Revising testing of composite precursors – A new framework for data capture in complex multi-material systems

Koptelov, A. A.; Belnoue, Jonathan P.-H.; Georgilas, Ioannis; Hallett, Stephen R.; Ivanov, Dmitry

doi:10.1016/j.compositesa.2021.106697

Cited by 2 publications

(10 citation statements)

References 47 publications

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“…However, every model used in this study is wellknown and was previously trialled and verified experimentally for the similar material types. The flow models present in the library are consistent with previous work (Koptelov et al, 2022). The properties of the laminate are defined by the flow and deformation characteristics of the individual plies.…”

Section: The Concept Of Autonomous Testing Frameworkmentioning

confidence: 55%

“…This paper continues the work done by (Koptelov et al, 2022) by implementing the theoretical framework into a full prototype combining standard testing equipment, bespoke consolidation rig, and autonomous module for human-free load trajectory navigation. The paper starts with a summary of key features and principles of the Autonomous Testing Framework (ATF).…”

Section: Introductionmentioning

confidence: 64%

“…The detailed algorithm of the consolidation sensor is shown in Figure 1. It is assumed that the compacted material can be adequately described by one of the consolidation models from a pre-defined library (Koptelov et al, 2022), but there is no prior knowledge about what flow type will dominate and appear to be most adequate for the material description. This library contains models of resin flow in the form of ordinary differential equations.…”

Section: The Concept Of Autonomous Testing Frameworkmentioning

confidence: 99%

“…A summary of all the models, material parameters, and abbreviations used can be found in Table 1. The reader is asked to refer to (Koptelov et al, 2022) for the full mathematical representation of the models considered.…”

Section: The Concept Of Autonomous Testing Frameworkmentioning

confidence: 99%

“…Belnoue et al, 2018). (Koptelov et al, 2022) demonstrated that the conventional testing poses a high risk of introducing fundamental error in results interpretation. A theoretical framework to tackle this problem was suggested and validated in virtual space.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Real-Time Characterisation of Composite Precursors in Manufacturing

et al. 2022

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This paper explores the application of a novel adaptive consolidation sensor framework for the characterisation of composite precursors. The designed framework develops material-driven test programmes in real-time and defines robust material models for the studied composite precursor. The proposed approach allows to remove any subjective judgement about the material behaviour and to reduce human involvement at the experimentation stage. The proposed framework along with the developed data transfer/acquisition hardware setup was put to the test within several characterisation exercises. Two different material systems were tested. The output of the proposed testing method—model and properties for the tested materials—is compared with the results of the conventional deterministic characterisation tests.

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Section: The Concept Of Autonomous Testing Frameworkmentioning

confidence: 55%

Section: Introductionmentioning

confidence: 64%

Section: The Concept Of Autonomous Testing Frameworkmentioning

confidence: 99%

Section: The Concept Of Autonomous Testing Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive Real-Time Characterisation of Composite Precursors in Manufacturing

et al. 2022

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Manufacturing Multi-Matrix Composites: Out-of-Vacuum Bag Consolidation

Radhakrishnan

Georgilas²,

Hamerton

et al. 2023

Journal of Manufacturing Science and Engineering

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The formation of porosity is a major challenge in any composite manufacturing process particularly in the absence of vacuum assistance. Highly localised injection of polymer matrix into regions of interest in a dry preform is a route to manufacturing multi-matrix fibre-reinforced composites with high filler concentrations which are otherwise difficult to achieve. Such multi-matrix fibre-reinforced composite systems, which combine multiple resins in continuous form offer improved structural performance around stress concentrators and multi-functional capabilities, unlike traditional composite materials. As the process lacks vacuum assistance, porosity becomes a primary issue to be addressed. This paper presents a rheo-kinetic coupled rapid consolidation procedure for optimizing the quality of localised matrix patches. The procedure involves manufacturing trials and analytical consolidation models to determine the best processing program for minimal voidage in the patch. The results provide a step towards an efficient manufacturing process for designing multi-matrix composites without the need for complex vacuum bag arrangements. By optimizing the quality of the localised matrix patches, the procedure described in this paper can improve the overall performance of multi-matrix composite systems. The ability to create these composites without the need for complex vacuum bag arrangements can also reduce the manufacturing cost and time associated with the manufacturing of multi-matrix fibre-reinforced composites.

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Revising testing of composite precursors – A new framework for data capture in complex multi-material systems

Cited by 2 publications

References 47 publications

Adaptive Real-Time Characterisation of Composite Precursors in Manufacturing

Adaptive Real-Time Characterisation of Composite Precursors in Manufacturing

Manufacturing Multi-Matrix Composites: Out-of-Vacuum Bag Consolidation

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