The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Large scale industrial DEM modelling
Abstract
Particle scale simulation of industrial particle flows using discrete element method (DEM) offers the opportunity for better understanding the flow dynamics leading to improvements in equipment design and operation that can potentially lead to large increases in equipment and process efficiency, throughput and/or product quality. Industrial applications can be characterized as large, involving complex particulate behaviour in typically complex geometries. In this paper, with a series of examples, we will explore the breadth of large scale modelling of industrial processes that is currently possible. Few of these applications will be examined in more detail to show how insights into the fundamentals of these processes can be gained through DEM modelling. Some examples of our collaborative validation efforts will also be described.
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Citations
Cites
A discrete numerical model for granular assemblies
Cundall, P. A., & Strack, O. D. L. (1979) · Géotechnique · doi:10.1680/geot.1979.29.1.47 · Cited by 17,527
Cited by
A method to model realistic particle shape and inertia in DEM
Ferellec, J.-F., & McDowell, G. R. (2010) · Granular Matter · doi:10.1007/s10035-010-0205-8 · Cited by 295
Cleary, P. W., & Serizawa, Y. (2019) · Applied Mathematical Modelling · doi:10.1016/j.apm.2018.12.024 · Cited by 13
Self-citation
Metadata
- Authors
- Cleary, P. W.
- Venue
- Engineering Computations
- Publisher
- Emerald
- Published
- 2004-03-01
- Volume
- 21
- Issue
- 2/3/4
- Pages
- 169-204
- ISSN
- 0264-4401 (ISSN-L)
- OpenAlex
- W2145015510
- Cited by
- 350
- References
- 1
- FWCI
- 7.19
- Type
- journal article
- Language
- en
- Open access
- closed
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- Cleary, P. W. (2004). Large scale industrial DEM modelling. Engineering Computations. https://doi.org/10.1108/02644400410519730
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
