Recent Submissions
Visual ensemble analysis of fluid flow in porous media across simulation codes and experiment
(2023) Bauer, Ruben; Ngo, Quynh Quang; Reina, Guido; Frey, Steffen; Flemisch, Bernd; Hauser, Helwig; Ertl, Thomas; Sedlmair, Michael
We study the question of how visual analysis can support the comparison of spatio-temporal ensemble data of liquid and gas flow in porous media. To this end, we focus on a case study, in which nine different research groups concurrently simulated the process of injecting CO 2into the subsurface. We explore different data aggregation and interactive visualization approaches to compare and analyze these nine simulations. In terms of data aggregation, one key component is the choice of similarity metrics that define the relationship between different simulations. We test different metrics and find that using the machine-learning model “S4” (tailored to the present study) as metric provides the best visualization results. Based on that, we propose different visualization methods. For overviewing the data, we use dimensionality reduction methods that allow us to plot and compare the different simulations in a scatterplot. To show details about the spatio-temporal data of each individual simulation, we employ a space-time cube volume rendering. All views support linking and brushing interaction to allow users to select and highlight subsets of the data simultaneously across multiple views. We use the resulting interactive, multi-view visual analysis tool to explore the nine simulations and also to compare them to data from experimental setups. Our main findings include new insights into ranking of simulation results with respect to experimental data, and the development of gravity fingers in simulations.
A new fully implicit two-phase pore-network model by utilizing regularization strategies
(2023) Wu, Hanchuan; Veyskarami, Maziar; Schneider, Martin; Helmig, Rainer
In this paper, we address the expensive computational cost resulting from limited time-step sizes during numerical simulations of two-phase flow in porous media using dynamic pore-network models. To overcome this issue, we propose a numerical method for dynamic pore-network models using a fully implicit approach. The proposed method introduces a regularization strategy considering the historical fluid configuration at the pore throat, which smooths the discontinuities in local conductivity caused by invasion and snap-off events. The results demonstrate the superiority of the proposed method in terms of accuracy, efficiency and consistency in comparison with other numerical schemes. With similar computational cost, determined by time-step sizes and number of Newton iterations, the developed method in this work yields more accurate results compared to similar schemes presented in the literature. Additionally, our results highlight the enhanced robustness of the our scheme, as it exhibits reduced sensitivity to variations in time-step sizes.
A data-driven approach to viscous fluid mechanics : the stationary case
(2023) Lienstromberg, Christina; Schiffer, Stefan; Schubert, Richard
We introduce a data-driven approach to the modelling and analysis of viscous fluid mechanics. Instead of including constitutive laws for the fluid’s viscosity in the mathematical model, we suggest directly using experimental data. Only a set of differential constraints, derived from first principles, and boundary conditions are kept of the classical PDE model and are combined with a data set. The mathematical framework builds on the recently introduced data-driven approach to solid-mechanics (Kirchdoerfer and Ortiz in Comput Methods Appl Mech Eng 304:81-101, 2016; Conti et al. in Arch Ration Mech Anal 229:79-123, 2018). We construct optimal data-driven solutions that are material model free in the sense that no assumptions on the rheological behaviour of the fluid are made or extrapolated from the data. The differential constraints of fluid mechanics are recast in the language of constant rank differential operators. Adapting abstract results on lower-semicontinuity and A-quasiconvexity, we show a Γ-convergence result for the functionals arising in the data-driven fluid mechanical problem. The theory is extended to compact nonlinear perturbations, whence our results apply not only to inertialess fluids but also to fluids with inertia. Data-driven solutions provide a new relaxed solution concept. We prove that the constructed data-driven solutions are consistent with solutions to the classical PDEs of fluid mechanics if the data sets have the form of a monotone constitutive relation.
Droplet formation, growth and detachment at the interface of a coupled free-flow-porous medium system : a new model development and comparison
(2023) Veyskarami, Maziar; Michalkowski, Cynthia; Bringedal, Carina; Helmig, Rainer
Coupled free-flow-porous medium systems are of great importance in various natural and industrial applications. Modeling of such systems is always challenging, especially when droplets form at the interface between the two domains. We propose a new concept to take droplet formation, growth and detachment at the interface into account. In this concept, we use pore-network modeling to describe the porous medium and the Navier-Stokes equations for the free-flow domain. New coupling conditions are developed which include droplet interactions with the free flow and the porous medium. Impacts of using different descriptions of the forces acting on the triple contact line and contact angle hysteresis on the predicted onset of the droplet detachment are examined. In addition, we compare the new approach with another model built using ANSYS Fluent based on the volume of fluid method. The results show that the new model is able to describe the droplet formation, growth and then detachment by the free flow. The proposed model provides a base for further developments to handle formation of multiple droplets at the interface between a free flow and a porous medium as well as to include the evaporation in future works.
Linearly combined transition model based on empirical spot growth correlations
(2023) Karsch, Maximilian; Van den Eynde, Jeroen; Steelant, Johan
The transition from laminar to turbulent flow in a hypersonic boundary layer is modeled using an intermittency-based linear combination approach. A simplified transition model like this enables a quick assessment of aero-thermal loads and the overall flight efficiency of high-speed vehicles during the initial design phase by weighting purely laminar and turbulent flow results on the basis of an empirically calculated intermittency. The transition model presented within this work includes an empirical model to account for Mach number, Reynolds number, wall temperature and pressure gradient effects on turbulent spot growth based on available turbulent spot studies in the literature. A validation of the transition model is carried out for a number of different test cases and a methodology to extend the model to generic geometries is presented to enable a more general application.
Model predictive control for compliant feed drives with offset-free tracking behavior
(2023) Leipe, Valentin; Hinze, Christoph; Lechler, Armin; Verl, Alexander
Industrial machine tool feed drives are predominantly controlled by cascade control due to their low tuning complexity and inherent robustness. However, the cascaded structure requires the inner cascades to have higher dynamics than the outer cascades, which limits the achievable dynamic accuracy. Direct control approaches, which substitute the position and velocity cascade, offer the potential to utilize the unused potential. A promising approach is model predictive control (MPC), which optimizes the manipulated variable with a plant model along a prediction horizon. However, model uncertainties between the nominal model and the real plant lead to tracking errors. Therefore, this paper presents, a linear MPC (LMPC) and an adaptive MPC (AMPC) with an additional integral action to robustly compensate for model mismatches. Both controllers use a compliant model, are real-time capable with a sample rate of 2kHzand consider state and input space constraints. The AMPC accounts for position-varying stiffness and friction. The controllers are experimentally compared with classical P-PI cascaded control on a ball screw drive. They show a tracking error reduction of 37%(LMPC) and 44%(AMPC) during a high speed motion profile and an increase in bandwidth of 180%(LMPC) and 184%(AMPC), resulting in significantly improved dynamic accuracy.
A recommender approach to enable effective and efficient self-service analytics in data lakes
(2023) Stach, Christoph; Eichler, Rebecca; Schmidt, Simone
As a result of the paradigm shift away from rather rigid data warehouses to general-purpose data lakes, fully flexible self-service analytics is made possible. However, this also increases the complexity for domain experts who perform these analyses, since comprehensive data preparation tasks have to be implemented for each data access. For this reason, we developed BARENTS, a toolset that enables domain experts to specify data preparation tasks as ontology rules, which are then applied to the data involved. Although our evaluation of BARENTS showed that it is a valuable contribution to self-service analytics, a major drawback is that domain experts do not receive any semantic support when specifying the rules. In this paper, we therefore address how a recommender approach can provide additional support to domain experts by identifying supplementary datasets that might be relevant for their analyses or additional data processing steps to improve data refinement. This recommender operates on the set of data preparation rules specified in BARENT-i.e., the accumulated knowledge of all domain experts is factored into the data preparation for each new analysis. Evaluation results indicate that such a recommender approach further contributes to the practicality of BARENTS and thus represents a step towards effective and efficient self-service analytics in data lakes.
Konzept zur Testfallgenerierung mittels Mixed Reality : Erweiterung der Testautomatisierung um Methoden der Mixed-Reality-in-the-Loop-Simulation (MRiLS)
(2023) Hönig, Jana; Littfinski, Daniel; Schnierle, Marc; Röck, Sascha; Verl, Alexander
Stochastic modeling with robust Kalman filter for real-time kinematic GPS single-frequency positioning
(2023) Wang, Rui; Becker, Doris; Hobiger, Thomas
The centimeter-level positioning accuracy of real-time kinematic (RTK) depends on correctly resolving integer carrier-phase ambiguities. To improve the success rate of ambiguity resolution and obtain reliable positioning results, an enhanced Kalman filtering procedure has been developed. Based on a posteriori residuals of measurements and state predictions, the measurement noise variance-covariance matrix for double-differenced measurements is adaptively estimated, rather than approximated by an empirical function which uses satellite elevation angle as input. Since, in real-world situations, unexpected outliers and carrier-phase outages can degrade the filter performance, a stochastic model based on robust Kalman filtering is proposed, for which the double-differenced measurement noise variance-covariance matrix is computed empirically with a modified version of the IGG (Institute of Geodesy and Geophysics) III method in order to detect and identify outliers. The performance of the proposed method is assessed by two tests, one with simulated data and one with real data. In addition, the performance of F-ratio and W-ratio tests as proxies for the success of ambiguity fixing is investigated. Experimental results reveal that the proposed method can improve the reliability and robustness of relative kinematic positioning for simulation scenarios as well as in a real urban test.
Investigation of the degradation phenomena of a proton exchange membrane electrolyzer stack by successive replacement of aged components in single cells
(2025) Kimmel, Benjamin; Morawietz, Tobias; Biswas, Indro; Sata, Noriko; Gazdzicki, Pawel; Gago, Aldo Saul; Friedrich, Kaspar Andreas
Due to their compactness and high flexibility to operate under dynamic conditions, proton exchange membrane water electrolyzers (PEMWEs) are ideal systems for the production of green hydrogen from renewable energy sources. For the widespread implementation of PEMWEs, an understanding of their degradation mechanism is crucial. In this work, we analyze a commercial PEMWE stack via a novel approach of breaking down from the stack to the single-cell level. Therefore, the disassembled stack components are cut to fit into single cells. Then, the aged components are successively replaced with pristine or regenerated components (cleaned and polished), and electrochemical characterizations are conducted to investigate the contributions of the individual components on performance losses. In addition, several underlying degradation phenomena are identified using different physical ex-situ analysis methods. The catalyst-coated membrane (CCM) contributes the most to performance degradation because of contamination and ionomer rearrangement. Additionally, traces of calcium, likely due to insufficient water purification used during operation or for cleaning the cell components, were found. Significant oxidation was observed on the anodic components, while the electronic conductivity on the cathode side remained unchanged. The combination of electrochemical characterization with stepwise regeneration processes and physical ex-situ analysis allows to draw conclusions about the impact of different components on degradation and to analyze the underlying aging mechanisms occurring in each component.