Morais Flávia P, Curto Joana M R
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, Portugal.
Heliyon. 2022 May 2;8(5):e09356. doi: 10.1016/j.heliyon.2022.e09356. eCollection 2022 May.
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.
全球对生活用纸需求的不断增长促使造纸行业寻找新方法来优化原材料配料管理，同时提高生活用纸性能。柔软度、强度和吸水性是提升行业和消费者关注度的关键生活用纸性能。纤维形态、纤维改性工艺步骤和结构性能会影响这些功能特性，因此，评估这些特性并建立描述它们的关系或模型的工作构成了一项多因素挑战。为此，我们旨在研究输入变量（形态、悬浮液和结构特性）与最终性能之间的权衡。我们考虑了关键变量，如配料原材料的类型，包括纤维混合物、机械和酶处理、添加剂添加以及工业基础生活用纸的类型。为了建立这些关系，我们使用了不同的数据驱动建模方法，包括多元线性回归（MLR）、人工神经网络（ANN）和基于三维纤维的模拟器。MLR和ANN模型是通过从实验设计中收集的数据建立的，制备了各向同性实验室结构并测试其结构和功能特性的变化。此外，使用基于三维纤维的模拟器研究纤维对结构性能的影响。这些结果表明，逼真的预测使我们能够将纤维和组织结构特征联系起来。总之，这项工作表明，这种计算建模方法可用于模拟纤维浆参数对最终生活用纸使用性能的影响，从而设计创新的生活用纸产品。
