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Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation
Powder Technology, Volume: 366, Pages: 527 - 536
Swansea University Authors: Tongming QU, Yuntian Feng
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DOI (Published version): 10.1016/j.powtec.2020.02.077
Abstract
This study proposes an automated calibration procedure for bond parameters in bonded discrete element modelling. By exploring the underlying physical correlations between microscopic parameters of bonds and macroscopic strength parameters of the continuum to be modelled, the microscopic shear streng...
Published in: | Powder Technology |
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ISSN: | 0032-5910 |
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Elsevier BV
2020
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URI: | https://cronfa.swan.ac.uk/Record/cronfa53715 |
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2020-03-03T14:29:14.3386970 v2 53715 2020-03-03 Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation 1a8144ef1058bc1310206808a4d274c3 Tongming QU Tongming QU true false d66794f9c1357969a5badf654f960275 0000-0002-6396-8698 Yuntian Feng Yuntian Feng true false 2020-03-03 This study proposes an automated calibration procedure for bond parameters in bonded discrete element modelling. By exploring the underlying physical correlations between microscopic parameters of bonds and macroscopic strength parameters of the continuum to be modelled, the microscopic shear strength and tensile strength are identified as independent variables for calibration purpose. Then a physics-informed iterative scheme is proposed to automatically approximate the bond parameters by viewing the micro-macro relation as an implicitly defined mathematical mapping function. As a result of highly non-convex features of this implicit mapping, the adaptive moment estimation (Adam), which is especially suitable for problems with noisy gradients, is adopted as the basic iterative scheme, in conjunction with other numerical techniques to approximately evaluate the partial derivatives involved. The whole procedure offers a simple and effective framework for bond parameter calibration. A numerical example of SiC ceramic is provided for validation. By compared with some existing calibration methods, the proposed method shows significant advantages in terms of calibration efficiency and accuracy. Journal Article Powder Technology 366 527 536 Elsevier BV 0032-5910 Discrete element method, Parallel bond model, Automated calibration, Adaptive moment estimation, Brittle solid, Physics-informed optimisation 15 4 2020 2020-04-15 10.1016/j.powtec.2020.02.077 COLLEGE NANME COLLEGE CODE Swansea University 2020-03-03T14:29:14.3386970 2020-03-03T14:29:14.3386970 Tongming QU 1 Yuntian Feng 0000-0002-6396-8698 2 Min Wang 3 Shengqiang Jiang 4 53715__16902__6a834a272a0c41afba095639591b5a2f.pdf 53715.pdf 2020-03-24T17:22:44.6529403 Output 1513904 application/pdf Accepted Manuscript true 2021-03-02T00:00:00.0000000 Released under the terms of a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND). true eng |
title |
Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation |
spellingShingle |
Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation Tongming QU Yuntian Feng |
title_short |
Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation |
title_full |
Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation |
title_fullStr |
Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation |
title_full_unstemmed |
Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation |
title_sort |
Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation |
author_id_str_mv |
1a8144ef1058bc1310206808a4d274c3 d66794f9c1357969a5badf654f960275 |
author_id_fullname_str_mv |
1a8144ef1058bc1310206808a4d274c3_***_Tongming QU d66794f9c1357969a5badf654f960275_***_Yuntian Feng |
author |
Tongming QU Yuntian Feng |
author2 |
Tongming QU Yuntian Feng Min Wang Shengqiang Jiang |
format |
Journal article |
container_title |
Powder Technology |
container_volume |
366 |
container_start_page |
527 |
publishDate |
2020 |
institution |
Swansea University |
issn |
0032-5910 |
doi_str_mv |
10.1016/j.powtec.2020.02.077 |
publisher |
Elsevier BV |
document_store_str |
1 |
active_str |
0 |
description |
This study proposes an automated calibration procedure for bond parameters in bonded discrete element modelling. By exploring the underlying physical correlations between microscopic parameters of bonds and macroscopic strength parameters of the continuum to be modelled, the microscopic shear strength and tensile strength are identified as independent variables for calibration purpose. Then a physics-informed iterative scheme is proposed to automatically approximate the bond parameters by viewing the micro-macro relation as an implicitly defined mathematical mapping function. As a result of highly non-convex features of this implicit mapping, the adaptive moment estimation (Adam), which is especially suitable for problems with noisy gradients, is adopted as the basic iterative scheme, in conjunction with other numerical techniques to approximately evaluate the partial derivatives involved. The whole procedure offers a simple and effective framework for bond parameter calibration. A numerical example of SiC ceramic is provided for validation. By compared with some existing calibration methods, the proposed method shows significant advantages in terms of calibration efficiency and accuracy. |
published_date |
2020-04-15T07:52:52Z |
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1821391163708407808 |
score |
11.047501 |