Direct numerical simulation of complex viscoelastic flows via fast lattice-Boltzmann solution of the Fokker–Planck equation

Micro–macro simulations of polymeric solutions rely on the coupling between macroscopic conservation equations for the fluid flow and stochastic differential equations for kinetic viscoelastic models at the microscopic scale. In the present work we introduce a novel micro–macro numerical approach, where the macroscopic equations are solved by a finite-volume method and the microscopic equation by a lattice-Boltzmann one. The kinetic model is given by molecular analogy with a finitely extensible non-linear elastic (FENE) dumbbell and is deterministically solved through an equivalent Fokker–Planck equation. The key features of the proposed approach are: (i) a proper scaling and coupling between the micro lattice-Boltzmann solution and the macro finite-volume one; (ii) a fast microscopic solver thanks to an implementation for Graphic Processing Unit (GPU) and the local adaptivity of the lattice-Boltzmann mesh; (iii) an operator-splitting algorithm for the convection of the macroscopic viscoelastic stresses instead of the whole probability density of the dumbbell configuration. This latter feature allows the application of the proposed method to non-homogeneous flow conditions with low memory-storage requirements. The model optimization is achieved through an extensive analysis of the lattice-Boltzmann solution, which finally provides control on the numerical error and on the computational time. The resulting micro–macro model is validated against the benchmark problem of a viscoelastic flow past a confined cylinder and the results obtained confirm the validity of the approach

Velocity autocorrelation function of a Brownian particle

In this article, we present molecular dynamics study of the velocity autocorrelation function (VACF) of a Brownian particle. We compare the results of the simulation with the exact analytic predictions for a compressible fluid from [6] and an approximate result combining the predictions from hydrodynamics at short and long times. The physical quantities which determine the decay were determined from separate bulk simulations of the Lennard-Jones fluid at the same thermodynamic state point.We observe that the long-time regime of the VACF compares well the predictions from the macroscopic hydrodynamics, but the intermediate decay is sensitive to the viscoelastic nature of the solvent.Comment: 7 pages, 6 figure

A Lagrangian-Eulerian simulation framework for viscoelastic fluid flows

Viscoelastic fluids appear in various industrial applications, including adhesive application, additive manufacturing, seam sealing and parts assembly with adhesive. These processes are characterized by complex geometry, moving objects and transient multiphase flow, making them inherently difficult to simulate numerically. Furthermore, substantial amount of work is typically necessary to setup simulations and the simulation times are often unfeasible for practical use.In this thesis a new Lagrangian-Eulerian numerical method for viscoelastic flow is proposed. The viscoelastic constitutive equation is solved in the Lagrangian frame of reference, while the momentum and continuity equations are solved on an adaptive octree grid with the finite volume method. Interior objects are modeled with implicit immersed boundary conditions. The framework handles multiphase flows with complex geometry with minimal manual effort. Furthermore, compared to other Lagrangian methods, no re-meshing due to grid deformation is necessary and a relatively small amount of Lagrangian nodes are required for accurate and stable results. No other stabilization method than both sides diffusion is found necessary. The new method is validated by numerical benchmarks which are compared to analytic solutions as well as numerical and experimental data from the literature. The method is implemented both for CPU computation and in a hybrid CPU-GPU version. A substantial increase in simulation speed is found for the CPU-GPU implementation. Finally, an industrially suitable model for swirl adhesive application is proposed and evaluated. The results are found to be in good agreement with experimental adhesive geometries

Computationally efficient viscoelastic flow simulation using a Lagrangian-Eulerian method and GPU-acceleration

A recently proposed Lagrangian-Eulerian method for viscoelastic flow simulation is extended to high performance calculations on the Graphics Processing Unit (GPU). The two most computationally intensive parts of the algorithm are implemented for GPU calculation, namely the integration of the viscoelastic constitutive equation at the Lagrangian nodes and the interpolation of the resulting stresses to the cell centers of the Eulerian grid. In the original CPU method, the constitutive equations are integrated with a second order backward differentiation formula, while with the proposed GPU method the implicit Euler method is used. To allow fair comparison, the latter is also implemented for the CPU. The methods are validated for two flows, a planar Poiseuille flow of an upper-convected Maxwell fluid and flow past a confined cylinder of a four-mode Phan Thien Tanner fluid, with identical results. The calculation times for the methods are compared for a range of grid resolutions and numbers of CPU threads, revealing a significant reduction of the calculation time for the proposed GPU method. As an example, the total simulation time is roughly halved compared to the original CPU method. The integration of the constitutive equation itself is reduced by a factor 50 to 250 and the unstructured stress interpolation by a factor 15 to 60, depending on the number of CPU threads used

Spectral Ewald Acceleration of Stokesian Dynamics for polydisperse suspensions

In this work we develop the Spectral Ewald Accelerated Stokesian Dynamics (SEASD), a novel computational method for dynamic simulations of polydisperse colloidal suspensions with full hydrodynamic interactions. SEASD is based on the framework of Stokesian Dynamics (SD) with extension to compressible solvents, and uses the Spectral Ewald (SE) method [Lindbo & Tornberg, J. Comput. Phys. 229 (2010) 8994] for the wave-space mobility computation. To meet the performance requirement of dynamic simulations, we use Graphic Processing Units (GPU) to evaluate the suspension mobility, and achieve an order of magnitude speedup compared to a CPU implementation. For further speedup, we develop a novel far-field block-diagonal preconditioner to reduce the far-field evaluations in the iterative solver, and SEASD-nf, a polydisperse extension of the mean-field Brownian approximation of Banchio & Brady [J. Chem. Phys. 118 (2003) 10323]. We extensively discuss implementation and parameter selection strategies in SEASD, and demonstrate the spectral accuracy in the mobility evaluation and the overall $\mathcal{O}(N\log N)$ computation scaling. We present three computational examples to further validate SEASD and SEASD-nf in monodisperse and bidisperse suspensions: the short-time transport properties, the equilibrium osmotic pressure and viscoelastic moduli, and the steady shear Brownian rheology. Our validation results show that the agreement between SEASD and SEASD-nf is satisfactory over a wide range of parameters, and also provide significant insight into the dynamics of polydisperse colloidal suspensions.Comment: 39 pages, 21 figure

A Lagrangian-Eulerian simulation method for viscoelastic flows applied to adhesive joining

Viscoelastic flows are important for many industrial processes, such as adhesive joining, polymer extrusion and additive manufacturing. Numerical simulations enable virtual evaluation and product realization, which can support the design phase and reduce the amount of costly physical testing. However, such applications are challenging to simulate. Thus, efficient, robust and user-friendly simulation methods are needed. In this thesis, a Lagrangian--Eulerian simulation framework for viscoelastic flow is presented. The constitutive equation is solved at Lagrangian nodes, convected by the flow, while the momentum and continuity equations are discretized with the finite volume method. The volume of fluid method is used to model free-surface flow, with an injection model for extrusion along arbitrary nozzle paths. The solver combines an automatic and adaptive octree background grid with implicit immersed boundary conditions. In contrast to boundary-conformed mesh techniques, the framework handles arbitrary geometry and moving objects efficiently. Furthermore, novel coupling methods between the Lagrangian and Eulerian solutions as well as unique treatment of the Lagrangian stresses at the fluid-fluid interface are developed. Consequently, the resulting method can simulate the complex flows associated with the intended applications, without the need for advanced stabilization techniques. The framework is validated for a variety of flows, including relevant benchmarks as well as industrial adhesive joining applications. The latter includes robot-carried adhesive extrusion onto a car fender as well as a hemming application. The results agree with the available experimental data. As such, the research presented in this thesis can contribute to enable virtual process development for joining applications

Multi-scale modeling of complex fluids and deformable fibrous media for liquid composite molding

In the last few years, the interest of the aerial and terrestrial transport industry in the fabrication of textile-reinforced composite materials has sensibly grown. This is basically due to the remarkable properties of these materials, which combine high mechanical strength with reduced weight. The manufacturing techniques that provide better control on the final quality of the components rely on autoclave curing: heat and pressure are applied on vacuum bags to achieve high volume fractions of the reinforcement and low number of defects due to the presence of voids. Nevertheless, autoclave curing implies high costs for the acquisition of the vessel and the process is energy and time consuming. To reduce the production costs, the industry has increased its interest in out-of-autoclave processing technologies, that is, liquid composite molding (LCM) techniques. In its most basic version, the technique consists in the injection of a catalyzed resin into a closed cavity, where a pre-placed fiber stack lies. When the resin has completely permeated the preform, the mold is subject to high temperatures to induce the curing of the resin to obtain the composite. The current challenge for this technology is to achieve the same quality standards for the final component as those achievable with in-autoclave processing. In LCM processes, the final quality of the component depends on several factors, such as: the structure of the textile, the arrangement of the layers, the adaption to the mold, the compaction process, the operating conditions, the geometry of the component, the configuration of the injection points for the resin, the physical and chemical interactions between the resin and the textile. All these factors affect the correct saturation of the reinforcement, and therefore process parameters must be adequately controlled in order to guarantee the required quality standards for the composite. In this sense, mold filling simulation software is a valuable tool for the process optimization; however the permeability of the reinforcement is required as an input parameter. An accurate evaluation of the permeability of the reinforcement however, represents a challenging task. Fibrous preforms for LCM generally present a hierarchical structure: the fibers are bunched in yarns, which in turn are bundled in a fabric. This structure, undergoes complex deformations during the production process: 1) during the compaction in the mold and 2) during the injection of the resin. This issue remarkably complicates an accurate evaluation of the permeability of the reinforcement and may be at the origin of the scatter observed in the experimental measurements. From a modeling point of view, the different length scales to be taken into account (typically ranging between one and three orders of magnitude) hinders a proper simulation of the deformation of the textile. The typical diameter of the fibers ranges indeed in few micrometers, while the characteristic dimension of the yarns is in the order of the millimeter. This issue represents a constraint for standard numerical approaches due to computational limits. In order to account for the effect on the permeability of the deformation of the hierarchical structure of the preform, multi-scale modeling techniques must be adopted. The objective of the thesis is the development of novel theoretical and numerical frameworks to account for the effect on the permeability of the multi-scale deformations that the textile undergoes during the two aforementioned stages of the process. The development focuses on the fiber-yarn level in 2D, where the yarn is always modeled as suspension of fibers by analogy with a complex fluid. The numerical implementations use computational fluid dynamic (CFD) tools. In order to address the problem, the permeability of a textile preform for LCM is first analyzed by experimental means. A standard CFD approach is then adopted for the simulation of a representative elementary volume of the textile; it is shown that, by means of this approach, the experimental permeability cannot be recovered over the full range of porosities. An X-ray computed microtomography of the textile is then performed. The obtained data are used for the virtual reconstruction of the exact geometry of the textile after its use for LCM. The simulations with this latter geometry provide better results; however the uncertainties on permeability still hold, and the permeability is always overestimated. These uncertainties are discussed in detail and motivate the work described hereafter. The first modeling block of the thesis concerns the analysis of the deformation that the textiles undergo during the compaction in the mold. A continuum model is first developed and validated for the squeeze flow of epoxy-based materials, the rheology of which is given by a viscoplastic constitutive law. The model is then applied to the compaction of yarns, where a viscoplastic behavior for the fiber bundle is assumed in the quasi-static regime of compression and by an analogy with flowing granular media. The rheological parameters are obtained from experimental data by a simplified analytical model for the deformation of the yarns under compaction. The commercial CFD code ANSYS Fluent is adopted for the numerical solution. The model yields information about the evolution of the fiber volume fraction during the compaction and is found to correctly recover the experimental force for high compression ratios. The second modeling block of the thesis concerns the analysis of the deformation that the textiles undergo during the injection of the resin. A numerical framework is first developed and validated for the direct numerical simulation of dilute colloidal suspensions of polymeric molecules. The numerical method consists in a coupled finite-volume/lattice-Boltzmann solution: finite volume method for hydrodynamics and lattice Boltzmann method for the sub-grid-scale physics. For computational efficiency, the lattice Boltzmann solution is accelerated on a graphic processing unit (GPGPU) with a tailored implementation and efficiently coupled with the macroscopic solver (ANSYS Fluent). The numerical method is then exploited for the solution of a mesoscopic model for the flow-induced fiber dynamics during the injection. A statistical model for the fiber dynamics is derived, based on analogy of the yarn with a non-Brownian suspension of particles with confining potentials. The fiber topology during the injection is recovered by a topological invariant and yields information about the change in permeability due to the clustering of fibers in steady-state, fully-saturated conditions. The results are presented in the form of phase diagrams, which show that in the deformable case the permeability can be up to one order of magnitude lower than in the rigid case. On the basis of the results obtained, the following main conclusions can be drawn: 1. The model developed for the compaction in the mold showed to be appropriate for a phenomenological analysis of the deformation of the yarns under compression. The model allows to analyze quantitatively the evolution of the fiber volume fraction, which yields useful information for a better understanding of the distribution of the fibers before the injection. 2. The model developed for the fiber dynamics during the injection, allows to analyze their topology induced by the fluid flow. The clustering of fibers significantly reduces the permeability at the fiber level, which could explain the overestimation obtained with simplified numerical approaches. The phase diagrams obtained for the permeability, both at the yarn and fiber level, allow to identify the best operating conditions for the infiltration of the resin. The proposed models have been developed using fluid dynamic techniques, which opens the possibility for a unified framework for the analysis, and ultimately, for a more precise estimation of the permeability. This work aims to represent a first tentative in this direction