Fibre-reinforced materials, such as carbon- and glass-fibre-reinforced plastics, provide high performance, vast amount of tailorability, and, therefore, they are increasingly used in multitude load-carrying structures from vehicles to wind-mills, elevators and containers. Everywhere where gravity is acting on a transported or moving product, a decrease in the weight by high-performance materials is a direct advantage.Thus, the tendency to decrease energy consumption and to develop greener and cleaner products drives industries which design and manufacture such products as ships, aircrafts, cars, elevators and wind-mills to use a minimum amount of raw materials. Thinner walls in structures make them light and consequently make them more efficient as moving requires less energy. Less material used means also less extracted raw material, less waste material and less material required to be recycled.
In addition, the fibre-reinforced composite industry faces a challenge of a slowing development speed of these materials. There are two main reasons behind the decreased development pace: i) The optimization of fibrous materials in structures is affected by many material properties that are
very difficult to determine accurately, with a statistically verified reliability; and ii) The testing and validation of very small material samples is slow and expensive in practice.
Despite all the benefits, there are downsides with composite materials. The complexity of the composite materials makes them hard to recycle1. For example, a recycled carbon fibre cannot directly replace a virgin fibre in existing applications, since the functionality of recycled fibres is not the same. Therefore, new applications fitting with the functionalities of recycled fibres are largely needed. For example in car industry, recovered fibres can be incorporated into less critical products. In order to do so, the properties of recovered fibres should be analysed against the requirements of existing automotive components. The current challenge, however, is the lack of agreed methodology for assessing the quality of recovered fibres. The view of our project team is that especially methods for high throughput characterization of fibre-matrix interfaces are currently missing. This is a significant drawback as recycling does not only influence the tensile strength of fibres but also their surface properties and thus, their capability to adhere on polymer matrix.
The solution to the aforementioned problems is not straightforward. The solution requires combining technologies from the fields of automation, robotics, chemistry, computational modelling, and material science. The current test methods used in the composite research and industry handle the fibre samples, thinner than human hair, by hand, manually. Therefore obviously, very little statistical reliability and cost efficiency can be reached using the current methods. Our solution is a data-based approach where we increase the amount of data particularly at the fundamental micro and nanoscales. We integrate nano, micro and meso-scale testing of materials with automated computational modelling. This means that we automate modelling and test simulation for each single test to obtain all the statistical data needed for the materials.
The main results of the research opening are i) an automatic microrobotic system which is able to characterize mechanical properties of fibres and fibre-
matrix interfaces in high throughput, ii) massive material data sets, and iii) numerical multi-scale material models which link the measurement data to properties at the product scale.
Thus, with the expertise and tool-set to be developed in the project, we will be able to produce vast amount of micro-scale data currently unavailable, and link this micro-scale data to product behaviour and performance using numerical models and knowhow in material science. In this project, these elements will be exposed to various environmental conditions (such as moisture, heat, ultra violet light, radiation, acids) and then strength parameters (such as the fibre strength and the interface strength between the fibre and the polymer matrix) can be measured at a fibre scale in high throughput using a novel microrobotic approach. The large amount of data produced by the microrobotic system will be used in numerical material models to understand the material behaviour at multiple length scales. This information can be used for developing better performing composite products as well as for quality control purposes.
The research opening will drastically influence composite research and industry by
- reducing costs of experimental validation both in academia and industry as the time-consuming and expensive tests at the level of bulk material (both fibres and matrix), coupons and components can be replaced by automated micro-scale tests;
- improving the competitiveness of the industry through faster fibre level modification and aging studies, and thus product development; and
- by reducing the amount of material needed in the final products without compromising their reliability and, subsequently, safety of operation.
The results influence most extensively the medium size companies in the field of composite materials, fibrous raw materials, and machine design and production using composite materials. For these companies, the current methodology to test a very large number of specimens at a component level is
overly expensive. With our results, they can also form experimentally validated multi-scale material models, ensure raw material quality, and minimize reclaims. The results from the project could improve the knowledge among composite structural designers in all areas of industry. This could also improve the quality and the competitiveness of the composite products.
In addition to the testing of composite materials, the approach of automated numerical modelling could be developed into a separate commercial product to be used in material research and development at large. Currently, there is no common automation product that would directly use raw
data recorded by testing equipment and develop a geometry model for subsequent simulation of the test. This is probably due to the multiplicity of testing equipment providers, test specimen types, and simulation targets. In our approach, the testing equipment and simulation output are set a priori. The approach can be extended to selected standard tests and selected testing equipment providers to be a separate product. In this kind of research and development, the partners could be well-known testing equipment providers.