spoke_6-MULTISCALE-MODELING-&-ENGINEERING--APPLICATIONS

SPOKE 6
MULTISCALE MODELLING & ENGINEERING APPLICATIONS

Context

The capacity to offer experiments on complex physical/chemical phenomena in “virtual” labs and to assess the performance of industrial devices has considerably increased over the last decades thanks to the availability of accurate and efficient mathematical models, previously solved using numerical models of powerful super-calculators. This increased capacity to virtually “simulate” (replicate) physical reality has led to the significant development of the sciences and industrial applications.

The complexity of a simulation is often determined by the fact that process-developing systems that evolve microscopically (“small” scale) play a significant part in determining macroscopic processes (“large” scale): this is known as multiple scales.  Multiscale modelling is vital when macroscale models are not accurate enough and microscale models are not efficient enough and/or offer too much information, e.g., in meteorology, forecasting micro-scale emission of pollutants is crucial (homes, businesses, and transport systems) to be able to predict the macro-scale impact of pollutants (ozone layer depletion, greenhouse effect, acid rain). Combining both positions, multiscale modelling tends to reach a reasonable compromise between accuracy and efficiency using different models for each of the different scales.

Spoke 6 Multiscale Modelling & Engineering Application deals with multiscale modelling of complex cybernetic/physical systems that evolve on multiple scales of time and space and with the development of models, algorithms, and codes capable of exploiting the abilities of high-performance computing machines (e.g., high-parallelism systems, with GPU, FPGA, or future computational accelerators, that may be quantum or based on open platforms such as RISC-V).

 

This Spoke has the ability to deal with issues that encompass subject areas, involving multiple scales (from the sub-nanoscopic scale of electrons and atoms to the meso- and maro- scales), large heterogeneous data sets, and interdisciplinary and multi-physical approaches, jointly with the unique ability to translate numerical and analytical technologies into applications of direct interest and use for many scientific and engineering areas, not to mention for society in general.

The methodologies developed in Spoke 6 will be applied in several areas of engineering, namely:

  • multi-scale modelling, from a subatomic to a circuital level, for the creation of devices, circuits and high-performance systems for the industry of semiconductors, in synergy with the ChipActs initiatives (The European legislative proposal on semiconductors, approved on February 8th, 2022, by the European Commission https://ec.europa.eu/info/strategy/priorities-2019-2024/europe-fit-digital-age/european-chips-act_en);
  • computational fluid dynamics for energy and power systems, turbomachines, efficient and green propulsion for the aerospace and automobile sectors, intensifying chemical and green chemical processes, pharmaceutical processes and drug administration, lab-on-chip and biosensing for biomedical applications (bio)nanotechnologies, assessment of environmental impact and of the security risk of industrial processes.
  • computing mechanics for machines and industrial production plants; structural components, systems and infrastructures;
  • electromagnetism and computational electronics of components and antenna array systems, high-frequency multichip models and integrated electronic-photonic circuits and systems, satellites, air/land/sea vehicles, efficient electric machines, and sustainable energy systems;
  • simulating devices and complex systems for the 4.0 industry and applications in the energy, aerospace, and automobile sectors;
  • elaboration of big data for the observation of Earth from space and/or systems of video surveillance or traffic management in smart cities with advanced machine-learning techniques to merge multisource and multi-spectrum data;

● analysis of massive data for engineering applications such as monitoring and detection of abnormalities/intrusions for security purposes and assessment of functional security of cyber-physical systems.

Istitution leader

Sapienza universita di roma

Istitution co-leader

universita-pisa

Istitutional partners

CNR
Politecnico di Milano
Politecnico di Torino
Università di Roma Tor Vergata
universita-bologna
Università della Calabria
università firenze
universita-pavia

Industrial partners

enel logotipo
Logo Eni
Fincantieri
logotipo IFAB
leonardo
terna-driving-energy
Thales Alenia Space