The increase in the number of structural applications of composite materials, especially in the aerospace and automotive industries, has led to a demand for robust models to simulate composite forming processes. The mechanical behaviour of composite materials during forming is relatively complex due to their fibre-matrix composition. Many research studies have been conducted in the past 25-plus years into experimental methods for the characterization of the mechanical behaviours that are exhibited by textile-reinforced composite material systems during forming and into the development of material models to be used in computer codes for forming simulations. These studies have been presented and discussed in the ESAFORM conferences since 1997 and especially in the 'Composite Forming Processes' mini-symposium launched in 2001. This article presents a survey of the research carried out in this context. Mechanical characterization tests specific to composite forming are presented as well as recent analysis techniques such as digital image correlation and X-ray tomography. Three-dimensional mechanical behaviour laws, in particular hypo- and hyperelastic, have been developed and extended to second gradient models. Specific shell approaches have been presented and their application to wrinkling analysis. Resin flow and permeability analysis is another area of research in composite forming processes which are discussed in this article. Research on certain processes is also presented, in particular thermoforming of thermoplastic composites, wet compression moulding, pultrusion, automated fibre placement and three-dimensional printing. This comprehensive review of the works of multiple research groups is a recognition of the breadth and depth of efforts that have been invested into the understanding of the manufacturability of textile-reinforced composite materials. 

https://link.springer.com/content/pdf/10.1007/s12289-022-01682-8.pdf

Advances in composite forming through 25 years of ESAFORM

Permeability of fibrous microstructures is a key material property for predicting the mold fill times and resin flow path during composite manufacturing. In this work, we report an efficient approach to predict the permeability of 3D microstructures from deep learning based permeability predictions of 2D cross-sections combined via a circuit analogy. After validating the network’s predictions in 2D and extending it to 3D, we investigate its capabilities for handling images of various sizes obtained from virtual and real microstructures. More than 90% of 2D predictions is within ± 30% of their counterparts obtained via flow simulations, similarly for 3D transverse permeability predictions, while in 3D case computational time is reduced from several thousands of seconds to less than 10 s. This work provides a robust and efficient framework for characterizing the permeability of fibrous microstructures and paves the way for extending this capability to estimate the permeability of fabric mesostructures. 

Deep learning accelerated prediction of the permeability of fibrous microstructures

Permeability measurements of engineering textiles exhibit large variability as no standardization method currently exists; numerical permeability prediction is thus an attractive alternative. It has all advantages of virtual material characterization, including the possibility to study the impact of material variability and small-scale parameters. This paper presents the results of an international virtual permeability benchmark, which is a first contribution to permeability predictions for fibrous reinforcements based on real images. In this first stage, the focus was on the microscale computation of fiber bundle permeability. In total 16 participants provided 50 results using different numerical methods, boundary conditions, permeability identification techniques. The scatter of the predicted axial permeability after the elimination of inconsistent results was found to be smaller (14%) than that of the transverse permeability (∼24%). Dominant effects on the permeability were found to be the boundary conditions in tangential direction, number of sub-domains used in the renormalization approach, and the permeability identification technique. 

Benchmark exercise on image-based permeability determination of engineering textiles: microscale predictions

This review shows the potential of using the Representative Volume Element concept for the multi-scale simulation of 3D woven high performance thermoset composites manufactured using the Resin Transfer Molding (RTM) process. Based on the reviewed state of art, this work unleashes the 5 most promising areas for future research that could advance the RTM process optimization. Area 1: Developing polymer constitutive models databases that rely on the experimental data at all ranges of degrees of cure and temperatures involved in the RTM process. Area 2: Verifying the accuracy of simulation tools on complex parts made of different preform types. Area 3: Increasing computational efficiency of degree of cure- and temperature-dependent viscoelastic constitutive models accounting for the stress relaxation. Area 4: Increasing computational efficiency of the multi-scale homogenization procedure. Area 5: Standardizing experimental measurements during different phases of the RTM process. 

A review on the Representative Volume Element-based multi-scale simulation of 3D woven high performance thermoset composites manufactured using resin transfer molding process

Capillary-driven saturation of the reinforcing structure is an important aspect of liquid composite molding processes. Interacting with the flow-induced saturation, process speed must be optimized to guarantee full wetting while being time-efficient. The well-known Lucas-Washburn equation gives an estimate of the capillary imbibition in porous materials but lacks accuracy in case of textile structures. In this work, capillary rise experiments of different glass and carbon reinforcements are compared. An extension to the Lucas-Washburn equation is proposed based on regression-based fitting and validated with the experimental results. It considers peripheral flow in the textile as well as gravitational effects. Good conformity could be shown for textiles with many cross-sections. Unidirectional, low fiber volume content and irregular-shaped fabrics are more difficult to handle. The accurate determination of the capillary radius and the peripheral fluid flow are key factors. 

A porous capillary tube approach for textile saturation

The out-of-plane permeability of two glass fibre fabrics was measured by 26 institutions using silicone oil as a test fluid. Participants in this study were free to select the test procedure, specimen dimensions and data analysis method, provided that testing was carried out at three target fibre volume fractions, 46%, 50% and 54%. While results showed a variability of two orders of magnitude between participants, most values were within a significantly narrower band. A majority of participants used 1D saturated test method. A few selected 1D unsaturated and 3D unsaturated flow method which gave very similar results. Focusing on analysis of data and results of 1D saturated flow measurements, results are not conclusive, but they are consistent with number of layers in a specimen, fibre volume fraction, injection pressure and sealing of specimen edges all having an effect on the measured permeability. Specifying limits for these parameters is expected to result in reduced scatter in measured permeability.

Out-of-plane permeability measurement for reinforcement textiles: A benchmark exercise

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Out-of-plane permeability measurement for reinforcement textiles: A benchmark exercise