The Strategic Research and Innovation Agenda (SRIA) highlights that the available technologies and procedures allow a 75% reduction in CO2 emissions per passenger kilometer, a 90% reduction in NOx, and a 65% reduction in perceived noise emission, by the year 2050.
Massive reduction in fuel consumption and costs are foreseen by the use of advanced lightweight composite materials in the coming decades. However composite structures exhibit poor acoustic isolation levels compared to conventional metallic ones. In order to maintain the comfort levels in the passenger and payload compartments within acceptable limits, additional acoustic and vibration isolation technologies (sound packages) are necessary. These sound packages can add substantial weight to the structure, compromising the weight savings, if their designs are sub-optimal.
There is an urgent need for the development of novel materials and design approaches for silent and lightweight multifunctional sound packages, for modern industrial applications. The No2Noise training network aims at developing an efficient high-fidelity 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 recruit 3 Early Stage Researchers (ESRs) who will enroll in Ph.D programmes in the academic beneficiaries along with the unique opportunity to spend at least half the time in the industrial beneficiaries solely for training. This includes:
A world-class training programme aimed at developing both the research as well as the transferable skills of the fellows.
Opportunity to work on a multidisciplinary, multisectoral network in multinational research environments.