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Industry empowerment to Multiphase fluid dynamics simulations using Artificial intelligence and Statistical methods on modern hardware architectures at Scale

Descrizione del progetto

Sviluppare nuove soluzioni per le simulazioni fluidodinamiche multifase

La transizione verso soluzioni energetiche più ecologiche e il miglioramento della produzione e dell'efficienza energetica richiedono l'introduzione e lo sviluppo di varie tecnologie che utilizzano flussi di fluidi multifase, trans/supercritici e non newtoniani dotati di capacità di trasferimento di calore e massa. Tuttavia, le simulazioni numeriche dirette non sono in grado di fornire l'accuratezza necessaria per il loro sviluppo. Il progetto SCALE, finanziato dal programma di azioni Marie Skłodowska-Curie, si prefigge di sviluppare nuove soluzioni e modelli di simulazione basati sull'apprendimento automatico, orientati ai dati e informati dalla fisica. Il progetto utilizzerà database specializzati e simulazioni LES e RANS al fine di valutare e addestrare le soluzioni, collaborando inoltre con esperti del settore per fornire formazione e ottimizzare lo sviluppo e la convalida di queste soluzioni.

Obiettivo

Multi-phase, trans/supercritical and non-Newtonian fluid flows with heat and mass transfer are critical in enhancing the performance of energy production, propulsion and biomedical systems. Examples include: hydraulic turbomachines, ship propellers, CO2-neutral e-fuels and e-motor cooling systems, particle-laden flows in inhalers and focused ultrasounds for drug delivery. What all these cases have in common is the high level of complexity which makes Direct Numerical Simulations impossible. State-of-the-art LES simulations rely on simplified assumptions but do not have yet the desired accuracy, while often require enormously expensive CPU resources. The aim of SCALE is to develop simulation methods and reduced-order models using physics-informed and data-driven Machine Learning and optimisation methods for such flow processes. These will be trained against ‘ground-truth’ databases that will be generated for the first time using both DNS and experimentally validated, industry-relevant LES and multi-fidelity RANS simulations. The new simulation tools will be applied for the first time to industrial problems and their ability to accelerate design times and improve accuracy will be jointly pursued and evaluated with the non-academic partners of SCALE. These are international corporations and market leaders in the aforementioned areas. Holistic training by experts from science and industry includes broad reviews on relevant scientific topics, modern high performance computing architectures suitable for performing such simulations, big data analytics as well as extensive support for mastering scientific tasks and transferring the knowledge acquired to industrial practice. SCALE will also deliver soft skills training from a well-connected cohort of leaders with the ability to communicate across disciplines and within the general public. This coupling of research with industry makes SCALE a truly outstanding network for doctoral candidates to start their career.

Coordinatore

OTTO-VON-GUERICKE-UNIVERSITAET MAGDEBURG
Contribution nette de l'UE
€ 521 078,40
Indirizzo
UNIVERSITAETSPLATZ 2
39106 Magdeburg
Germania

Mostra sulla mappa

Regione
Sachsen-Anhalt Sachsen-Anhalt Magdeburg, Kreisfreie Stadt
Tipo di attività
Higher or Secondary Education Establishments
Collegamenti
Costo totale
Nessun dato

Partecipanti (5)

Partner (11)