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HEДокторантска мрежа2023–2028

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

„Хоризонт Европа“ — Действия „Мария Склодовска-Кюри“

Период
2023-10-01 → 2028-03-31
Финансиране от ЕС
2 635 135 €
Участници
17
Схема
HORIZON-TMA-MSCA-DN

Линиите свързват координатора с партньорите.

Накратко на български

Многофазните течности се анализират чрез изкуствен интелект и математически модели, например за оптимизиране на охлаждането на електрически двигатели. Това помага за разработването на устойчиви технологии в транспорта, енергетиката и фармацевтичната индустрия.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

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

SCALE develops optimisation strategies to address real-world industrial applications aligning with the objectives of the European Green Deal and the Horizon Europe mission on Cancer. The Doctoral Candidates develop data-driven numerical CFD models to predict the behaviour of multiphase flows. This prediction is essential for developing sustainable and innovative technologies with the help of CFD applications. The industrial applications addressed in SCALE are hydraulic turbomachines, hydrodynamic propulsion, decarbonisation strategies for transportation, pharmaceutical industries, additives, heat transfer and thermal management concepts for electric motors (e-motors). The research topics are divided into three Work Packages: WP1: Physics-based and data-driven wall treatment models for non-Newtonian fluids and heat transfer effect WP2: Physics-informed data-driven surrogate models of complex SGS processes in multi-phase flows WP3: Consistent data-driven optimization approaches for high-order nonlinear discretisation methods

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

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.

Оригинален текст от CORDIS (на английски).

Участници

Връзки

Данни: CORDIS, © Европейски съюз