Unraveling Turbulence through Ensemble Decomposition
Turbulence governs essentially all large-scale flows on our planet, including our atmosphere and oceans. With a vast number of engineering applications in transportation technology, renewable energies, and more, turbulence has a d...
Turbulence governs essentially all large-scale flows on our planet, including our atmosphere and oceans. With a vast number of engineering applications in transportation technology, renewable energies, and more, turbulence has a direct impact on our lives. However, developing predictive theories of turbulence, which ultimately all modeling applications rely on, remains one of the outstanding scientific challenges. Moreover, while massive simulations on the largest supercomputers are nowadays an established tool, reaching realistically high Reynolds numbers remains prohibitive. Already today, analyzing the sheer amount of peta-scale simulation data requires new paradigms for making meaningful progress. Fundamentally new approaches are needed to achieve a breakthrough. UniTED will deliver such an approach by a unique, synergistic combination of data-driven theory and large-scale computations. How? Recently, I showed that the complex statistics of turbulence can be disentangled into much simpler sub-ensembles. This significant reduction of complexity points toward exciting new theoretical pathways and novel computational methodologies, which I will explore in this project. In UniTED, we will (A) dissect the multi-scale structure of turbulence through massively parallel computations. This will (B) provide the foundation for a statistical theory of turbulence which is based on a novel ensemble decomposition approach. Combining (A) and (B), we will (C) develop a novel ensemble-based simulation approach, enabling unprecedented insights into turbulence at high Reynolds numbers. We will then use this approach to (D) provide big data for modeling small-scale turbulence using physics-informed machine learning. UniTED will boost our fundamental understanding of turbulence at very high Reynolds numbers and provide new modeling approaches in a breadth of fields such as computational engineering, the Earth sciences, renewable energy, and plasma physics.ver más
Seleccionando "Aceptar todas las cookies" acepta el uso de cookies para ayudarnos a brindarle una mejor experiencia de usuario y para analizar el uso del sitio web. Al hacer clic en "Ajustar tus preferencias" puede elegir qué cookies permitir. Solo las cookies esenciales son necesarias para el correcto funcionamiento de nuestro sitio web y no se pueden rechazar.
Cookie settings
Nuestro sitio web almacena cuatro tipos de cookies. En cualquier momento puede elegir qué cookies acepta y cuáles rechaza. Puede obtener más información sobre qué son las cookies y qué tipos de cookies almacenamos en nuestra Política de cookies.
Son necesarias por razones técnicas. Sin ellas, este sitio web podría no funcionar correctamente.
Son necesarias para una funcionalidad específica en el sitio web. Sin ellos, algunas características pueden estar deshabilitadas.
Nos permite analizar el uso del sitio web y mejorar la experiencia del visitante.
Nos permite personalizar su experiencia y enviarle contenido y ofertas relevantes, en este sitio web y en otros sitios web.