Abstract: Within diffuse interface models for multiphase problems, the curvature of the phase boundary can be expressed as the difference of two terms, a Laplacian and a second, gradient, term of the diffuse interface variable, φ. In phase field simulations of microstructure evolution, the second term is often replaced by f'(φ) =∂f/∂φ, where f(φ) is the potential function in the free energy functional of the underlying physical model. We show here that this replacement systematically deteriorates the accuracy in local curvature evaluation as compared to a discretized evaluation of the second term. Analytic estimates reveal that the discretization errors in the Laplacian and in the second term have roughly the same spatial dependence across the interface, thus leading to a cancellation of errors in κ. This is confirmed in a test case, where the discretization error can be determined via comparison to the exact solution. If, however, the second term is replaced by a quasi exact expression, the error in ∆φ enters κ without being compensated and can obscure the behavior of the local curvature. Due to the antisymmetric variations of this error term, approaches using the average curvature, as obtained from an integral along the interface normal, are immune to this problem.

Abstract: Astrophysical phenomena cover many order of magnitude in spatial and temporal scales. An additional complexity is introduced by the multi-physics aspects of the Universe. We present the Astrophysical Multipurpose Software Environment (AMUSE), which was designed specifically to allow researchers to simulate these processes on high-performance architectures. In AMUSE subgrid physical phenomena can be taken into account explicitly. The coupling across scales and across physical domains is realized by means of operator splitting. In multi-scale simulations, when the underlying physics shares the same Hamiltonian, we demonstrate that this coupling strategy captures the right physics to second order. When employing the operator splitting strategy across discipline we validate the results by comparison with historic results. Simulation projects can be setup in AMUSE in a declarative fashion in which the coupling strategies are described at a meta level. These descriptions allow for the strict separation of individual modules for multi-scale and multi-domain simulations in the form of patterns. In this study we describe how these patterns are implemented in AMUSE and where they can be used to help the modeling celestial phenomena.

Abstract: Improving operating room (OR) management in large hospitals has been a challenging problem that remains largely unresolved. Fifty percent of hospital income depends on OR activities and among the main concerns in most institutions is to improve the efficiency of a large OR suite that. We advocate that optimizing surgical flow in large OR suites is a complex multifactorial problem with an underlying multiscale structure. Numerous components of the system can combine nonlinearly result in the large accumulated delays observed in daily clinical practice. We propose a multiscale agent-based model (ABM) of surgical flow. We developed a smartOR system that utilizes a dedicated network of non-invasive, wireless sensors to automatically track the state of the OR and accurately computes major indicators of performances such as turnover time between procedures. We show that our model can fit these time measurements and that a multiscale description of the system is possible. We will discuss how this model can be used to quantify and target the main limiting factors in optimizing OR suite efficiency.

Abstract: A powerful way to deal with a complex system is to build a coarse-grained model capable of catching its main physical features, while still being computationally affordable. Inevitably, such coarse-grained models introduce a set of phenomenological parameters, which are often not easily deducible from the underlying atomistic system. We present a novel approach to the calculation of these parameters, based on the recently introduced variationally enhanced sampling method. It allows us to obtain the parameters from atomistic simulations, providing thus a direct connection between the microscopic and the mesoscopic scale. The coarse-grained model we consider is that of Ginzburg-Landau, valid around a second order critical point. In particular we use it to describe a Lennard-Jones fluid in the region close to the liquid-vapor critical point. The procedure is general and can be adapted to other coarse-grained models.