Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-4965
Publication type: | Article in scientific journal |
Type of review: | Peer review (publication) |
Title: | Procedure for experimental data assessment for numerical solver validation in the context of model based prediction of powder coating patterns |
Authors: | Siyahhan, Bercan Boldrini, Marlon Hauri, Samuel Reinke, Nils Boiger, Gernot Kurt |
DOI: | 10.21256/zhaw-4965 10.21152/1750-9548.12.4.373 |
Published in: | The International Journal of Multiphysics |
Volume(Issue): | 12 |
Issue: | 4 |
Page(s): | 373 |
Pages to: | 392 |
Issue Date: | Dec-2018 |
Publisher / Ed. Institution: | International Society of Multiphysics |
ISSN: | 1750-9548 2048-3961 |
Language: | English |
Subjects: | Model based prediction; Data assessment; Powder coating; Simulation; Experiments; Optical measurement; Numerical solver; Validation |
Subject (DDC): | 530: Physics |
Abstract: | In the scope of this study an experimental powder coating setup is designed and the method to extract statistically significant trends from the data generated is developed. The ultimate goals are to i) validate a previously developed 3D Euler-LaGrangian numerical solver and to ii) characterize the essential parameters for industrial powder coating processes in subsequent phases. The experiments involved coating a flat plate substrate with a corona spraying pistol. The resulting coating thickness has been quantified through the state of the art Coatmaster technology. The raw data generated from the Coatmaster has been filtered and rigorously analyzed to identify statistically significant trends. Furthermore, characteristic variables have been constructed for subsequent comparison to the numerical solver. This study reveals the challenges involved in assessing experimental data to extract meaningful comparisons for numerical solver validation. |
URI: | https://digitalcollection.zhaw.ch/handle/11475/14287 |
Fulltext version: | Published version |
License (according to publishing contract): | CC BY 4.0: Attribution 4.0 International |
Departement: | School of Engineering |
Organisational Unit: | Institute of Computational Physics (ICP) |
Appears in collections: | Publikationen School of Engineering |
Files in This Item:
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2018_Siyahhan_Procedure_for_experimental_data_assessment_for_numerical.pdf | 2.8 MB | Adobe PDF | View/Open |
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Siyahhan, B., Boldrini, M., Hauri, S., Reinke, N., & Boiger, G. K. (2018). Procedure for experimental data assessment for numerical solver validation in the context of model based prediction of powder coating patterns. The International Journal of Multiphysics, 12(4), 373–392. https://doi.org/10.21256/zhaw-4965
Siyahhan, B. et al. (2018) ‘Procedure for experimental data assessment for numerical solver validation in the context of model based prediction of powder coating patterns’, The International Journal of Multiphysics, 12(4), pp. 373–392. Available at: https://doi.org/10.21256/zhaw-4965.
B. Siyahhan, M. Boldrini, S. Hauri, N. Reinke, and G. K. Boiger, “Procedure for experimental data assessment for numerical solver validation in the context of model based prediction of powder coating patterns,” The International Journal of Multiphysics, vol. 12, no. 4, pp. 373–392, Dec. 2018, doi: 10.21256/zhaw-4965.
SIYAHHAN, Bercan, Marlon BOLDRINI, Samuel HAURI, Nils REINKE und Gernot Kurt BOIGER, 2018. Procedure for experimental data assessment for numerical solver validation in the context of model based prediction of powder coating patterns. The International Journal of Multiphysics. Dezember 2018. Bd. 12, Nr. 4, S. 373–392. DOI 10.21256/zhaw-4965
Siyahhan, Bercan, Marlon Boldrini, Samuel Hauri, Nils Reinke, and Gernot Kurt Boiger. 2018. “Procedure for Experimental Data Assessment for Numerical Solver Validation in the Context of Model Based Prediction of Powder Coating Patterns.” The International Journal of Multiphysics 12 (4): 373–92. https://doi.org/10.21256/zhaw-4965.
Siyahhan, Bercan, et al. “Procedure for Experimental Data Assessment for Numerical Solver Validation in the Context of Model Based Prediction of Powder Coating Patterns.” The International Journal of Multiphysics, vol. 12, no. 4, Dec. 2018, pp. 373–92, https://doi.org/10.21256/zhaw-4965.
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