optimization. Additionally, in order for the optimal designs to be robust against manufacturing variations, a method is developed which allows to assess the maximum production tolerance of a design from which onwards possible design variations are likely to violate design constraints. In contrast to the usually applied failure rate, the production tolerance is a valid requirement for suppliers w.r.t. expensive parts produced in low-quantity, and therefore is a more suitable optimization objective. Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus4-47136 CY - Cottbus ER - TY - GEN A1 - Martin, Ivo A1 - Hartwig, Lennard A1 - Bestle, Dieter T1 - A multi-objective optimization framework for robust axial compressor airfoil design T2 - Structural and Multidisciplinary Optimization Y1 - 2019 U6 - https://doi.org/10.1007/s00158-018-2164-3 SN - 1615-1488 SN - 1615-147X VL - 59 IS - 6 SP - 1935 EP - 1947 ER -