Turbulenz ist ein wesentlicher Bestandteil atmosphärischer Wolken. Die turbulente Mischung trockener mit feuchter Luft verstärkt Fluktuationen in den physikalischen Feldern von Wasserdampf und Temperatur. Aufgrund der starken Intermittenz und des chaotischen Charakters turbulenter Strömungen beeinflussen…
The mixing of scalar substances in fluid flows by stirring and diffusion is ubiquitous in natural flows, chemical engineering, and microfluidic drug delivery. Here, we present a spectral quantum algorithm for scalar mixing by solving the advection–diffusion equation in a quantum computational fluid dynamics…
Diese Dissertation untersucht das Zusammenspiel von Quantendynamik, Quanteninformationstheorie und Quantum Reservoir Computing (QRC). Im Zentrum steht die Frage, wie sich Quantensysteme zeitlich entwickeln und inwieweit das Verständnis dieser Zeitentwicklung Einblicke in QRC geben kann. Die Arbeit führt…
The mixing properties of vapor content, temperature, and particle fields are of paramount importance in cloud turbulence as they pertain to essential processes, such as cloud water droplet evaporation and entrainment. Our study examines the mixing of a single cloudy air (which implies droplet-laden)…
In recent years, data-driven deep learning models have gained significant importance in the analysis of turbulent dynamical systems. Within the context of reduced-order models, convolutional autoencoders (CAEs) pose a universally applicable alternative to conventional approaches. They can learn nonlinear…
The time-dependent one-dimensional nonlinear Schrödinger equation (NLSE) is solved numerically by a hybrid pseudospectral-variational quantum algorithm that connects a pseudospectral step for the Hamiltonian term with a variational step for the nonlinear term. The Hamiltonian term is treated as an integrating…
The time-dependent one-dimensional nonlinear Schrödinger equation (NLSE) is solved numerically by a hybrid pseudospectral-variational quantum algorithm that connects a pseudospectral step for the Hamiltonian term with a variational step for the nonlinear term. The Hamiltonian term is treated as an integrating…
We study the dynamics of thermal and momentum boundary regions in three-dimensional direct numerical simulations of Rayleigh–Bénard convection for the Rayleigh-number range 10^5 ≤ Ra ≤ 10^11 and Pr = 0.7. Using a Cartesian slab with horizontal periodic boundary conditions and an aspect ratio of 4, we…
The impact of variable material properties, such as temperature-dependent thermal conductivity and dynamical viscosity, on the dynamics of a fully compressible turbulent convection flow beyond the anelastic limit is studied in the present work by two series of three-dimensional direct numerical simulations…
Two quantum algorithms are presented for the numerical solution of a linear one-dimensional advection-diffusion equation with periodic boundary conditions. Their accuracy and performance with increasing qubit number are compared point-by-point with each other. Specifically, we solve the linear partial…
In dieser Arbeit wird das Potenzial von Machine-Learning-Algorithmen (ML) zur Verbesserung der Parametrisierung von großskaligen atmosphärischen Simulationen untersucht. Herkömmliche Ansätze verwenden oft Vereinfachungen oder rechenintensive Methoden. Diese Arbeit beabsichtigt, einen physikalisch konsistenten…
Wie tickt die Sonne? Warum hat sie einen Elfjahresyzklus? Die Theorie des solaren Dynamos hat sich seit ihren Anfängen im frühen neunzehnten Jahrhundert weit entwickelt. Aber auch heute ist noch nicht vollends verstanden, wie das solare Magnetfeld entsteht. Die Qualität wissenschaftlicher Theorien wird…
We employ a linear stability analysis and direct numerical simulations to study the characteristics of wall modes in thermal convection in a rectangular box under strong and inclined magnetic fields. The walls of the convection cell are electrically insulated. The stability analysis assumes periodicity…
Two hybrid quantum-classical reservoir computing models are presented to reproduce the low-order statistical properties of a two-dimensional turbulent Rayleigh-Bénard convection flow at a Rayleigh number Ra=105 and Prandtl number Pr=10. These properties comprise the mean vertical profiles of the root…
Thermische Konvektion ist der essentielle Mechanismus durch welchen Wärme in vielen natürlichen Strömungen übertragen wird und weist zugleich oftmals eine Hierarchie von verschiedenen Strömungsstrukturen auf. Jedes Umfeld kann dabei über seine eigenen charakteristischen Randbedingungen verfügen, wobei…
The spatial prediction of the turbulent flow of the unsteady von Kármán vortex street behind a cylinder at Re = 1000 is studied. For this, an echo state network (ESN) with 6000 neurons was trained on the raw, low-spatial resolution data from particle image velocimetry. During prediction, the ESN is provided…
We detail our developments in the high-fidelity spectral-element code Neko that are essential for unprecedented large-scale direct numerical simulations of fully developed turbulence. Major innovations are modular multi-backend design enabling performance portability across a wide range of GPUs and CPUs,…
New York, NY: The Association for Computing Machinery, 2023-11-11
We explore the mechanisms of heat transfer in a turbulent constant heat flux-driven Rayleigh–Bénard convection flow, which exhibits a hierarchy of flow structures from granules to supergranules. Our computational framework makes use of time-dependent flow networks. These are based on trajectories of…
Diese Arbeit präsentiert direkte numerische Simulationen von turbulenter Strömung feuchter Luft durch einen gekühlten, vertikalen Kanal. Die Kombination von Feuchtigkeit, Temperatur und Mischkonvektion tritt in der Belüftung von Fahrgasträumen auf. In dieser Anwendung stellt unerwünschte Kondensation…