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arXiv 2023年

作者： Marquardt, Jan E. Hafen, Nicolas Krause, Mathias J. Lattice Boltzmann Research Group Institute of Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology Karlsruhe76131 Germany

This study addresses the challenge of simulating realistic particle systems by proposing a novel particle decomposition scheme that improves the parallel performance of surface resolved particle simulations. Realistic particle systems often involve large numbers of particles and complex particle shapes. The resulting need to account for shape factors requires the inclusion of even more particles to obtain statistically meaningful results. However, the computational cost increases with the number of particles, making efficient parallelization crucial. Therefore, the proposed scheme aims to improve the scalability by optimizing the communication and data management between processors. Through hindered settling experiments, the applicability and performance of the novel particle decomposition scheme are thoroughly investigated using the homogenized lattice Boltzmann method. The results show that the proposed method significantly improves the performance, especially in scenarios with a large number of particles, by reducing communication constraints and improving scalability. This research contributes to the advancement of computational methods for efficient study of complex particle systems and provides valuable insights for future developments in this field. Copyright © 2023, The Authors. All rights reserved.

关键词： Scalability

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Impact of engine oil volatility and viscosity on blow-by aerosol formation

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Automotive and Engine technology 2022年第1期7卷 153-163页

作者： Scheiber, Kai-Michael Nowak, Niclas Lorenz, Magnus Lukas Pfeil, Jürgen Koch, Thomas Kasper, Gerhard Institute of Internal Combustion Engines Karlsruhe Institute of Technology Karlsruhe Germany Institute of Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology Karlsruhe Germany Daimler Truck AG Stuttgart Germany

Particulate emissions from diesel engines are a matter of public concern and continued industrial development. For an internal combustion engine, particles may originate either from the after treatment box or from the crankcase ventilation system. This paper quantifies and discusses particle sources within the crankcase ventilation system of a medium-duty 4-cylinder and a heavy-duty 6-cylinder engine and their dependence on the engine oil parameters viscosity (expressed as Noack number) and HTHS volatility. Crankcase aerosol spectra were measured by an optical particle counter in the size range of 0.3–5 µm. For a few cases data of filter samples downstream the separator unit are discussed for the total blow-by aerosol. Engines were found to behave very similarly with regard to changes in either oil parameter, with volatility generally being the far stronger factor of influence. Total particle mass concentration increased by a factor of up to 5 for a rise in Noack volatility of about 13–25%. The mass concentration downstream of the separator also increases with oil volatility. A variation of HTHS viscosity from 3.5 to 2.6 mPas generated a marginal change in aerosol output by a factor of about 1.2. However, and unexpectedly, the most viscose oil generated the relatively highest particle mass concentrations for both engines.

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Time-Aware Data Profiling With Decision Tree Pattern Mining

Time-Aware Data Profiling With Decision Tree Pattern Mining

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IEEE Conference on Commerce and Enterprise Computing, CEC

作者： Alexander Grote Wolfgang Badwitz Michael Thomas Knierim Christof Weinhardt Information Process Engineering FZI Forschungszentrum Informatik Karlsruhe Germany Institute of Information Systems & Marketing Karlsruhe Institute of Technology (KIT) Karlsruhe Germany

Data quality issues can lead to significant financial losses, which necessitates the use of data profiling to monitor the statistical properties of datasets and detect harmful deviations early. However, many existing data profiling solutions cannot perform multi-column feature analysis. On the other hand, machine learning algorithms, particularly decision trees, are effective at discovering non-linear and multivariate patterns within tabular data. In this study, we propose a framework that combines the interpretable pattern-mining capabilities of decision trees with time series forecasting to identify significant changes in data. We evaluate our framework on a real-world dataset from a leading telecommunications provider in Germany, which includes a known anomaly resulting from a faulty database entry. Our results indicate that our framework successfully detects data changes and provides interpretable descriptions for each anomaly, highlighting its relevancy for practitioners.

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Influence of high-speed impact cutting on the electromagnetic properties of non-oriented electrical steel sheets

Influence of high-speed impact cutting on the electromagneti...

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International Electric Drives Production Conference (EDPC)

作者： Jonas Matt Martin Doppelbauer Process Development Drive Systems Mercedes-Benz AG Stuttgart Germany Institute of Electrical Engineering Karlsruhe Institute of Technology Karlsruhe Germany

The constantly growing requirements for increasing the range of battery electric vehicles and an associated increase in the efficiency of electrical machines for traction drives also pose challenges for manufacturing processes and the selection of suitable processing parameters in the manufacturing chain. High-speed impact cutting (HSIC) has been investigated to a limited extent for electrical steel sheets and represents an essential opportunity to improve the soft magnetic behavior in the cut edge zone. This paper aims to investigate and validate the primary characteristics that result from HSIC on the softmagnetic properties. Accordingly, it is shown and quantified how the degradation of the soft magnetic behavior is formed in the zone affected by shear cutting, with a comparative representation to conventional shear cutting. It is also shown how the secondary properties change as a result of the improved cutting surface quality.

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Multidimensional separation due to selective spherical agglomeration—Evidence of shape separation via X-ray microtomography

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Particuology 2021年第5期19卷 316-323页

作者： Julia Schreier Ulrich Brockel University of Applied Sciences Trier Institute for Micro-Process-Engineering and Particle Technology(IMiP)Umwelt-Campus BirkenfeldP.O.Box 1380D-55761 BirkenfeldGermany

Objective of this work was to develop a novel method for characterizing real 3D shapes of particles smaller than 20μm by X-ray microtomography(X-RMT).Multidimensional separation of heterogenous solids through agglomeration in suspension will improve recycling processes as the particle shape and the agglomerate size are used for shape-selective *** the present paper we discuss the fundamentals of X-ray tomography and the experimental setup for selective spherical agglomeration in suspension.A specific preparation method of the particulate sample for X-RMT followed by 3D image processing,are essential for the shape analysis expressed as *** also discuss the limitation of this method due to the so-called Partial Volume Effect and particle clusters in the order of magnitude of X-RMT *** proof of concept,we used a mixture of graphite platelets and spheronized graphite particles for a shape selective-agglomeration in *** remaining fines were analyzed and showed more platelets than in the *** indicates that spheronized particles are preferably bound in the *** findings show that,based on the discussed sample preparation and a 3D image analysis in connection with X-RMT,particle shapes of micronized particles can be discriminated.

关键词： Multidimensional separation X-ray microtomography Selective agglomeration Particle shape Graphite

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Self-healing Fuel Cells by Biological Actuators 30

Self-healing Fuel Cells by Biological Actuators

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30th CIRP Life Cycle engineering Conference, LCE 2023

作者： Gartner, Patrizia Lanza, Gisela Rudat, Jens Bilger, Maximilian Grünert, Tom Nesterov-Mueller, Alexander Zimmerer, Nadine Quarz, Philipp Scharfer, Philip Schabel, Wilhelm Jung, André P. Stahlberger, Mareen Bräse, Stefan wbk Institute of Production Science Kaiserstr.12 Karlsruhe76131 Germany KIT Institute of Process Engineering in Life Sciences 2: Technical Biology Kaiserstr.12 Karlsruhe76131 Germany KIT Institute of Microstructure Technology Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen76344 Germany KIT Thin Film Technology Kaiserstr.12 Karlsruhe76131 Germany KIT Institute of Biological and Chemical Systems Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen76344 Germany

A completely novel approach aims to extend the lifetime of polymer electrolyte membrane fuel cells (PEM-FCs) many times over through a self-healing mechanism, thus contributing to the transition to a sustainable economy and mobility. Many start-up cycles in truck or car applications lead to pinholes in the proton-conducting polymer membranes (Nafion™). Since there is no way to repair this type of defect when the fuel cell is already assembled, the performance of the fuel cell stack is continuously reduced towards the end of its lifetime. The BioHealing project, an interdisciplinary consortium at the karlsruhe institute of technology, investigates an innovative biohybrid technology that can repair occurring pinholes selectively in fuel cell membranes by a self-healing mechanism without disassembling the fuel cell stack. This is enabled by a biohybrid system, i.e., integrating biological and technical components. The filler-forming enzymes are functionally immobilised on the polymer membrane surface via a special peptide linker to enable site-directed filler production during membrane electrode assembly. For self-healing, a substrate is injected into the gas inlet of the fuel cell stack, the enzymatic reaction is catalysed, and the substrate is converted into the filler, a biological polymerised product that seals the existing pinholes. In this publication, the concept is presented with initial research results. The concept includes characterisation of surface properties and functional groups of the Nafion™ membrane, immobilisation of the specially designed fluorophilic peptide linker, selection of suitable enzymes to be screened for activity and stability, and investigation of the filler to be successfully esterified with the membrane. © 2023 The Authors. Published by Elsevier B.V.

关键词： Proton exchange membrane fuel cells (PEMFC)

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Identification of Reaction Rate Parameters from Uncertain Spatially Distributed Concentration Data Using Gradient-Based Pde Constrained Optimization

SSRN

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SSRN 2023年

作者： Ito, Shota Jeßberger, Julius Simonis, Stephan Bukreev, Fedor Kummerländer, Adrian Zimmermann, Alexander Thäter, Gudrun Pesch, Georg R. Thöming, Jorg Krause, Mathias J. Lattice Boltzmann Research Group Karlsruhe Institute of Technology Karlsruhe Germany Institute of Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology Karlsruhe Germany Institute for Applied and Numerical Mathematics Karlsruhe Institute of Technology Karlsruhe Germany Center for Environmental Research and Sustainable Technology University of Bremen Bremen Germany School of Chemical and Bioprocess Engineering University College Dublin Dublin Ireland

A promising approach to quantify reaction rate parameters is to formulate and solve inverse problems by minimizing the deviation between simulation and measurement. One major challenge may become the non-uniqueness of the recovered parameters due to the ill-posed problem formulation, which requires sophisticated approaches such as regularization. This study investigates the feasibility of using spatially distributed reference data, i.e., concentration distributions of reactive flows, which could be obtained by magnetic resonance imaging (MRI), instead of isolated points or integral values to recover reaction rate parameters. We propose a combined framework of computational fluid dynamics (CFD) and gradient-based optimization methods, which minimizes the difference between the simulated concentration distribution and a given data set by automatic iterative parameter adjustments. The forward problem is formulated as a coupled system of reaction-advection-diffusion equations (RADE), which is solved by the lattice Boltzmann method (LBM). Therefore, a system of non-linear partial differential equations (PDE) acts as optimization constraints, limiting the possible outcomes of the inverse problem. A benchmark test case using a CFD simulation as reference data confirms the validity of the presented method by successfully identifying up to three \textit{a priori} set reaction parameters reversely. With it, initial relative errors could be reduced from around $150\%$ to $10^{-3}\%$ in 13 optimization steps corresponding to 37 simulations. Even after reducing the accessible reference data from 2D concentration distributions to 1D outflow concentration distribution or by adding noise signals onto the reference data with a signal-to-noise ratio (SNR) of 5, our framework successfully recovered the parameters with a relative error of $\approx 1\%$. Both, the chosen LBM and optimization algorithms are implemented in the open-source library OpenLB. © 2023, The Authors. All rights re

关键词： Computational fluid dynamics

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HOMOGENIZED LATTICE BOLTZMANN METHODS FOR FLUID FLOW THROUGH POROUS MEDIA – PART I: KINETIC MODEL DERIVATION

arXiv

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arXiv 2023年

作者： Simonis, Stephan Hafen, Nicolas Jeßberger, Julius Dapelo, Davide Thäter, Gudrun Krause, Mathias J. Institute for Applied and Numerical Mathematics Karlsruhe Institute of Technology Karlsruhe76131 Germany Institute of Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology Karlsruhe76131 Germany Lattice Boltzmann Research Group Karlsruhe Institute of Technology Karlsruhe76131 Germany School of Engineering University of Liverpool LiverpoolL69 3BX United Kingdom

In this series of studies, we establish homogenized lattice Boltzmann methods (HLBM) for simulating fluid flow through porous media. Our contributions in part I are twofold. First, we assemble the targeted partial differential equation system by formally unifying the governing equations for nonstationary fluid flow in porous media. A matrix of regularly arranged, equally sized obstacles is placed into the domain to model fluid flow through porous structures governed by the incompressible nonstationary Navier–Stokes equations (NSE). Depending on the ratio of geometric parameters in the matrix arrangement, several homogenized equations are obtained. We review existing methods for homogenizing the nonstationary NSE for specific porosities and discuss the applicability of the resulting model equations. Consequently, the homogenized NSE are expressed as targeted partial differential equations that jointly incorporate the derived aspects. Second, we propose a kinetic model, the homogenized Bhatnagar–Gross–Krook Boltzmann equation, which approximates the homogenized nonstationary NSE. We formally prove that the zeroth and first order moments of the kinetic model provide solutions to the mass and momentum balance variables of the macrocopic model up to specific orders in the scaling parameter. Based on the present contributions, in the sequel (part II), the homogenized NSE are consistently approximated by deriving a limit consistent HLBM discretization of the homogenized Bhatnagar–Gross–Krook Boltzmann *** Codes 35Q30, 35Q20, 35B27 Copyright © 2023, The Authors. All rights reserved.

关键词： Porous materials

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A Digital Urban Twin Enabling Interactive Pollution Predictions and Enhanced Planning

arXiv

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arXiv 2025年

作者： Teutscher, Dennis Bukreev, Fedor Kummerländer, Adrian Simonis, Stephan Bächler, Peter Rezaee, Ashkan Hermansdorfer, Mariusz Krause, Mathias J. Lattice Boltzmann Research Group Karlsruhe Institute of Technology Englerstr. 2 Karlsruhe Baden-Württemberg76131 Germany Institute for Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology Straße am Forum 8 Karlsruhe Baden-Württemberg76131 Germany Institute for Applied and Numerical Mathematics Karlsruhe Institute of Technology Englerstr. 2 Karlsruhe Baden-Württemberg76131 Germany Henning Larsen Vesterbrogade 76 Hovedstaden Copenhagen1620 Denmark

Digital twin (DT) technology is increasingly used in urban planning, leveraging real-time data integration for environmental monitoring. This paper presents an urban-focused DT that combines computational fluid dynamics simulations with live meteorological data to analyze pollution dispersion. Addressing the health impacts of pollutants like particulate matter and nitrogen dioxide, the DT provides real-time updates on air quality, wind speed, and direction. Using OpenStreetMap’s XML-based data, the model distinguishes between porous elements like trees and solid structures, enhancing urban flow analysis. The framework employs the lattice Boltzmann method (LBM) within the open-source software OpenLB to simulate pollution transport. Nitrogen dioxide and particulate matter concentrations are estimated based on traffic and building emissions, enabling hot-spot identification. The DT was used from November 7 to 23, 2024, with hourly updates, capturing pollution trends influenced by wind patterns. Results show that alternating east-west winds during this period create a dynamic pollution distribution, identifying critical residential exposure areas. This work contributes a novel DT framework that integrates real-time meteorological data, OpenStreetMap-based geometry, and high-fidelity LBM simulations for urban wind and pollution modeling. Unlike existing DTs, which focus on structural monitoring or large-scale environmental factors, this approach enables fine-grained, dynamic analyses of urban airflow and pollution dispersion. By allowing interactive modifications to urban geometry and continuous data updates, the DT serves as a powerful tool for adaptive urban planning, supporting evidence-based policy making to improve air quality and public health. Copyright © 2025, The Authors. All rights reserved.

关键词： Air quality

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A Stochastic Galerkin Lattice Boltzmann Method for Incompressible Fluid Flows with Uncertainties

SSRN

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SSRN 2024年

作者： Zhong, Mingliang Xiao, Tianbai Krause, Mathias J. Frank, Martin Simonis, Stephan Scientific Computing Center Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany State Key Laboratory of High Temperature Gas Dynamics Centre for Interdisciplinary Research in Fluids Institute of Mechanics Chinese Academy of Sciences Beijing100190 China School of Engineering Science University of Chinese Academy of Sciences Beijing100049 China Institute for Applied and Numerical Mathematics Karlsruhe Institute of Technology Karlsruhe76131 Germany Institute of Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology Karlsruhe76131 Germany Lattice Boltzmann Research Group Karlsruhe Institute of Technology Karlsruhe76131 Germany

Efficient modeling and simulation of uncertainties in computational fluid dynamics (CFD) remains a crucial challenge. In this paper, we present the first stochastic Galerkin (SG) lattice Boltzmann method (LBM) built upon the generalized polynomial chaos (gPC). The proposed method offers an efficient and accurate approach that depicts the propagation of uncertainties in stochastic incompressible flows. Formal analysis shows that the SG LBM preserves the correct Chapman-Enskog asymptotics and recovers the corresponding macroscopic fluid equations. Numerical experiments, including the Taylor-Green vortex flow, lid-driven cavity flow, and isentropic vortex convection, are presented to validate the solution algorithm. The results demonstrate that the SG LBM achieves the expected spectral convergence and the computational cost is significantly reduced compared to the sampling-based non-intrusive approaches, e.g., the routinely used Monte Carlo method. We obtain a speedup factor of 5.72 compared to Monte Carlo sampling in a randomized two-dimensional Taylor-Green vortex flow test case. By leveraging the accuracy and flexibility of LBM and the efficiency of gPC-based SG, the proposed SG LBM provides a powerful framework for uncertainty quantification in CFD practice. © 2024, The Authors. All rights reserved.

关键词： Computational fluid dynamics

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