scispace - formally typeset
Open AccessJournal ArticleDOI

Ueber das Zeitgesetz des kapillaren Aufstiegs von Flüssigkeiten

Richard Lucas
- 01 Jul 1918 - 
- Vol. 23, Iss: 1, pp 15-15
About
This article is published in Colloid and Polymer Science.The article was published on 1918-07-01 and is currently open access. It has received 1052 citations till now.

read more

Citations
More filters
Journal ArticleDOI

Structural evidence for the timescale separated liquid imbibition phenomenon in porous media

TL;DR: In this paper, the internal surface structure of the pore wall rugosity was modeled by nitrogen sorption, and a direct analytical correlation with the observed imbibition rate change between the short timescale and the longer timescale absorption was provided.
Book ChapterDOI

Kennzeichnung, Herstellung und Eigenschaften poröser Körper

K.-E. Zimens
TL;DR: In this paper, porosen Korpern herrschen besondere energetische and stoffliche Verhaltnisse, da die oberflachlich liegenden Bausteine unsymmetrisch gebunden und infolgedessen ihre Bindungskrafte nicht vollstandig abgesattigt sind.
Journal ArticleDOI

Computational Simulation of Spontaneous Liquid Penetration and Depression Between Vertical Parallel Plates

TL;DR: In this paper, a computational fluid dynamics model was developed to study the dynamics of meniscus formation and capillary flow between vertical parallel plates, where an arbitrary Lagrangian-Eulerian approach was employed to predict and reconstruct the shape of the maniscus with no need to employ implicit interface tracking schemes.
Journal ArticleDOI

A new multi-pore fractal model to delineate the effect of various factors on imbibition in shales

TL;DR: In this article, the pore characteristics of shale are analyzed by field emission scanning electron microscopy (FSEM) and fractal analysis, and a multi-pore fractal model is then developed for imbibition in shales, honoring capillary forces, osmotic pressure and pore structure.
Journal ArticleDOI

An artificial neural network approach to capillary rise in porous media

TL;DR: In this article, an artificial neural network was used to predict the time of capillary rise for a known given height for 15 liquids and 15 different powders, and two statistical parameters, the product moment correlation coefficient (r 2) and the performance factor (PF/3), were used to correlate the actual experimentally obtained times of capillar rise to: (i) their equivalent values as predicted by a designed and trained Artificial Neural Network; and (ii) their corresponding values as calculated by the L...