Sensitivity of Filter Cake Permeability to Systematic Variations in Particle Shape and Size: A Bottom-Up Stochastic Analysis

Löwer, Erik

Sensitivity of Filter Cake Permeability to Systematic Variations in Particle Shape and Size: A Bottom-Up Stochastic Analysis

Contributing person datacite.contributor.ProjectLeader	Urs Alexander Peuker
Contributing person datacite.contributor.ProjectLeader	Volker Schmidt
Contributing person datacite.contributor.ProjectMember	Orkun Furat
Contributing person datacite.contributor.ProjectMember	Phillip Gräfensteiner
Contributing person datacite.contributor.ProjectMember	Benedikt Prifling
References to related material datacite.relatedItem.IsSupplementTo	publication 'Sensitivity of Filter Cake Permeability to Systematic Variations in Particle Shape and Size: A Bottom-Up Stochastic Analysis'
Description of the data datacite.resourceType	All containing data is described in the enclosed README.md. The dataset contains nine different image stacks from X-ray microscopy scans of filter cakes. For each scan, the following files are provided: - image stack in HDF5 format (one file contains a series of 16-bit images) - `parameters.PNG` – screenshot of acquisition and reconstruction parameters - `insitu.PNG` – screenshot of one projection of sample - `overview.PNG` – representative slice and rendered 3D visualisation of sample for quick overview. Besides this measurement data the datasheets for the two investigated particle systems are provided. Additionally, the generated and analyzed artificial structures of the filter cakes are also attached. They are grouped into folders that specify the grid point on the 5-dimensional parameter grid, with four realizations each for the different packing densities or porosities. The image data consists of 16-bit images, with each particle having its own label.
Type of the data datacite.resourceTypeGeneral	Image
Total size of the dataset datacite.size	27986852237
Author dc.contributor.author	Löwer, Erik
Upload date dc.date.accessioned	2026-04-28T07:50:54Z
Publication date dc.date.available	2026-04-28T07:50:54Z
Data of data creation dc.date.created	2025-06
Publication date dc.date.issued	2026-04-28
Abstract of the dataset dc.description.abstract	The data belongs to the corresponding publication "Sensitivity of Filter Cake Permeability to Systematic Variations in Particle Shape and Size: A Bottom-Up Stochastic Analysis" with the following abstract. A key question in filtration process design is understanding the filtration properties of a specific particle system. Current methods, like the Carman-Kozeny equation, struggle to accurately predict specific cake resistance and capillary pressure from a given particle size distribution, leading to reliance on limited empirical correlations. This poses challenges for process simulation, as the transition from particle characteristics to filter cake properties remains unclear. This work aims to correlate the distribution of multi-dimensional particle properties—both size and shape—with the properties of the resulting 3D filter cake morphology. We use tomographic image data of real filter cakes to validate a stochastic 3D model which describes the relationship between particle properties and multiphase filter cake characteristics using generated virtual particles that statistically resemble the actual data. Validation is provided by filter cakes from two different particle systems: spherical glass and broken quartz particles ranging in size from 40 to 300 μm with sphericity values from 0.5 to 1. Artificial, but realistic particles following the same particle property distributions are utilized to construct virtual filter cake structures using a forced bias algorithm, which statistically represent actual cake structures. The generated virtual cake structures allow for deriving trends in permeability by systematically varying particle properties virtually. The dataset provides the used raw data and the generated artifical cake structures which were used for the correlation of several particle, structure and process parameters of the investigated filtration process.
Public reference to this page dc.identifier.uri	https://opara.zih.tu-dresden.de/handle/123456789/2094
Public reference to this page dc.identifier.uri	https://doi.org/10.25532/OPARA-1109
Publisher dc.publisher	Technische Universität Bergakademie Freiberg
Licence dc.rights	Attribution 4.0 International	en
URI of the licence text dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
Specification of the discipline(s) dc.subject.classification	4::42::403::403-03
Specification of the discipline(s) dc.subject.classification	3::33::312::312-01
Title of the dataset dc.title	Sensitivity of Filter Cake Permeability to Systematic Variations in Particle Shape and Size: A Bottom-Up Stochastic Analysis
Research instruments opara.descriptionInstrument	Zeiss Xradia Versa 510
Underlying research object opara.descriptionObject.Substance	glass beads < 200 µm (B70, Sigmund Linder GmbH, Germany))
Underlying research object opara.descriptionObject.Substance	quartz sand < 300 µm (BCS211, Strobel Quarzsand GmbH, Germany)
Underlying research object opara.descriptionObject.Substance	glycerol > 98.5 wt.-% (VWR International LLC, USA)
Underlying research object opara.descriptionObject.Substance	potassium iodide > 99.9 wt.-% (Carl Roth, Germany)
Software opara.descriptionSoftware.ResourceProcessing	ZEISS Xradia XMReconstructor v16.0
Software opara.descriptionSoftware.ResourceProcessing	Python v3.9
Software opara.descriptionSoftware.ResourceProduction	ZEISS Scout and Scan v16.0
Project abstract opara.project.description	A central question in the design of filtration processes still is: what are the filtration properties of a given particle system? The state of the art, like the established Carman-Kozeny-equation, is not capable to calculate with technically sufficient accuracy the specific cake resistance or the capillary pressure distribution form a given particle size distribution. That is why there are still several empirical correlations in this field, which are only valid in a small field of definition and which therefore cannot be seen as universally valid. In the context of process simulation it is therefore not possible to implement the step from particle properties to the properties of the corresponding pore system, i.e. the corresponding filter cake. The aim of this project is the correlation of the distribution of multi-dimensional particle properties, where both the particle size and the particle shape are regarded as distributed properties, with the distribution of properties of the 3D morphology of the filter cake built up from these particles. Tortuosity and pore size are examples for distributed cake properties. For this purpose, methods from experimental process engineering are combined with digital computer-based methods. Analytical particle characterization as well as tomographic image data of the investigated particle systems and of the resulting filter cake structures serve as the basis for characterizing the particle properties and the 3D morphology of two- or three-phase filter cake structures using parametric stochastic models. On the one hand, the multi-dimensional distribution of particle property vectors (e.g. particle size and shape characteristics) and the properties of the resulting multi-phase filter cake system are modeled with parametric copula approaches. On the other hand, parametric 3D structure models are calibrated, which can then generate virtual 3D particles or multi-phase filter cake structures, so-called digital twins, that are equivalent in a statistical sense to the tomographic image data. Both copula models and 3D structure models are described with only a few parameters, which enables efficient characterization of the underlying particle and pore systems. Then regression techniques are used to determine transfer functions, which map parameters of the models describing the particle systems onto the model parameters describing the filter cake structure. In this way, it will become possible to predict the process behavior (e.g. de-watering, cake washing, dispersion) of a filter cake, solely from the knowledge of the underlying (multivariate) probability distribution of multi-dimensional particle properties.
Funding Acknowledgement opara.project.fundingAcknowledgement	The authors of this data submission thank the German Research Foundation (DFG) for funding the research project 496815304, where multivariate structure and process models for filter cake structures are developed, and for funding of the micro-CT device (INST 67/129-1).
Public project website(s) opara.project.publicReference	https://gepris.dfg.de/gepris/projekt/496815304
Project title opara.project.title	Development of multivariant structure and process models for filter cakes, combining experimental methods of process engineering with digital computer based methods