TY - CHAP A1 - Pöthkow, Kai A1 - Hege, Hans-Christian ED - Laidlaw, David ED - Vilanova, Anna T1 - Uncertainty Propagation in DT-MRI Anisotropy Isosurface Extraction T2 - New Developments in the Visualization and Processing of Tensor Fields Y1 - 2012 SP - 209 EP - 225 PB - Springer CY - Berlin ER - TY - JOUR A1 - Pöthkow, Kai A1 - Weber, Britta A1 - Hege, Hans-Christian T1 - Probabilistic Marching Cubes JF - Computer Graphics Forum Y1 - 2011 U6 - https://doi.org/10.1111/j.1467-8659.2011.01942.x VL - 30 IS - 3 SP - 931 EP - 940 ER - TY - JOUR A1 - Pöthkow, Kai A1 - Hege, Hans-Christian T1 - Nonparametric Models for Uncertainty Visualization JF - Computer Graphics Forum Y1 - 2013 U6 - https://doi.org/10.1111/cgf.12100 target VL - 32 IS - 3 SP - 131 EP - 140 ER - TY - JOUR A1 - Pöthkow, Kai A1 - Petz, Christoph A1 - Hege, Hans-Christian T1 - Approximate Level-Crossing Probabilities for Interactive Visualization of Uncertain Isocontours JF - International Journal for Uncertainty Quantification Y1 - 2013 U6 - https://doi.org/10.1615/Int.J.UncertaintyQuantification.2012003958 VL - 3 IS - 2 SP - 101 EP - 117 ER - TY - THES A1 - Pöthkow, Kai T1 - Modeling, Quantification and Visualization of Probabilistic Features in Fields with Uncertainties N2 - Eine grundlegende Eigenschaft von naturwissenschaftlichen Daten ist, dass der wahre Wert einer Größe nicht beliebig genau bestimmbar ist. Es ist lediglich möglich, ihn durch Intervalle einzugrenzen oder die Unsicherheit durch eine Wahrscheinlichkeitsverteilung zu charakterisieren. Dies gilt für alle reellwertigen Daten, sowohl für Mess-, als auch für Simulationsergebnisse. Beispiele sind Messungen von grundlegenden physikalischen Größen wie Geschwindigkeit oder auch langfristige Temperaturvorhersagen, die durch Klimamodelle berechnet werden. Die Unsicherheit von Ergebnissen ist eine wichtige Information, die in Natur- und Ingenieurwissenschaften häufig durch Konfidenzintervalle in 1D-Plots und Tabellen angezeigt wird. Im Gegensatz dazu ist es bisher bei der Visualisierung von 2D- und 3D-Daten mithilfe von Standardmethoden meist unmöglich, die Datenunsicherheit zu repräsentieren. Diese Arbeit stellt wahrscheinlichkeitstheoretisch fundierte Methoden vor, die die Analyse und Visualisierung von Skalar-, Vektor- und Tensorfeldern mit Unsicherheiten ermöglichen. Der Fokus liegt dabei auf der Extraktion von raumzeitlichen geometrischen und topologischen Merkmalen aus den Feldern (z.B. Isokonturen und kritische Punkte). Wir nutzen parametrische und nichtparametrische Zufallsfelder, um Variabilität und räumliche Korrelation mathematisch zu modellieren. Die Wahrscheinlichkeitsverteilungen werden aus Ensemble-Datensätzen geschätzt, die mehrere Simulationsergebnisse (z.B. basierend auf variierenden Simulationsparametern) zusammenfassen. Wir untersuchen die Konditionszahlen von Merkmalsextraktionsmethoden, um die Sensitivität, d.h. die Verstärkung oder Abschwächung der Unsicherheit der Ergebnisse relativ zu Unsicherheiten in den Eingangsdaten abzuschätzen. Wir stellen einen allgemeiner Ansatz für die probabilistische Merkmalsextraktion vor, der die Basis für die Berechnung räumlicher Wahrscheinlichkeitsverteilungen von verschiedenen Merkmalen in Skalar-, Vektor- und Tensorfeldern bildet. In diesem Framework werden Wahrscheinlichkeiten für die Existenz von Merkmalen aus lokalen Randverteilungen und formalen Merkmalsdefinitionen berechnet. Numerisch können die Wahrscheinlichkeiten durch Monte-Carlo­-Integration bestimmt werden. Um den hohen Rechenaufwand dieses Ansatzes zu vermeiden, schlagen wir schnelle Berechnungsmethoden vor, wobei Merkmalswahrscheinlichkeiten näherungsweise mit Hilfe von Surrogatfunktionen bzw. Lookup-Tabellen geschätzt werden. Die vorgeschlagenen Methoden werden anhand von Daten aus Klima- und Biofluidmechaniksimulationen sowie aus der medizinischen Bildgebung qualitativ und quantitativ evaluiert. KW - uncertainty quantification KW - feature extraction KW - probability Y1 - 2015 UR - http://www.diss.fu-berlin.de/diss/receive/FUDISS_thesis_000000099462?lang=en ER - TY - CHAP A1 - Agudo Jácome, Leonardo A1 - Hege, Hans-Christian A1 - Paetsch, Olaf A1 - Pöthkow, Kai T1 - 3D Reconstruction, Visualization and Quantification of Dislocations from Transmission Electron Microscopy Stereo-Pairs T2 - Microscopy and Microanalysis 2016, July 24-28 Columbus, Ohio Y1 - 2016 UR - https://www.microscopy.org/MandM/2016/program/abstracts/PDP-57.pdf ER - TY - JOUR A1 - Goubergrits, Leonid A1 - Osman, Jan A1 - Mevert, Ricardo A1 - Kertzscher, Ulrich A1 - Pöthkow, Kai A1 - Hege, Hans-Christian T1 - Turbulence in blood damage modeling JF - The International Journal of Artificial Organs N2 - Purpose: To account for the impact of turbulence in blood damage modeling, a novel approach based on the generation of instantaneous flow fields from RANS simulations is proposed. Methods: Turbulent flow in a bileaflet mechanical heart valve was simulated using RANS-based (SST k-ω) flow solver using FLUENT 14.5. The calculated Reynolds shear stress (RSS) field is transformed into a set of divergence-free random vector fields representing turbulent velocity fluctuations using procedural noise functions. To consider the random path of the blood cells, instantaneous flow fields were computed for each time step by summation of RSS-based divergence-free random and mean velocity fields. Using those instantaneous flow fields, instantaneous pathlines and corresponding point-wise instantaneous shear stresses were calculated. For a comparison, averaged pathlines based on mean velocity field and respective viscous shear stresses together with RSS values were calculated. Finally, the blood damage index (hemolysis) was integrated along the averaged and instantaneous pathlines using a power law approach and then compared. Results: Using RSS in blood damage modeling without a correction factor overestimates damaging stress and thus the blood damage (hemolysis). Blood damage histograms based on both presented approaches differ. Conclusions: A novel approach to calculate blood damage without using RSS as a damaging parameter is established. The results of our numerical experiment support the hypothesis that the use of RSS as a damaging parameter should be avoided. Y1 - 2016 U6 - https://doi.org/10.5301/ijao.5000476 VL - 39 IS - 4 SP - 147 EP - 210 ER - TY - CHAP A1 - Jácome, Leonardo Agudo A1 - Eggeler, Gunter A1 - Pöthkow, Kai A1 - Paetsch, Olaf A1 - Hege, Hans-Christian T1 - Three-Dimensional Characterization of Superdislocation Interactions in the High Temperature and Low Stress Creep Regime of Ni-Base Superalloy Single Crystals T2 - Proceedings of CREEP 2015 – 13th International Conference on Creep and Fracture of Engineering Materials and Structures, May 31 – June 4, 2015, Toulouse, France N2 - Monocrystaline Ni-base superalloys are the material of choice for first row blades in jet engine gas turbines. Using a novel visualization tool for 3D reconstruction and visualization of dislocation line segments from stereo-pairs of scanning transmission electron microscopies, the superdislocation substructures in Ni-base superalloy LEK 94 (crept to ε = 26%) are characterized. Probable scenarios are discussed, how these dislocation substructures form. Y1 - 2015 SP - 16 EP - 17 ER - TY - JOUR A1 - Pöthkow, Kai A1 - Hege, Hans-Christian T1 - Positional Uncertainty of Isocontours: Condition Analysis and Probabilistic Measures JF - IEEE Transactions on Visualization and Computer Graphics Y1 - 2011 U6 - https://doi.org/10.1109/TVCG.2010.247 VL - 17 IS - 10 SP - 1393 EP - 1406 ER - TY - JOUR A1 - Petz, Christoph A1 - Pöthkow, Kai A1 - Hege, Hans-Christian T1 - Probabilistic Local Features in Uncertain Vector Fields with Spatial Correlation JF - Computer Graphics Forum Y1 - 2012 VL - 31 IS - 3 SP - 1045 EP - 1054 ER - TY - JOUR A1 - Goubergrits, Leonid A1 - Schaller, Jens A1 - Kertzscher, Ulrich A1 - van den Bruck, Nils A1 - Pöthkow, Kai A1 - Petz, Christoph A1 - Hege, Hans-Christian A1 - Spuler, Andreas T1 - Statistical wall shear stress maps of ruptured and unruptured middle cerebral artery aneurysms JF - J. R. Soc. Interface Y1 - 2012 U6 - https://doi.org/10.1098/rsif.2011.0490 VL - 9 IS - 69 SP - 677 EP - 688 ER - TY - JOUR A1 - Agudo Jácome, Leonardo A1 - Hege, Hans-Christian A1 - Paetsch, Olaf A1 - Pöthkow, Kai T1 - Three-dimensional reconstruction and quantification of dislocation substructures from transmission electron microscopy stereo pairs JF - Ultramicroscopy N2 - A great amount of material properties is strongly influenced by dislocations, the carriers of plastic deformation. It is therefore paramount to have appropriate tools to quantify dislocation substructures with regard to their features, e.g., dislocation density, Burgers vectors or line direction. While the transmission electron microscope (TEM) has been the most widely-used equipment implemented to investigate dislocations, it usually is limited to the two-dimensional (2D) observation of three-dimensional (3D) structures. We reconstruct, visualize and quantify 3D dislocation substructure models from only two TEM images (stereo pairs) and assess the results. The reconstruction is based on the manual interactive tracing of filiform objects on both images of the stereo pair. The reconstruction and quantification method are demonstrated on dark field (DF) scanning (S)TEM micrographs of dislocation substructures imaged under diffraction contrast conditions. For this purpose, thick regions (>300 nm) of TEM foils are analyzed, which are extracted from a Ni-base superalloy single crystal after high temperature creep deformation. It is shown how the method allows 3D quantification from stereo pairs in a wide range of tilt conditions, achieving line length and orientation uncertainties of 3% and 7°, respectively. Parameters that affect the quality of such reconstructions are discussed. Y1 - 2018 U6 - https://doi.org/10.1016/j.ultramic.2018.08.015 VL - 195 SP - 157 EP - 170 ER - TY - GEN A1 - Agudo Jácome, Leonardo A1 - Hege, Hans-Christian A1 - Paetsch, Olaf A1 - Pöthkow, Kai T1 - Three-Dimensional Reconstruction and Quantification of Dislocation Substructures from Transmission Electron Microscopy Stereo-Pairs N2 - A great amount of material properties is strongly influenced by dislocations, the carriers of plastic deformation. It is therefore paramount to have appropriate tools to quantify dislocation substructures with regard to their features, e.g., dislocation density, Burgers vectors or line direction. While the transmission electron microscope (TEM) has been the most widely-used equipment implemented to investigate dislocations, it usually is limited to the two-dimensional (2D) observation of three-dimensional (3D) structures. We reconstruct, visualize and quantify 3D dislocation substructure models from only two TEM images (stereo-pairs) and assess the results. The reconstruction is based on the manual interactive tracing of filiform objects on both images of the stereo-pair. The reconstruction and quantification method are demonstrated on dark field (DF) scanning (S)TEM micrographs of dislocation substructures imaged under diffraction contrast conditions. For this purpose, thick regions (> 300 nm) of TEM foils are analyzed, which are extracted from a Ni-base superalloy single crystal after high temperature creep deformation. It is shown how the method allows 3D quantification from stereo-pairs in a wide range of tilt conditions, achieving line length and orientation uncertainties of 3 % and 7°, respectively. Parameters that affect the quality of such reconstructions are discussed. T3 - ZIB-Report - 18-50 KW - dislocation, diffraction contrast, scanning transmission electron microscopy, stereoscopy, visualization Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-70339 SN - 1438-0064 ER -