Fast Multipole Methods for Three-Dimensional N-body Problems

We are developing computational tools for the simulations of three-dimensional flows past bodies undergoing arbitrary motions. High resolution viscous vortex methods have been developed that allow for extended simulations of two-dimensional configurations such as vortex generators. Our objective is to extend this methodology to three dimensions and develop a robust computational scheme for the simulation of such flows. A fundamental issue in the use of vortex methods is the ability of employing efficiently large numbers of computational elements to resolve the large range of scales that exist in complex flows. The traditional cost of the method scales as Omicron (N(sup 2)) as the N computational elements/particles induce velocities at each other, making the method unacceptable for simulations involving more than a few tens of thousands of particles. In the last decade fast methods have been developed that have operation counts of Omicron (N log N) or Omicron (N) (referred to as BH and GR respectively) depending on the details of the algorithm. These methods are based on the observation that the effect of a cluster of particles at a certain distance may be approximated by a finite series expansion. In order to exploit this observation we need to decompose the element population spatially into clusters of particles and build a hierarchy of clusters (a tree data structure) - smaller neighboring clusters combine to form a cluster of the next size up in the hierarchy and so on. This hierarchy of clusters allows one to determine efficiently when the approximation is valid. This algorithm is an N-body solver that appears in many fields of engineering and science. Some examples of its diverse use are in astrophysics, molecular dynamics, micro-magnetics, boundary element simulations of electromagnetic problems, and computer animation. More recently these N-body solvers have been implemented and applied in simulations involving vortex methods. Koumoutsakos and Leonard (1995) implemented the GR scheme in two dimensions for vector computer architectures allowing for simulations of bluff body flows using millions of particles. Winckelmans presented three-dimensional, viscous simulations of interacting vortex rings, using vortons and an implementation of a BH scheme for parallel computer architectures. Bhatt presented a vortex filament method to perform inviscid vortex ring interactions, with an alternative implementation of a BH scheme for a Connection Machine parallel computer architecture

Simulations of vortex generators

We are interested in the study, via direct numerical simulations, of active vortex generators. Vortex generators may be used to modify the inner part of the boundary layer or to control separation thus enhancing the performance and maneuverability of aerodynamic configurations. We consider generators that consist of a surface cavity elongated in the stream direction and partially covered with a moving lid that at rest lies flush with the boundary. Streamwise vorticity is generated and ejected due to the oscillatory motion of the lid. The present simulations complement relevant experimental investigations of active vortex generators at NASA Ames and Stanford University (Saddoughi, 1994, and Jacobson and Reynolds, 1993). Jacobson and Reynolds (1993) used a piezoelectric device in water, allowing for small amplitude high frequency oscillations. They placed the lid asymmetrically on the cavity and observed a strong outward velocity at the small gap of the cavity. Saddoughi used a larger mechanically driven device in air to investigate this flow and he observed a jet emerging from the wide gap of the configuration, contrary to the findings of Jacobson and Reynolds. Our task is to simulate the flows generated by these devices and to conduct a parametric study that would help us elucidate the physical mechanisms present in the flow. Conventional computational schemes encounter difficulties when simulating flows around complex configurations undergoing arbitrary motions. Here we present a formulation that achieves this task on a purely Lagrangian frame by extending the formulation presented by Koumoutsakos, Leonard and Pepin (1994). The viscous effects are taken into account by modifying the strength of the particles, whereas fast multipole schemes employing hundreds of thousands of particles allow for high resolution simulations. The results of the present simulations would help us assess some of the effects of three-dimensionality in experiments and investigate the role of two-dimensional vortex generation due to an oscillating lid

3D simulations of self-propelled, reconstructed jellyfish using vortex methods

We present simulations of the vortex dynamics associated with the self-propelled motion of jellyfish. The geometry is obtained from image segmentation of video recordings from live jellyfish. The numerical simulations are performed using three-dimensional viscous, vortex particle methods with Brinkman penalization to impose the kinematics of the jellyfish motion. We study two types of strokes recorded in the experiment1. The first type (stroke A) produces two vortex rings during the stroke: one outside the bell during the power stroke and one inside the bell during the recovery stroke. The second type (stroke B) produces three vortex rings: one ring during the power stroke and two vortex rings during the recovery stroke. Both strokes propel the jellyfish, with stroke B producing the highest velocity. The speed of the jellyfish scales with the square root of the Reynolds number. The simulations are visualized in a fluid dynamics video.Comment: 1 page, 1 figur

Data-Driven Forecasting of High-Dimensional Chaotic Systems with Long Short-Term Memory Networks

We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.Comment: 31 page

Coupling Lattice Boltzmann and Molecular Dynamics models for dense fluids

We propose a hybrid model, coupling Lattice Boltzmann and Molecular Dynamics models, for the simulation of dense fluids. Time and length scales are decoupled by using an iterative Schwarz domain decomposition algorithm. The MD and LB formulations communicate via the exchange of velocities and velocity gradients at the interface. We validate the present LB-MD model in simulations of flows of liquid argon past and through a carbon nanotube. Comparisons with existing hybrid algorithms and with reference MD solutions demonstrate the validity of the present approach.Comment: 14 pages, 5 figure

C-start: optimal start of larval fish

We investigate the C-start escape response of larval fish by combining flow simulations using remeshed vortex methods with an evolutionary optimization. We test the hypothesis of the optimality of C-start of larval fish by simulations of larval-shaped, two- and three-dimensional self-propelled swimmers. We optimize for the distance travelled by the swimmer during its initial bout, bounding the shape deformation based on the larval mid-line curvature values observed experimentally. The best motions identified within these bounds are in good agreement with in vivo experiments and show that C-starts do indeed maximize escape distances. Furthermore we found that motions with curvatures beyond the ones experimentally observed for larval fish may result in even larger escape distances. We analyse the flow field and find that the effectiveness of the C-start escape relies on the ability of pronounced C-bent body configurations to trap and accelerate large volumes of fluid, which in turn correlates with large accelerations of the swimme