Brunel Composites Centre (BCC) sits between the knowledge base and industry, supporting partners in industry by transfering academic research in novel composites processing and joining technologies into industrial application. http://bura.brunel.ac.uk/handle/2438/25440 2026-06-30T19:57:17Z 2026-06-30T19:57:17Z Khan, T Ali, MA Irfan, MS Cantwell, WJ Rehan, U http://bura.brunel.ac.uk/handle/2438/33423 2026-06-13T02:01:33Z 2022-12-15T00:00:00Z

Title: Visualizing pseudo‐ductility in carbon/glass fiber hybrid composites manufactured using infusible thermoplastic Elium® resin Authors: Khan, T; Ali, MA; Irfan, MS; Cantwell, WJ; Rehan, U Abstract: In this study, two different type of glass and carbon fiber hybrid laminates were manufactured using a low-viscosity thermoplastic resin that is, Elium®. A detailed microstructure visualization study was conducted using X-ray computed tomography (XCT) analysis. The viscoelastic properties were examined through dynamic mechanical analysis. The mechanical performance was investigated through flexural and tensile tests along with a fractographic study using optical and scanning electron microscopy. The XCT analysis revealed a weak interface between the Elium® resin and the glass fabric, with glass fiber specimens exhibiting a void content of 1.24%, in contrast to the carbon fiber specimens which showed void content of only 0.28%. Therefore, adding glass fabric layers in the hybrid laminates increased the void content, which had a negative impact on the overall mechanical performance. The average flexural strength of the hybrid specimen having G₂C₄G₂ stacking sequence was observed to be 254% higher than pure GFRPC specimens. Similarly, the tensile strength and Young's modulus of the same hybrid specimen showed 155% and 380% increases, respectively, compared to the GFRPC specimens. This increase was primarily due to higher stiffness of the carbon fibers and their better fiber – matrix interface. Whereas the tensile strain of the hybrid specimen having G₃C₂G₃ stacking sequence was 37% higher than that of the CFRPC specimens. The SEM images highlighted fiber fracture and brittle failure modes in the carbon fiber specimens, in contrast to fiber pullout, interfacial failure, poor fiber-matrix bonding and ductile failure modes in the glass fiber specimens. Description: Data Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.

2022-12-15T00:00:00Z Syerko, E Schmidt, T May, D Binetruy, C Advani, SG Lomov, S Silva, L Abaimov, S Aissa, N Akhatov, I Ali, M Asiaban, N Broggi, G Bruchon, J Caglar, B Digonnet, H Dittmann, J Drapier, S Endruweit, A Guilloux, A Kandinskii, R Leygue, A Mahato, B Martínez-Lera, P Matveev, M Michaud, V Middendorf, P Moulin, N Orgéas, L Park, CH Rief, S Rouhi, M Sergeichev, I Shakoor, M Shishkina, O Swolfs, Y Tahani, M Umer, R Vanclooster, K Vorobyev, R http://bura.brunel.ac.uk/handle/2438/33422 2026-06-13T02:01:32Z 2023-01-06T00:00:00Z

Title: Benchmark exercise on image-based permeability determination of engineering textiles: Microscale predictions Authors: Syerko, E; Schmidt, T; May, D; Binetruy, C; Advani, SG; Lomov, S; Silva, L; Abaimov, S; Aissa, N; Akhatov, I; Ali, M; Asiaban, N; Broggi, G; Bruchon, J; Caglar, B; Digonnet, H; Dittmann, J; Drapier, S; Endruweit, A; Guilloux, A; Kandinskii, R; Leygue, A; Mahato, B; Martínez-Lera, P; Matveev, M; Michaud, V; Middendorf, P; Moulin, N; Orgéas, L; Park, CH; Rief, S; Rouhi, M; Sergeichev, I; Shakoor, M; Shishkina, O; Swolfs, Y; Tahani, M; Umer, R; Vanclooster, K; Vorobyev, R Abstract: 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. Description: Data availability: Data will be made available on request.; Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S1359835X22005784?via%3Dihub#s0105 .

2023-01-06T00:00:00Z Ali, MA Khan, T Khan, K Umer, R http://bura.brunel.ac.uk/handle/2438/33410 2026-06-22T08:48:24Z 2022-09-01T00:00:00Z

Title: Micro CT Based Stochastic Design and Flow Analysis of Dry Fiber Preforms Manufactured by Automated Fiber Placement Authors: Ali, MA; Khan, T; Khan, K; Umer, R Abstract: The effective design of channels in dry tape preforms is crucial for achieving desired preform permeability for successful resin injection for composites manufacturing using Automated Fiber Placement (AFP) process. This work investigates the correlation between spatial variability of the preforms and the in-plane permeability using an X-ray Computed Tomography (XCT) based characterization framework. The tomographic images of two different dry carbon tape preforms with different tape widths were used to generate realistic and XCT based stochastic models to be used for numerical permeability predictions. The variability in the tape placement by the robotic head and its effect on preform permeability was also examined through stochastic geometric modeling of the laid preform. A benchmark transient permeability measurement set-up was utilized to obtain experimental in-plane preform permeability through 2D radial mold filling. The in-plane numerical permeability values showed significant scatter, with a coefficient of variance of 75-130%, which deviated from the experimental measurements by approximately one order of magnitude. These findings strongly re-affirm that the experimental permeability measurement technique based on transient mold filling of dry fiber AFP preforms is complex however, the XCT based stochastic modeling technique is an effective way to estimate the permeability of dry fiber AFP preforms virtually.

2022-09-01T00:00:00Z Ud Din, I Medhin, Y Aslam, N Salman, M Bathusha, S Umer, R Khan, KA http://bura.brunel.ac.uk/handle/2438/33163 2026-04-18T02:01:27Z 2022-06-26T00:00:00Z

Title: Rate Dependent Electromechancal Characterization And Modeling Of Graphene Based Fiber Reinforced Polymer Laminates Authors: Ud Din, I; Medhin, Y; Aslam, N; Salman, M; Bathusha, S; Umer, R; Khan, KA Abstract: Fiber reinforced polymer (FRP) composite laminates are used in numerous structures that require high strength-to-weight ratio. The health status of these laminates is traditionally monitored using point strain gauge arrays, fiber optics etc. installed at critical locations. In this work, a composite laminate capable of sensing its own health has been developed using embedded fabric sensor. In this study, a manufacturing protocol is developed for in-situ reduction of graphene oxide (GO) coated fabric into rGO coated fabric. A vacuum assisted resin transfer molding process was used to fabricate the composite laminates with embedded rGO coated fabric sensors. The piezoresistivity of the composite laminate was measured both before and during fabrication. The in-plane tension tests were carried out at three different loading rates (0.2, 2, 20 mm/min) to determine the rate-dependent piezoresistive response of composite laminates. We recorded both the piezoresistivity and load-displacement data simultaneously to obtain the electromechanical response of the fabricated samples.

2022-06-26T00:00:00Z