63 Dokumente gefunden
Numerical studies of turbulent mixing in clouds
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…
Spectral quantum algorithm for passive scalar transport in shear flows
aus: Scientific reports
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…
London: Springer Nature, 2025-11-21
Investigating quantum evolution using Krylov complexity and its applications in quantum reservoir computing
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…
Diffuselet method for three-dimensional turbulent mixing of a cloudy air filament
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)…
College Park, MD: APS, 2025-07-16
Slim multi-scale convolutional autoencoder-based reduced-order models for interpretable features of a complex dynamical system
aus: APL machine learning
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…
Melville, NY: AIP Publishing, 2025-02-26
Numerical solution of nonlinear Schrödinger equation by a hybrid pseudospectral-variational quantum algorithm
aus: Scientific reports
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…
London: Springer Nature, 2025-02-07
Numerical solution of nonlinear Schrödinger equation by a hybrid pseudospectral-variational quantum algorithm
aus: Scientific reports
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…
London: Springer Nature, 2025-02-07
No sustained mean velocity in the boundary region of plane thermal convection
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…
Cambridge [u.a.]: Cambridge Univ. Press, 2024-09-02
Compressible turbulent convection: the role of temperature-dependent thermal conductivity and dynamic viscosity
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…
[S.l.]: American Institute of Physics, 2024-07-26
Two quantum algorithms for solving the one-dimensional advection-diffusion equation
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…
Amsterdam [u.a.]: Elsevier Science, 2024-07-18
Reduced order modeling of thermal convection flows: a reservoir computing approach
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…
Synchronising the Rayleigh-Bénard instability in a liquid metal flow using electromagnetic forces
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…
Wall-attached convection under strong inclined magnetic fields
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…
Cambridge [u.a.]: Cambridge Univ. Press, 2024-01-25
Reduced-order modeling of two-dimensional turbulent Rayleigh-Bénard flow by hybrid quantum-classical reservoir computing
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…
College Park, MD: APS, 2023-12-13
Large-scale flow structures in turbulent Rayleigh-Bénard convection: dynamical origin, formation, and role in material transport
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…
Spatial prediction of the turbulent unsteady von Kármán vortex street using echo state networks
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…
[S.l.]: American Institute of Physics, 2023-11-27
Exploring the ultimate regime of turbulent Rayleigh-Bénard Convection through unprecedented spectral-element simulations
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
Collective variables between large-scale states in turbulent convection
The dynamics in a confined turbulent convection flow is dominated by multiple long-lived macroscopic circulation states that are visited subsequently by the system in a Markov-type hopping process. In the present work, we analyze the short transition paths between these subsequent macroscopic system…
College Park, MD: APS, 2023-07-28
Thermal boundary condition studies in large aspect ratio Rayleigh-Bénard convection
We study the influence of thermal boundary conditions on large aspect ratio Rayleigh-Bénard convection by a joint analysis of experimental and numerical data sets for a Prandtl number Pr=7 and Rayleigh numbers Ra=105−106. The spatio-temporal experimental data are obtained by combined Particle Image Velocimetry…
Paris: Gauthier-Villars, 2023-06-20