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NATURE REVIEWS METHODS PRIMERS 2024年第1期4卷 1页

作者： [Anonymous] Biomimetic Design Laboratory Department of Physics Northeastern University Boston MA USA Process Imaging Laboratory Institute of Materials Science and Technology Technische Universität Berlin Berlin Germany Process Imaging Laboratory Institute of Applied Materials Helmholtz-Zentrum Berlin für Materialien und Energie Berlin Germany Laboratory of Micro and Materials Mechanics Department of Microsystems Engineering University of Freiburg Freiburg Germany

This PrimeView highlights the structures formed with different freeze casting moulds.

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Data-driven Temperature Estimation for a Multi-Stage Press Hardening process

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IFAC-PapersOnLine 2023年第2期56卷 4252-4257页

作者： Malte Wrobel Juri Martschin Thomas Meurer Erman Tekkaya Digital Process Engineering Group Institute for Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology (KIT) 76187 Karlsruhe Germany Institute of Forming Technology and Lightweight Components Dortmund University 44227 Dortmund Germany

In a multi-stage press hardening process with a sheet material in a progressive die the material is first rapidly austenitized, pre-cooled, stretch-formed, and finally die bent. The product properties result from the thermo-mechanical history. With the aim to estimate and subsequently to directly control these properties a data-driven estimation of the spatial-temporal temperature distribution in the sheet is developed in this work. Therefore a data-driven dynamical model is designed via the Dynamic Mode Decomposition (DMD) using a Finite Element (FE) simulation as data basis. This model is extended to a parameter-dependent formulation (parametric DMD) capturing the process parameters stroke rate, blank holder force, and austenitization temperature, which serve as inputs to the model. The approach is verified by a comparison of the data-driven model with the original FE model. To estimate the temperature distribution a discrete time system representation is formulated, where the stage dependent and hence time varying output matrix is constructed for thermocouples integrated into the individual stages. Based on this a Kalman filter is designed and evaluated in simulation.

关键词： Dynamic Mode Decomposition Finite Element Method Model Order Reduction Metal Sheet Forming Software Sensor Observers Temperature Estimation

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EM-DETR: Efficient Multi-scale DETR for Gas Leak Detection Based on Infrared Imaging

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IEEE Sensors Journal 2025年第11期25卷 20538-20546页

作者： Wang, Qi Zhu, Shilin Lu, Zhenlin Sun, Yunlong Qian, Yizhuo Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao066004 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Northeastern University College of Information Science and Engineering Shenyang110819 China Beijing Institute of Microelectronics Technology Beijin100076 China

Industrial gases play a crucial role in modern industrial production. However, many industrial gases are only visible in the infrared spectrum. Therefore, using infrared camera for gas leak detection is essential for the normal operation of production lines and the safety of personnel. Existing automatic leak detection algorithms based on convolutional neural networks often involve numerous handcrafted feature components, resulting in complex model architectures, with hyperparameter selection significantly impacting model performance. To address these issues, we propose an efficient and high-performance end-to-end object detection network, the Efficient Multi-scale Detection Transformer (EM-DETR), for automatic gas leak detection. To reduce model computational overhead, we design a new efficient encoder. Additionally, to handle leaks of varying ranges due to gas dispersion, we implement bidirectional fusion of multi-scale features to capture granularity information of gases at different scales. Finally, based on the similar unified distribution of gas leak images, we introduce a pre-auxiliary loss to adjust the learnable object queries initialized. Experimental results demonstrate that the EM-DETR R50/R101 outperforms previous methods, achieving 40.7%/43.2% AP on gas leak infrared image datasets with minimal parameters and computational resources, providing a superior solution for automatic gas leak detection using infrared camera. © 2001-2012 IEEE.

关键词： Convolutional neural networks

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Simulation of Particle-Agglomerate Transport in a Particle Filter using Lattice Boltzmann Methods

Simulation of Particle-Agglomerate Transport in a Particle F...

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22nd International Stuttgart Symposium, ISSYM 2022

作者： Hafen, Nicolas Krause, Mathias J. Dittler, Achim Gas Particle Systems Karlsruhe Institute of Technology Karlsruhe76131 Germany Lattice Boltzmann Research Group Karlsruhe Institute of Technology Karlsruhe76131 Germany Institute of Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology Karlsruhe76131 Germany Institute for Applied and Numerical Mathematics Karlsruhe Institute of Technology Karlsruhe76131 Germany Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9783658370107

Wall-flow filters are used as particle filters in the exhaust gas after treatment of combustion engines. Soot is deposited in the filter and removed from it by regeneration through oxidation. However, an inert portion (ash) remains in the filter and forms different deposition patterns. Those patterns affect the separation efficiency as well as the overall pressure drop. The formation of deposition patterns is caused by rearrangement processes during regeneration, which result from the break-up of the particle layer as well as the resuspension and transport of individual agglomerates. With the help of the Homogenized Lattice Boltzmann Method (HLBM), resolved particle simulations are carried out within the framework of the open source software OpenLB. This allows the forces acting on the agglomerates to be determined and detachment and transport processes to be modelled. The focus of the present work is on a detailed investigation of the flow-induced transport of individual particle-agglomerates. © Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2022.

关键词： Wall flow

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Automated classification of granular bainite and polygonal ferrite by electron backscatter diffraction verified through local structural and mechanical analyses

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Journal of Materials Research 2023年第18期38卷 4177-4191页

作者： Jentner, R.M. Tsai, S.P. Welle, A. Scholl, S. Srivastava, K. Best, J.P. Kirchlechner, C. Dehm, G. Max-Planck-Institut Für Eisenforschung GmbH Max-Planck-Straβe 1 Düsseldorf40237 Germany Department of Materials Science and Engineering National Taiwan University Roosevelt Road 1 Taipei10617 Taiwan Karlsruhe Nano Micro Facility and Institute of Functional Interfaces Karlsruhe Institute of Technology Karlsruhe76021 Germany AG der Dillinger Hüttenwerke Werkstraße 1 Dillingen/Saar66763 Germany Institute for Applied Materials Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany

Differentiation of granular bainite and polygonal ferrite in high-strength low-alloy (HSLA) steels possesses a significant challenge, where both nanoindentation and chemical analyses do not achieve an adequate phase classification due to the similar mechanical and chemical properties of both constituents. Here, the kernel average misorientation from electron backscatter diffraction (EBSD) was implemented into a Matlab code to differentiate and quantify the microstructural constituents. Correlative electron channeling contrast imaging (ECCI) validated the automated phase classification results and was further employed to investigate the effect of the grain tolerance angle on classification. Moreover, ECCI investigations highlighted that the grain structure of HSLA steels can be subdivided into four grain categories. Each category contained a different nanohardness or substructure size that precluded a nanoindentation-based phase classification. Consequently, the automated EBSD classification approach based on local misorientation achieved a reliable result using a grain tolerance angle of 5°. Graphical abstract: [Figure not available: see fulltext.] © 2023, The Author(s).

关键词： Backscattering

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Local Heat Transfer Coefficient Measurements on Shaft Spray Cooled End Windings

Local Heat Transfer Coefficient Measurements on Shaft Spray ...

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IEEE International Conference on Electric Machines and Drives (IEMDC)

作者： Felix Hoffmann Jonas Bender Mattis Parche Thomas Wetzel Martin Doppelbauer Institute of Electrical Engineering (ETI) Karlsruhe Institute of Technology (KIT) Institute of Thermal Process Engineering (TVT) Karlsruhe Institute of Technology (KIT) Karlsruhe Germany

High power density electrical machines are mainly limited due to their cooling system. Oil spray cooled end windings are one possibility to significantly increase the power density. However, foundations for the estimation of the cooling capability are rather scarce in the design process. Different approaches to estimate the global heat transfer coefficients for spray cooled end windings exist in literature. However, local heat transfer coefficients, which are essential for the prediction of hot spots, can not be estimated. In this contribution, we present local heat transfer coefficient measurements for shaft spray cooled end windings. It is shown that the existence of a sump remarkably lowers the heat transfer coefficient, whereas it is almost constant over the remaining circumference. The rotational speed has a minor influence on the heat transfer. The latter is only increasing for very high speeds. A modeling approach for the Nusselt number is developed to apply it to different coolants. The achieved mean absolute percentage error between experimental and modeled Nusselt is 10.8%.

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Model-based Estimator Design for the Curing process of a Concrete Structure

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IFAC-PapersOnLine 2023年第2期56卷 3241-3246页

作者： Denis Ratke Thomas Meurer Yannik Schwarz David Sanio Peter Mark Digital Process Engineering Group Institute of Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology 76187 Karlsruhe Germany Institute of Concrete Structures Faculty of Civil and Environmental Engineering Ruhr University Bochum 44801 Bochum Germany

Concrete is one of the most important building materials and is used as a collective term for different dispersions of cement and aggregates. High performance concrete (HPC) is a rather new type of concrete mixture. A topic of current research is the behavior of fresh concrete during heat treatment. It is known that the heat treatment of fresh concrete accelerates the reaction of the cement and thus the chemically complex process of hydration. The mathematical representation of the curing concrete is a further step towards the systematic investigation. The objective of this work is the development of a state estimator to determine the temperature behavior of the fresh HPC mixture under heat treatment. Using a continuum representation describing the spatial-temporal evolution of temperature, moisture, and maturity of fresh HPC during heat treatment a finite-dimensional approximation is derived using a high order finite difference scheme. Experimental data is included for model parameterization by optimization. Based on this, three different nonlinear extensions of the Kalman filter (KF) techniques are realized and compared combining simulated and experimental data.

关键词： Partial differential equations Curing concrete Civil engineering Kalman filter Nonlinear observer design Parameter identification Distributed parameter systems

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DMD-Based Model Predictive Control for a Coupled PDE-ODE System

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IFAC-PapersOnLine 2023年第2期56卷 4258-4263页

作者： Dirk Wolfram Thomas Meurer Chair of Automation and Control Faculty of Engineering Kiel University 24143 Kiel Germany Digital Process Engineering Group Institute for Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology (KIT) 76187 Karlsruhe Germany

Models resulting from the application of the finite element method (FEM) are usually high dimensional, thus in general preventing the application of optimal control concepts under real-time conditions. In this work a system consisting of the heat equation defined on a 3-dimensional domain with local in-domain thermal actuators is considered, whose modeling results in a coupled PDE-ODE description. Based on simulation data, a data driven reduced order model is determined using the Dynamic Mode Decomposition with control (DMDc). Based on the DMDc model a model predictive control (MPC) approach with state estimator is developed to realize a desired temperture profile on the given domain. The concept is evaluated involving the high-dimensional finite element model as plant model.

关键词： Distributed parameter systems Reduced order model Data-driven control Model predictive control Heat conduction

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Design-for-manufacture of a dual-chamber nozzle for hydrodynamic focusing of the Aerosol-on-Demand jet-printhead

Design-for-manufacture of a dual-chamber nozzle for hydrodyn...

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Design, Test, Integration and Packaging of MEMS/MOEMS

作者： Martin Ungerer Ulrich Gengenbach Karanvir Singh Grewal Achim Wenka Ingo Sieber Institute for Automation and Applied Informatics (IAI) Karlsruhe Institiute of Technology (KIT) Karlsruhe Germany Department of Mechanical Engineering Punjab Engineering College Chandigarh India Institute for Micro Process Engineering (IMVT) Karlsruhe Institiute of Technology (KIT) Karlsruhe Germany

In this paper, we present the design of a dual-chamber nozzle (DCN) for a newly developed concept of a printhead for Aerosol-on-Demand (AoD) jet-printing using fluid dynamic modelling and simulation. In this newly developed concept, the ink is atomized inside of the nozzle chamber by ultrasonic excitation. This enables on-demand operation of the printhead. Focusing is achieved by means of a sheath gas and the nozzle geometry. To achieve a collimated aerosol jet, a DCN is advantageous. Computational fluid dynamics (CFD) is used to perform the design layout of a DCN for AoD jet-printing, with the goal of finding a design-for-manufacture.

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POTENTIAL FOR DAMAGE TO FRUITS DURING TRANSPORT THROUGH CROSS-SECTION CONSTRICTIONS

arXiv

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arXiv 2024年

作者： Marquardt, Jan E. Eysel, Bastian Sadric, Martin Rauh, Cornelia Krause, Mathias J. Lattice Boltzmann Research Group Institute of Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology Karlsruhe76131 Germany Institute of Food Biotechnology and Food Process Engineering Faculty III Process Sciences Technische Universität Berlin Berlin10623 Germany Lattice Boltzmann Research Group Institute for Applied and Numerical Mathematics Karlsruhe Institute of Technology Karlsruhe76131 Germany

Fruit preparations are used in various forms in the food industry. For example, they are used as an ingredient in dairy products such as yogurt with added fruit. The dispersed fruit pieces can be described as soft particles with viscoelastic material behavior. The continuous phase is represented by fluids with complex flow behavior depending on the formulation. Characterization has shown that this can be described by the Herschel-Bulkley model. Since damage to fruit pieces is undesirable in industrial transport processes, the potential for damage to fruit pieces during transport of pipes in cross-sectional constrictions is analyzed. The analysis is performed numerically using the homogenized lattice Boltzmann method and validated by an experiment on industrial fruit preparations at pilot plant scale. The results show a strong dependence of the damage potential on the (local) Metzner-Reed Reynolds number. Copyright © 2024, The Authors. All rights reserved.

关键词： Fruits

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