Quantitative characterization of hydrophobic agglomeration at different mixing intensities using a copula-based probabilistic modeling approach

The agglomeration of small poorly wetted alumina particles in a stirred tank is investigated. For different experimental conditions, two bivariate probability densities for the area-equivalent diameter and aspect ratio of primary particles and agglomerates, respectively, are determined, using 2D image data from an inline camera system. Throughout each experiment, these densities do not change since the geometries of primary particles are unaffected by the experimental conditions, while large agglomerates fragment into multiple smaller ones, which results in an equilibrium state regarding the distribution of agglomerate descriptors. Mixtures of these densities are used to model the contents of the stirred tank at each time step of the experiments. Analytical functions, whose parameters characterize the agglomeration dynamics, are fitted to the time-dependent weights of these mixtures. This enables a quantitative comparison of agglomeration processes, highlighting the impact of mixing intensity on the joint distribution of agglomerate descriptors.

Publication Details

Journal
ArXiv.org
Published
2025-03-28
Primary Topic
Cardiac electrophysiology and arrhythmias
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantitative characterization of hydrophobic agglomeration at different mixing intensities using a copula-based probabilistic modeling approach

ArXiv.org
Cardiac electrophysiology and arrhythmias
article

Quantitative characterization of hydrophobic agglomeration at different mixing intensities using a copula-based probabilistic modeling approach

article en

Abstract

The agglomeration of small poorly wetted alumina particles in a stirred tank is investigated. For different experimental conditions, two bivariate probability densities for the area-equivalent diameter and aspect ratio of primary particles and agglomerates, respectively, are determined, using 2D image data from an inline camera system. Throughout each experiment, these densities do not change since the geometries of primary particles are unaffected by the experimental conditions, while large agglomerates fragment into multiple smaller ones, which results in an equilibrium state regarding the distribution of agglomerate descriptors. Mixtures of these densities are used to model the contents of the stirred tank at each time step of the experiments. Analytical functions, whose parameters characterize the agglomeration dynamics, are fitted to the time-dependent weights of these mixtures. This enables a quantitative comparison of agglomeration processes, highlighting the impact of mixing intensity on the joint distribution of agglomerate descriptors.

ArXiv.org
Sustainable cities and communities
Openalex Percentile: Top 37%
Cardiac electrophysiology and arrhythmias
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Quantitative characterization of hydrophobic agglomeration at different mixing intensities using a copula-based probabilistic modeling approach · ArXiv.org (2025) | TGRS Research Map | TGRS