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Application of DEM-based metamodels in bulk handling equipment design: Methodology and DEM case study.

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Title: Application of DEM-based metamodels in bulk handling equipment design: Methodology and DEM case study.
Authors: Fransen, Marc P.1 (AUTHOR) m.p.fransen@tudelft.nl, Langelaar, Matthijs2 (AUTHOR), Schott, Dingena L.1 (AUTHOR)
Source: Powder Technology. Nov2021, Vol. 393, p205-218. 14p.
Subjects: Granular flow, Proof of concept
Abstract: Developments in discrete element modelling (DEM) enable detailed modelling of granular flows in bulk handling equipment (BHE) but due to the computational expense of DEM, wide use in analysing equipment performance is not yet feasible. Metamodels are a viable option to effectively use DEM in analysing BHE performance. Metamodels are able to approximate the behaviour of BHE efficiently for a wide range of design parameter values. We present a methodology to construct and validate DEM-based metamodels as well as a discharging hopper case study illustrating the use and benefits of metamodels in combination with DEM. For three different metamodels trained on a DEM data set, the results show that the metamodel quality highly depends on the number of samples and finding proper hyper-parameter values. The constructed metamodels are found capable of adequately representing the relation between performance and design parameters. It is concluded that methodically constructed metamodels are a valuable addition in describing BHE behaviour. [Display omitted] • Metamodels overcome computational expense of PBM in design exploration. • Proof of concept for three model fitting techniques applied to DEM data of a hopper. • Metamodel construction including selection, training and validation • Evaluation of metamodel reliability and accuracy for DEM data [ABSTRACT FROM AUTHOR]
Copyright of Powder Technology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 152367293
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PubType: Academic Journal
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  Data: Developments in discrete element modelling (DEM) enable detailed modelling of granular flows in bulk handling equipment (BHE) but due to the computational expense of DEM, wide use in analysing equipment performance is not yet feasible. Metamodels are a viable option to effectively use DEM in analysing BHE performance. Metamodels are able to approximate the behaviour of BHE efficiently for a wide range of design parameter values. We present a methodology to construct and validate DEM-based metamodels as well as a discharging hopper case study illustrating the use and benefits of metamodels in combination with DEM. For three different metamodels trained on a DEM data set, the results show that the metamodel quality highly depends on the number of samples and finding proper hyper-parameter values. The constructed metamodels are found capable of adequately representing the relation between performance and design parameters. It is concluded that methodically constructed metamodels are a valuable addition in describing BHE behaviour. [Display omitted] • Metamodels overcome computational expense of PBM in design exploration. • Proof of concept for three model fitting techniques applied to DEM data of a hopper. • Metamodel construction including selection, training and validation • Evaluation of metamodel reliability and accuracy for DEM data [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Powder Technology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.powtec.2021.07.048
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      – Code: eng
        Text: English
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        PageCount: 14
        StartPage: 205
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      – SubjectFull: Granular flow
        Type: general
      – SubjectFull: Proof of concept
        Type: general
    Titles:
      – TitleFull: Application of DEM-based metamodels in bulk handling equipment design: Methodology and DEM case study.
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            NameFull: Fransen, Marc P.
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            NameFull: Langelaar, Matthijs
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            NameFull: Schott, Dingena L.
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              Text: Nov2021
              Type: published
              Y: 2021
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              Value: 393
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