Nazih Assaad Al Ayoubi , Hugues Digonnet , Luisa Silva , Christophe Binetruy , Thierry Renault , Sebastien Comas-Cardona
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引用次数: 0
Abstract
This work aims to introduce a groundbreaking approach by directly computing the Fokker–Planck equation, providing a mesoscopic scale orientation indicator based on the 2D-probability density function (PDF) of the fibers’ orientation state. Unlike conventional methods that rely on pre-averaged quantities and closure approximations, our method offers enhanced accuracy and information preservation. The model’s enhanced accuracy can be served as a foundational tool for future studies, enabling the development of comprehensive models describing the fluid-flow coupling problem with precision. Consequently, this advancement facilitates the simulation of real-case scenarios, such as the dynamic motion of fibers during the injection phase of molten thermoplastics within a mold cavity. The novelty of this work lies in its application of the Streamline-Upwind/Petrov–Galerkin (SUPG) finite element method, on both orientation and physical spaces. Our model shows the potential to improve the understanding and prediction of fiber behavior in industrial applications, offering valuable insights into process optimization and design. Implemented within a finite element framework, a comprehensive investigation is conducted into the effects of mesh refinement, time scheme, and time stepping on the computational modeling of the PDF evolution, aiming to strike an optimal balance between model precision and computational efficiency. The validation tests were conducted for the case of simple shear flow to examine the influence of the interaction coefficient and the fiber shape factor on the resolution of the probability distribution function. The numerical results demonstrate the evolution of fiber orientation over time under Poiseuille flow conditions.
这项工作旨在引入一种开创性的方法,通过直接计算福克-普朗克方程,提供基于纤维取向状态的二维概率密度函数(PDF)的中观尺度取向指标。与依赖预平均量和闭合近似值的传统方法不同,我们的方法具有更高的精度和信息保存能力。该模型精度的提高可作为未来研究的基础工具,从而开发出精确描述流体-流动耦合问题的综合模型。因此,这一进步有助于模拟实际情况,如熔融热塑性塑料在模腔内注射阶段纤维的动态运动。这项工作的新颖之处在于将流线-上风/Petrov-Galerkin(SUPG)有限元方法应用于定向和物理空间。我们的模型显示了在工业应用中提高对纤维行为的理解和预测的潜力,为工艺优化和设计提供了宝贵的见解。我们在有限元框架内对网格细化、时间方案和时间步长对 PDF 演化计算建模的影响进行了全面研究,旨在实现模型精度和计算效率之间的最佳平衡。在简单剪切流的情况下进行了验证测试,以检验相互作用系数 CI 和纤维形状系数 λ 对概率分布函数分辨率的影响。数值结果表明了在波瓦流条件下纤维取向随时间的演变。
期刊介绍:
The Journal of Non-Newtonian Fluid Mechanics publishes research on flowing soft matter systems. Submissions in all areas of flowing complex fluids are welcomed, including polymer melts and solutions, suspensions, colloids, surfactant solutions, biological fluids, gels, liquid crystals and granular materials. Flow problems relevant to microfluidics, lab-on-a-chip, nanofluidics, biological flows, geophysical flows, industrial processes and other applications are of interest.
Subjects considered suitable for the journal include the following (not necessarily in order of importance):
Theoretical, computational and experimental studies of naturally or technologically relevant flow problems where the non-Newtonian nature of the fluid is important in determining the character of the flow. We seek in particular studies that lend mechanistic insight into flow behavior in complex fluids or highlight flow phenomena unique to complex fluids. Examples include
Instabilities, unsteady and turbulent or chaotic flow characteristics in non-Newtonian fluids,
Multiphase flows involving complex fluids,
Problems involving transport phenomena such as heat and mass transfer and mixing, to the extent that the non-Newtonian flow behavior is central to the transport phenomena,
Novel flow situations that suggest the need for further theoretical study,
Practical situations of flow that are in need of systematic theoretical and experimental research. Such issues and developments commonly arise, for example, in the polymer processing, petroleum, pharmaceutical, biomedical and consumer product industries.