113
Views
0
CrossRef citations to date
0
Altmetric
Articles

Heat Transfer of Aggregate in a Drying Drum Based on the Multi-Scale Model and Fluid-Solid Coupling

, &
Pages 506-517 | Received 12 Sep 2022, Accepted 11 Dec 2022, Published online: 29 Dec 2022
 

Abstract

The simulation of engineering research is difficult, especially the engineering problem of the large differences between the size of the equipment and materials processed. At present, two methods are used to solve this problem, i.e. the equal scale reduction model and the study of only a part of it, which makes it inconsistent with the actual situation. To find a better way to improve this problem, the multi-scale is introduced. In this study, the heat transfer of the particles in a drying drum with engineering size is studied by multi-scale and fluid-solid coupling methods. The general situation of the drying drum is introduced, and the fluid-solid coupling mechanism based on multi-scale is established. A method of establishing a particle micro model is proposed. The feasibility of this method is proved by simulation and experiment, and the accuracy of the proposed model is improved by 15.62% compared with the traditional model.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the science and technology project of the Zhejiang transportation department (2021011), the science and technology innovation team of Shaanxi province (2020TD0012), and the science and technology programme of the Tibet autonomous region (XZ2019TL-G-02).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 473.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.