Challenges in computational materials modelling and simulation: A case-study to predict tissue paper properties
The growing demand for tissue papers worldwide encourages the paper industry to find new approaches to optimize the raw materials furnish management, and simultaneously to improve tissue paper performance. Softness, strength, and absorption are the key tissue properties that enhance the attention of...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-05-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844022006442 |
| _version_ | 1828337552113795072 |
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| author | Flávia P. Morais Joana M.R. Curto |
| author_facet | Flávia P. Morais Joana M.R. Curto |
| author_sort | Flávia P. Morais |
| collection | DOAJ |
| description | The growing demand for tissue papers worldwide encourages the paper industry to find new approaches to optimize the raw materials furnish management, and simultaneously to improve tissue paper performance. Softness, strength, and absorption are the key tissue properties that enhance the attention of both industry and consumers. Fiber morphology, fiber modification process steps, and structural properties affect these functional properties, and, therefore, the efforts to evaluate them and establish the relationship or models that describe them constitute a multifactorial challenge. For this purpose, we aimed to investigate the trade-off between the input variables (morphological, suspension, and structural properties) and the final properties. Key variables like the type of furnish raw materials, including the fiber mixture, mechanical and enzymatic treatments, additives incorporation, and the type of industrial base tissue papers were taken under consideration. To achieve these relationships, we used different data-driven modeling approaches including multiple linear regression (MLR), artificial neural networks (ANN), and a 3D fiber-based simulator. The MLR and ANN models were built by data collected from an experimental design, and isotropic laboratory structures were prepared and tested for changes in structural and functional properties. Moreover, a 3D fiber-based simulator was used to investigate the influence of fibers on structural properties. These results indicated that the realistic predictions enabled us to link fiber and tissue structure characteristics. In conclusion, this work has revealed that this computational modeling approach can be used to model the effect of fiber pulps parameters with final end-use tissue properties, allowing to design innovative tissue products. |
| first_indexed | 2024-04-13T22:16:52Z |
| format | Article |
| id | doaj.art-d475296e6b6e404685f1811c3fbcce33 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-13T22:16:52Z |
| publishDate | 2022-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-d475296e6b6e404685f1811c3fbcce332022-12-22T02:27:30ZengElsevierHeliyon2405-84402022-05-0185e09356Challenges in computational materials modelling and simulation: A case-study to predict tissue paper propertiesFlávia P. Morais0Joana M.R. Curto1Fiber Materials and Environmental Technologies (FibEnTech-UBI), Universidade da Beira Interior, R. Marquês de D’Ávila e Bolama, 6201-001, Covilhã, Portugal; Corresponding author.Fiber Materials and Environmental Technologies (FibEnTech-UBI), Universidade da Beira Interior, R. Marquês de D’Ávila e Bolama, 6201-001, Covilhã, Portugal; Chemical Process Engineering and Forest Products Research Centre (CIEPQPF), University of Coimbra, R. Sílvio Lima, Polo II, 3004-531, Coimbra, PortugalThe growing demand for tissue papers worldwide encourages the paper industry to find new approaches to optimize the raw materials furnish management, and simultaneously to improve tissue paper performance. Softness, strength, and absorption are the key tissue properties that enhance the attention of both industry and consumers. Fiber morphology, fiber modification process steps, and structural properties affect these functional properties, and, therefore, the efforts to evaluate them and establish the relationship or models that describe them constitute a multifactorial challenge. For this purpose, we aimed to investigate the trade-off between the input variables (morphological, suspension, and structural properties) and the final properties. Key variables like the type of furnish raw materials, including the fiber mixture, mechanical and enzymatic treatments, additives incorporation, and the type of industrial base tissue papers were taken under consideration. To achieve these relationships, we used different data-driven modeling approaches including multiple linear regression (MLR), artificial neural networks (ANN), and a 3D fiber-based simulator. The MLR and ANN models were built by data collected from an experimental design, and isotropic laboratory structures were prepared and tested for changes in structural and functional properties. Moreover, a 3D fiber-based simulator was used to investigate the influence of fibers on structural properties. These results indicated that the realistic predictions enabled us to link fiber and tissue structure characteristics. In conclusion, this work has revealed that this computational modeling approach can be used to model the effect of fiber pulps parameters with final end-use tissue properties, allowing to design innovative tissue products.http://www.sciencedirect.com/science/article/pii/S24058440220064423D fiber-based simulatorArtificial neural networkMultiple linear regressionTissue functional propertiesTissue paper materials |
| spellingShingle | Flávia P. Morais Joana M.R. Curto Challenges in computational materials modelling and simulation: A case-study to predict tissue paper properties Heliyon 3D fiber-based simulator Artificial neural network Multiple linear regression Tissue functional properties Tissue paper materials |
| title | Challenges in computational materials modelling and simulation: A case-study to predict tissue paper properties |
| title_full | Challenges in computational materials modelling and simulation: A case-study to predict tissue paper properties |
| title_fullStr | Challenges in computational materials modelling and simulation: A case-study to predict tissue paper properties |
| title_full_unstemmed | Challenges in computational materials modelling and simulation: A case-study to predict tissue paper properties |
| title_short | Challenges in computational materials modelling and simulation: A case-study to predict tissue paper properties |
| title_sort | challenges in computational materials modelling and simulation a case study to predict tissue paper properties |
| topic | 3D fiber-based simulator Artificial neural network Multiple linear regression Tissue functional properties Tissue paper materials |
| url | http://www.sciencedirect.com/science/article/pii/S2405844022006442 |
| work_keys_str_mv | AT flaviapmorais challengesincomputationalmaterialsmodellingandsimulationacasestudytopredicttissuepaperproperties AT joanamrcurto challengesincomputationalmaterialsmodellingandsimulationacasestudytopredicttissuepaperproperties |