Numerical investigations on a yarn structure at the microscale towards scale transition
Introduction
Dry fabrics comprised of high performance materials as Kevlar, Spectra, Zylon and Twaron have been largely adopted in protection systems due to their high penetration resistance and high strength to weight ratio. Some of applications include protecting clothing and containment systems for jet engines.
The outstanding performances of these materials in impact applications are directly related to a large number of parameters which includes fibres mechanical behaviour, weaving type and fibres reciprocal interaction. The energy absorbed by a fabric during an impact could be attributed to a large number of phenomena as fabric acceleration, fabric deformation, friction dissipation by yarn-to-yarn or fiber-to-fibre interactions. All these aspects cannot be individually evaluated using experimental approaches, which are restricted to the evaluation of macroscopic phenomena as penetration or projectile residual speed.
Since their first applications, numerical simulations turned to be a powerful tool to understand and to evaluate mechanical behaviour of dry fabrics under ballistic impact.
Some models assumed the fabric as an homogeneous medium [1], [2], [3], [4] while others were based on a mesoscale representation of the structure [5], [6], [7], [8], [9], [10].
In the first case, the computational efficiency is preferred to the model accuracy. The discrete nature of the fabric here is not addressed and capturing phenomena as yarn pull-out, individual yarn breakage or inter-yarn friction dissipation becomes difficult or impossible.
In the second case, fabric architecture is explicitly modelled. Representing the yarn individually, it is possible to have a more realistic description of the failure mechanisms near the impact zone and evaluate the effect of yarns interaction.
More recently fibre-level modelling has been adopted for an entire fabric or a part of it [11], [12], [13], [14]. Since their high computational requirement, these last models are only justified when microscopic effects, as fibre–fibre interaction or yarn section rearrangement, would be tracked.
The original approach, denoted Digital Element Method, was developed by Wang et al. to simulate weaving processes [15], [16], [17]. This method was successively improved by different authors [18], [19] and finally extended to impact applications [11], [14]. In this specific approach, yarns are modelled as a group of “Digital Fibres”. The term “Digital” refers to the fibres section which is larger than reality.
Each “Digital Fibre” was discretized as a sequence of pin-joined trusses while their transversal behaviour was included in the contact model. Usually, a coarse discretization (few dozen of Digital Fibres) was adopted for each yarn.
This method shows considerable improvements in results and phenomena description compared to the mesoscale models, however it relies on some hypotheses that still have to be verified:
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an elastic equivalence between Digital Fibres and real fibres was established only in longitudinal direction and no information was provided concerning their transverse mechanical behavior as well as the mechanical contact law among fibres. However, it has been demonstrated that inter-fibres contact plays an important role during an impact [12];
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optimum number of Digital Fibers was obtained by a convergence study on the ballistic performance of the whole fabric. This equivalence could fall if the mechanical response of a single yarn is analysed, as the yarns resultant mechanical behaviour is influenced by their reciprocal interaction within the fabrics.
More recently Nilakantan and Sockalingam [13], [20], [21] approached the filament-level modelling in a more radical way. In these works, a single yarn submitted to transverse impact is analysed. Each fiber of the yarn was considered and modelled using 3D Finite Elements, in order to describe accurately their transverse behaviour. Contact, friction and material anisotropy were considered too. The role of different parameters as fibres transversal stiffness, shear modulus and friction on yarn ballistic performance was exploited. The high computational time, given by the large number of degrees of freedom involved in the simulation, is one of the major drawback of this method. In this work, the same test performed by Nilakantan is reproduced using a revisited version of the Discrete Element Method (DEM) [22]. As in Digital Element Method, each fibre is discretized as a pin-joined sequence of truss elements. However, three main points differentiate it from the works by Wang:
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contact is evaluated using a particle-based approach;
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the multifilament analysis concerns a single yarn instead of a fabric;
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all the 400 fibres are explicitly modeled.
Results of the simulation are then compared to those presented by Nilakantan [13], in order to validate the proposed approach. In the final part a multiscale approach based on the Digital Element Formulation is presented. A comparison between the proposed real scale model and its equivalent “Digital Fibres” model is finally discussed.
Section snippets
Test set up
The model consists in a 25.4 mm length Kevlar KM2 600 single yarn clamped at the extremities (Fig. 1) and impacted transversally in the centre by a cylindrical projectile. As in [13], all the 400 filaments which compose the yarn are modelled. Fibres are assumed to be straight and circular with an constant diameter equal to 12 μm. A cylindrical projectile with a mass of 9.91 mg is located in the centre of the yarn with contact condition at the initial time. Its specific dimensions are a height
Discrete Element Approach
It has been demonstrated that fabric ballistic performances are strongly influenced by parameters involved in contact mechanisms [25], [26], [27], [12], then it should be carefully treated in these numerical models. In order to deal efficiently with contact mechanic, a revisited version of the Discrete Element Method (DEM) inspired by the models developed by Wang [11] hereafter is proposed. Discrete Element Method was firstly developed for simulation of granular media by Cundall [28], [29].
Model validation
Fig. 7 reports the yarn deformed shape at 0 μs(a), 10 μs(b), 25 μs(c) and 40 μs(d).
Classical transverse displacement wave is clearly observed. It begins to propagate when the cylindrical bullet and yarn get into contact and moves leftwards to the clamped edge in the period between 0 μs and 20 μs. When the wave reaches the boundary conditions it is reflected and moves rightwards to the impact point, 20 μs-30 μs. Finally when it reaches the impact point the yarn fails. The so called spreading wave is
Conclusion
In this work, the application of a 1D multifilament model to the real scale single yarn modelling has been explored. Kevlar fibres have been modelled by a series of discrete particles relatively connected by truss elements. Those particles are used to deal with the contact according to the Discrete Element Method, while the axial deformation is provided by the bonds between the elements. Results have been compared to those obtained using a multifilament 3D finite elements model and a good
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2018, Defence TechnologyCitation Excerpt :Barauskas and Abraitiene [6] were the first to present a multiscale modeling approach for woven fabrics that explicitly incorporated two length scales (i.e. yarn, fabric) within the same finite element model using a single finite element formulation (i.e. 2D shell element). Since then, other multiscale models [7–15] have also incorporated multiple length scales (e.g. fiber, yarn, fabric) using multiple finite element formulations (e.g. 1D truss element, 2D shell element, 3D solid element) within the same finite element model; including fiber-level modeling of single yarns [14,16–18] and fiber-level modeling of the entire fabric [13,19–21]. Advancements in probabilistic modeling techniques have made possible the incorporation of experimentally-observed sources of statistical variability into the finite element simulations thereby enabling the vital transition from the deterministic-only capability of virtual testing to now predicting the probabilistic penetration performance of armor systems [22].
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