Modeling and Simulation of the Penetration of a Compound Droplet into a Throat in a Pore-Throat Structure
PHYSICS OF FLUIDS(2023)
Xi An Jiao Tong Univ
Abstract
We present a theoretical and numerical study of a compound droplet flowing through a single pore-throat structure. By quantifying the capillary pressures in the pore and throat under various geometrical conditions, we derive a theoretical model to predict whether the compound droplet is able to penetrate into the throat in a pore-throat structure. Meanwhile, the lattice Boltzmann simulations are conducted to assess the capability and accuracy of the theoretical model. Through a combination of theoretical analysis and lattice Boltzmann simulations, we then investigate the effect of inner droplet size, compound droplet size, and surface wettability on the invasion behavior of a compound droplet. The results show that with increasing the inner droplet size or the compound droplet size, the compound droplet undergoes the transition from the state where the entire compound droplet can pass through the throat to the state where only a part of outer droplet penetrates into and blocks the throat. Although the theoretical predictions show good agreement with the simulation results for most of the cases investigated, it is found that the proposed theoretical model is not applicable to the cases in which the droplets are intermediate-wetting or wetting to the solid surface. This is because the shape of newly formed interface in the pore significantly deviates from the initial circle, which violates the assumption made in the derivation of the theoretical model.
MoreTranslated text
Key words
Lattice Boltzmann Method
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined