In this paper we introduce a novel method to adaptive incompressible SPH simulations. Instead of using a scheme with a number of fixed particle sizes or levels, our approach allows continuous particle sizes. This enables us to define optimal particle masses with respect to, e.g., the distance to the fluid's surface. A required change in mass due to the dynamics of the fluid is properly and stably handled by our scheme of mass redistribution. This includes temporally smooth changes in particle masses as well as sudden mass variations in regions of high flow dynamics. Our approach guarantees low spatial variations in particle size, which is a core property in order to achieve large adaptivity ratios for incompressible fluid simulations. Conceptually, our approach allows for infinite continuous adaptivity, practically we achieved adaptivity ratios up to 5 orders of magnitude, while still being mass preserving and numerically stable, yielding unprecedented vivid surface detail at comparably low computational cost and moderate particle counts.

a) tsim = 3 s (b) tsim = 16 s (c) tsim = 16 s (detergent in blue) Figure 1: The pan's surface is cleansed from grease (orange) due to detergent concentration (blue in 1(c)) on the fluid's surface. AbstractSurface effects play an essential role in fluid simulations. A vast number of dynamics including wetting of surfaces, cleansing, and foam dynamics are based on surface-surface and surface-bulk interactions, which in turn rely on a robust surface computation. In this paper we introduce a conservative Lagrangian formulation of surface effects based upon incompressible smoothed particle hydrodynamics (SPH). The key concept of our approach is to realize an implicit definition of the fluid's (free) surface by assigning each particle a value estimating its surface area. Based on this consistent surface representation, a conservative coupling of bulk and surface is achieved. We demonstrate the applicability and robustness of our approach for several types of surface-relevant effects including adsorption, diffusion and reaction kinetics.

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We present a summary of the development and clinical use of two custom designed high-fidelity virtual-reality simulator training platforms. This simulator development program began in 2016 to support the phase III clinical trial Archway (ClinicalTrials.gov identifier, NCT03677934) intended to evaluate the Port Delivery System (PDS) developed by Genentech Inc. and has also been used to support additional clinical trials. The two simulators address two specific ophthalmic surgical procedures required for the successful use of PDS and provide state-of-the-art physical simulation models and graphics. The simulators incorporate customized active haptic feedback input devices that approximate different hand pieces including a custom hand piece specifically designed for PDS implantation. We further describe the specific challenges of the procedure and the development of corresponding training strategies realized within the simulation platform.

We propose a framework for unified visualization of advective and diffusive concentration fluxes, which play a key role in many phenomena like, e.g. Marangoni convection and microscopic mixing. The main idea is the decomposition of fluxes into their concentration and velocity parts. Using this flux decomposition, we are able to convey advective-diffusive concentration transport using integral lines. In order to visualize superimposed flux effects, we introduce a new graphical metaphor, the stream feather, which adds extensions to stream tubes pointing in the directions of deviating fluxes. The resulting unified visualization of macroscopic advection and microscopic diffusion allows for deeper insight into complex flow scenarios that cannot be achieved with current volume and surface rendering techniques alone. Our approach for flux decomposition and visualization of advective-diffusive flows can be applied to any kind of (simulation) data if velocity and concentration data are available. We demonstrate that our techniques can easily be integrated into Smoothed Particle Hydrodynamics (SPH) based simulations.