Frederick R. Phelan

Textile composites: modelling strategies

Textile materials are characterised by the distinct hierarchy of structure, which should be represented by a model of textile geometry and mechanical behaviour. In spite of a profound investigation of textile materials and a number of theoretical models existing in the textile literature for different structures, a model covering all structures typical for composite reinforcements is not available. Hence the challenge addressed in the present work is to take full advantage of the hierarchical principle of textile modelling, creating a truly integrated modelling and design tool for textile composites. It allows handling of complex textile structure computations in computer time counted by minutes instead of hours of the same non-linear, non-conservative behaviour of yarns in compression and bending. The architecture of the code implementing the model corresponds to the hierarchical structure of textile materials. The model of the textile geometry serves as a base for meso-mechanical and permeability models for composites, which provide therefore simulation tools for analysis of composite processing and properties.

Lattice Boltzmann methods for modeling microscale flow in fibrous porous media

A lattice Boltzmann description of fluid flow in heterogeneous porous media is presented which is intended for modeling flow processes which occur in liquid composite molding applications. The lattice Boltzmann method is equivalent to solving a hybrid method of the Stokes and Brinkman equations, with the Brinkman equation being implemented to model flow through porous structures, while the Stokes equation is applied to the open regions outside the porous structures. The Brinkman equation is recovered through a modification of the particle equilibrium distribution function, which reduces the magnitude of momentum at specified lattice sites, while leaving the direction of momentum unchanged. As a test of the new lattice Boltzmann model, steady transverse flow (saturated) through a square array of porous cylinders of elliptical cross section is investigated. Cell permeabilities obtained from the lattice Boltzmann simulations are in excellent agreement with a lubrication model, validating the lattice Boltzman...

The Application of Optical Coherence Tomography to Problems in Polymer Matrix Composites

Abstract The Composites Group at the National Institute of Standards and Technology has found optical coherence tomography (OCT) to be a powerful tool for non-destructive characterization of polymer matrix composites. Composites often exhibit superior properties to traditional materials such as wood and metal. However, the barrier to their widespread infiltration into consumer markets is cost. Composites can be made more cost competitive by improved composite design, process optimization, and quality control. OCT provides a means of evaluating the three aforementioned areas. OCT is a very versatile technique that can be applied to a variety of problems in polymer composites such as: microstructure determination for permeability and mechanical property prediction, void, dry spot, and defect detection, and damage evaluation. Briefly, OCT uses a low coherence source such as a superluminescent diode laser with a fiber optic based Michelson interferometer. In this configuration, the composite is the fixed arm of the interferometer. Reflections from heterogeneities within the sample are mapped as a function of thickness for any one position. Volume information is generated by translating the sample on a motorized stage. Information about the location and size of a feature within the composite is obtained. In this work, the power of OCT for imaging composite microstructure and damage is presented. An example of permeability prediction using the composite microstructure imaged from OCT is demonstrated. The effect of image processing on the value of permeability is discussed. Using the same sample, OCT imaging of composite impact damage is compared to more traditional techniques, X-ray computed tomography and confocal microscopy.

Numerical simulation of injection/compression liquid composite molding. Part 2: Preform compression

Abstract In the injection/compression liquid composite molding process (I/C-LCM), a liquid polymer resin is injected into a partially open mold, which contains a preform of reinforcing fibers. After some or all of the resin has been injected, the mold is closed, compressing the preform and causing additional resin flow. This paper addresses compression of the preform, with particular emphasis on modeling three-dimensional mold geometries and multi-layer preforms in which the layers have different mechanical responses. First, a new constitutive relation is developed to model the mechanical response of fiber mats during compression. We introduce a new form of nonlinear elasticity for transversely isotropic materials. A special case of this form is chosen that includes the compressive stress generated by changes in mat thickness, but suppresses all other responses. This avoids the need to model slip of the preform along the mold surface. Second, a finite element method, based on the principle of virtual displacement, is developed to solve for the deformation of the preform at any stage of mold closing. The formulation includes both geometric and material nonlinearities, and uses a full Newton–Raphson iteration in the solution. An open gap above the preform can be incorporated by treating the gap as a distinct material layer with a very small stiffness. Examples show that this approach successfully predicts compression in dry preforms for three-dimensional I/C-LCM molds.

Numerical simulation of injection/compression liquid composite molding. Part 1. Mesh generation

Abstract This paper presents a numerical simulation of injection/compression liquid composite molding, where the fiber preform is compressed to a desired degree after an initial charge of resin has been injected into the mold. Due to the possibility of an initial gap at the top of the preform and out-of-plane heterogeneity in the multi-layered fiber preform, a full three-dimensional (3D) flow simulation is essential. We propose an algorithm to generate a suitable 3D finite element mesh, starting from a two-dimensional shell mesh representing the geometry of the mold cavity. Since different layers of the preform have different compressibilities, and since properties such as permeability are a strong function of the degree of compression, a simultaneous prediction of preform compression along with the resin flow is necessary for accurate mold-filling simulation. The algorithm creates a coarser mechanical mesh to simulate compression of the preform, and a finer flow mesh to simulate the motion of the resin in the preform and gap. Lines connected to the top and bottom plates of the mold, called spines, are used as conduits for the nodes. A method to generate a surface parallel to a given surface, thereby maintaining the thickness of the intermediate space, is used to construct the layers of the preform in the mechanical mesh. The mechanical mesh is further subdivided along the spines to create the flow mesh. Examples of the three-dimensional meshes generated by the algorithm are presented.

Chaotic mixing in microfluidic devices driven by oscillatory cross flow

The kinematics of oscillatory cross flow has been studied numerically as a means for generating chaotic mixing in microfluidic devices for both confined and continuous throughput flow configurations. The flow is analyzed using numerical simulation of the unsteady Navier–Stokes equations combined with tracking of single and multispecies passive tracer particles. Two characteristics of chaotic flow are demonstrated: the stretching and folding of material lines leading to particle dispersion and a positive “effective” Lyapunov exponent. The primary mechanism for the generation of chaotic flow is a periodic combination of stretching (which occurs via shear in the channels) and rotation (which occurs via the timing of the oscillations), making these systems effective tendril-whorl type flows. First, the case of confined mixing is studied. It is shown that chaotic flow is generated in a cross-cell device when sinusoidally driven, out-of-phase, perpendicular fluid streams intersect in the flow domain. Calculatio...

Shear and dilational interfacial rheology of surfactant-stabilized droplets.

A new measurement method is suggested that is capable of probing the shear and dilational interfacial rheological responses of small droplets, those of size comparable to real emulsion applications. Freely suspended aqueous droplets containing surfactant and non-surface-active tracer particles are transported through a rectangular microchannel by the plane Poiseuille flow of the continuous oil phase. Optical microscopy and high-speed imaging record the shape and internal circulation dynamics of the droplets. Measured circulation velocities are coupled with theoretical descriptions of the droplet dynamics in order to determine the viscous (Boussinesq) and elastic (Marangoni) interfacial effects. A new Marangoni-induced stagnation point is identified theoretically and observed experimentally. Particle velocimetry at only two points (including gradients) in the droplet is sufficient to determine the amplitudes of the dilational and shear responses. We investigate the sensitivity for measuring interfacial properties and compare results from droplets stabilized by a small-molecule surfactant (butanol) and those stabilized by relatively large block copolymer molecules. Future increased availability of shear and dilational interfacial rheological properties is anticipated to lead to improved rules of thumb for emulsion preparation, stabilization, and general practice.

Bayesian calibration of coarse-grained forces: Efficiently addressing transferability

Generating and calibrating forces that are transferable across a range of state-points remains a challenging task in coarse-grained (CG) molecular dynamics. In this work, we present a coarse-graining workflow, inspired by ideas from uncertainty quantification and numerical analysis, to address this problem. The key idea behind our approach is to introduce a Bayesian correction algorithm that uses functional derivatives of CG simulations to rapidly and inexpensively recalibrate initial estimates f0 of forces anchored by standard methods such as force-matching. Taking density-temperature relationships as a running example, we demonstrate that this algorithm, in concert with various interpolation schemes, can be used to efficiently compute physically reasonable force curves on a fine grid of state-points. Importantly, we show that our workflow is robust to several choices available to the modeler, including the interpolation schemes and tools used to construct f0. In a related vein, we also demonstrate that our approach can speed up coarse-graining by reducing the number of atomistic simulations needed as inputs to standard methods for generating CG forces.