Imperial College London

DrVitoTagarielli

Faculty of EngineeringDepartment of Aeronautics

Reader in Mechanics of Solids
 
 
 
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Contact

 

+44 (0)20 7594 5167v.tagarielli

 
 
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Location

 

218City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

93 results found

Bisio V, Montomoli F, Rossin S, Tagarielli VLet al., 2024, On the pressure wave emanating from a deflagration flame front, Heliyon, Vol: 10, ISSN: 2405-8440

We consider a spherical flame expanding from an ignition point through a homogeneous, flammable gaseous mixture. We analytically predict the transient pressure and velocity fields ahead of the flame as a function of the flame front position, which is assumed to evolve in time according to a power-law relation. The predictions are successfully validated by CFD simulations. We show that the model is also effective for analyzing real deflagration problems, by predicting measurements taken in hydrocarbon deflagration tests.

Journal article

Ge W, Tagarielli V, 2024, Data-driven homogenisation of the response of heterogeneous ductile solids with isotropic damage, Materials and Design, ISSN: 0264-1275

We propose and implement a computational procedure to derive a data-driven surrogate constitutive model capturing the elastic-plastic response and progressive damage of aheterogeneous solid. This is demonstrated by analysing the deformation response of a volume element of a non-linear, n-phase random composite, used in this study as a model material. Finite Element simulations are conducted, imposing pseudo-random, multiaxial, non-proportional histories of macroscopic strain to such volume element. The corresponding predicted histories of macroscopic stresses and other variables are recorded, to form part of a training dataset for the surrogate model. Essential additional training data is obtained by recording the changes in the homogenised stiffness matrix of the volume element during the deformation, by performing a series of linear perturbation analyses. Supervised machine learning is applied to the data, proposing suitable sets of inputs andoutputs and implementing a phenomenological constitutive model based on simple neural networks. This results in a data-driven model of high accuracy.

Journal article

Zhou J, Pellegrino A, Tagarielli V, 2023, A new technique to measure the dynamic fracture toughness of solids, Polymer Testing, Vol: 127, ISSN: 0142-9418

We propose and assess a new experimental technique to measure the fracture toughness of engineering materials and its sensitivity to strain rate. The proposed method is based on a ring expansion technique and it overcomes the limitations of current dynamic fracture tests, as it is not affected by transient stress wave propagation during loading and it results in spatially uniform remote stress and strain fields prior to fracture; the method is also suitable to achieve remote strain rates well in excess of 1000 s−1. We demonstrate the technique by measuring the plane-stress Mode I fracture toughness of PMMA specimens at remote strain rates ranging from 10−3 s−1 to 102 s−1. The experiments show an increase of the toughness of the material with increasing strain rate.

Journal article

Tasdemir B, Tagarielli V, Pellegrino A, 2023, A data-driven model of the yield and strain hardening response of commercially pure titanium in uniaxial stress, Materials and Design, Vol: 229, Pages: 1-10, ISSN: 0264-1275

This study presents a technique to develop data-driven constitutive models for the elastic-plastic response of materials, and applies this technique to the case of commercially pure titanium. The complex yield and strain hardening characteristics of this solid are captured for random non-monotonic uniaxial loading, without relying on specific theoretical descriptions. The surrogate model is obtained by supervised machine learning, relying on feed-forward neural networks trained with data obtained from random loading of titanium specimens in uniaxial stress. Uniaxial tests are conducted in strain control, applying random histories of axial strain in the range [−0.04, 0.04], to prevent the occurrence of significant damage. The corresponding stress versus strain histories are subdivided into a finite number of increments, and machine learning is applied to predict the change in stress in each increment. A suitable architecture of the data-driven model, key to obtaining accurate predictions, is presented. The predictions of the surrogate model are validated by comparing to experiments not used in the training process, and compared to those of an established theoretical model. An excellent agreement is obtained between the measurements and the predictions of the data-driven surrogate model.

Journal article

Chavoshi SZ, Tagarielli VL, 2023, Data-driven prediction of the probability of creep-fatigue crack initiation in 316H stainless steel, Fatigue and Fracture of Engineering Materials and Structures, Vol: 46, Pages: 212-227, ISSN: 1460-2695

Stainless steel components in advanced gas-cooled reactors (AGRs) are susceptible to creep–fatigue cracking at high temperatures. Quantifying the probability of creep–fatigue crack initiation requires probabilistic numerical simulations; these are complex and computationally intensive. Here, we present a data-driven approach to develop fast probabilistic surrogate models of creep–fatigue crack initiation in 316H stainless steel. We perform a set of Monte Carlo simulations based on the R5V2/3 high temperature assessment procedure and determine the sensitivity of the probability of crack initiation to loads and operating conditions. The data are used to train different supervised machine learning models considering Bayesian hyperparameter optimization. We discuss the relative performance of such models and show that a gradient tree boosting algorithm results in surrogate models with the highest accuracy.

Journal article

Plocher J, Tagarielli V, Panesar A, 2023, Predictions of the elastic-plastic compressive response of functionally graded polymeric composite lattices manufactured by Three-Dimensional Printing, Journal of Engineering Materials and Technology, Vol: 145, Pages: 1-10, ISSN: 0094-4289

We use 3D printing to manufacture lattices with uniform and graded relative density, madefrom a composite parent material comprising a nylon matrix reinforced by short carbon fibres.The elastic-plastic compressive response of these solids is measured up to their densificationregime. Data from experiments on the lattices with uniform relative density is used to deducethe dependence of their elastic-plastic homogenised constitutive response on their relativedensity, in the range 0.2-0.8. This data is used to calibrate Finite Element (FE) simulations ofthe compressive response of Functionally Graded Lattices (FGLs), which are found in goodagreement with the corresponding measurements, capturing the salient features of the measuredstress versus strain responses. This exercise is repeated for two lattice topologies (body-centredcubic and Schwarz-P). The phenomenological constitutive models produced in this study canbe used in topology optimisation to maximise the performance of 3D printed FGLs componentsin terms of stiffness, strength or energy absorption.

Journal article

Tasdemir B, Pellegrino A, Tagarielli V, 2022, A strategy to formulate data-driven constitutive models from random multiaxial experiments, Scientific Reports, Vol: 12, ISSN: 2045-2322

We present a test technique and an accompanying computational framework to obtain data-driven, surrogate constitutive models that capture the response of isotropic, elastic–plastic materials loaded in-plane stress by combined normal and shear stresses. The surrogate models are based on feed-forward neural networks (NNs) predicting the evolution of state variables over arbitrary increments of strain. The feasibility of the approach is assessed by conducting virtual experiments, i.e. Finite Element (FE) simulations of the response of a hollow, cylindrical, thin-walled test specimen to random histories of imposed axial displacement and rotation. In these simulations, the specimen’s material is modelled as an isotropic, rate-independent elastic–plastic solid obeying J2 plasticity with isotropic hardening. The virtual experiments allow assembling a training dataset for the surrogate models. The accuracy of two different surrogate models is evaluated by performing predictions of the response of the material to the application of random multiaxial strain histories. Both models are found to be effective and to have comparable accuracy.

Journal article

Bisio V, Montomoli F, Rossin S, Ruggiero M, Tagarielli VLet al., 2022, Predictions and uncertainty quantification of the loading induced by deflagration events on surrounding structures, Process Safety and Environmental Protection, Vol: 158, Pages: 445-460, ISSN: 0957-5820

The threat of accidental hydrocarbon explosions is of major concern to industrial operations; in particular, there is a need for design tools to assess and quantify the effects of potential deflagration events. Here we present a design methodology based on analytical models that allow assessing the loading and structural response of objects exposed to pressure waves generated by deflagration events. The models allow determining: i) the importance of Fluid-Structure Interaction (FSI) effects; ii) the transient pressure histories on box-like or circular cylindrical objects, including the effects of pressure clearing; iii) the dynamic response of structural components that can be idealised as fully clamped beams. We illustrate by three case studies the complete design methodology and validate the analytical models by comparing their predictions to those of detailed CFD and FE simulations. We employ the validated analytical models to perform Monte Carlo analyses to quantify, for box-like structures, how the uncertainty in input design variables propagates through to the expected maximum force and impulse. We present this information in the form of non-dimensional uncertainty maps.

Journal article

Song Y, magmanlac D, Tagarielli V, 2022, A new stiffness-sensing test to measure damage evolution in solids, Scientific Reports, Vol: 12, Pages: 1-14, ISSN: 2045-2322

We propose and assess a procedure to measure the damage evolution in solids as a function of the applied strain, by conducting stiffness-sensing mechanical tests. These tests consist in superimposing to a monotonically increasing applied strain numerous, low-amplitude unloading/reloading cycles, and extracting the current stiffness of the specimens from the slope of the stress–strain curve in each of the unloading/reloading cycles. The technique is applied to a set of polymeric and metallic solids with a wide range of stiffness, including CFRP laminates loaded through the thickness, epoxy resins, injection-moulded and 3D printed PLA and sintered Ti powders. The tests reveal that, for all the materials tested, damage starts developing at the very early stages of deformation, during what is commonly considered an elastic response. We show that the test method is effective and allows enriching the data extracted from conventional mechanical tests, for potential use in data-driven constitutive models. We also show that the measurements are consistent with the results of acoustic and resistive measurements, and that the method can be used to quantify the viscous response of the materials tested.

Journal article

Zhou J, Tagarielli V, 2022, On the development of new test techniques to measure the tensile response of materials at high and ultra-high strain rates, Experimental Mechanics, Vol: 62, Pages: 151-164, ISSN: 0014-4851

Background: There is a lack of reliable methods to obtain valid measurements of the tensileresponse of high performance materials such as fibre composites, ceramics and textile productsat high rates of strain. Objective: We propose and assess two new test techniques aimed atmeasuring valid tensile stress versus strain curves at high and ultra-high strain rates. Methods:We conduct detailed, non-linear explicit Finite Element (FE) simulations of the transientresponse of the test apparatus and specimen during the tests and we develop simple analyticalmodels to interpret the test measurements. We consider two test techniques: one based on thesplit Hopkinson bar apparatus, and suitable for strain rates of up to 1000 /s, and a secondtechnique relying on ballistic impact and aimed at measurements at strain rates higher than1000 /s. Results: The simulations are successfully validated using test data at strain rates oforder 200 /s and then used to predict the test performance at strain rates up to approximately5500 /s. We find that both techniques can give valid stress versus strain curves across a widerange of strain rates. Conclusions: We identify the limits of both techniques and recommendoptimal measurement strategies for dynamic testing of materials with different ductility.

Journal article

Song Y, Schiffer A, Tagarielli V, 2021, The effects of heterogeneous mechanical properties on the response of a ductile material, Scientific Reports, Vol: 11, Pages: 1-17, ISSN: 2045-2322

We investigate numerically the small-strain, elastic-plastic response of statistically isotropic materials with non-uniform spatial distributions of mechanical properties.The numerical predictions are compared to simple bounds derived analytically. We explore systematically the effects of heterogeneity on the macroscopic stiffness, strength, asymmetry, stabilityand size dependence. Monte Carlo analyses of the response of statistical volume elements are conducted at different strain triaxiality using computational homogenisation, and allow exploring the macroscopic yield behaviour of the heterogeneous material. We illustrate quantitatively how the pressure-sensitivity of the yield surface of the solid increases with heterogeneity in the elastic response. We use the simple analytical models developed here to derive an approximate scaling law linking the fatigue endurance threshold of metallic alloys to their stiffness, yield strength and tensile strength.

Journal article

Ge W, Tagarielli V, 2021, A computational framework to establish data-driven constitutive models for time- or path-dependent heterogeneous solids, Scientific Reports, Vol: 11, Pages: 1-18, ISSN: 2045-2322

We propose and implement a computational procedure to establish data-driven surrogateconstitutive models for heterogeneous materials. We study the multiaxial response of non-linearn-phase composites via Finite Element (FE) simulations and computational homogenisation.Pseudo-random, multiaxial, non-proportional histories of macroscopic strain are imposed onvolume elements of n-phase composites, subject to periodic boundary conditions, and thecorresponding histories of macroscopic stresses and plastically dissipated energy are recorded.The recorded data is used to train surrogate, phenomenological constitutive models based onneural networks (NNs), and the accuracy of these models is assessed and discussed. We analyseheterogeneous composites with hyperelastic, viscoelastic or elastic-plastic local constitutivedescriptions. In each of these three cases, we propose and assess optimal choices of inputs andoutputs for the surrogate models and strategies for their training. We find that the proposedcomputational procedure can capture accurately and effectively the response of non-linear nphase composites subject to arbitrary mechanical loading.

Journal article

Tagarielli V, 2021, The sensitivity of the tensile properties of PMMA, Kevlar® and Dyneema® to temperature and strain rate, Polymer, Vol: 225, Pages: 1-11, ISSN: 0032-3861

We employed a new test technique to measure the tensile response of PMMA, Kevlar® and Dyneema® products at strain rates ranging from 10−4 to 323 s−1. We then extended this technique to allow quasi-static measurements at temperatures in the range −40 to 70 °C. We characterised a monolithic polymer blend, a Kevlar® 49 fibre yarn, a Dyneema SK75 yarn and a Dyneema® tape, exploring the effects of temperature and strain rate on their tensile responses. The sensitivities of the tensile properties to temperature and strain rate were correlated using the time-temperature equivalence, allowing estimates of the mechanical properties of Kevlar and Dyneema at strain rates in excess of 103 s−1.

Journal article

Tagarielli V, Gauch H, Bisio V, Montomoli F, lines O, rossin Set al., 2020, Predictions of the transient loading exerted on circular cylinders by arbitrary pressure waves in air, Journal of Fluid Mechanics, Vol: 901, ISSN: 0022-1120

This study investigates the transient loading exerted on rigid circular cylinders by impinging pressure waves of arbitrary shape, amplitude, and time duration. Numerical calculations are used to predict the transient flow around the cylinder for wide ranges of geometric and loading parameters. An analytical model is developed to predict the transient loading history on the cylinder and this is found in good agreement with the results of the numerical calculations. Both models are used to identify and explore the different loading regimes, and to construct non16 dimensional maps to allow direct application of the findings of this study to the design of structures exposed to the threat of pressure wave loading.

Journal article

Tagarielli V, quino G, Petrinic N, 2020, Effects of water absorption on the mechanical properties of GFRPs, Composites Science and Technology, Vol: 199, Pages: 1-11, ISSN: 0266-3538

This study reports on the effects of water absorption on the anisotropic mechanical response ofan epoxy resin reinforced with E-glass fibres. Composite specimens were conditioned byimmersion in pure water at 50ºC for different time durations, up to full saturation. Water saturation resulted in reduction of stiffness and strength, in the range of strain rate0.001−700s− 1. Experiments on re-dried specimens after water saturation showed only a small recoverability of the original mechanical properties. Water absorption increased the sensitivity of the mechanical response of the GFRPs to the applied strain rate. Finite element simulations of the response of a unit cell of the unidirectional composite were performed to understand the role of the hygroscopic stresses induced by water absorption, and it was found that this is negligible due to the active mechanisms of viscoelastic relaxation.

Journal article

Chavoshi SZ, Tagarielli VL, Zhao L, Nikbin Ket al., 2020, Finite element analysis of creep-fatigue-oxidation interactions in 316H stainless steel, ENGINEERING FAILURE ANALYSIS, Vol: 116, ISSN: 1350-6307

Journal article

Chavoshi S, Tagarielli V, Shi Z, Lin J, Wang S, Jiang J, Dear J, Nikbin Ket al., 2020, Predictions of the mechanical response of sintered FGH96 powder compacts, Journal of Engineering Materials and Technology, Vol: 142, ISSN: 0094-4289

This paper presents predictions of the response of sintered FGH96 Ni-based superalloy powder compacts at high temperature, obtained by analysis of 3D representative volume elements generated by both X-ray tomography and a virtual technique. The response ofthe material to a multiaxial state of stress/strain for porosities as large as 0.3 is explored, obtaining the yield surfaces and their evolution as well as scaling laws for both elastic and plastic properties. The two modelling approaches are found in good agreement. The sensitivity of the predictions to particle size, inter-particle friction, applied strain rate,and boundary conditions is also examined.

Journal article

Albuquerque Da Silva Matos M, Tagarielli V, Pinho S, 2020, On the electrical conductivity of composites with a polymeric matrix and a non-uniform concentration of carbon nanotubes, Composites Science and Technology, Vol: 188, ISSN: 0266-3538

We present a multiscale modelling approach to explore the effects of a non-uniform concentration of carbon nanotubes (CNTs) on the electrical conductivity of CNT-polymer composites. Realistic three-dimensional representative volume elements (RVEs) are generated from a two-dimensional CNT concentration map, obtained via microscopy techniques. The RVEs capture the measured probability density function of the CNT concentration and include a length-scale to represent the details of the spatial distribution of the concentration. The homogenized conductivity of the RVEs is computed via multiscale FE analyses for different values of such length-scale, and it is compared to measurements. The modelling strategy is then used to explore the effects of the microstructural features of these materials on their electrical conductivity.

Journal article

Pathan M, ponnusami S, pathan J, pitisongsawat R, Erice B, Petrinic N, Tagarielli Vet al., 2019, Predictions of the mechanical properties of unidirectional fibre composites by supervised machine learning, Scientific Reports, Vol: 9, ISSN: 2045-2322

We present an application of data analytics and supervised machine learning to allow accuratepredictions of the macroscopic stiffness and yield strength of a unidirectional composite loaded in thetransverse plane. Predictions are obtained from the analysis of an image of the material microstructure,as well as knowledge of the constitutive models for fibres and matrix, without performing physicallybased calculations. The computational framework is based on evaluating the 2-point correlation functionof the images of 1800 microstructures, followed by dimensionality reduction via principal componentanalysis. Finite element (FE) simulations are performed on 1800 corresponding statistical volumeelements (SVEs) representing cylindrical fibres in a continuous matrix, loaded in the transverse plane.A supervised machine learning (ML) exercise is performed, employing a gradient-boosted treeregression model with 10-fold cross-validation strategy. We show how the model obtained is able toaccurately predict the homogenized properties of arbitrary microstructures without performing FEcalculations of their response.

Journal article

Pedrazzini S, Galano M, Audebert F, Siegkas P, Gerlach R, Tagarielli VL, Smith GDWet al., 2019, High strain rate behaviour of nano-quasicrystalline Al93Fe3Cr2Ti2 alloy and composites, Materials Science and Engineering: A, Vol: 764, ISSN: 0921-5093

We demonstrate the outstanding dynamic strength of nano-quasicrystalline Al93Fe3Cr2Ti2 at.% alloy and composites. Unlike most crystalline Al alloys, this alloy exhibits substantial strain rate sensitivity and retains ductility at high strain rates. This opens new pathways for use in safety-critical materials requiring impact resistance.

Journal article

Tagarielli V, Gauch H, Montomoli F, Bisio V, rossin Set al., 2019, Predictions of the transient loading on box-like objects by arbitrary pressure waves in air, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol: 475, ISSN: 1364-5021

This study investigates the transient loading on rigid, isolated, box-like objects by impinging pressure waves of variable intensity and time duration. A numerical solver is used to predict the transient flow around the object and theconsequent pressure on the object’s surface. An analytical model is developed which is capable of predicting the transient loading history on the faces of a box-like object; it was found in good agreement with the numerical predictions.The numerical and analytical models are then used to construct non-dimensional design maps. Different regimes ofloading are identified and explored.

Journal article

Morais MVC, Oliva-Avilés AI, Matos MAS, Tagarielli VL, Pinho ST, Hübner C, Henning Fet al., 2019, On the effect of electric field application during the curing process on the electrical conductivity of single-walled carbon nanotubes–epoxy composites, Carbon, Vol: 150, Pages: 153-167, ISSN: 0008-6223

Single-walled carbon nanotube (SWCNT)/epoxy composites were cured under external electric fields and the influence of the processing parameters (electric field magnitude and frequency, SWCNT concentration and curing temperature)on the electrical response of the system was evaluated. A mold for the electric field application was designed and manufactured, allowing in situ measurements of the electrical resistivity of the composite, during and after the curing process. The resulting electrical properties revealed a strong dependence on the processing parameters. By rising the curing temperature, the solid bulk resistivity was decreased by one order of magnitude. Further reduction was observed with electric fields, up to an additional order of magnitude. Such improvements can be related with the decrease in viscosity and improvement of interconnected-nanotube paths within the polymer matrix. The effect of the electric field on the rotation and interconnection of the SWCNTs was investigated using a classical mechanics model based on the dielectrophoretic theory for the liquid state. The influence of inter-nanotube distances on the bulk electrical properties was calculated at different particle concentrations, using finite element models of the microstructure. This processing technique presents promising results for enhancing the electrical conductivity of polymer composites with carbon-based nanoparticles.

Journal article

Zhou J, Pellegrino A, Heisserer U, Duke PW, Curtis PT, Morton J, Petrinic N, Tagarielli VLet al., 2019, A new technique for tensile testing of engineering materials and composites at high strain rates, PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, Vol: 475, ISSN: 1364-5021

Journal article

Gauch HL, Bisio V, Rossin S, Montomoli F, Tagarielli VLet al., 2019, Transient Loading on Turbomachinery Packages due to Pressure Waves Caused by Accidental Deflagration Events, ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition, Publisher: American Society of Mechanical Engineers

<jats:title>Abstract</jats:title> <jats:p>In this study we present the application of numerical and analytical models to predict the transient loading of structures by impinging pressure and shock waves in air, which have been recently developed by the authors. Non-dimensional design maps are provided which yield predictions of the maximum loads on structures as a function of the problem parameters. Practical example applications, with reference to typical structures used in turbomachinery packages, are presented. These examples demonstrate the superiority of the new modelling techniques to current industrial design guidelines which are mostly extrapolated from simplified methods developed for shock waves. Finally, conclusions are drawn regarding the nature of the loading exerted on the structure in different regimes of problem parameters.</jats:p>

Conference paper

Matos MAS, Pinho ST, Tagarielli VL, 2019, Predictions of the electrical conductivity of composites of polymers and carbon nanotubes by an artificial neural network, Scripta Materialia, Vol: 166, Pages: 117-121, ISSN: 1359-6462

Industrial applications of conductive polymer composites with carbon nanotubes require precise tailoring of their electrical properties. While existing theoretical methods to predict the bulk conductivity require fitting to experiments and often employ power-laws valid only in the vicinity of the percolation threshold, the accuracy of numerical methods is accompanied with substantial computational efforts. In this paper we use recently developed physically-based finite element analyses to successfully train an artificial neural network to make predictions of the bulk conductivity of carbon nanotube-polymer composites at negligible computational cost.

Journal article

Schiffer A, Zacharopoulos P, Foo D, Tagarielli Vet al., 2019, A coarse model for the multiaxial elastic-plastic response of ductile porous materials, Journal of Applied Mechanics, ISSN: 0021-8936

We propose a modelling strategy to predict the mechanical response of porous solids to imposed multiaxial strainhistories. A coarse representation of the microstructure of a porous material is obtained by subdividinga volume element in cubic cells by a regular tessellation; some of these cells are modelled as a plastically incompressible elastic-plastic solid, representing the parent material, while the remaining cells, representing the pores, are treated as a weak and soft compressible solid displaying densification behaviour at large compressive strains. The evolution of homogenised deviatoric and hydrostatic stress is explored in strain-control at different porosities. The predictionsare found in good agreement with previously published numerical studies in which the microstructural geometry was explicitly modelled.

Journal article

Albuquerque Da Silva Matos M, Pinho S, Tagarielli V, 2019, Application of machine learning to predict the multiaxial strain-sensing response of CNT-polymer composites, Carbon, Vol: 146, Pages: 265-275, ISSN: 0008-6223

We present predictive multiscale models of the multiaxial strain-sensing response of conductive CNT-polymer composites. Detailed physically-based finite element (FE) models at the micron scale are used to produce training data for an artificial neural network; the latter is then used, at macroscopic scale, to predict the electro-mechanical response of components of arbitrary shape subject to a non-uniform, multiaxial strain field, allowing savings in computational time of six orders of magnitude. We apply this methodology to explore the application of CNT-polymer composites to the construction of different types of sensors and to damage detection.

Journal article

Li D, Song W, Tagarielli V, Lee KYet al., 2019, UHMWPE fibre yarn established continuous wavy network construction reinforced epoxy foam composite

© CCM 2020 - 18th European Conference on Composite Materials. All rights reserved. Sandwich-structured composites consisting of continuous ultrahigh molecular weight polyethylene (UHMWPE) fibre yarn as through-thickness reinforcement for the epoxy foam core were fabricated in this work. Preliminary test showed that the introduction of continuous UHMWPE fibers improved the shear modulus (Gc) of the foam core by 50%, from Gc = 110 MPa for un-reinforced polymeric foam core to Gc = 163 MPa for polymeric foam core reinforced with 2 vol.-% continuous UHMWPE fibre yarns. The shear strength of the epoxy foam core also improved by up to 10% with the introduction of continuous UHMWPE fibre yarns. The internal morphology of the reinforced epoxy foam cores is also discussed in this work.

Conference paper

Li D, Song W, Tagarielli V, Lee KYet al., 2019, UHMWPE fibre yarn established continuous wavy network construction reinforced epoxy foam composite

Sandwich-structured composites consisting of continuous ultrahigh molecular weight polyethylene (UHMWPE) fibre yarn as through-thickness reinforcement for the epoxy foam core were fabricated in this work. Preliminary test showed that the introduction of continuous UHMWPE fibers improved the shear modulus (Gc) of the foam core by 50%, from Gc = 110 MPa for un-reinforced polymeric foam core to Gc = 163 MPa for polymeric foam core reinforced with 2 vol.-% continuous UHMWPE fibre yarns. The shear strength of the epoxy foam core also improved by up to 10% with the introduction of continuous UHMWPE fibre yarns. The internal morphology of the reinforced epoxy foam cores is also discussed in this work.

Conference paper

Li D, Song W, Tagarielli V, Lee KYet al., 2019, UHMWPE fibre yarn established continuous wavy network construction reinforced epoxy foam composite

© CCM 2020 - 18th European Conference on Composite Materials. All rights reserved. Sandwich-structured composites consisting of continuous ultrahigh molecular weight polyethylene (UHMWPE) fibre yarn as through-thickness reinforcement for the epoxy foam core were fabricated in this work. Preliminary test showed that the introduction of continuous UHMWPE fibers improved the shear modulus (Gc) of the foam core by 50%, from Gc = 110 MPa for un-reinforced polymeric foam core to Gc = 163 MPa for polymeric foam core reinforced with 2 vol.-% continuous UHMWPE fibre yarns. The shear strength of the epoxy foam core also improved by up to 10% with the introduction of continuous UHMWPE fibre yarns. The internal morphology of the reinforced epoxy foam cores is also discussed in this work.

Conference paper

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