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

Syerko, Elena; Schmidt, Tim; May, David; Binetruy, C.; Advani, Suresh G.; Lomov, Stepan Vladimirovitch; Silva, L.; Abaimov, S.; Aissa, N.; Akhatov, Iskander; Ali, Mohammad; Asiaban, N.; Broggi, Guillaume; Bruchon, Julien; Caglar, Baris; Digonnet, Hugues; Dittmann, Jörg; Drapier, Sylvain; Endruweit, A.; Guilloux, Antonin; Kandinskii, R.; Leygue, Adrien; Mahato, B.; Martínez-Lera, P.; Matveev, Mikhail Y.; Michaud, Véronique; Middendorf, Peter; Moulin, Nicolas; Orgéas, Laurent; Park, C.H.; Rief, Stefan; Rouhi, Mohammad Sadegh; Sergeichev, I.; Shakoor, M.; Shishkina, Oksana; Swolfs, Y.; Tahani, M.; Umer, Rehan; Vanclooster, K.; Vorobyev, R.

doi:10.1016/j.compositesa.2022.107397

Cited by 23 publications

(19 citation statements)

References 34 publications

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“…The interest in image-based permeability prediction has increased in recent years, as demonstrated by a new benchmark exercise, which also aims to develop guidelines for numerical permeability prediction. In fact, despite this method having many advantages, such as the possibility to consider the material variability and small-scale parameters, study multiple influencing factors, and reduce the material waste, some challenging issues include the need for elevated computing power, the potential errors related to image acquisition and geometry reconstruction, the presence of several numerical methods and influencing parameters, and the multi-scale porosity of fiber reinforcements [ 112 ].…”

Section: Measurement Methodsmentioning

confidence: 99%

An Overview of the Measurement of Permeability of Composite Reinforcements

2023

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Liquid composite molding (LCM) is a class of fast and cheap processes suitable for the fabrication of large parts with good geometrical and mechanical properties. One of the main steps in an LCM process is represented by the filling stage, during which a reinforcing fiber preform is impregnated with a low-viscosity resin. Darcy’s permeability is the key property for the filling stage, not usually available and depending on several factors. Permeability is also essential in computational modeling to reduce costly trial-and-error procedures during composite manufacturing. This review aims to present the most used and recent methods for permeability measurement. Several solutions, introduced to monitor resin flow within the preform and to calculate the in-plane and out-of-plane permeability, will be presented. Finally, the new trends toward reliable methods based mainly on non-invasive and possibly integrated sensors will be described.

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Section: Measurement Methodsmentioning

confidence: 99%

An Overview of the Measurement of Permeability of Composite Reinforcements

2023

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“…Alternatively, predictive permeability characterisation models are also an attractive area of research in order to overcome many of the tedious and temperamental aspects of the experimental approaches. In addition to the previously mentioned micro-and meso-scale modelling approaches for virtual permeability characterisation [16,17,18,32], there have also been efforts to develop iterative, macro-scale, simulation-enhanced methods for 3D permeability characterisation [49]. These are designed to support experimental procedures for greater accuracy and reliability overall, compared with conventional 3D methods that are based on the theoretical calculations for, and transformations from, an equivalent isotropic flow [50,51].…”

Section: Characterisation Methodsmentioning

confidence: 99%

“…However, despite the apparent simplicity of such a fluid dynamics model, the geometric complexity and stochastic nature of these materials makes accurate flow prediction particularly difficult. Micro-scale models, considering the flow between individual fibres in a preform, may simply rely on conventional Computational Fluid Dynamics (CFD) packages to predict 2D or 3D flow, based on simple geometric approximations or real scans from X-ray micro-tomography [17]. As the simulation scale increases though, reasonable limits on the size and number of constitutive elements in the model necessitate significant degrees of homogenisation or geometric simplification.…”

Section: Vacuum Infusion Process Modelling 21 Backgroundmentioning

confidence: 99%

Challenges in permeability characterisation for modelling the manufacture of wind turbine blades

Pierce

2023

IOP Conf. Ser.: Mater. Sci. Eng.

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As wind turbine blades continue to increase in size, and market competition grows, lean manufacturing has become even more important for OEMs. The rapid development of new blade designs, with greater performance, and reduced production waste are driving the need for predictive modelling of the blade infusion process. Such simulations are reliant upon Darcy’s Law for the description of fluid flow through porous materials and therefore depend greatly on the permeability properties of the blade preform materials. The characterisation of fabric permeability, although unstandardised, has been well studied in recent years as the focus of numerous international benchmarking efforts. However, the effective permeability properties of infusion consumables, core materials, and pre-cast elements are not so well defined or validated, despite their significance on infusion behaviour. Hence, the great variety of preform materials, stacking configurations, geometric features, and transition regions in wind turbine blades present considerable challenges in terms of permeability characterisation and subsequent modelling. This article reviews some of the challenges, opportunities, and alternatives for characterising permeability in common blade preform materials, along with examples of how these properties have been applied in numerical models to better simulate the resin infusion manufacturing process for wind turbine blades.

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“…With this, one can solve the momentum equations in terms of only the velocity field without considering additional degrees of freedom (DoFs) associated with the pressure. Despite the limitations and challenges associated with the choice of value for the penalty parameter itself, as discussed in [15], the reduction in the total number of degrees of freedom to solve is attractive for computationally costly problems such as the one in the virtual permeability benchmark [3] discussed further in Section 5.1. Thus, with the computational cost in mind, a modelling choice was made to use the penalty-based approach in this work.…”

Section: Modelling Of Single-phase Steady-state Porous Media Flow At ...mentioning

confidence: 99%

“…Different numerical methodologies for the solution of this problem with different discretisation techniques, physical variables formulation, boundary conditions, etc., exist in the literature. A recent benchmark on the image-based permeability determination of fibrous materials has illustrated this diversity of numerical approaches [ 3 ]. The most widely used numerical approximation methods are the Finite Volume Method (FVM) [ 4 ] and the Finite Element Method (FEM) [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

A Novel Finite Element-Based Method for Predicting the Permeability of Heterogeneous and Anisotropic Porous Microstructures

Mulye,

Syerko,

Binetruy

et al. 2024

Materials

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Permeability is a fundamental property of porous media. It quantifies the ease with which a fluid can flow under the effect of a pressure gradient in a network of connected pores. Porous materials can be natural, such as soil and rocks, or synthetic, such as a densified network of fibres or open-cell foams. The measurement of permeability is difficult and time-consuming in heterogeneous and anisotropic porous media; thus, a numerical approach based on the calculation of the tensor components on a 3D image of the material can be very advantageous. For this type of microstructure, it is important to perform calculations on large samples using boundary conditions that do not suppress the transverse flows that occur when flow is forced out of the principal directions. Since these are not necessarily known in complex media, the permeability determination method must not introduce bias by generating non-physical flows. A new finite element-based method proposed in this study allows us to solve very high-dimensional flow problems while limiting the biases associated with boundary conditions and the small size of the numerical samples addressed. This method includes a new boundary condition, full permeability tensor identification based on the multiscale homogenization approach, and an optimized solver to handle flow problems with a large number of degrees of freedom. The method is first validated against academic test cases and against the results of a recent permeability benchmark exercise. The results underline the suitability of the proposed approach for heterogeneous and anisotropic microstructures.

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

Cited by 23 publications

References 34 publications

An Overview of the Measurement of Permeability of Composite Reinforcements

An Overview of the Measurement of Permeability of Composite Reinforcements

Challenges in permeability characterisation for modelling the manufacture of wind turbine blades

A Novel Finite Element-Based Method for Predicting the Permeability of Heterogeneous and Anisotropic Porous Microstructures

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