DEM-bond model: A computational framework for designing mechanically enhanced polymer nanosphere-based ordered nanostructures DOI Creative Commons
Dan Chen, Zhiren Chen, Tengfang Zhang

et al.

Materials & Design, Journal Year: 2025, Volume and Issue: unknown, P. 113998 - 113998

Published: April 1, 2025

Language: Английский

Reconstruction of the solid–liquid two-phase flow field in the pipeline based on limited pipeline wall information DOI

Shengpeng Xiao,

Chuyi Wan, Hongbo Zhu

et al.

Physics of Fluids, Journal Year: 2025, Volume and Issue: 37(2)

Published: Feb. 1, 2025

Pipeline hydraulic transportation is the primary method for transporting deep-sea mineral resources and fossil fuels. blockage often causes excessive pressure in pipeline, leading to pipeline breakage or even cargo leakage, which severely impacts safety can easily trigger secondary disasters. Therefore, clarifying global flow field within pipelines, such as particle distribution, crucial monitoring controlling systems. This study uses a limited number of measurable wall sensor values inputs deep learning models reconstruction, with solid–liquid two-phase three-dimensional output. Three model frameworks from existing studies are summarized, their reconstruction effects compared. Based on this, new framework proposed. It expands low-dimensional same size using pseudo-decoder then processes them through an autoencoder. The results indicate that achieves further accuracy improvements compared previous three frameworks, R2 mean squared error reaching 0.933 5.13 ×10−4, respectively. Additionally, skip connection configuration model, dataset size, rate, well arrangement sensors accuracy, investigated. Finally, transferability demonstrated by reconstructing fluid velocity fields flow.

Language: Английский

Citations

1

The hydraulic conveying of coarse particles in pipelines: Flow characteristics and the critical non-deposition velocity DOI

Y. M. Huang,

Yuehao Sun, Zhen Chen

et al.

Physics of Fluids, Journal Year: 2025, Volume and Issue: 37(3)

Published: March 1, 2025

The hydraulic conveying of coarse solid particles in pipelines plays a critical role the design and operation deep-sea mining. In this study, computational fluid dynamics–discrete element method is employed to investigate problem numerically, based on which theoretical analyses are carried out. Numerical simulation lifting vertical pipeline reveals key characteristics particle motions, uncovers effects feed concentration, speed, size performance lifting. results also show distribution typical phenomenon velocity fluctuation, may induce pressure pulsations affecting operational safety potentially accelerate erosion practical engineering scenarios. Additionally, terms horizontal pipeline, similarity rule derived dimensional analysis theory, with new formula non-deposition established. This allows quantitative estimation from size, diameter, parameters fluid. Compared existing empirical formulations, present shows better consistency experimental data applicability broader range flow parameters. study provides support possesses reference values optimization transport mining, such as improving efficiency reducing energy consumption.

Language: Английский

Citations

0

Concentration prediction of coarse particle two-phase flow in vertical pipe transportation based on machine learning ensemble and numerical simulation methods DOI
Chuyi Wan,

Shengpeng Xiao,

Dai Zhou

et al.

Powder Technology, Journal Year: 2025, Volume and Issue: unknown, P. 120878 - 120878

Published: March 1, 2025

Language: Английский

Citations

0

DEM-bond model: A computational framework for designing mechanically enhanced polymer nanosphere-based ordered nanostructures DOI Creative Commons
Dan Chen, Zhiren Chen, Tengfang Zhang

et al.

Materials & Design, Journal Year: 2025, Volume and Issue: unknown, P. 113998 - 113998

Published: April 1, 2025

Language: Английский

Citations

0