ASCEND · Next-Generation Accelerated and Scalable Modelling Frameworks for Chemically Reactive Flows
„Хоризонт Европа“ — Действия „Мария Склодовска-Кюри“
- Период
- 2027-03-01 → 2031-02-28
- Финансиране от ЕС
- 3 697 498 €
- Участници
- 15
- Схема
- HORIZON-TMA-MSCA-DN
Линиите свързват координатора с партньорите. За проекти отпреди 2014 г. CORDIS не винаги дава точни координати. Тези точки са на ниво град или държава.
Накратко на български
Моделирането на химически реакции при горива като водород и амоняк се ускорява чрез изкуствен интелект и суперкомпютри. Това помага за по-бързото разработване на чисти енергийни системи и технологии за намаляване на въглеродните емисии.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Цел на проекта
Accelerating Europe’s green and digital transitions requires advanced tools capable of modelling and optimising the complex reactive flows that underpin clean energy systems, propulsion technologies, and fire-safety applications. Yet current simulation approaches remain too computationally demanding to capture the multi-physics behaviour of low- and zero-carbon fuels such as hydrogen, ammonia, and e-fuels, which are essential for decarbonising hard-to-electrify sectors. ASCEND addresses this challenge by delivering the next-generation fully integrated modelling framework that leverages artificial intelligence (AI) and high-performance computing (HPC) technologies to accelerate reactive Computational Fluid Dynamics (CFD) simulations. By enabling order-of-magnitude reductions in computational cost while preserving physical fidelity, ASCEND will set a new European benchmark for predictive, fuel-flexible simulation tools.ASCEND will train 12 Doctoral Candidates to become a new generation of experts at the interface of combustion science, scientific machine learning (SciML), and high-performance computing. Bringing together six leading European universities and research centres, supported by a diverse group of industrial and academic associated partners, the programme offers interdisciplinary training in physics-informed ML, uncertainty quantification, GPU-aware numerical methods, and computational fluid dynamics. This will equip researchers with the cutting-edge skills needed to design fast, trustworthy, and scalable digital tools.By developing physics-informed, hardware-accelerated ML frameworks that drastically reduce computational cost while maintaining high physical fidelity, ASCEND will strengthen Europe’s scientific leadership, accelerate innovation in clean energy technologies, and contribute to a highly skilled workforce vital for achieving EU climate, digital, and sustainability objectives.
Оригинален текст от CORDIS (на английски).
Участници
- QUEEN MARY UNIVERSITY OF LONDON · LONDONКоординаторОбединеното кралство
- BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACION · BARCELONAИспания
- CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS · ParisФранция
- EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH · ZuerichШвейцария
- ETEX · ZaventemНиво градБелгия
- FORSCHUNGSZENTRUM JULICH GMBH · JULICHГермания
- NORTH CAROLINA STATE UNIVERSITY · RaleighСъединени щати
- SHELL RESEARCH LIMITED · LondonОбединеното кралство
- SIEMENS ENERGY INDUSTRIAL TURBOMACHINERY LIMITED · LINCOLNОбединеното кралство
- TECHNISCHE UNIVERSITAET BRAUNSCHWEIG · BraunschweigГермания
- TECHNISCHE UNIVERSITAT DARMSTADT · DarmstadtГермания
- THE UNIVERSITY OF EDINBURGH · EdinburghОбединеното кралство
- UNIVERSITAT POLITECNICA DE CATALUNYA · BARCELONAИспания
- UNIVERSITEIT GENT · GentБелгия
- Virtwin-Energy AB · StockholmНиво градШвеция
Връзки
Данни: CORDIS, © Европейски съюз