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| 1 | NeuroPNM:Model reduction of pore network models using neural networks显示文摘Reacting particle systems play an important role in many industrial applications,for example biomass drying or the manufacturing of pharmaceuticals.The numerical modeling and simulation of such systems is therefore of great importance for an efficient,reliable,and environmentally sustainable operation of the processes.The complex thermodynamical,chemical,and flow processes that take place in the particles are a particular challenge in a simulation.Furthermore,typically a large number of particles is involved,rendering an explicit treatment of individual ones impossible in a reactor-level simulation.One approach for overcoming this challenge is to compute effective,physical parameters from single-particle,high-resolution simulations.This can be combined with model reduction methods if the dynamical behaviour of particles must be captured.Pore network models with their unrivaled resolution have thereby been used successfully as high-resolution models,for instance to obtain the macroscopic diffusion coeffcient of drying.Both parameter identification and model reduction have recently gained new impetus by the dramatic progress made in machine learning in the last decade.We report results on the use of neural networks for parameter identification and model reduction based on three-dimensional pore network models(PNM).We believe that our results provide a powerful complement to existing methodologies for reactor-level simulations with many thermally-thick particles. | Robert Jendersie Ali Mjalled Xiang Lu Lucas Reineking Abdolreza Kharaghani Martin Monnigmann Christian Lessig | 2024 | Particuology2024，86，3： | 0 |
| 2 | Multi-point temperature measurements in packed beds using phosphor thermometry and ray tracing simulations显示文摘Packed bed reactors are commonly found in the process industry,for example in flame-assisted calci-nation for cement production.Understanding the heat transfer inside the bed is essential for process control,product quality and energy efficiency.Here we propose a technique to determine the internal temperature distribution of packed beds based on a combination of lifetime-based phosphor ther-mometry,ray tracing simulations,and assimilation of temperature data using finite element heat transfer simulations.To establish and validate the technique,we considered a reproducible regular packing of 6 mm diameter aluminum spheres,with one of the spheres in the top layer being electrically heated.If a sphere inside the packing is coated with thermographic phosphors and excitation light is directed to-wards the packing,luminescence from the coated sphere exits the packed bed after multiple reflection and the sphere's temperature can be determined.Isothermal measurements showed that the temper-ature obtained by phosphor thermometry is independent of the luminescent sphere location.When imaging the luminescence on a camera,the luminescence distribution in recorded image depended,however,on the position of the sphere.Therefore,in setups with multiple phosphor-coated spheres,their signals can be separated using a least squares fit.We demonstrate the approach using a setup with three luminescent spheres and validated the temperature readings against thermocouple measurements.To obtain the spatial signatures for individual sphere positions required for the least squares fit,ray tracing simulations were used.These provide an efficient alternative to single sphere measurements that are only practical for regular spherical packed beds.Multi-point measurements were used as input to a finite element heat transfer simulations to determine parameters such as particle-to-particle air gap distance.With these,the full temperature distribution inside the bed could be assimilated from the measured values. | Guangtao Xuan Mirko Ebert Simson Julian Rodrigues Nicole Vorhauer-Huget Christian Lessig Benoit Fond | 2024 | Particuology2024，85，2： | 0 |
| 3 | A numerical and experimental comparison of heat transfer in a quasi two-dimensional packed bed显示文摘Heat transfer plays a major role in many industrial processes taking place in packed beds.An accurate and reliable simulation of the heat exchange between particles is therefore crucial for a reliable operation and to optimize the processes in the bed.The discrete ordinates method(DOM)provides an established numerical technique to model radiative heat transfer in granular media that offers the possibility to consider the directional dependence of the radiation propagation.In this work,DOM is compared with Monte Carlo ray tracing,which provides an alternative method for heat transfer simulations.Geomet-rically simple configurations are used to investigate the influence of the angular discretization on the accuracy of the results and the computation time in both methods.The obtained insights are then transferred to a more complex configuration of a quasi two-dimensional test rig consisting of metal rods for which also experimental results are available.Our results show that both DOM and Monte Carlo ray tracing allow for an accurate simulation of heat transfer in packed beds.Monte Carlo ray tracing requires thereby computation times that are surprisingly competitive(although still somewhat slower)compared to DOM and allows for an easier computation of highly accurate reference solutions.In our preliminary comparison to the experimental test rig,Monte Carlo ray tracing also provides the advantage that it can more easily model highly specular materials such as stainless steel.Both methods are comparable for diffuse materials such as magnesium oxide. | Matthias Tyslik Mirko Ebert Martin Schiemann Siegmar Wirtz Christian Lessig | 2024 | Particuology2024，84，1： | 0 |
| 4 | Ray tracing particle image velocimetry-Challenges in the application to a packed bed显示文摘Ray tracing Particle Image Velocimetry(RT-PIV)is an optical technique for high resolution velocity measurements in challenging optical systems,such as transparent packed beds,that uses ray tracing to correct for distortions introduced by transparent geometries in the light paths.The ray tracing based correction is a post processing step applied to the raw PIV particle images before classical PIV evaluation.In this study,RT-PIV is performed in the top layer of a body centred cubic(bcc)sphere packing with gaseous flow,where optical access is obtained by the use of transparent N-BK7 glass balls with a diameter of d=40 mm.RT-PIV introduces new experimental and numerical challenges,for example a limited field of view,illumination difficulties,a very large required depth of field and high sensitivity to geometric parameters used in the ray tracing correction.These challenges and their implications are the main scope and discussed in the present work.Further,the validation of the ray tracing reconstruction step is presented and examples for the obtained corrected vector fields in a packed bed are given.The results show the strength of the method in reconstructing velocity fields behind transparent spheres that would not have been accessible by optical measurement techniques without the ray tracing correction. | Christin Velten Mirko Ebert Christian Lessig Katharina Zahringer | 2024 | Particuology2024，84，1： | 0 |
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