TY - CHAP A1 - Birkenmaier, Clemens A1 - Krenkel, Lars ED - Chinesta, F. ED - Abgrall, R. ED - Allix, O. ED - Kalistke, M T1 - Convolutional Neural Networks for Approximation of Internal Non-Newtonian Multiphase Flow Fields T2 - 14th World Congress on Computational Mechanics (WCCM), ECCOMAS Congress 2020: 19–24 July 2020, Paris, France N2 - Neural networks (NNs) as an alternative method for universal approximation of differential equations have proven to be computationally efficient and still sufficiently accurate compared to established methods such as the finite volume method (FVM). Additionally, analysing weights and biases can give insights into the underlying physical laws. FVM and NNs are both based upon spacial discretisation. Since a Cartesian and equidistant grid is a raster graphics, image-to-image regression techniques can be used to predict phase velocity fields as well as particle and pressure distributions from simple mass flow boundary conditions. The impact of convolution layer depth and number of channels of a ConvolutionDeconvolution Regression Network (CDRN), on prediction performance of internal non-Newtownian multiphase flows is investigated. Parametric training data with 2055 sets is computed using FVM. To capture significant non-Newtownian effects of a particle-laden fluid (e.g. blood) flowing through small and non-straight channels, an Euler-Euler multiphase approach is used. The FVM results are normalized and mapped onto an equidistant grid as supervised learning target. The investigated NNs consist of n= {3, 5, 7} corresponding encoding/decoding blocks and different skip connections. Regardless of the convolution depth (i.e. number of blocks), the deepest spacial down-sampling via strided convolution is adjusted to result in a 1 × 1 × f · 2nfeature map, with f = {8, 16, 32}. The prediction performance expressed is as channel-averaged normalized root mean squared error (NRMSE). With a NRMSE of < 2 · 10-3, the best preforming NN has f = 32 initial feature maps, a kernel size of k = 4, n = 5 blocks and dense skip connections. Average inference time from this NN takes < 7 · 10-3s. Worst accuracy at NRMSE of approx 9 · 10-3is achieved without any skips, at k = 2, f = 16 and n = 3, but deployment takes only < 2 · 10-3s Given an adequate training, the prediction accuracy improves with convolution depth, where more features have higher impact on deeper NNs. Due to skip connections and batch normalisation, training is similarly efficient, regardless of the depth. This is further improved by blocks with dense connections, but at the price of a drastically larger model. Depending on geometrical complexity, spacial resolution is critical, as it increases the number of learnables and memory requirements massively. KW - Deep Learning KW - Convolutional neural networks KW - Non-Newtonian multiphase flow Y1 - 2021 U6 - https://doi.org/10.23967/wccm-eccomas.2020.107 PB - CIMNE ER - TY - GEN A1 - Tauwald, Sandra Melina A1 - Quadrio, Maurizio A1 - Rütten, Markus A1 - Stemmer, Christian A1 - Krenkel, Lars T1 - High Spatial Resolution Tomo-PIV of the Nasopharynx Focussing on the Physiological Breathing Cycle T2 - 23. DGLR Fach-Symposium Strömungen mit Ablösung, 09./10. November 2022, Berlin, Deutschland N2 - Investigations of complex patient-specific flow in the nasopharynx requires high resolution numerical calculations validated by reliable experiments. When building the validation base and the benchmark of computational fluid dynamics, an experimental setup of the nasal airways was developed. The applied optical measurement technique of tomo-PIV supplies information on the governing flow field in three dimensions. This paper presents tomo-PIV measurements of the highly complex patient-specific geometry of the human trachea. A computertomographic scan of a person’s head builds the basis of the experimental silicone model of the nasal airways. An optimised approach for precise refractive index matching avoids optical distortions even in highly complex non-free-of-sight 3D geometries. A linear-motor-driven pump generates breathing scenarios, based on measured breathing cycles. Adjusting of the CCD cameras‘ double-frame-rate PIV-Δt enables the detailed analysis of flow structures during different cycle phases. Merging regions of interest enables high spatial resolution acquisition of the flow field. KW - Tomographic PIV KW - Flow visualisation KW - Physiological Breathing KW - Nasal airflow Y1 - 2022 UR - https://www.dlr.de/as/Portaldata/5/Resources/dokumente/veranstaltungen/stab_workshop/Jahresbericht2022.pdf CY - Göttingen ER - TY - GEN A1 - Stelzer, Vera A1 - Tauwald, Sandra Melina A1 - Vielsmeier, Veronika A1 - Cieplik, Fabian A1 - Kandulski, Arne A1 - Schneider-Brachert, Wulf A1 - Wuensch, Olaf A1 - Rütten, Markus A1 - Krenkel, Lars T1 - Generation, Distribution, and Contagiousness of Surgical Smoke during Tracheotomies T2 - 23. DGLR Fach-Symposium Strömungen mit Ablösung, 09./10. November 2022, Berlin, Deutschland N2 - Surgical smoke has been a little discussed topic in the context of the current pandemic. Surgical smoke is generated during the cauterization of tissue with heat-generating devices and consists of 95% water vapor and 5% cellular debris in the form of particulate matter. In-vivo investigations are performed during tracheotomies where surgical smoke is produced during tissue electrocautery. Furthermore, in-vitro parametric studies to investigate the particle number and size distribution and the spatial distribution of surgical smoke with laser light sheet technique are conducted. The higher the power of the high-frequency-device the larger the particles in size and the higher the resulting particle counts. The images taken show the densest smoke at 40W with artificial saliva. The resulting characteristic size distribution, which may include viruses and bacterial components, confirms that the risk arising from surgical smoke should be considered. Furthermore, the experiments will provide the database for further numerical investigations. Y1 - 2022 UR - https://www.dlr.de/as/Portaldata/5/Resources/dokumente/veranstaltungen/stab_workshop/Jahresbericht2022.pdf CY - Göttingen ER - TY - GEN A1 - Krenkel, Lars T1 - Maskenpflicht für Aerosole – wie wir medizinisches Personal in der Pandemie schützen T2 - TRIOKON Digital 2021 : Zukunft Ostbayern, 29.09.2021, Weiden, Deutschland KW - Aerosole KW - Pandemie KW - SARS-CoV-2 Y1 - 2021 UR - https://www.youtube.com/watch?v=bYRFpp_Xxvc ER - TY - GEN A1 - Stelzer, Vera A1 - Rütten, Markus A1 - Krenkel, Lars T1 - Numerical Investigation of a 3D Dragonfly Wing Captured with a High-Resolution Micro-CT T2 - 8th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS Congress 2022, 5-9 June 2022, Oslo, Norway N2 - The special wing geometry of dragonflies consisting of veins and a membrane forming a corrugated profile leads to special aerodynamic characteristics. To capture the governing flow regimes of a dragonfly wing in detail, a realistic wing model has to be investigated. Therefore, this study aimed to analyze the aerodynamic characteristics of a 3D dragonfly wing reconstructed from a high-resolution micro-CT scan. Afterwards, a spatially high discretized mesh was generated using the mesh generator CENTAUR™ 14.5.0.2 (CentaurSoft, Austin, TX, US) to finally conduct Computational Fluid Dynamics (CFD) investigations in Fluent® 2020 R2 (ANSYS, Inc., Canonsburg, PA, US). Due to the small dimensions of the wing membrane, only the vein structure of a Camacinia Gigantea was captured at a micro-CT voxel size of 7 microns. The membrane was adapted and connected to the vein structure using a Boolean union operation. Occurring nconsistencies after combining the veins and the membrane were corrected using an adapted pymesh script [1]. As an initial study, only one quarter of the wing (outer wing section) was investigated to reduce the required computational effort. The resulting hybrid mesh consisting of 10 pseudo-structured prism layers along the wing surface and tetrahedra in the farfield area has 43 mio. nodes. The flow around the wing was considered to be incompressible and laminar using transient calculations. When the flow passes the vein structures, steady vortices occur in the corrugation valleys leading to recirculation zones. Therefore, the dragonfly wing resembles the profile of an airfoil. This leads to comparable lift coefficients of dragonfly wings and airfoil profiles at significantly reduced structural weight. The reconstructed geometry also included naturally occurring triangular prismlike serrated structures at the leading edge of the wing, which have comparable effects to micro vortex generators and might stabilize the recirculation zones. Further work aims to investigate the aerodynamic properties of a complete dragonfly wing during wing flapping. KW - CFD KW - Dragonfly KW - Aerodynamics KW - Gliding Flight Y1 - 2022 ER - TY - GEN A1 - Birkenmaier, Clemens A1 - Krenkel, Lars T1 - Towards a realistic model of blood viscosity and coagulation in membrane oxygenators T2 - 6th European Conference on Computational Mechanics (Solids, Structures and Coupled Problems) - ECCM 6; 7th European Conference on Computational Fluid Dynamics - ECFD 7 : Glasgow, Scotland, UK, June 11-15, 2018 N2 - Modelling blood flow an shear induced coagulation in membraene oxygenators (MO) is challenging. The relevant geometry of oxygenator fibers (OF) and chaining threads is complex and spans several length scales. In relevant scales and regimes blood shows several significant non-Newtonian effects. Existing models are only capable of accounting for some, but not all relevant effects. Additionally, coagulation processes are influencing fluid properties and geometry significantly. Due to the enormous size of the discretised geometries highly detailed viscosity and coagulation properties of blodd flow in MOs. First step is to find a gemoetry dependent viscosity representation on basis of parametric micro channel experiments with anti-coagulated blood. Next step is a statistic coagulation model, based on micro channel experiments with human (re-calcified citrated) whole blood an evaluation of clinically used osygenators. Since shear rate dependent (i.e. viscosity dependet) coagulation in return influences the viscosity, a combined model with suitable implementation in a RANS framework is necessary. Towards this end, micro channel experiments with new and used single OFs triggering coagulation are performed. Structures of multimeric von Willebrand fibers (vWF), as indicator for shear induced coagulation, are compared to computed and measured flow conditions, using immunofluorescence microscopy, RANS-computations and µPIV, respectively. Preliminary examinations in clinically used MOs show good agreement between occurring structures of vWF, cell depositions and computed flow patterns (geometry form µCT-Scans). However, computed shear rates might be to low to actually trigger activation of vWF. The complex geometry of MOs results in huge meshes, which makes RANS with statistical modelling of viscosity and coagulation a reasonable approach. Towards this end, experimental data on micro channel level with evaluation on real application level is crucial. Especially regarding clotting processes, micro fluidic experiments are powerful research tool. KW - Blood Viscosity KW - Shear Raed Induced Coagulation KW - Membrane Oxygenator Y1 - 2018 ER - TY - CHAP A1 - Birkenmaier, Clemens A1 - Steiger, Tamara A1 - Philipp, Alois A1 - Lehle, Karla A1 - Krenkel, Lars T1 - Flow-induced accumulations of von Willebrand factor inside oxygenators during extracorporeal life support therapy T2 - Proceedings of 12th International Conference BIOMDLORE 2018, June 28–30, 2018, Białystok, Poland N2 - BACKGROUND: Shear-induced conformational changes of von Willebrand factor (vWF) may be responsible for coagulation disorder and clot formation inside membrane oxygenators (MOs) during extracorporeal membrane oxygenation (ECMO) therapy. OBJECTIVE: The aim was to identify vWF structures inside clinically used MOs and employ computational fluid dynamics to verify the corresponding flow conditions. METHODS: Samples from gas exchange membranes (GEM) from MOs were analysed for accumulations of vWF and P-selectin-positive platelets using immunofluorescence techniques. Streamlines and shear rates of the flow around GEMs were computed using a laminar steady Reynolds-Averaged-Navier-Stokes approach. RESULTS: Most samples were colonized with equally distributed leukocytes, integrated in thin cobweb-like vWF-structures. Only 25 % of the samples showed extended accumulations of vWF. Computed streamlines showed considerable cross flow between interconnected neighbouring channels. Stagnation points were non-symmetric and contact faces were washed around closely. The occurring maximum shear rates ranged from 2,500 to 3,000 1/s. CONCLUSIONS: If pronounced vWF structures are present, shape and extent match the flow computations well. Computed shear rates bear a critical degree of uncertainty due to the improper viscosity model. If flow conditions inside the MO were sufficient to affect vWF, a more consistent distribution of vWF across the samples should be present. KW - Blood Viscosity KW - Shear Rate Induced Coagulation KW - Hemodynamics KW - Membrane Oxygenator KW - von Willebrand factor Y1 - 2018 SN - 978-1-5386-2396-1 U6 - https://doi.org/10.1109/BIOMDLORE.2018.8467205 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Birkenmaier, Clemens A1 - Krenkel, Lars ED - Dillmann, Andreas ED - Heller, Gerd ED - Krämer, Ewald ED - Wagner, Claus T1 - Convolutional Neural Networks for Approximation of Blood Flow in Artificial Lungs T2 - New Results in Numerical and Experimental Fluid Mechanics XIII: Contributions to the 22nd STAB/DGLR Symposium N2 - Blood flow in channels of varying diameters <500μm exhibits strong non-linear effects. Multiphase finite volume approaches are feasible, but still computationally costly. Here, the feasibility of applying convolutional neural networks for blood flow prediction in artificial lungs is investigated. Training targets are precomputed using an Eulerian two-phase approach. To match with experimental data, the interphase drag and lift, as well as intraphase shear-thinning are adapted. A recursively branching regression network and convolution/deconvolution networks with plain skip connections and densely connected skips are investigated. A priori knowledge is incorporated in the loss functional to prevent the network from learning non-physical solutions. Inference from neural networks is approximately six orders of magnitude faster than the classical finite volume approach. Even if resulting in comparably coarse flow fields, the neural network predictions can be used as close to convergence initial solutions greatly accelerating classical flow computations. KW - Deep learning fluid mechanics KW - Multiphase blood flow Y1 - 2021 SN - 978-3-030-79560-3 U6 - https://doi.org/10.1007/978-3-030-79561-0_43 IS - 1. Auflage SP - 451 EP - 460 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Tauwald, Sandra Melina A1 - Quadrio, Maurizio A1 - Rütten, Markus A1 - Stemmer, Christian A1 - Krenkel, Lars T1 - High Spatial Resolution Tomo-PIV of the Trachea Focussing on the Physiological Breathing Cycle T2 - New Results in Numerical and Experimental Fluid Mechanics XIV - Contributions to the 23nd STAB/DGLR Symposium N2 - Investigations of complex patient-specific flow in the nasopharynx requires high resolution numerical calculations validated by reliable experiments. When building the validation base and the benchmark of computational fluid dynamics, an experimental setup of the nasal airways was developed. The applied optical measurement technique of tomo-PIV supplies information on the governing flow field in three dimensions. This paper presents tomo-PIV measurements of the highly complex patient-specific geometry of the human trachea. A computertomographic scan of a person’s head builds the basis of the experimental silicone model of the nasal airways. An optimised approach for precise refractive index matching avoids optical distortions even in highly complex non-free-of-sight 3D geometries. A linear-motor-driven pump generates breathing scenarios, based on measured breathing cycles. Adjusting of the CCD cameras‘ double-frame-rate PIV-Δt enables the detailed analysis of flow structures during different cycle phases. Merging regions of interest enables high spatial resolution acquisition of the flow field. KW - Tomographic PIV KW - Flow visualisation KW - Breathing cycle KW - Nasal airflow Y1 - 2023 N1 - Accepted for publication, not yet published PB - Springer ER - TY - GEN A1 - Birkenmaier, Clemens A1 - Dornia, Christian A1 - Lehle, Karla A1 - Krenkel, Lars T1 - Feasibility of detecting thrombotic deposits in membrane oxygenators using micro computed tomography T2 - 25th Congress of the European Society of Biomechanics, July 7-10, 2019, Vienna, Austria Y1 - 2019 UR - https://esbiomech.org/conference/archive/2019vienna/Contribution_129.pdf ER - TY - CHAP A1 - Tschurtschenthaler, Karl A1 - Krenkel, Lars A1 - Schreiner, Rupert T1 - Mechano-optical micro pillar sensor for biofluidmechanic wall shear stress measurements T2 - 25th Congress of the European Society of Biomechanics (ESB), July 7-10, 2019, Vienna, Austria Y1 - 2019 UR - https://esbiomech.org/conference/archive/2019vienna/Contribution_608.pdf ER - TY - GEN A1 - Tauwald, Sandra Melina A1 - Krenkel, Lars T1 - Elementary experimental setup for flow visualization in upper human respiratory tract T2 - 25th Congress of the European Society of Biomechanics, July 7-10, 2019, Vienna, Austria Y1 - 2019 UR - https://esbiomech.org/conference/archive/2019vienna/Contribution_195.pdf ER - TY - GEN A1 - Wagner, Thomas A1 - Krenkel, Lars A1 - Dönitz, Christian A1 - Brawanski, Alexander T1 - Influence of CFD Strategy on WSS and OSI Determination for Intracranial Aneurysm Rupture Assessment T2 - 25th Congress of the European Society of Biomechanics, July 7-10, 2019, Vienna, Austria Y1 - 2019 ER - TY - GEN A1 - Krenkel, Lars T1 - Relevanz von Aerosolen im klinischen Kontext T2 - Innovationstag Hygiene 2021, Continental Arena, Regensburg, Deutschland Y1 - 2021 ER - TY - GEN A1 - Krenkel, Lars A1 - Michel, Johanna A1 - Keil, Niklas A1 - Daschner, Jan T1 - Experimental Investigation of Logitudinal Folds in Endotracheal Tube Cuffs and their Correlation to Silent Breathing T2 - 23. DGLR Fach-Symposium Strömungen mit Ablösung, 09./10. November 2022, Berlin, Deutschland N2 - Air leakage past High-Volume-Low-Pressure (HVLP) endotracheal tube (ETT) cuffs creates a potential infection risk for health care professionals during ventilation of patients suffering from contagious airborne diseases. However, unlike silent aspiration, a phenomenon where fluids enter the airways of intubated patients, the aspect of aerosol emergence through cuff folds -what we called accordingly “silent breathing” (SB)- has not been investigated in detail so far. This study investigates air leakage past HVLP cuffs with varying cuff pressures under realistic artificial breathing scenarios experimentally and in addition numerically. The focus was laid on the parametric investigation of the occurrence and furthermore on different influencing factors of silent breathing. The morphology of the folds responsible for the leakage was captured using high-resolution 3D microcomputed tomography (μCT). For the numerical investigations (Com-putational Fluid Dynamics - CFD), the commercial CFD Software package FLUENT 2021 R2 (ANSYS, Inc., Canonsburg, PA, US), as well as the DLR in-house research code THETA has been used. KW - Silent Breathing KW - Aerosols KW - CFD KW - Endotracheal Intubation Y1 - 2022 UR - https://www.dlr.de/as/Portaldata/5/Resources/dokumente/veranstaltungen/stab_workshop/Jahresbericht2022.pdf CY - Göttingen ER - TY - CHAP A1 - Rütten, Markus A1 - Krenkel, Lars A1 - Quadrio, Maurizio T1 - Simulation and Analyis of the Unsteady Flow within Nasal Airways T2 - 9th European Congress on Computational Methods in Applied Sciences and Engineering - ECCOMAS Congress, 3-7 June 2024, Lisbon, Portugal Y1 - 2024 UR - https://re.public.polimi.it/handle/11311/1269952 ER - TY - JOUR A1 - Pointner, Daniel A1 - Kranz, Michael A1 - Wagner, Maria Stella A1 - Haus, Moritz A1 - Lehle, Karla A1 - Krenkel, Lars T1 - Automated deep learning based detection of cellular deposits on clinically used ECMO membrane lungs JF - Frontiers in Bioinformatics N2 - Introduction: Despite the promising application of extracorporeal membrane oxygenation (ECMO) in the treatment of critically ill patients, coagulation-associated technical complications, primarily clot formation and critical bleeding, remain a major challenge during ECMO therapy. The deposition of nucleated cells on the surface has been shown, yet the role of these cells towards complication development is still matter of ongoing research. In particular, the membrane lung (MemL) is prone to clot formation. Therefore, the investigation of nuclear deposits on its hollow-fibers may provide insights for a better understanding of the cellular mechanisms involved in the development of ECMO complications. Methods: To support current research, this study aimed to develop a deep learning–based tool for the automated detection and quantitative analysis of nuclear depositions on MemL hollow-fiber mats. A customized fluorescence microscopy workflow, combined with a semi-automated iterative labeling strategy, was used to generate a high-quality dataset for model training. Results: Six configurations of instance segmentation models were evaluated, with a Mask R-CNN with ResNet 101 backbone using dilated convolution providing the most balanced performance in both nuclei count and area accuracy. Compared with U-Net–based approaches such as Cellpose or StarDist, the proposed model demonstrated superior segmentation of overlapping and low-intensity nuclei, maintaining accuracy even in densely packed cellular regions. Discussion: We present an automated image analysis tool for clinically used MemLs, which exhibit complex three-dimensional hollow-fiber architectures and irregular cellular deposits that challenge conventional tools. A dedicated graphical user interface enables streamlined detection, morphometric analysis, and spatial clustering of nuclei, establishing a reproducible workflow for high-throughput analysis of fluorescence microscopy images. This approach eliminates labor-intensive manual counting and facilitates large-scale studies on cell-fiber interactions and disease-related correlations. Y1 - 2026 U6 - https://doi.org/10.3389/fbinf.2026.1771574 N1 - Corresponding author der OTH Regensburg: Daniel Pointner, Lars Krenkel VL - 6 PB - Frontiers ER -