Parallel computing server for numerical characterization of space transportation vehicles
Componente | Categoria |
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Francesco Creta | Componenti il gruppo di ricerca |
Francesco Nasuti | Componenti il gruppo di ricerca |
Daniele Bianchi | Componenti il gruppo di ricerca |
Renato Paciorri | Componenti il gruppo di ricerca |
Massimiliano Giona | Componenti il gruppo di ricerca |
Paolo Gualtieri | Componenti il gruppo di ricerca |
Matteo Bernardini | Componenti il gruppo di ricerca |
Sergio Pirozzoli | Componenti il gruppo di ricerca |
Advanced numerical simulations can boost the design process of new paradigms in space transportation systems, whose necessity is brought by the introduction of small satellites and by the request of space access cost and footprint reduction.
The scope of the project is the numerical characterization of the phenomena involved in space transportation systems. The main pillars of the research are: (i) external flow of space launcher in the lift-off and ascent phases; (ii) hypersonic flows for atmospheric re-entry description; (iii) interaction between turbulent motions and chemical reaction in Liquid
Rocket Engines (LRE); (iv) combustion and propellant grain regression in Solid Rocket Motors (SRM) and Hybrid Rocket Engines (HRE); (v) liquid spray injection, atomization, vaporization and combustion in LRE;
(vi) wall heat fluxes and cooling system for LRE; (vii) wall flows in cooling channels of LRE; (viii) shock-wave oscillations in overexpanded nozzles during the sea-level startup; (ix) thermo-chemical models for propulsive applications.
A variable fidelity approach will be adopted: hi-fidelity techniques will be employed for the characterization of basic physical phenomena and restricted portions of the problem of interest; low-fidelity techniques will be employed to support design phase and system optimization strategies. Big-data analysis and response surface techniques will be employed in conjunction with both hi- and low- fidelity numerical strategies to generate surrogate models to alleviate the numerical and experimental burden of the optimization processes.
For this purpose a mid-size parallel computing server is requested. The server should be equipped with: (i) a number of CPUs sufficient to execute hundreds of threads simultaneously; (ii) an amount of RAM memory of the order of half a terabyte to cope with large physical domains; (iii) an amount of hard memory of the order of the tens of terabytes for the storage of the produced data.