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A discrete geometric approach for simulating the dynamics of thin viscous threads (1202.4971v2)

Published 22 Feb 2012 in physics.flu-dyn, cs.CG, math.DG, and nlin.PS

Abstract: We present a numerical model for the dynamics of thin viscous threads based on a discrete, Lagrangian formulation of the smooth equations. The model makes use of a condensed set of coordinates, called the centerline/spin representation: the kinematical constraints linking the centerline's tangent to the orientation of the material frame is used to eliminate two out of three degrees of freedom associated with rotations. Based on a description of twist inspired from discrete differential geometry and from variational principles, we build a full-fledged discrete viscous thread model, which includes in particular a discrete representation of the internal viscous stress. Consistency of the discrete model with the classical, smooth equations is established formally in the limit of a vanishing discretization length. The discrete models lends itself naturally to numerical implementation. Our numerical method is validated against reference solutions for steady coiling. The method makes it possible to simulate the unsteady behavior of thin viscous jets in a robust and efficient way, including the combined effects of inertia, stretching, bending, twisting, large rotations and surface tension.

Citations (853)

Summary

  • The paper presents a discrete geometric model that reduces simulation complexity by using a centerline/spin representation.
  • It employs a Lagrangian formulation with discrete differential geometry to accurately capture strain rates and internal stresses.
  • The robust numerical scheme shows linear convergence and reliably replicates both steady and non-steady viscous thread dynamics.

A Discrete Geometric Approach for Simulating the Dynamics of Thin Viscous Threads

The paper presents an innovative numerical model for simulating the dynamics of thin viscous threads through a discrete geometric approach. This model, grounded in a Lagrangian formulation, promises to offer an effective framework for capturing the intricate behaviors encountered in various industrial processes and natural phenomena where thin viscous threads play a crucial role.

Context and Motivation

The simulation of thin viscous threads is essential for multiple critical applications, from industrial fiber drawing to understanding natural phenomena like lava formation. Traditional models often grapple with the complex, nonlinear and high-dimensional nature of the governing partial differential equations (PDEs). This research seeks to advance beyond existing limitations by introducing a condensed coordinate system termed the centerline/spin representation, which reduces computational degrees of freedom and enhances stability.

Model Formulation

The proposed model is built upon a meticulous Lagrangian formulation, employing discrete differential geometry principles. The centerline/spin representation forms the backbone of this approach, where the dynamic properties are formulated in terms of a reduced set of coordinates. This representation elegantly connects the centerline's tangent with the material frame, thus eliminating two out of three degrees of rotational freedom. This kinematical constraint is exploited to simplify the inherent complexity of the problem while ensuring numerical stability and consistency with smooth equations in the vanishing discretization limit.

Numerical Implementation

The paper meticulously details the transition from smooth to discrete formulations, ensuring that essential physical quantities such as strain rates and internal stresses are adequately represented in the discrete setting. A key highlight is the introduction of a robust space discretization scheme which aligns well with geometric principles, specifically using the concept of parallel transport to define twist in the discrete field. The explicit expressions for discrete strain rates and their incorporation into Rayleigh potentials underscore the model's innovative blend of geometry and physics.

Validation and Results

The practical efficacy of the model is demonstrated through extensive validation against known reference solutions such as steady coiling behavior, a haLLMark problem in fluid dynamics. The simulations indicate excellent agreement with established results, particularly in replicating the coiling radius dependency on fall height, including capturing subtle bifurcation phenomena. A rigorous convergence paper further strengthens the credibility of the proposed method, showcasing linear convergence with mesh refinement and time step reduction.

Moreover, the model's capability to handle non-steady dynamics is evidenced through the simulation of complex transient phenomena and the fluid-mechanical sewing machine setup. This latter example, involving a thread impacting a moving surface, underscores the method's adeptness at capturing intricate patterns and dynamic transitions, thus showcasing the model's robustness and versatility.

Implications and Future Directions

The implications of this research are vast. Practically, the model presents a reliable tool for engineering applications involving fiber drawing, viscous coiling, and other processing techniques where predictive simulations are crucial. Theoretically, the blend of discrete differential geometry with fluid dynamics paves the way for novel approaches in modeling other slender body phenomena, potentially extending to viscoelastic fluids or incorporating non-Newtonian behavior.

Looking forward, there is ample scope to enhance the model by integrating more complex boundary interactions and coupling with multi-physics processes such as heat transfer. Exploring adaptive meshing techniques further can also help in efficiently handling severe stretching or localized phenomena without compromising on computational efficiency.

Conclusion

This paper introduces a sophisticated numerical model that marks a significant step in the simulation of thin viscous threads, leveraging the power of discrete geometric techniques to address long-standing challenges in stability and computational demand. Through detailed formulation, rigorous validation, and insightful numerical experiments, the research lays a robust foundation for future advancements and applications in both industrial and natural settings.