A European Industrial Doctorate Network underMarie Sklodowska Curie Grant 765472
The ‘N2N’ project
Modern aeronautical and automobile structures are increasingly made of composite materials due to their strength to weight benefits. Despite their superior structural characteristics, composite structures exhibit poor acoustic isolation levels compared to conventional metallic ones. As a result and in order to maintain the comfort levels in the passenger and payload compartments within acceptable limits, additional acoustic and vibrational isolation technologies (sound packages) are necessary for several transport applications. These sound packages can add substantial weight to the structure if not designed optimally, compromising the weight benefits gained by the use of composites.
The aforementioned challenges imply an urgent need for the development of lightweight and multifunctional structures, for modern industrial transport applications. The N2N Training Network aims at developing a high-fidelity and efficient Multidisciplinary Design Optimization (MDO) scheme for multifunctional composites having poroelastic inclusions.
Key Aims & Objectives
Developing multiscale models for obtaining a comprehensive description of random poroelastic materials coupled to a composite structural segment.
Understanding the interaction of acoustic waves with such complex materials.
Developing reliable tools for providing near-optimal designs for multifunctional composite structures that combine lightweight properties with exceptional acoustic and vibration isolation.
N2N will provide a world-class training environment for the 3 Early Stage Researchers (ESRs). This includes:
A training programme aimed at developing both the research as well as the transferable skills of the Fellows.
Opportunity to work in a multidisciplinary, multisectoral (industrial and academic) research environment.
The N2N project (Innovative Training Network in lightweight and silent, multifunctional composite structures) is funded under the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Actions Grant: 765472.